ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 52,2026 Issue 5
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- The Future Projections of Extreme Weather, Climate and Water Events and Strategic Responses
- A Review of Downburst Genesis Mechanism and Warning
- The Pattern Structure and Thermodynamic and Dynamic Processes of Severe Storms Associated with Linear Convective Gales
- Analysis on Extremity and Characteristics of the “21·7” Severe Torrential Rain in Henan Province
- Diagnostic Analysis on Water Vapor and Jet Characteristics of the July 2021 Severe Torrential Rain in Henan Province
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LI Nina, JIN Ronghua, GONG Yu, DAI Kan, CAO Yong, NIE Gaozhen, LIN Jian, WEI Qing, WU Haixu, LUO Huakun, LONG Mingsheng, WANG Jianmin
2026,52(5):513-526, DOI: 10.7519/j.issn.1000-0526.2026.030501
Abstract:
In 2024, China Meteorological Administration (CMA), in collaboration with Tsinghua University, developed the forecasting model following an innovative “AI-Physics” hybrid approach—Fengqing Model. With the designs such as a multi-scale latent space projection architecture and an energy-conservation loss function, the model has been equipped with global short- and medium-range weather forecasting capabilities and has been applied in forecasting operations. This paper comprehensively evaluates the forecasting ability of Fengqing Model in China and the surrounding areas in 2024 from several metrics such as forecasting accuracy and bias distribution. Two kinds of typical synoptic processes, i.e., typhoon and rainstorm, are also focused on deeply exploring the model’s performance in the forecasts of disastrous weather. The results show that the 500 hPa geopotential height forecasts by Fengqing Model maintain a predictive skill beyond 10 days. The root mean square errors of 2 m temperature and 850 hPa temperature are significantly lower than those from the European Centre for Medium-Range Weather Forecasts (ECMWF-IFS), having a maximum improvement of 37.66%. In terms of typical weather processes, Fengqing Model demonstrates its superior performance in typhoon track forecasting to ECMWF-IFS, but it underestesmates the typhoon intensity. In addition, Fengqing Model has a good forecasting ability for rainstorm, with smaller forecast errors for the locations of typhoon rain and Meiyu front rainfall belt. The TS score of rainstorm forecasts in the medium-range (73-168 h lead time) is improved by 43.53% compared to that of ECMWF-IFS forecasts. Overall, the Fengqing Model presents considerable potential in operational forecasting, although further improvements are needed in activity level and typhoon intensity prediction at medium- and long-range lead times.
In 2024, China Meteorological Administration (CMA), in collaboration with Tsinghua University, developed the forecasting model following an innovative “AI-Physics” hybrid approach—Fengqing Model. With the designs such as a multi-scale latent space projection architecture and an energy-conservation loss function, the model has been equipped with global short- and medium-range weather forecasting capabilities and has been applied in forecasting operations. This paper comprehensively evaluates the forecasting ability of Fengqing Model in China and the surrounding areas in 2024 from several metrics such as forecasting accuracy and bias distribution. Two kinds of typical synoptic processes, i.e., typhoon and rainstorm, are also focused on deeply exploring the model’s performance in the forecasts of disastrous weather. The results show that the 500 hPa geopotential height forecasts by Fengqing Model maintain a predictive skill beyond 10 days. The root mean square errors of 2 m temperature and 850 hPa temperature are significantly lower than those from the European Centre for Medium-Range Weather Forecasts (ECMWF-IFS), having a maximum improvement of 37.66%. In terms of typical weather processes, Fengqing Model demonstrates its superior performance in typhoon track forecasting to ECMWF-IFS, but it underestesmates the typhoon intensity. In addition, Fengqing Model has a good forecasting ability for rainstorm, with smaller forecast errors for the locations of typhoon rain and Meiyu front rainfall belt. The TS score of rainstorm forecasts in the medium-range (73-168 h lead time) is improved by 43.53% compared to that of ECMWF-IFS forecasts. Overall, the Fengqing Model presents considerable potential in operational forecasting, although further improvements are needed in activity level and typhoon intensity prediction at medium- and long-range lead times.
LIU Junjie, LU Bo, LI Hao, CHEN Lei, ZHONG Xiaohui, ZHOU Chenguang, HU Jiahui, WU Jie, ZHAO Chunyan, XIN Yuhang, ZHAO Yang, QIAN Qifeng
2026,52(5):527-537, DOI: 10.7519/j.issn.1000-0526.2026.032901
Abstract:
Based on the hindcast datasets from the Fengshun Model and the S2S-ECMWF Model, together with CMA-RA1.0 and NCEP reanalysis data and station observations during 2017-2021, the pentad-scale prediction skills of the Fengshun Model and the S2S-ECMWF Model for midsummer (July-August) temperature over China are comparatively verified. Three metrics of temporal correlation coefficient (TCC), anomaly correlation coefficient (ACC), and integrated prediction score (IPS) are adopted. The results are as follows. The verification results based on different reference datasets are generally consistent, demonstrating their good robustness. Overall, the Fengshun Model shows superior prediction skill to the S2S-ECMWF Model, with TCC, ACC and IPS values improved by 7.9%, 18.4%, and 1.5%, respectively. Spatially, the Fengshun Model exhibits higher TCC skill in the Huang-Huai (Yellow River-Huaihe River), Jiang-Huai (Yangtze River-Huaihe River), Central China, South China, East China, and Xinjiang regions, but showing relatively lower skill in Northeast China, Inner Mongolia, the Qinghai-Xizang Plateau, and Southwest China. Temporally, the Fengshun Model demonstrates superior prediction skill with 1 pentad and 4-8 pentad lead times, with the highest skill appearing at a 6 pentad lead time, and improvements in TCC, ACC and IPS can reach 42%, 260%, and 4.5%, respectively, which indicates an extended predictability window. This advantage is primarily attributed to the Fengshun Model’s better characterization of 500 hPa geopotential height anomalies over key circulation regions in mid-latitudes of Asia. However, the Fengshun Model shows a relatively weak prediction skill with 2 pentad to 3 pentad lead times, which is likely due to the decay of initial atmospheric signals and insufficient influence from underlying surface information. Future improvement focus will be put on incorporating multi-layer surface information to further enhance the Model’s prediction performance.
Based on the hindcast datasets from the Fengshun Model and the S2S-ECMWF Model, together with CMA-RA1.0 and NCEP reanalysis data and station observations during 2017-2021, the pentad-scale prediction skills of the Fengshun Model and the S2S-ECMWF Model for midsummer (July-August) temperature over China are comparatively verified. Three metrics of temporal correlation coefficient (TCC), anomaly correlation coefficient (ACC), and integrated prediction score (IPS) are adopted. The results are as follows. The verification results based on different reference datasets are generally consistent, demonstrating their good robustness. Overall, the Fengshun Model shows superior prediction skill to the S2S-ECMWF Model, with TCC, ACC and IPS values improved by 7.9%, 18.4%, and 1.5%, respectively. Spatially, the Fengshun Model exhibits higher TCC skill in the Huang-Huai (Yellow River-Huaihe River), Jiang-Huai (Yangtze River-Huaihe River), Central China, South China, East China, and Xinjiang regions, but showing relatively lower skill in Northeast China, Inner Mongolia, the Qinghai-Xizang Plateau, and Southwest China. Temporally, the Fengshun Model demonstrates superior prediction skill with 1 pentad and 4-8 pentad lead times, with the highest skill appearing at a 6 pentad lead time, and improvements in TCC, ACC and IPS can reach 42%, 260%, and 4.5%, respectively, which indicates an extended predictability window. This advantage is primarily attributed to the Fengshun Model’s better characterization of 500 hPa geopotential height anomalies over key circulation regions in mid-latitudes of Asia. However, the Fengshun Model shows a relatively weak prediction skill with 2 pentad to 3 pentad lead times, which is likely due to the decay of initial atmospheric signals and insufficient influence from underlying surface information. Future improvement focus will be put on incorporating multi-layer surface information to further enhance the Model’s prediction performance.
2026,52(5):538-551, DOI: 10.7519/j.issn.1000-0526.2026.030903
Abstract:
Aiming at the fine-scale forecasting challenge of 2 m temperature (T2m) in complex terrain areas, this paper selects the Guangxi Region, a typical area with complex terrain, as the research object and proposes a physics-constrained deep learning forecasting model named PSD-Net, which integrates the forecast products of the Pangu-Weather Model. The forecast products of Pangu-Weather (PANGU) are used as feature variables input. The generator based on the super-resolution generative adversarial network is employed to extract multi-scale features. Power-spectral-density and Kullback-Leibler divergence are explicitly injected into the loss function as constraint terms so as to improve the consistency of forecast products with observations in spectral fidelity and probability distribution. Compared to the T2m forecast performance of the ECMWF, SCMOC and PANGU products in the Guangxi Region in 2024, both the grided forecasts and station-based forecasts of PSD-Net outperform the compared forecast products. In particular, the mean absolute error (MAE) of the gridded forecasts is reduced by 37.6% relative to that of PANGU and the accuracy is improved by 17 percentage points. The growths of both MAE and root mean square error (RMSE) for the 1-72 h T2m forecast products from PSD-Net are less than those of the compared forecast products, and there is a gentle error growth at lead time 25-72 h. In a word, this study has verified the effectiveness of the physics-constrained deep learning framework in fine-scale T2m forecasting which could provide a new approach for the combination of meteorological and AI models.
Aiming at the fine-scale forecasting challenge of 2 m temperature (T2m) in complex terrain areas, this paper selects the Guangxi Region, a typical area with complex terrain, as the research object and proposes a physics-constrained deep learning forecasting model named PSD-Net, which integrates the forecast products of the Pangu-Weather Model. The forecast products of Pangu-Weather (PANGU) are used as feature variables input. The generator based on the super-resolution generative adversarial network is employed to extract multi-scale features. Power-spectral-density and Kullback-Leibler divergence are explicitly injected into the loss function as constraint terms so as to improve the consistency of forecast products with observations in spectral fidelity and probability distribution. Compared to the T2m forecast performance of the ECMWF, SCMOC and PANGU products in the Guangxi Region in 2024, both the grided forecasts and station-based forecasts of PSD-Net outperform the compared forecast products. In particular, the mean absolute error (MAE) of the gridded forecasts is reduced by 37.6% relative to that of PANGU and the accuracy is improved by 17 percentage points. The growths of both MAE and root mean square error (RMSE) for the 1-72 h T2m forecast products from PSD-Net are less than those of the compared forecast products, and there is a gentle error growth at lead time 25-72 h. In a word, this study has verified the effectiveness of the physics-constrained deep learning framework in fine-scale T2m forecasting which could provide a new approach for the combination of meteorological and AI models.
Using Generative Adversarial Network to Improve Heavy Precipitation Nowcasting in the Jianghuai Area
2026,52(5):552-565, DOI: 10.7519/j.issn.1000-0526.2025.080801
Abstract:
This paper proposes two deep learning-based short-term heavy precipitation nowcasting methods for the Jianghuai Area by optimizing generative adversarial network (GAN), namely PhySGAN (combining PhyDNet and SGAN) and PhyMGAN (combining PhyDNet and MGAN), so as to provide precipitation forecasts in the next 3 hours for the Jianghuai Area. Based on the forecast skill score, the performance assessment in “complex scenarios” and the analysis of typical application examples, this paper analyzes the forecast performance of the two methods in the short-time heavy precipitation (≥20 mm·h-1) forecasts in Jiangsu Province during the flood season of 2024. The results show that the TS scores of short-term heavy precipitation within 3 hours in different verification periods of PhySGAN and PhyMGAN are significantly improved compared with those of the basic experiment PhyDNet and the general GAN experiment PhyGAN. The two new methods can correct the low frequency problem of short-term heavy precipitation forecasts by PhyDNet and PhyGAN, so that the TS score increases with the increase of the forecast lead time, thereby effectively extending the nowcasting lead time of short-term heavy precipitation. Judged from the forecast performance shown by each method in “complex scenarios”, deep learning can reflect the evolution of the generation and dissipation of heavy precipitation relative to the traditional extrapolation methods. PhySGAN and PhyMGAN show better forecast performance than PhyDNet and PhyGAN. The former has a better ability to depict local details such as the shape and intensity of heavy precipitation, while the latter has a better representation of the overall contour and position of the heavy precipitation rain band. Combined with the application of typical heavy precipitation cases during the flood season, both PhySGAN and PhyMGAN can forecast the precipitation enhancement process in advance in both systematic heavy precipitation and local heavy precipitation cases, effectively guiding the early warning of disasters. In addition, PhyMGAN has a certain indicative effect on extreme rainfall intensities above 50 mm·h-1, while PhySGAN can better reflect the changes in the shape and position of the rain band.
This paper proposes two deep learning-based short-term heavy precipitation nowcasting methods for the Jianghuai Area by optimizing generative adversarial network (GAN), namely PhySGAN (combining PhyDNet and SGAN) and PhyMGAN (combining PhyDNet and MGAN), so as to provide precipitation forecasts in the next 3 hours for the Jianghuai Area. Based on the forecast skill score, the performance assessment in “complex scenarios” and the analysis of typical application examples, this paper analyzes the forecast performance of the two methods in the short-time heavy precipitation (≥20 mm·h-1) forecasts in Jiangsu Province during the flood season of 2024. The results show that the TS scores of short-term heavy precipitation within 3 hours in different verification periods of PhySGAN and PhyMGAN are significantly improved compared with those of the basic experiment PhyDNet and the general GAN experiment PhyGAN. The two new methods can correct the low frequency problem of short-term heavy precipitation forecasts by PhyDNet and PhyGAN, so that the TS score increases with the increase of the forecast lead time, thereby effectively extending the nowcasting lead time of short-term heavy precipitation. Judged from the forecast performance shown by each method in “complex scenarios”, deep learning can reflect the evolution of the generation and dissipation of heavy precipitation relative to the traditional extrapolation methods. PhySGAN and PhyMGAN show better forecast performance than PhyDNet and PhyGAN. The former has a better ability to depict local details such as the shape and intensity of heavy precipitation, while the latter has a better representation of the overall contour and position of the heavy precipitation rain band. Combined with the application of typical heavy precipitation cases during the flood season, both PhySGAN and PhyMGAN can forecast the precipitation enhancement process in advance in both systematic heavy precipitation and local heavy precipitation cases, effectively guiding the early warning of disasters. In addition, PhyMGAN has a certain indicative effect on extreme rainfall intensities above 50 mm·h-1, while PhySGAN can better reflect the changes in the shape and position of the rain band.
JI Zhongping, GU Dejun, GAO Xiaorong, XU Yanhong, LI Shanshan, LIANG Qiaoqian, TU Jing, LIANG Weijie
2026,52(5):566-579, DOI: 10.7519/j.issn.1000-0526.2026.022801
Abstract:
The low-frequency oscillation characteristics of continuous rainstorm processes in Guangdong during the pre-flood season in 2023 are analyzed by means of wavelet analysis and Lanczos temporal filter. The focus of this study is on revealing the mean atmospheric circulation field and its evolution characteristics in different phases of quasi-biweekly oscillations and the source of the low-frequency signals of the continuous warm-sector rainstorms with strong southwesterly winds in the northwest of Guangdong Province. The results show that the three continuous rainstorms exhibited a quasi-7-18 d periodic oscillation, located in the positive phase of two quasi-30-60 d intraseasonal oscillations. The continuous warm-sector rainstorms with strong southwesterly winds mainly occurred in the northwest of Guangdong in 22-26 June when there were stable “west blocking” and “east blocking” at the middle and high latitudes. During this period, the northwest of Guangdong was located at the bottom of the plateau trough and the edge of the western Pacific subtropical high at 500 hPa, and at the left side of southwest monsoon axis and the right side of the cyclonic circulations at 850 hPa. During the intermittent-start-peak period of the continuous warm-sector rainstorm processes with strong southwesterly winds, the low-frequency signals in the mid-to-upper levels originated from the southern branch wave train with the eastward propagation and southward extension of baroclinic low-frequency anticyclones and cyclones within or to the south of the Iranian Plateau and Qinghai-Xizang Plateau. The low-frequency signals in the lower levels arose from the eastward movement and southward extension of the eastern Mongolian Plateau low-frequency anticyclone and the progressively intensifying low-frequency cyclone east of the Sichuan Basin and Yunnan-Guizhou Plateau. They induced the center of South Asian high to move eastward gradually and the western Pacific subtropical high to weaken and retreat eastward. At the same time, the Qinghai-Xizang Plateau was controlled by low-frequency cyclonic circulation in intermittent periods and gradually became dominated by the low-frequency anticyclone circulation in the peak period, while North China and South China were controlled first by low-frequency anticyclone circulation in intermittent periods and then gradually by the low-frequency cyclonic circulation in the peak period. These findings could provide some references for medium-to-extended range forecasting of continuous warm-sector rainstorm.
The low-frequency oscillation characteristics of continuous rainstorm processes in Guangdong during the pre-flood season in 2023 are analyzed by means of wavelet analysis and Lanczos temporal filter. The focus of this study is on revealing the mean atmospheric circulation field and its evolution characteristics in different phases of quasi-biweekly oscillations and the source of the low-frequency signals of the continuous warm-sector rainstorms with strong southwesterly winds in the northwest of Guangdong Province. The results show that the three continuous rainstorms exhibited a quasi-7-18 d periodic oscillation, located in the positive phase of two quasi-30-60 d intraseasonal oscillations. The continuous warm-sector rainstorms with strong southwesterly winds mainly occurred in the northwest of Guangdong in 22-26 June when there were stable “west blocking” and “east blocking” at the middle and high latitudes. During this period, the northwest of Guangdong was located at the bottom of the plateau trough and the edge of the western Pacific subtropical high at 500 hPa, and at the left side of southwest monsoon axis and the right side of the cyclonic circulations at 850 hPa. During the intermittent-start-peak period of the continuous warm-sector rainstorm processes with strong southwesterly winds, the low-frequency signals in the mid-to-upper levels originated from the southern branch wave train with the eastward propagation and southward extension of baroclinic low-frequency anticyclones and cyclones within or to the south of the Iranian Plateau and Qinghai-Xizang Plateau. The low-frequency signals in the lower levels arose from the eastward movement and southward extension of the eastern Mongolian Plateau low-frequency anticyclone and the progressively intensifying low-frequency cyclone east of the Sichuan Basin and Yunnan-Guizhou Plateau. They induced the center of South Asian high to move eastward gradually and the western Pacific subtropical high to weaken and retreat eastward. At the same time, the Qinghai-Xizang Plateau was controlled by low-frequency cyclonic circulation in intermittent periods and gradually became dominated by the low-frequency anticyclone circulation in the peak period, while North China and South China were controlled first by low-frequency anticyclone circulation in intermittent periods and then gradually by the low-frequency cyclonic circulation in the peak period. These findings could provide some references for medium-to-extended range forecasting of continuous warm-sector rainstorm.
2026,52(5):580-594, DOI: 10.7519/j.issn.1000-0526.2026.040202
Abstract:
This study classified the weather situations of heavy precipitation events in the Yangtze River Delta Region from September 2022 to September 2024 and evaluated the forecast performance of the numerical models CMA-MESO, CMA-GFS, CMA-TYM, CMA-SH9 and the ECMWF model under four main weather types. The research results show that in the 24 h precipitation forecasts, there is a high false alarm rate of forecast for light rain, while torrential rain and above are difficult to accurately forecast, thus the TS score is low. In the 3 h forecasts, the CMA-MESO model performs best for light precipitation. However, under cold shear and low-vortex shear types, heavy precipitation becomes harder to capture, and the model forecast performance weak. In terms of spatial feature evaluation, except the CMA-SH9 model, most models have northern systematic errors in the low-vortex shear and subtropical high with low trough types in the north-south direction, but the situation is the opposite for the typhoon body and periphery type. In the east-west direction, these models generally exhibit an eastern systematic bias in the typhoon body and periphery types, while in other weather types, most models have western systematic errors. For the evaluation of temporal characteristics, all the models have the highest accuracy in forecasting the start time of precipitation, followed by the forecast of end time, and the accuracy in forecasting the peak time is relatively low.
This study classified the weather situations of heavy precipitation events in the Yangtze River Delta Region from September 2022 to September 2024 and evaluated the forecast performance of the numerical models CMA-MESO, CMA-GFS, CMA-TYM, CMA-SH9 and the ECMWF model under four main weather types. The research results show that in the 24 h precipitation forecasts, there is a high false alarm rate of forecast for light rain, while torrential rain and above are difficult to accurately forecast, thus the TS score is low. In the 3 h forecasts, the CMA-MESO model performs best for light precipitation. However, under cold shear and low-vortex shear types, heavy precipitation becomes harder to capture, and the model forecast performance weak. In terms of spatial feature evaluation, except the CMA-SH9 model, most models have northern systematic errors in the low-vortex shear and subtropical high with low trough types in the north-south direction, but the situation is the opposite for the typhoon body and periphery type. In the east-west direction, these models generally exhibit an eastern systematic bias in the typhoon body and periphery types, while in other weather types, most models have western systematic errors. For the evaluation of temporal characteristics, all the models have the highest accuracy in forecasting the start time of precipitation, followed by the forecast of end time, and the accuracy in forecasting the peak time is relatively low.
2026,52(5):595-607, DOI: 10.7519/j.issn.1000-0526.2025.080601
Abstract:
Based on the S-band dual-polarization radar data from Qingpu (Shanghai), Nantong (Jiangsu), Hangzhou, Jiaxing, Huzhou and Ningbo (Zhejiang), the applicability evaluation of three volume coverage patterns (VCP21D, VCP11D and VCP216D) is assessed under general precipitation, severe convective and typhoon conditions. The evaluation is based on three methods, that is, the subjective identification of characteristic tracer factors, the interpolation of reflectivity factor isosurfaces, and the comparison of dual-radar wind field retrieval. The results indicate that the precipitation mode (VCP21D) and the convective modes (VCP11D and VCP216D） can accurately identify the 0℃ layer bright band characteristic. VCP21D, compared to VCP216D, shows better stability in recognizing the melting layer height, with a smaller standard deviation and a better match to actual conditions. The convective modes VCP11D and VCP216D can significantly enhance vertical observational resolution relative to the precipitation mode VCP21D. This improvement is crucial for detecting key severe weather phenomena, such as ZDR columns and mesoscale cyclones. Meanwhile, compared to VCP11D, the additional 1.0° elevation angle in VCP216D is particularly effective in capturing mesoscale features such as low-level gust fronts and sea breeze fronts. Also, this additional scan can eliminate the impact from ground clutter echoes for data quality improvement. In the comparison of isosurface interpolations the data from VCP11D and VCP216D are more detailed than that from VCP21D at the 5 km altitude. In the comparison of wind field retrieval, the availability and accuracy of the retrieved data, from the dual-radar wind field retrieval results of convective modes VCP11D and VCP216D are more significantly improved compared to those of the precipitation mode VCP21D.
Based on the S-band dual-polarization radar data from Qingpu (Shanghai), Nantong (Jiangsu), Hangzhou, Jiaxing, Huzhou and Ningbo (Zhejiang), the applicability evaluation of three volume coverage patterns (VCP21D, VCP11D and VCP216D) is assessed under general precipitation, severe convective and typhoon conditions. The evaluation is based on three methods, that is, the subjective identification of characteristic tracer factors, the interpolation of reflectivity factor isosurfaces, and the comparison of dual-radar wind field retrieval. The results indicate that the precipitation mode (VCP21D) and the convective modes (VCP11D and VCP216D） can accurately identify the 0℃ layer bright band characteristic. VCP21D, compared to VCP216D, shows better stability in recognizing the melting layer height, with a smaller standard deviation and a better match to actual conditions. The convective modes VCP11D and VCP216D can significantly enhance vertical observational resolution relative to the precipitation mode VCP21D. This improvement is crucial for detecting key severe weather phenomena, such as ZDR columns and mesoscale cyclones. Meanwhile, compared to VCP11D, the additional 1.0° elevation angle in VCP216D is particularly effective in capturing mesoscale features such as low-level gust fronts and sea breeze fronts. Also, this additional scan can eliminate the impact from ground clutter echoes for data quality improvement. In the comparison of isosurface interpolations the data from VCP11D and VCP216D are more detailed than that from VCP21D at the 5 km altitude. In the comparison of wind field retrieval, the availability and accuracy of the retrieved data, from the dual-radar wind field retrieval results of convective modes VCP11D and VCP216D are more significantly improved compared to those of the precipitation mode VCP21D.
2026,52(5):608-620, DOI: 10.7519/j.issn.1000-0526.2025.122001
Abstract:
In mid-December 2023, Shanxi Province experienced a weather event of low temperature, rain, snow and icing. On 13 December, wire icing occurred in Yuanqu County located in southern Shanxi, significantly disrupting people’s lives and production activities. Using conventional meteorological observations, Doppler weather radar data and the ERA5 reanalysis datasets, this paper investigates the formation mechanism of this serious disaster event caused by wire icing. The results show that this wire icing event in Yuanqu was of the mixed rime and glaze type, which was caused by the combined effects of short-duration freezing rain in the early stage and prolonged freezing fog in the subsequent period. Freezing fog played a more significant role than freezing rain. In the north frontal zone at 500 hPa, the horizontal trough in front of the high pressure ridge near the Ural Mountains and a deep cold vortex near the Sea of Okhotsk both remained stable with less movement. The short-wave trough ahead of the bottom of the horizontal trough moved rapidly eastward into Shanxi, while in the south frontal zone, the southwest jet stream at 700 hPa was strong. The cold trough in the northeast-southwest direction at 850 hPa was located over North China, and the surface inverted-trough in Hetao Area developed violently, interacting with the return-flow weather pattern. Besides, the southwest warm-humid airflow ascended along the low-level cold air cushion, providing a favorable large-scale circulation background for the formation of freezing rain and freezing fog in Yuanqu. The temperature advection configuration of “upper warming and lower cooling” in vertical direction led to a “cold-warm-cold temperature” structure in Yuanqu from low to high levels, with the mid-level temperature above 0℃ and the lower-level temperature below 0℃. The short-term freezing rain in Yuanqu, triggered by the short-wave trough, was attributed to the melting mechanism. The vertical humidity advection configuration of “wet above and dry at bottom”, coupled with sinking motion together made the lower atmosphere highly saturated. Additionally, temperature inversion continued in the lower atmosphere. These conditions collectively facilitated the long-term persistence of freezing fog in Yuanqu. Abundant supercooled water droplets that had two phases of rapid growth continuously impinged on the wire surfaces, causing ice accretion to become thickened progressively. Southeasterly airflow ascended along the windward slopes of the horn-shaped terrain, and also played a certain role in promoting the thickening of accretion on wires.
In mid-December 2023, Shanxi Province experienced a weather event of low temperature, rain, snow and icing. On 13 December, wire icing occurred in Yuanqu County located in southern Shanxi, significantly disrupting people’s lives and production activities. Using conventional meteorological observations, Doppler weather radar data and the ERA5 reanalysis datasets, this paper investigates the formation mechanism of this serious disaster event caused by wire icing. The results show that this wire icing event in Yuanqu was of the mixed rime and glaze type, which was caused by the combined effects of short-duration freezing rain in the early stage and prolonged freezing fog in the subsequent period. Freezing fog played a more significant role than freezing rain. In the north frontal zone at 500 hPa, the horizontal trough in front of the high pressure ridge near the Ural Mountains and a deep cold vortex near the Sea of Okhotsk both remained stable with less movement. The short-wave trough ahead of the bottom of the horizontal trough moved rapidly eastward into Shanxi, while in the south frontal zone, the southwest jet stream at 700 hPa was strong. The cold trough in the northeast-southwest direction at 850 hPa was located over North China, and the surface inverted-trough in Hetao Area developed violently, interacting with the return-flow weather pattern. Besides, the southwest warm-humid airflow ascended along the low-level cold air cushion, providing a favorable large-scale circulation background for the formation of freezing rain and freezing fog in Yuanqu. The temperature advection configuration of “upper warming and lower cooling” in vertical direction led to a “cold-warm-cold temperature” structure in Yuanqu from low to high levels, with the mid-level temperature above 0℃ and the lower-level temperature below 0℃. The short-term freezing rain in Yuanqu, triggered by the short-wave trough, was attributed to the melting mechanism. The vertical humidity advection configuration of “wet above and dry at bottom”, coupled with sinking motion together made the lower atmosphere highly saturated. Additionally, temperature inversion continued in the lower atmosphere. These conditions collectively facilitated the long-term persistence of freezing fog in Yuanqu. Abundant supercooled water droplets that had two phases of rapid growth continuously impinged on the wire surfaces, causing ice accretion to become thickened progressively. Southeasterly airflow ascended along the windward slopes of the horn-shaped terrain, and also played a certain role in promoting the thickening of accretion on wires.
2026,52(5):621-630, DOI: 10.7519/j.issn.1000-0526.2026.011701
Abstract:
To improve snowfall forecast accuracy and aviation meteorological services at Lhasa Airport, by employing the improved Jenkinson-Collison (J-C) circulation type classification method, this paper classifies and diagnoses 56 snowfall events that occurred during 2013—2020 at Lhasa Airport. The results are that, with the improved method, a classification success rate of 92.9% is achieved, and three types, i.e., the cyclonic type (12.5%), low-pressure trough type (42.9%) and westerly advection type (37.5%) of snowfall events are identified. There are only 7.1% of snowfall events remaining unclassified-significantly lower than that by the traditional method. The characteristics of the three identified circulation types are significantly different. The cyclonic type, corresponding to plateau vortices, features the strongest dynamics and water vapor conditions, with the most average snowfall (3.4 mm) and longest duration (358 min). The low-pressure trough type, influenced by the southern branch trough, shows the most unstable atmospheric stratification but relatively weak dynamics and water vapor, resulting in the lowest mean snowfall (1.2 mm) and shortest duration (170 min). The westerly advection type, dominated by warm ridges and upper-level jets, has the most stable atmospheric stratification, with a “low-level convergence and upper-level divergence” moisture structure. Its intermediate snowfall indicators lie between those of the other two types, that is, the average snowfall is 1.8 mm and the duration is 280 min. These findings could provide a scientific basis for refined snowfall forecasting and help improve the aviation meteorological services at Lhasa Airport.
To improve snowfall forecast accuracy and aviation meteorological services at Lhasa Airport, by employing the improved Jenkinson-Collison (J-C) circulation type classification method, this paper classifies and diagnoses 56 snowfall events that occurred during 2013—2020 at Lhasa Airport. The results are that, with the improved method, a classification success rate of 92.9% is achieved, and three types, i.e., the cyclonic type (12.5%), low-pressure trough type (42.9%) and westerly advection type (37.5%) of snowfall events are identified. There are only 7.1% of snowfall events remaining unclassified-significantly lower than that by the traditional method. The characteristics of the three identified circulation types are significantly different. The cyclonic type, corresponding to plateau vortices, features the strongest dynamics and water vapor conditions, with the most average snowfall (3.4 mm) and longest duration (358 min). The low-pressure trough type, influenced by the southern branch trough, shows the most unstable atmospheric stratification but relatively weak dynamics and water vapor, resulting in the lowest mean snowfall (1.2 mm) and shortest duration (170 min). The westerly advection type, dominated by warm ridges and upper-level jets, has the most stable atmospheric stratification, with a “low-level convergence and upper-level divergence” moisture structure. Its intermediate snowfall indicators lie between those of the other two types, that is, the average snowfall is 1.8 mm and the duration is 280 min. These findings could provide a scientific basis for refined snowfall forecasting and help improve the aviation meteorological services at Lhasa Airport.
2026,52(5):631-640, DOI: 10.7519/j.issn.1000-0526.2026.042401
Abstract:
In February 2026, the Northern Hemisphere polar vortex exhibited a dipole pattern, with its primary center located over northern Canada and a secondary center over the region from Novaya Zemlya to the Sea of Okhotsk in the Eastern Hemisphere. Most mid-to-high latitude areas of China were situated in the front of high pressure ridge, where geopotential heights were dominated by positive anomalies. The main body of cold air activity was relatively weak, resulting in above-normal temperatures in most parts of China. The national average temperature was 2.1℃ higher than the corresponding climatological normal, ranking the third highest for February since 1961. The position and intensity of the southern branch trough this month were close to normal. With the phased cold air activities in northern China, warm and cold air masses converged frequently over northern China, leading to numerous rain and snow events in the northern regions. Four notable precipitation processes occurred nationwide in February, with uneven spatial distribution. Precipitation was above normal in southern North China, Huanghuai Region, south-eastern Northwest China, northern Xinjiang, northeastern Inner Mongolia and northern Northeast China, while below-normal precipitation was observed across most other areas. In addition, two cold wave events, two sand-dust events and five heavy fog events successively affected China in this month. Among them, the sand-dust event from 20 to 23 was the most extensive and intense dust weather process, and the rain and snow event from 25 to 27 was the heaviest and most extensive precipitation process in February
In February 2026, the Northern Hemisphere polar vortex exhibited a dipole pattern, with its primary center located over northern Canada and a secondary center over the region from Novaya Zemlya to the Sea of Okhotsk in the Eastern Hemisphere. Most mid-to-high latitude areas of China were situated in the front of high pressure ridge, where geopotential heights were dominated by positive anomalies. The main body of cold air activity was relatively weak, resulting in above-normal temperatures in most parts of China. The national average temperature was 2.1℃ higher than the corresponding climatological normal, ranking the third highest for February since 1961. The position and intensity of the southern branch trough this month were close to normal. With the phased cold air activities in northern China, warm and cold air masses converged frequently over northern China, leading to numerous rain and snow events in the northern regions. Four notable precipitation processes occurred nationwide in February, with uneven spatial distribution. Precipitation was above normal in southern North China, Huanghuai Region, south-eastern Northwest China, northern Xinjiang, northeastern Inner Mongolia and northern Northeast China, while below-normal precipitation was observed across most other areas. In addition, two cold wave events, two sand-dust events and five heavy fog events successively affected China in this month. Among them, the sand-dust event from 20 to 23 was the most extensive and intense dust weather process, and the rain and snow event from 25 to 27 was the heaviest and most extensive precipitation process in February
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Available online: May 29, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.052501
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During the prolonged operation of weather radar systems, equipment malfunctions and external interferences frequently result in abnormal radar echoes. These anomalies impair the radar’s effectiveness in monitoring, warning, and forecasting severe weather events. To address this issue, this study manually labeled radial and circular types of abnormal echoes based on historical data, and utilized data augmentation techniques to construct a radar mosaic dataset of abnormal echoes consisting of 20,000 images. Building upon the advanced semantic segmentation model DeepLabv3+, we introduced several optimizations: first, a streamlined ResNet50 backbone with reduced parameters was adopted; second, the SimAM attention mechanism to enhance feature extraction and emphasize critical features was incorporated; third, intermediate layers in the decoder path are added to integrate additional details and contextual information through layer fusion. Consequently, the DeepLab-ARER model for recognition of abnormal radar echo in radar mosaic data was developed. Experimental evaluations demonstrated that DeepLab-ARER achieved superior performance in identifying both types of abnormal echoes, with a mean pixel accuracy (MPA) of 96.75% and a mean intersection-over-union (MIOU) of 93.95%, representing significant improvements over the original DeepLabv3+ model. This research provides robust technical solutions for the automatic recognition of abnormal echoes in radar mosaic data and establishes a solid foundation for enhancing the quality of radar mosaic data in operational applications.
During the prolonged operation of weather radar systems, equipment malfunctions and external interferences frequently result in abnormal radar echoes. These anomalies impair the radar’s effectiveness in monitoring, warning, and forecasting severe weather events. To address this issue, this study manually labeled radial and circular types of abnormal echoes based on historical data, and utilized data augmentation techniques to construct a radar mosaic dataset of abnormal echoes consisting of 20,000 images. Building upon the advanced semantic segmentation model DeepLabv3+, we introduced several optimizations: first, a streamlined ResNet50 backbone with reduced parameters was adopted; second, the SimAM attention mechanism to enhance feature extraction and emphasize critical features was incorporated; third, intermediate layers in the decoder path are added to integrate additional details and contextual information through layer fusion. Consequently, the DeepLab-ARER model for recognition of abnormal radar echo in radar mosaic data was developed. Experimental evaluations demonstrated that DeepLab-ARER achieved superior performance in identifying both types of abnormal echoes, with a mean pixel accuracy (MPA) of 96.75% and a mean intersection-over-union (MIOU) of 93.95%, representing significant improvements over the original DeepLabv3+ model. This research provides robust technical solutions for the automatic recognition of abnormal echoes in radar mosaic data and establishes a solid foundation for enhancing the quality of radar mosaic data in operational applications.
Available online: May 27, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.051303
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Abstract:From 23 to 29 July 2025 (referred to as "25.7"), extraordinary heavy rainfall occurred in Beijing and other North China areas. Based on multi-source observational data, ERA5 reanalysis, RISE, and RMAPS-NOW high-resolution grid analysis data, this paper analyses the characteristics of rainfall stages, the fine features and causes of extreme rainstorm convection. The results showing: (1) The "25.7" heavy rainfall occurred in late July under a stable circulation background where the Subtropical-High （SH） pressure was significantly shifted westward and northward and stronger than usual, with active tropical systems on its southern side. The four stages of rainfall corresponded to the periphery of the SH, the northward lift of the SH, the slight southward retreat of the SH, and the influence of an upper-level trough and cold air.The lower atmosphere had warm anomalies, with a positive 925hPa water vapour flux anomaly and a significantly enhanced water vapour convergence area in northern and eastern Beijing, creating conditions of high temperature, high humidity and high CAPE. (2) This heavy rain is characterised by its long duration, large cumulative rainfall, nocturnal occurrence, localised and extremity. Extreme heavy rain occurred in the second phase (night of the 26th) and the third phase (night of the 27th), concentrated in the northern mountainous areas, featuring a "weak overall but strong locally" pattern, accompanied by extreme hourly heavy rainfall. (3) The radar echoes in the second stage of precipitation showed obvious backward triggering and "training effect" characteristics, The second phase of precipitation echoes is characterised by rearward convection triggering and the "training effect", lasting 4-5 hours, with heavy rain occurring at altitudes of 200-600 m; while the third phase is characterised by continuous generation and dissipation of convection within banded echoes, lasting more than ten hours, with heavy rain mainly below 300 m altitude. (4) A conceptual model of the "25.7" extreme rainfall has been established. The exit area of the meso-scale Low Level Jet, the convergence of southerly and southeasterly winds in the the boundary layer , as well as the horn-shaped terrain and windward slopes of the mountains, resulted in local deep-level convergence and uplift, providing the favourable dynamic and topographic conditions for extreme rainfall in the second and third stages. In addition, the release of latent heat in the middle and upper layers of the atmosphere had a positive feedback effect on the intensification of rainfall. However, the extreme rainfall conditions between the second and three stages were also different: the former involved the warm region heavy rainfall at the edge of the SH, where the southern boundary-layer jet exit area formed a line of convergence along the northern shallow mountains, which was conducive to the triggering and stagnation of backward convection, and the extreme rainfall was caused by the "training effect"; the third stage was influenced by a weak cold air and was related to dynamic convergence on the southern side of a shear line and a meso-scale low vortex.
Abstract:From 23 to 29 July 2025 (referred to as "25.7"), extraordinary heavy rainfall occurred in Beijing and other North China areas. Based on multi-source observational data, ERA5 reanalysis, RISE, and RMAPS-NOW high-resolution grid analysis data, this paper analyses the characteristics of rainfall stages, the fine features and causes of extreme rainstorm convection. The results showing: (1) The "25.7" heavy rainfall occurred in late July under a stable circulation background where the Subtropical-High （SH） pressure was significantly shifted westward and northward and stronger than usual, with active tropical systems on its southern side. The four stages of rainfall corresponded to the periphery of the SH, the northward lift of the SH, the slight southward retreat of the SH, and the influence of an upper-level trough and cold air.The lower atmosphere had warm anomalies, with a positive 925hPa water vapour flux anomaly and a significantly enhanced water vapour convergence area in northern and eastern Beijing, creating conditions of high temperature, high humidity and high CAPE. (2) This heavy rain is characterised by its long duration, large cumulative rainfall, nocturnal occurrence, localised and extremity. Extreme heavy rain occurred in the second phase (night of the 26th) and the third phase (night of the 27th), concentrated in the northern mountainous areas, featuring a "weak overall but strong locally" pattern, accompanied by extreme hourly heavy rainfall. (3) The radar echoes in the second stage of precipitation showed obvious backward triggering and "training effect" characteristics, The second phase of precipitation echoes is characterised by rearward convection triggering and the "training effect", lasting 4-5 hours, with heavy rain occurring at altitudes of 200-600 m; while the third phase is characterised by continuous generation and dissipation of convection within banded echoes, lasting more than ten hours, with heavy rain mainly below 300 m altitude. (4) A conceptual model of the "25.7" extreme rainfall has been established. The exit area of the meso-scale Low Level Jet, the convergence of southerly and southeasterly winds in the the boundary layer , as well as the horn-shaped terrain and windward slopes of the mountains, resulted in local deep-level convergence and uplift, providing the favourable dynamic and topographic conditions for extreme rainfall in the second and third stages. In addition, the release of latent heat in the middle and upper layers of the atmosphere had a positive feedback effect on the intensification of rainfall. However, the extreme rainfall conditions between the second and three stages were also different: the former involved the warm region heavy rainfall at the edge of the SH, where the southern boundary-layer jet exit area formed a line of convergence along the northern shallow mountains, which was conducive to the triggering and stagnation of backward convection, and the extreme rainfall was caused by the "training effect"; the third stage was influenced by a weak cold air and was related to dynamic convergence on the southern side of a shear line and a meso-scale low vortex.
Available online: May 21, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.051302
Abstract:
Addressing the persistent demand for historical analogue references in operational weather forecasting and the deficiencies of traditional retrieval methods in efficiency and objectivity, this paper proposes a rapid retrieval technology for similar historical weather events based on image fingerprinting and multi-element synergy. Technology initially employs fingerprint similarity detection algorithms from imageology to establish a similarity quantification method for single weather element fields. Subsequently, guided by synoptic principles and considering the coupling characteristics between upper-air circulation and surface element fields, a multi-element synergistic query algorithm is designed to more accurately identify historical precipitation fields and corresponding circulation patterns like a target weather process. Based on these techniques, a historical similar weather retrieval platform was developed using a "Cloud + Client" architecture, enabling efficient retrieval of historical analogues. The platform has been operationally trialed at the National Meteorological Center, demonstrating good application potential and practical value in forecasting several weather events. Statistical verification indicates that the similar cases retrieved by this method significantly outperform climatological states in terms of anomaly correlation coefficient and root mean square error. Finally, this paper discusses future development directions for technology, particularly in algorithm optimization, objective evaluation, and deepening application.
Addressing the persistent demand for historical analogue references in operational weather forecasting and the deficiencies of traditional retrieval methods in efficiency and objectivity, this paper proposes a rapid retrieval technology for similar historical weather events based on image fingerprinting and multi-element synergy. Technology initially employs fingerprint similarity detection algorithms from imageology to establish a similarity quantification method for single weather element fields. Subsequently, guided by synoptic principles and considering the coupling characteristics between upper-air circulation and surface element fields, a multi-element synergistic query algorithm is designed to more accurately identify historical precipitation fields and corresponding circulation patterns like a target weather process. Based on these techniques, a historical similar weather retrieval platform was developed using a "Cloud + Client" architecture, enabling efficient retrieval of historical analogues. The platform has been operationally trialed at the National Meteorological Center, demonstrating good application potential and practical value in forecasting several weather events. Statistical verification indicates that the similar cases retrieved by this method significantly outperform climatological states in terms of anomaly correlation coefficient and root mean square error. Finally, this paper discusses future development directions for technology, particularly in algorithm optimization, objective evaluation, and deepening application.
Available online: May 20, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.051401
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Using conventional observations, dense surface automatic station data, NCEP/FNL reanalysis, Doppler radar data, and WRF model simulations, this study investigates a severe convective event triggered by the collision between a gust front and a sea breeze front in Xiamen, China, and examines its underlying mechanisms. The results show that the event occurred at the edge of the subtropical high, where upper-level divergence overlapped with low-level convergence. An unstable thermodynamic stratification characterized by dry upper levels and moist lower levels, together with strong thermal instability, provided a favorable environment for convective development. The cold outflow generated by earlier convective cells expanded outward to form a gust front, while the sea breeze front developed continuously along the Xiamen coast. After the two boundaries collided near the urban area of Xiamen, low-level convergence and local lifting were markedly enhanced, thereby initiating convection. WRF simulations further indicate that following the collision, the shallow-layer specific humidity in the collision region increased by about 2.5 g·kg?1, the maximum convective available potential energy increased by more than 1000 J·kg?1, and the vorticity intensified to 25×10?? s?1, suggesting significant enhancement of moisture supply, instability, and dynamic lifting. The convergence-induced ascent allowed air parcels to overcome the level of free convection, thereby initiating and sustaining convection. Subsequently, convective cells near the collision zone merged and triggered a cloud-bridge cell, which further developed into a multicellular merging process and produced short-duration heavy rainfall in Xiamen. Thereafter, a surface convergence line and shallow shear system on the rear side of the collision region maintained a deeper convergence-ascent structure. In combination with sufficient moisture and instability, the model indicated a subsequent convective regeneration process. The findings suggest that the collision between a gust front and a sea breeze front can trigger and sustain severe convection through enhanced low-level convergence, moisture transport, and instability, providing useful implications for nowcasting and warning of local severe convection in Xiamen and other coastal areas.
Using conventional observations, dense surface automatic station data, NCEP/FNL reanalysis, Doppler radar data, and WRF model simulations, this study investigates a severe convective event triggered by the collision between a gust front and a sea breeze front in Xiamen, China, and examines its underlying mechanisms. The results show that the event occurred at the edge of the subtropical high, where upper-level divergence overlapped with low-level convergence. An unstable thermodynamic stratification characterized by dry upper levels and moist lower levels, together with strong thermal instability, provided a favorable environment for convective development. The cold outflow generated by earlier convective cells expanded outward to form a gust front, while the sea breeze front developed continuously along the Xiamen coast. After the two boundaries collided near the urban area of Xiamen, low-level convergence and local lifting were markedly enhanced, thereby initiating convection. WRF simulations further indicate that following the collision, the shallow-layer specific humidity in the collision region increased by about 2.5 g·kg?1, the maximum convective available potential energy increased by more than 1000 J·kg?1, and the vorticity intensified to 25×10?? s?1, suggesting significant enhancement of moisture supply, instability, and dynamic lifting. The convergence-induced ascent allowed air parcels to overcome the level of free convection, thereby initiating and sustaining convection. Subsequently, convective cells near the collision zone merged and triggered a cloud-bridge cell, which further developed into a multicellular merging process and produced short-duration heavy rainfall in Xiamen. Thereafter, a surface convergence line and shallow shear system on the rear side of the collision region maintained a deeper convergence-ascent structure. In combination with sufficient moisture and instability, the model indicated a subsequent convective regeneration process. The findings suggest that the collision between a gust front and a sea breeze front can trigger and sustain severe convection through enhanced low-level convergence, moisture transport, and instability, providing useful implications for nowcasting and warning of local severe convection in Xiamen and other coastal areas.
Available online: May 19, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.050702
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To address the characteristics of X-band phased array radar, which offers high spatiotemporal resolution but limited observation coverage and various data reliability errors, this study proposes a high-quality data fusion method with S-band operational radar. First, the optical flow method is applied to extrapolate the motion trends of S-band radar data, enhancing its temporal resolution from the original 6 minutes to 1.5 minutes, synchronized with X-band radar. Subsequently, the optimal interpolation algorithm and pyramid transform algorithm are employed for spatial fusion of dual-band radar data, yielding the corresponding products SXnet-O and SXnet-K. Statistical analysis based on nearly 5,000 radar volume scanscases from the Guangdong-Hong Kong-Macao Greater Bay Area radar network during May–June 2022 demonstrates that the fused data achieve a 12% improvement in temporal correlation coefficient and a 28% reduction in root mean square error compared to the original X-band data. The spatial coverage reaches 96% of the union area of both radars, approximately 30% higher than that of a single radar. Comparative results indicate that SXnet-O significantly outperforms SXnet-K in system bias control (92% of deviations within ±2 dB), parameter consistency, and boundary stability. For data correction, SXnet-O reduces the deviation from the S-band reference by 5% compared to the original X-band data while effectively integrating the structural precision of X-band with the observational stability of S-band. This method provides a methodological foundation for data fusion applications in dense phased array weather radar networks.
To address the characteristics of X-band phased array radar, which offers high spatiotemporal resolution but limited observation coverage and various data reliability errors, this study proposes a high-quality data fusion method with S-band operational radar. First, the optical flow method is applied to extrapolate the motion trends of S-band radar data, enhancing its temporal resolution from the original 6 minutes to 1.5 minutes, synchronized with X-band radar. Subsequently, the optimal interpolation algorithm and pyramid transform algorithm are employed for spatial fusion of dual-band radar data, yielding the corresponding products SXnet-O and SXnet-K. Statistical analysis based on nearly 5,000 radar volume scanscases from the Guangdong-Hong Kong-Macao Greater Bay Area radar network during May–June 2022 demonstrates that the fused data achieve a 12% improvement in temporal correlation coefficient and a 28% reduction in root mean square error compared to the original X-band data. The spatial coverage reaches 96% of the union area of both radars, approximately 30% higher than that of a single radar. Comparative results indicate that SXnet-O significantly outperforms SXnet-K in system bias control (92% of deviations within ±2 dB), parameter consistency, and boundary stability. For data correction, SXnet-O reduces the deviation from the S-band reference by 5% compared to the original X-band data while effectively integrating the structural precision of X-band with the observational stability of S-band. This method provides a methodological foundation for data fusion applications in dense phased array weather radar networks.
Available online: May 19, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.051301
Abstract:
Based on the surface meteorological observation precipitation data and the ERA5 reanalysis data, the rainstorm that occurred in North China from July 23 to 30 in 2025 is investigated from the perspectives of circulation evolution and water vapor conditions. The findings reveal that the rainstorm was characterized by its prolonged duration and extensive impact area. The spatial distribution of precipitation markedly differed from that of previous rainstorms. The main precipitation zone stretched over 1,000 km from east to west, exhibiting a nearly zonal pattern. Two main rain belts were identified, situated in the Plateau (a secondary terrain region) and the plain area (a tertiary terrain region) of North China, respectively.The anomalous large-scale circulation patterns were observed during this precipitation event. The abnormally persistent northward-shifted Western Pacific Subtropical High, a stagnant westerly shortwave trough, and the shear lines generated in the lower troposphere were the key weather systems directly influencing the rainstorm. Throughout the precipitation evolution, the South Asian High and the Western Pacific Subtropical High underwent a reciprocal advancing and retreating process. The low-latitude weather system remained active, with typhoons Francisco and Co-may emerging continuously near East China coastlines, supplying ample water vapor for the precipitation. The westward expansion of the Western Pacific Subtropical High and its surrounding anticyclonic circulation dominated the eastern side of the Qinghai-Tibet Plateau, fostering two water vapor transport belts and convergence zones within the main precipitation area, which corresponded to the two rain belts in the secondary and tertiary terrain regions.The water vapor budget analysis indicates that the primary sources of water vapor in the tertiary terrain region were its southern and western boundaries (with outflow from the secondary terrain region). Compared to the secondary terrain region, the tertiary terrain region exhibited weaker water vapor inflow and net gain, it demonstrated a higher precipitation conversion rate and greater precipitation volume.
Based on the surface meteorological observation precipitation data and the ERA5 reanalysis data, the rainstorm that occurred in North China from July 23 to 30 in 2025 is investigated from the perspectives of circulation evolution and water vapor conditions. The findings reveal that the rainstorm was characterized by its prolonged duration and extensive impact area. The spatial distribution of precipitation markedly differed from that of previous rainstorms. The main precipitation zone stretched over 1,000 km from east to west, exhibiting a nearly zonal pattern. Two main rain belts were identified, situated in the Plateau (a secondary terrain region) and the plain area (a tertiary terrain region) of North China, respectively.The anomalous large-scale circulation patterns were observed during this precipitation event. The abnormally persistent northward-shifted Western Pacific Subtropical High, a stagnant westerly shortwave trough, and the shear lines generated in the lower troposphere were the key weather systems directly influencing the rainstorm. Throughout the precipitation evolution, the South Asian High and the Western Pacific Subtropical High underwent a reciprocal advancing and retreating process. The low-latitude weather system remained active, with typhoons Francisco and Co-may emerging continuously near East China coastlines, supplying ample water vapor for the precipitation. The westward expansion of the Western Pacific Subtropical High and its surrounding anticyclonic circulation dominated the eastern side of the Qinghai-Tibet Plateau, fostering two water vapor transport belts and convergence zones within the main precipitation area, which corresponded to the two rain belts in the secondary and tertiary terrain regions.The water vapor budget analysis indicates that the primary sources of water vapor in the tertiary terrain region were its southern and western boundaries (with outflow from the secondary terrain region). Compared to the secondary terrain region, the tertiary terrain region exhibited weaker water vapor inflow and net gain, it demonstrated a higher precipitation conversion rate and greater precipitation volume.
Available online: May 18, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.050703
Abstract:
Using station observation data and the NCEP/NCAR reanalysis data, this study analyzes the main climatic characteristics, large-scale atmospheric circulation anomalies, and East Asian winter monsoon features in China during the winter of 2025/2026, with a focus on the causes of the abnormally active dust weather in February. The results show that in the winter of 2025/2026, the average temperature was –1.5°C, which was 1.5°C higher than the climatological average, ranking as the second highest for the same period since 1961. The average precipitation was 27.4 mm, 35.3% below the climatological average, with a spatial distribution characterized by more precipitation in the north and less in the south. The 500 hPa geopotential height field over the mid–high latitudes of Eurasia were dominated by zonal circulation, with relatively straight westerly isohypses, and the East Asian winter monsoon intensity was weaker than normal. During the winter, a total of six dust weather processes affected China, which was 4.2 more than the climatological average (1.8). Among them, there were three dust storm processes, 2.7 more than the climatological average (0.3), and the number of dust days reached 7.7, the highest for winter since 1991. The cause analysis indicates that the dust source regions experienced significant warm and dry conditions, with below-average precipitation and above-average temperatures, leading to low vegetation coverage and a substantial reduction in surface resistance to wind erosion, thereby providing abundant material conditions for dust storms. Against this background, the synergistic effect of strong cold air and the Mongolian cyclone generated a large pressure gradient and triggered extreme gale winds, which, combined with enhanced thermal lifting due to large temperature differences between upper and lower levels, resulted in large a。mounts of dust being lifted into the atmosphere and transported downstream. Global climate warming has further exacerbated the drying trend in the dust source regions, increasing the frequency of the superposition of such warm-dry conditions
Using station observation data and the NCEP/NCAR reanalysis data, this study analyzes the main climatic characteristics, large-scale atmospheric circulation anomalies, and East Asian winter monsoon features in China during the winter of 2025/2026, with a focus on the causes of the abnormally active dust weather in February. The results show that in the winter of 2025/2026, the average temperature was –1.5°C, which was 1.5°C higher than the climatological average, ranking as the second highest for the same period since 1961. The average precipitation was 27.4 mm, 35.3% below the climatological average, with a spatial distribution characterized by more precipitation in the north and less in the south. The 500 hPa geopotential height field over the mid–high latitudes of Eurasia were dominated by zonal circulation, with relatively straight westerly isohypses, and the East Asian winter monsoon intensity was weaker than normal. During the winter, a total of six dust weather processes affected China, which was 4.2 more than the climatological average (1.8). Among them, there were three dust storm processes, 2.7 more than the climatological average (0.3), and the number of dust days reached 7.7, the highest for winter since 1991. The cause analysis indicates that the dust source regions experienced significant warm and dry conditions, with below-average precipitation and above-average temperatures, leading to low vegetation coverage and a substantial reduction in surface resistance to wind erosion, thereby providing abundant material conditions for dust storms. Against this background, the synergistic effect of strong cold air and the Mongolian cyclone generated a large pressure gradient and triggered extreme gale winds, which, combined with enhanced thermal lifting due to large temperature differences between upper and lower levels, resulted in large a。mounts of dust being lifted into the atmosphere and transported downstream. Global climate warming has further exacerbated the drying trend in the dust source regions, increasing the frequency of the superposition of such warm-dry conditions
Zhang Zeyu, Bai Lanqiang, Cai Kanglong, Huang Shuting, Huang Xianxiang, Yang Lei, Xu Zongheng, Wang Xiuming, zhangtao, Li Cailing, ZHANG Jingjing
Available online: May 11, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.050701
Abstract:
Basic characteristics of tornadoes in China during 2024 were presented primarily based on an integrated analysis of multi-source data and on-site ground damage surveys. Despite potential underestimation arising from observational limitations and the inherently stochastic nature of public reports, a total of 78 tornadoes and 40 waterspouts were identified. Tornadoes were primarily concentrated in Northeast China, the Beijing-Tianjin-Hebei region, the Huang-Huai area, and the Pearl River Delta. Most occurred between June and September, with July being the most active month and a diurnal peak in the afternoon. The intensities of 51 tornadoes were assessed based on damage surveys, including 12 rated EF0, 26 EF1, 9 EF2, and 4 EF3. Waterspouts were primarily observed along the southern coast and over Bohai Bay, with peak occurrence in August and a pronounced diurnal maximum around 0600 Beijing time. The year 2024 was characterized by a high frequency of tornado outbreaks, with 4 major events accounting for 44% of the annual total tornado occurrences. Notably, a tornado outbreak associated with an upper-level trough occurred in Shandong Province on 5 July, making it the province with the highest tornado occurrence that year. Under the influence of the strong 2023 winter El Ni?o event, convective available potential energy in southern China in spring 2024 was significantly higher than the climatological mean. Supported by this favorable thermodynamic environment, 67% of Guangdong"s tornadoes occurred from late March to late April, reflecting an unusually high early-spring concentration. Additionally, a societal high-impact nocturnal severe weather event in Nanchang underscores the persistent difficulties in identifying and confirming nighttime tornadoes.
Basic characteristics of tornadoes in China during 2024 were presented primarily based on an integrated analysis of multi-source data and on-site ground damage surveys. Despite potential underestimation arising from observational limitations and the inherently stochastic nature of public reports, a total of 78 tornadoes and 40 waterspouts were identified. Tornadoes were primarily concentrated in Northeast China, the Beijing-Tianjin-Hebei region, the Huang-Huai area, and the Pearl River Delta. Most occurred between June and September, with July being the most active month and a diurnal peak in the afternoon. The intensities of 51 tornadoes were assessed based on damage surveys, including 12 rated EF0, 26 EF1, 9 EF2, and 4 EF3. Waterspouts were primarily observed along the southern coast and over Bohai Bay, with peak occurrence in August and a pronounced diurnal maximum around 0600 Beijing time. The year 2024 was characterized by a high frequency of tornado outbreaks, with 4 major events accounting for 44% of the annual total tornado occurrences. Notably, a tornado outbreak associated with an upper-level trough occurred in Shandong Province on 5 July, making it the province with the highest tornado occurrence that year. Under the influence of the strong 2023 winter El Ni?o event, convective available potential energy in southern China in spring 2024 was significantly higher than the climatological mean. Supported by this favorable thermodynamic environment, 67% of Guangdong"s tornadoes occurred from late March to late April, reflecting an unusually high early-spring concentration. Additionally, a societal high-impact nocturnal severe weather event in Nanchang underscores the persistent difficulties in identifying and confirming nighttime tornadoes.
Available online: May 06, 2026 , DOI: 10.7519/j.issn.1000-0526.2025.121901
Abstract:
Current deep learning-based QPE methods using radar reflectivity factors mostly adopt global mapping strategies, which to some extent limits the model’s ability to analyze local precipitation features. To this end, this study proposes a Dual-branch Composite Wavelet Attention UNet (DCWA-UNet). The model is mainly improved from two aspects: (1) A hybrid architecture consisting of a dual-branch encoder (main branch + simplified convolutional downsampling branch) and a feature aggregation subnetwork is designed, enabling end-to-end mapping from radar volume scan data to station precipitation intensity, thereby constructing a station-centered sample system. (2) A Composite Wavelet Attention Module (CWAM) is introduced to enhance the model’s representation capability for radar echoes through multi-scale feature decomposition and dynamic weight allocation; meanwhile, a weighted mean square error loss function is adopted to emphasize the gradient contribution of heavy precipitation. Using ground-based precipitation observation and radar observation data over the Sichuan Basin during the summers of 2019–2021, a dataset containing 4020 samples is constructed for model training and testing, and comparative experiments are conducted with deep learning models such as SimVP. The results show that DCWA-UNet achieves obvious comprehensive performance advantages under different precipitation intensities, with particularly significant improvements in Critical Success Index and Mean Absolute Error within the precipitation range of [0.1, 30) mm·h?1: for precipitation intensities of [5, 10) mm·h?1, the CSI of DCWA-UNet is significantly higher than that of SimVP and other comparative models, and the MAE is reduced by 4.9% compared to SimVP; for [10, 30) mm·h?1 precipitation, the CSI is improved by 4.0% and the MAE is reduced by 4.0% compared to SimVP, while the false alarm rate is the lowest among all comparative models.
Current deep learning-based QPE methods using radar reflectivity factors mostly adopt global mapping strategies, which to some extent limits the model’s ability to analyze local precipitation features. To this end, this study proposes a Dual-branch Composite Wavelet Attention UNet (DCWA-UNet). The model is mainly improved from two aspects: (1) A hybrid architecture consisting of a dual-branch encoder (main branch + simplified convolutional downsampling branch) and a feature aggregation subnetwork is designed, enabling end-to-end mapping from radar volume scan data to station precipitation intensity, thereby constructing a station-centered sample system. (2) A Composite Wavelet Attention Module (CWAM) is introduced to enhance the model’s representation capability for radar echoes through multi-scale feature decomposition and dynamic weight allocation; meanwhile, a weighted mean square error loss function is adopted to emphasize the gradient contribution of heavy precipitation. Using ground-based precipitation observation and radar observation data over the Sichuan Basin during the summers of 2019–2021, a dataset containing 4020 samples is constructed for model training and testing, and comparative experiments are conducted with deep learning models such as SimVP. The results show that DCWA-UNet achieves obvious comprehensive performance advantages under different precipitation intensities, with particularly significant improvements in Critical Success Index and Mean Absolute Error within the precipitation range of [0.1, 30) mm·h?1: for precipitation intensities of [5, 10) mm·h?1, the CSI of DCWA-UNet is significantly higher than that of SimVP and other comparative models, and the MAE is reduced by 4.9% compared to SimVP; for [10, 30) mm·h?1 precipitation, the CSI is improved by 4.0% and the MAE is reduced by 4.0% compared to SimVP, while the false alarm rate is the lowest among all comparative models.
Available online: April 27, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.030401
Abstract:
Northern Ningxia is situated in the temperate continental climate zone of northwestern China, where complex topography and the climatological characteristics of warm-season convective storms (CS) remain not fully understood. This study utilizes CINRAD/CD radar products and sounding data from Yinchuan during May–September from 2011 to 2016 to investigate the climatological characteristics of CS in northern Ningxia under different prevailing wind directions at 500 hPa and 700 hPa. For the first time in this research domain, we present a comprehensive analysis integrating mean circulation patterns, convective environments, and CS intensity. Results demonstrate that solar radiative heating and topographic forcing from the Helan Mountains dominate the formation of CS climatological characteristics in northern Ningxia. Upon this foundation, dynamically varying prevailing winds induce more complex and diverse patterns in CS occurrence frequency, occurrence efficiency (defined as the ratio of CS occurrence frequency under a specific prevailing wind direction to the total frequency of that wind direction), diurnal variation, and spatial distribution. Notably, when southwesterly winds prevail at 500 hPa while easterly winds prevail at 700 hPa, the influence of prevailing winds becomes particularly pronounced. The mean 500 hPa circulation pattern associated with CS occurrence under a given prevailing wind direction characterizes the typical synoptic–scale systems and convective environments favorable for CS development under that flow regime, thereby directly determining CS occurrence efficiency and intensity. When northerly or northwesterly winds prevail at 500 hPa, northern Ningxia is positioned behind the trough, resulting in the lowest CS occurrence efficiency, the highest CAPE and CIN, and the strongest CS intensity. Under southerly or southwesterly wind regimes, the region is situated between the ridge and trough, where favorable moisture transport conditions lead to maximum CS occurrence efficiency; however, the minimal vertical temperature difference results in relatively weaker CS development. During prevailing westerly flows, the mid–latitude circulation exhibits zonal characteristics with frequent upstream shortwave trough activity, yielding intermediate levels of CS occurrence efficiency, CS intensity, and environmental parameters. At 700 hPa, differences in CS occurrence efficiency and intensity across various prevailing wind directions are relatively smaller, with CS intensity showing a strong correspondence to the vertical temperature gradient.
Northern Ningxia is situated in the temperate continental climate zone of northwestern China, where complex topography and the climatological characteristics of warm-season convective storms (CS) remain not fully understood. This study utilizes CINRAD/CD radar products and sounding data from Yinchuan during May–September from 2011 to 2016 to investigate the climatological characteristics of CS in northern Ningxia under different prevailing wind directions at 500 hPa and 700 hPa. For the first time in this research domain, we present a comprehensive analysis integrating mean circulation patterns, convective environments, and CS intensity. Results demonstrate that solar radiative heating and topographic forcing from the Helan Mountains dominate the formation of CS climatological characteristics in northern Ningxia. Upon this foundation, dynamically varying prevailing winds induce more complex and diverse patterns in CS occurrence frequency, occurrence efficiency (defined as the ratio of CS occurrence frequency under a specific prevailing wind direction to the total frequency of that wind direction), diurnal variation, and spatial distribution. Notably, when southwesterly winds prevail at 500 hPa while easterly winds prevail at 700 hPa, the influence of prevailing winds becomes particularly pronounced. The mean 500 hPa circulation pattern associated with CS occurrence under a given prevailing wind direction characterizes the typical synoptic–scale systems and convective environments favorable for CS development under that flow regime, thereby directly determining CS occurrence efficiency and intensity. When northerly or northwesterly winds prevail at 500 hPa, northern Ningxia is positioned behind the trough, resulting in the lowest CS occurrence efficiency, the highest CAPE and CIN, and the strongest CS intensity. Under southerly or southwesterly wind regimes, the region is situated between the ridge and trough, where favorable moisture transport conditions lead to maximum CS occurrence efficiency; however, the minimal vertical temperature difference results in relatively weaker CS development. During prevailing westerly flows, the mid–latitude circulation exhibits zonal characteristics with frequent upstream shortwave trough activity, yielding intermediate levels of CS occurrence efficiency, CS intensity, and environmental parameters. At 700 hPa, differences in CS occurrence efficiency and intensity across various prevailing wind directions are relatively smaller, with CS intensity showing a strong correspondence to the vertical temperature gradient.
Available online: April 24, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.041701
Abstract:
Based on the precipitation data of 155 meteorological stations in the eastern part of Northwest China from 1961 to 2022, as well as historical datasets including global atmospheric data, sea surface temperature (SST), and sea ice data, this study integrates the Temporal Convolutional Network(TCN) module and the Convolutional Block Attention Module(CBAM) into the Long Short-Term Memory (LSTM) deep learning algorithm. A climate-smart prediction model for summer precipitation in the eastern part of Northwest China(named CBAM-TCN-LSTM) based on the fusion of deep learning algorithms was thereby established. The predictive performance of the model was verified, and its predictive capability was compared with that of multiple other deep learning algorithms.The results show that the intelligent prediction model based on the fusion of multiple deep learning algorithms outperforms single-algorithm deep learning models. During the independent sample validation period(2018–2022), the PS score for summer precipitation prediction ranged from 60% to 80%, with an average value of 73.8%.The Anomaly Correlation Coefficient (ACC) was positive for all years except 2020, with a mean value of 0.14, representing a significant improvement over other models. When compared with 7 current mainstream models (including machine learning algorithms, deep learning networks, and time-series networks), the CBAM-TCN-LSTM model exhibited superior performance across all five evaluation metrics: PS, PC, ACC, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). Furthermore, the CBAM-TCN-LSTM model was successfully applied in the 2023 flood season forecasting operation, accurately predicting the characteristic of below-normal summer precipitation in most areas of the eastern part of Northwest China, with a PS score of 90%.By building a precipitation prediction model that combines the TCN module and the CBAM module on the basis of the LSTM model (which has strong time-series predictive capability), this study provides a scientific basis and technical support for regional precipitation prediction, and the model holds good prospects for popularization and application.
Based on the precipitation data of 155 meteorological stations in the eastern part of Northwest China from 1961 to 2022, as well as historical datasets including global atmospheric data, sea surface temperature (SST), and sea ice data, this study integrates the Temporal Convolutional Network(TCN) module and the Convolutional Block Attention Module(CBAM) into the Long Short-Term Memory (LSTM) deep learning algorithm. A climate-smart prediction model for summer precipitation in the eastern part of Northwest China(named CBAM-TCN-LSTM) based on the fusion of deep learning algorithms was thereby established. The predictive performance of the model was verified, and its predictive capability was compared with that of multiple other deep learning algorithms.The results show that the intelligent prediction model based on the fusion of multiple deep learning algorithms outperforms single-algorithm deep learning models. During the independent sample validation period(2018–2022), the PS score for summer precipitation prediction ranged from 60% to 80%, with an average value of 73.8%.The Anomaly Correlation Coefficient (ACC) was positive for all years except 2020, with a mean value of 0.14, representing a significant improvement over other models. When compared with 7 current mainstream models (including machine learning algorithms, deep learning networks, and time-series networks), the CBAM-TCN-LSTM model exhibited superior performance across all five evaluation metrics: PS, PC, ACC, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). Furthermore, the CBAM-TCN-LSTM model was successfully applied in the 2023 flood season forecasting operation, accurately predicting the characteristic of below-normal summer precipitation in most areas of the eastern part of Northwest China, with a PS score of 90%.By building a precipitation prediction model that combines the TCN module and the CBAM module on the basis of the LSTM model (which has strong time-series predictive capability), this study provides a scientific basis and technical support for regional precipitation prediction, and the model holds good prospects for popularization and application.
Available online: April 23, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.022501
Abstract:
This study proposes an online performance monitoring method for weather radars based on ground clutter characteristics, aiming to evaluate radar system status and enhance the stability and reliability of observational data. The method identifies stable ground clutter regions by exploiting the spatiotemporal persistence of clutter and the high occurrence probability of strong echoes. An empirical cumulative distribution function (ECDF) is then constructed, with the 98th percentile extracted as the monitoring indicator, and a relative calibration bias (RCA) metric introduced to quantitatively characterize system deviations. A case study with the Jingzhou radar demonstrates that the method can effectively capture stable clutter features under various weather conditions, different ranges, and anomalous propagation scenarios. Further applications across multiple radars in Hubei Province verify its reliability in detecting system performance biases and data anomalies, confirming its feasibility for online monitoring of weather radar performance and providing strong support for improving the long-term stability of radar observations.
This study proposes an online performance monitoring method for weather radars based on ground clutter characteristics, aiming to evaluate radar system status and enhance the stability and reliability of observational data. The method identifies stable ground clutter regions by exploiting the spatiotemporal persistence of clutter and the high occurrence probability of strong echoes. An empirical cumulative distribution function (ECDF) is then constructed, with the 98th percentile extracted as the monitoring indicator, and a relative calibration bias (RCA) metric introduced to quantitatively characterize system deviations. A case study with the Jingzhou radar demonstrates that the method can effectively capture stable clutter features under various weather conditions, different ranges, and anomalous propagation scenarios. Further applications across multiple radars in Hubei Province verify its reliability in detecting system performance biases and data anomalies, confirming its feasibility for online monitoring of weather radar performance and providing strong support for improving the long-term stability of radar observations.
Available online: April 18, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.041601
Abstract:
Based on visibility observation, millimeter wave radar, EC reanalysis data, and wrfv4.2 version, IAP-LACS (3M), Morrison05 (2M) and Thompson 08 (2M) tests were designed for a high concentration, wide range and high impact sea fog process in April 2021. SW99 algorithm and FSL algorithm were used to diagnose and analyze visibility, and the following main conclusions were obtained: from April 1 to 2, 2021, 850hPa Zhejiang was between southwest wind and easterly shear. The southwest wind in the South was conducive to water vapor transport and the development of temperature ridge. There was an inversion layer near the surface along the coast. The junction is stable and the water vapor condition is good. In this process, the FSL algorithm diagnosis visibility results are obviously strong, and there is no gradient. SW99 algorithm is close to the actual situation in terms of intensity and range. The IAP-LACS (3M) of SW99 algorithm performs best in strength and range compared with the other two schemes. IAP-LACS (3M) better simulated the high value area of low-level cloud water content in Zhoushan and Taizhou Wenzhou coast, and better simulated the sea fog enhancement process along the coast of Sanshan gate from 22:00 on the 1st to 00:00 on the 2nd. The improvement of this scheme on the simulation of low-level cloud water content in the sea fog process is an important reason to improve the prediction effect of the sea fog. The comparative analysis of the three groups of schemes on the element simulation of Yuhuan station shows that the temperature simulation of 2m in the three groups of schemes from 12:00 to 16:00 on the 1st day is high, but the dew point temperature is close to the actual situation, so the relative humidity in the corresponding time is relatively small, which may be one of the reasons for the missing report of sea fog in Taizhou Wenzhou coastal area at the corresponding time. The IAP-LACS (3M) has the best temperature and dew point temperature simulation effect after 20:00 on the 1st day. In this process, IAP-LACS (3M) has a good matching relationship between the distribution of the high value area of numerical concentration output and the distribution of low visibility. At present, most cloud micro schemes do not output numerical concentration, and the droplet number concentration is an important parameter affecting visibility. IAP-LACS (3M) provides conditions for the introduction of numerical concentration into visibility diagnosis scheme.
Based on visibility observation, millimeter wave radar, EC reanalysis data, and wrfv4.2 version, IAP-LACS (3M), Morrison05 (2M) and Thompson 08 (2M) tests were designed for a high concentration, wide range and high impact sea fog process in April 2021. SW99 algorithm and FSL algorithm were used to diagnose and analyze visibility, and the following main conclusions were obtained: from April 1 to 2, 2021, 850hPa Zhejiang was between southwest wind and easterly shear. The southwest wind in the South was conducive to water vapor transport and the development of temperature ridge. There was an inversion layer near the surface along the coast. The junction is stable and the water vapor condition is good. In this process, the FSL algorithm diagnosis visibility results are obviously strong, and there is no gradient. SW99 algorithm is close to the actual situation in terms of intensity and range. The IAP-LACS (3M) of SW99 algorithm performs best in strength and range compared with the other two schemes. IAP-LACS (3M) better simulated the high value area of low-level cloud water content in Zhoushan and Taizhou Wenzhou coast, and better simulated the sea fog enhancement process along the coast of Sanshan gate from 22:00 on the 1st to 00:00 on the 2nd. The improvement of this scheme on the simulation of low-level cloud water content in the sea fog process is an important reason to improve the prediction effect of the sea fog. The comparative analysis of the three groups of schemes on the element simulation of Yuhuan station shows that the temperature simulation of 2m in the three groups of schemes from 12:00 to 16:00 on the 1st day is high, but the dew point temperature is close to the actual situation, so the relative humidity in the corresponding time is relatively small, which may be one of the reasons for the missing report of sea fog in Taizhou Wenzhou coastal area at the corresponding time. The IAP-LACS (3M) has the best temperature and dew point temperature simulation effect after 20:00 on the 1st day. In this process, IAP-LACS (3M) has a good matching relationship between the distribution of the high value area of numerical concentration output and the distribution of low visibility. At present, most cloud micro schemes do not output numerical concentration, and the droplet number concentration is an important parameter affecting visibility. IAP-LACS (3M) provides conditions for the introduction of numerical concentration into visibility diagnosis scheme.
Available online: April 17, 2026 , DOI: 10.7519/j.issn.1000-0526.2025.100701
Abstract:
Using conventional observation data and Suizhou S-band dual polarization weather radar observation data, short-time heavy rain is classified into strong weather scale system forcing type (referred to as "strong forcing type") and weak weather scale system forcing type (referred to as "weak forcing type") according to the weather circulation pattern. The distribution characteristics and dual polarization radar echo characteristics of the two types are compared and analyzed.The results show that:(1)Strong forcing type have more occurrences, wider ranges, more stations, and longer durations.(2)In the strong forcing type, July has the highest frequency, followed by June, and the lowest in August. Dahong Mountain and Tongbai Mountain being the most frequent areas.The daily variation characteristics show a three peak distribution, with the highest occurrence occurring from 05:00 to 08:00, followed by 23:00 to 00:00, and the third occurring around 15:00. In the weak forcing type, the frequency of occurrence is basically the same in July and August, with the least in June. The distribution of high-frequency areas is scattered, but mountainous areas are still high-frequency areas. The daily variation follows a unimodal distribution, with the peak occurring at 15:00.(3)Both two types have the characteristics of higher rainfall intensity, stronger echo intensity, higher concentration of liquid particles, higher echo top, larger diameter of liquid particles. (4)In the same rainfall intensity level, there is no significant difference in the combined combined reflectivity(CR), 1 km horizontal reflectivity(Zh), and echo top height (ET) of two types of short-term heavy precipitation, and they all have low centroid characteristics, with the strong forcing type having more obvious low centroid characteristics. However, the interval and average values of the 1 km differential reflectivity(Zdr) and specific differential phase (Kdp) for the strong forcing type are significantly smaller than those for the weak forcing type, while the interval and average values of the 1 km correlation coefficient(CC) are slightly larger than those for the weak forcing type. This indicates that the weak forcing type has larger particle diameters in the lower layers and is more prone to incomplete melting of ice phase particles in the lower layers.
Using conventional observation data and Suizhou S-band dual polarization weather radar observation data, short-time heavy rain is classified into strong weather scale system forcing type (referred to as "strong forcing type") and weak weather scale system forcing type (referred to as "weak forcing type") according to the weather circulation pattern. The distribution characteristics and dual polarization radar echo characteristics of the two types are compared and analyzed.The results show that:(1)Strong forcing type have more occurrences, wider ranges, more stations, and longer durations.(2)In the strong forcing type, July has the highest frequency, followed by June, and the lowest in August. Dahong Mountain and Tongbai Mountain being the most frequent areas.The daily variation characteristics show a three peak distribution, with the highest occurrence occurring from 05:00 to 08:00, followed by 23:00 to 00:00, and the third occurring around 15:00. In the weak forcing type, the frequency of occurrence is basically the same in July and August, with the least in June. The distribution of high-frequency areas is scattered, but mountainous areas are still high-frequency areas. The daily variation follows a unimodal distribution, with the peak occurring at 15:00.(3)Both two types have the characteristics of higher rainfall intensity, stronger echo intensity, higher concentration of liquid particles, higher echo top, larger diameter of liquid particles. (4)In the same rainfall intensity level, there is no significant difference in the combined combined reflectivity(CR), 1 km horizontal reflectivity(Zh), and echo top height (ET) of two types of short-term heavy precipitation, and they all have low centroid characteristics, with the strong forcing type having more obvious low centroid characteristics. However, the interval and average values of the 1 km differential reflectivity(Zdr) and specific differential phase (Kdp) for the strong forcing type are significantly smaller than those for the weak forcing type, while the interval and average values of the 1 km correlation coefficient(CC) are slightly larger than those for the weak forcing type. This indicates that the weak forcing type has larger particle diameters in the lower layers and is more prone to incomplete melting of ice phase particles in the lower layers.
Available online: April 15, 2026 , DOI: 10.7519/j.issn.1000-0526.2025.082001
Abstract:
Based on rice phenological stages and meteorological observations from nationwide single-season and double-season rice regions, combined with major agro-meteorological disaster indicators, disaster intensity and hazard indices were constructed to analyze the changing characteristics of heat stress, cold stress, drought, and compound heat and drought stresses from 1991 to 2024. The results indicate that in the period of 1991-2024, heat stress in single-season rice has significantly intensified, with the peak observed in 2022 while the area percentage exposed to heat stress. Meanwhile, early rice heat stress has shown fluctuating changes and has been gradually increasing since 2017. Obstruction-type chilling injury in rice in Northeast China has been weakened, while it weakens after 2017 and merely occurs in recent two years. The intensity of cold dew wind in late rice has been stronger after 2017 and peaked in 2020 after that it decresed. Drought has exhibited large fluctuations, with the most severe conditions occurring in single-season and late rice in 2022, and the area percentage exposed to drought in single-season ric and late rice is higher than that in early rice. The compound heat and drought stresses in single-season rice has been more severe than in early rice. At the spatial scale, areas for severer heat stress in single-season rice have been concentrated in northeastern Sichuan, central Chongqing, and eastern Hubei, while for early rice, they have been located in southeastern Hunan central Zhejiang, central-southern Jiangxi, and central Fujian where the heat stress intend to intensify. The obstruction-type chilling injury in Northeast China have been identified from southwest to northeast, and cold dew wind for late rice tends to increase from south to north. The drought in single-season rice is severe in Northeast China in comparison with that in southern areas, and that in early rice decreases from south to north which is opposite in late rice. High intensity for compound heat and drought stresses in single-season rice have been concentrated in northeastern Sichuan, central Chongqing, eastern Hubei and western Hunan, while for early rice, they have been located in northern Zhejiang and southeastern Jiangxi. In these areas exposed to high intensity of disasters, the hazard is generally heavy, which can help guide for taking prevention of specific disasters. Keywords: rice, heat stress, cold stress, drought, combined disaster, intensity index
Based on rice phenological stages and meteorological observations from nationwide single-season and double-season rice regions, combined with major agro-meteorological disaster indicators, disaster intensity and hazard indices were constructed to analyze the changing characteristics of heat stress, cold stress, drought, and compound heat and drought stresses from 1991 to 2024. The results indicate that in the period of 1991-2024, heat stress in single-season rice has significantly intensified, with the peak observed in 2022 while the area percentage exposed to heat stress. Meanwhile, early rice heat stress has shown fluctuating changes and has been gradually increasing since 2017. Obstruction-type chilling injury in rice in Northeast China has been weakened, while it weakens after 2017 and merely occurs in recent two years. The intensity of cold dew wind in late rice has been stronger after 2017 and peaked in 2020 after that it decresed. Drought has exhibited large fluctuations, with the most severe conditions occurring in single-season and late rice in 2022, and the area percentage exposed to drought in single-season ric and late rice is higher than that in early rice. The compound heat and drought stresses in single-season rice has been more severe than in early rice. At the spatial scale, areas for severer heat stress in single-season rice have been concentrated in northeastern Sichuan, central Chongqing, and eastern Hubei, while for early rice, they have been located in southeastern Hunan central Zhejiang, central-southern Jiangxi, and central Fujian where the heat stress intend to intensify. The obstruction-type chilling injury in Northeast China have been identified from southwest to northeast, and cold dew wind for late rice tends to increase from south to north. The drought in single-season rice is severe in Northeast China in comparison with that in southern areas, and that in early rice decreases from south to north which is opposite in late rice. High intensity for compound heat and drought stresses in single-season rice have been concentrated in northeastern Sichuan, central Chongqing, eastern Hubei and western Hunan, while for early rice, they have been located in northern Zhejiang and southeastern Jiangxi. In these areas exposed to high intensity of disasters, the hazard is generally heavy, which can help guide for taking prevention of specific disasters. Keywords: rice, heat stress, cold stress, drought, combined disaster, intensity index
Available online: April 03, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.040201
Abstract:
The persistent drought event cross the winter and spring in Yunnan (YN-WSPDE) have a significant impact on the planting of major autumn crops and the safety of people"s life and property, and it is of great scientific significance for meteorological disaster prevention and reduction to investigate the change and cause of this events. As a fundamental part of the research on YN-WSPDE, how to define the YN-WSPDE standard is studied based on daily precipitation and temperature observation data of 125 stations in Yunnan from 1961 to 2024, as well as the NCEP/NCAR daily reanalysis atmospheric circulation data during the same period. By analyzing the spatiotemporal characteristics of drought in winter and spring in Yunnan, it was found that the drought distribution in Yunnan is characterized by less in the east and more in the west, and more in the north and less in the south. The regions with the highest drought occurrence are mainly concentrated in the eastern part of northwest Yunnan, including Lijiang, Dali, and northern Chuxiong, while the southern parts of Honghe and Xishuangbanna have less drought occurrence. The WSPDEs standard for single station and provincial region in Yunnan are defined as: the station standard refers to the occurrence of light or above level drought in both winter and spring in a year, with moderate or above level drought occurring in one of the seasons. When 25 stations (1/5 of the total number of stations in the Yunnan) experience the WSPDE in a year, and the average precipitation anomaly percentage in both winter and spring is ≤-10%, it is defined as a WSPDE in provincial area. Preliminary analysis results show that the continuously anomalous geopotential height difference at 500-hPa between the north and south in the Eastern of East Asia, as well as anomalous anticyclone at 700-hPa over the Bay of Bengal basin, have a significant impact on the YN-WSPDE.
The persistent drought event cross the winter and spring in Yunnan (YN-WSPDE) have a significant impact on the planting of major autumn crops and the safety of people"s life and property, and it is of great scientific significance for meteorological disaster prevention and reduction to investigate the change and cause of this events. As a fundamental part of the research on YN-WSPDE, how to define the YN-WSPDE standard is studied based on daily precipitation and temperature observation data of 125 stations in Yunnan from 1961 to 2024, as well as the NCEP/NCAR daily reanalysis atmospheric circulation data during the same period. By analyzing the spatiotemporal characteristics of drought in winter and spring in Yunnan, it was found that the drought distribution in Yunnan is characterized by less in the east and more in the west, and more in the north and less in the south. The regions with the highest drought occurrence are mainly concentrated in the eastern part of northwest Yunnan, including Lijiang, Dali, and northern Chuxiong, while the southern parts of Honghe and Xishuangbanna have less drought occurrence. The WSPDEs standard for single station and provincial region in Yunnan are defined as: the station standard refers to the occurrence of light or above level drought in both winter and spring in a year, with moderate or above level drought occurring in one of the seasons. When 25 stations (1/5 of the total number of stations in the Yunnan) experience the WSPDE in a year, and the average precipitation anomaly percentage in both winter and spring is ≤-10%, it is defined as a WSPDE in provincial area. Preliminary analysis results show that the continuously anomalous geopotential height difference at 500-hPa between the north and south in the Eastern of East Asia, as well as anomalous anticyclone at 700-hPa over the Bay of Bengal basin, have a significant impact on the YN-WSPDE.
Available online: April 02, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.031101
Abstract:
Based on multi-source observations and ERA5 reanalysis data, this study systematically analyzed an extreme rainfall event in North China in late July 2025. It revealed the diversity in the initiation, organization, and propagation mechanisms of Mesoscale Convective Systems (MCSs) during three extreme rainfall days (July 24, 25, and 27) under a similar large-scale warm sector background, and investigated their synoptic causes.The results indicate that: (1) The event was characterized by significant extremity with high rainfall intensity and large accumulation. The multiple extreme precipitation centers within the southern warm-sector rainband posed the main forecast challenge. (2) The MCS evolution varied significantly by day. On July 24, convection initiated at the foothills, and the extreme rainfall was dominated by a "training effect" from backward-propagating and band-shaped convection, resulting in the most widespread rainfall area spanning mountains, foothills, and plains. On July 25, convection originated in the mountains, and the extreme rainfall was associated with a quasi-stationary system, leading to the most localized precipitation. On July 27, convection mostly initiated in the plains and intensified after moving to the foothills, with extreme rainfall linked to a "training effect" from line-shaped convection.(3) The primary cause for this diversity lies in the varied interactions between the environmental field and complex terrain. On July 24, the strongest synoptic-scale forcing, characterized by a strong and deep Low-Level Jet (LLJ) coupled with orographic lift and sustained moisture transport, played a key role in convective initiation and back-propagation. On July 25, under the control of the subtropical high, a weaker and shallower LLJ limited downstream propagation, making orographic lift the dominant mechanism for triggering and enhancement, which was accompanied by a mesocyclone-like structure that produced the strongest local hourly rainfall. On July 27, under the weakest synoptic-scale forcing, convection was triggered by boundary layer easterlies and a weak low-level convergence line, while a mesoscale front and orographic lifting of southwesterly flow facilitated its intensification and maintenance.
Based on multi-source observations and ERA5 reanalysis data, this study systematically analyzed an extreme rainfall event in North China in late July 2025. It revealed the diversity in the initiation, organization, and propagation mechanisms of Mesoscale Convective Systems (MCSs) during three extreme rainfall days (July 24, 25, and 27) under a similar large-scale warm sector background, and investigated their synoptic causes.The results indicate that: (1) The event was characterized by significant extremity with high rainfall intensity and large accumulation. The multiple extreme precipitation centers within the southern warm-sector rainband posed the main forecast challenge. (2) The MCS evolution varied significantly by day. On July 24, convection initiated at the foothills, and the extreme rainfall was dominated by a "training effect" from backward-propagating and band-shaped convection, resulting in the most widespread rainfall area spanning mountains, foothills, and plains. On July 25, convection originated in the mountains, and the extreme rainfall was associated with a quasi-stationary system, leading to the most localized precipitation. On July 27, convection mostly initiated in the plains and intensified after moving to the foothills, with extreme rainfall linked to a "training effect" from line-shaped convection.(3) The primary cause for this diversity lies in the varied interactions between the environmental field and complex terrain. On July 24, the strongest synoptic-scale forcing, characterized by a strong and deep Low-Level Jet (LLJ) coupled with orographic lift and sustained moisture transport, played a key role in convective initiation and back-propagation. On July 25, under the control of the subtropical high, a weaker and shallower LLJ limited downstream propagation, making orographic lift the dominant mechanism for triggering and enhancement, which was accompanied by a mesocyclone-like structure that produced the strongest local hourly rainfall. On July 27, under the weakest synoptic-scale forcing, convection was triggered by boundary layer easterlies and a weak low-level convergence line, while a mesoscale front and orographic lifting of southwesterly flow facilitated its intensification and maintenance.
Available online: March 10, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.011201
Abstract:
Abstract:On 17th (hereinafter referred to as “1217”)and from 24th to 26th December 2021 (hereinafter referred to as “1225”), Shandong Peninsula experienced two Bohai sea-effect snowfall events.Compared with “1217”,the cold air intensity was stronger and snowfall duration was longer for “1225”, but the total snowfall amount was less and intensity of snowfall was weaker than “1217”. In order to clarify the reasons, thermodynamic and dynamical characters were analyzed and compared by using data of moored buoy station,S-band Doppler weather radar,conventional sounding, hourly snowfall observation data from ground automatic meteorological stations and ERA5( ECMWF Reanalysis v5). The main results are as follows:During the first snowfall phase of "1225", sea-air temperature difference(temperature difference between sea surface and 850hPa air) was 28°C, which exceeded "1217" (24°C). During the second snowfall phase, both events exhibited comparable sea-air temperature between 24°C and 25°C. However, throughout the snowfall period,"1225" displayed an?intermittent weakening of low-level cold advection, with?advection intensities consistently weaker than "1217". This weaker thermal advection?impaired the development of?lower-level thermal and moisture conditions?for the "1225". During "1217", the intense core of cold advection extended vertically to 700～500 hPa, whereas during "1225" it was confined to 875～750 hPa and was weaker than"1217". Consequently, the inversion layer developed above the cold advection center in "1225" displayed both lower height and reduced thickness relative to "1217". This structural difference further suppressed depth of the conditionally unstable (or neutral) layer beneath the inversion,thereby limiting the vertical extent of shallow convective clouds and ultimately diminishing snowfall intensity. During the second snowfall phase of "1225", steering wind direction (mean wind direction from 1000 hPa to 700 hPa) over the Bohai Sea and its upstream regions was 327°, deviating by 11° from "1217" with a larger westerly component. Consequently, the low-level tongue, mesoscale shear line and heavy snow echo band all displayed larger zonal component and positioned predominantly offshore resulting in inconspicuous snowfall over the peninsula ultimately. Cold advection constitutes a primary physical driver modulating the thermal structure of sea-effect snowfall. Simultaneously, it indirectly governs the initiation and evolution of mesoscale shear lines by inducing a low-level warm tongue, thereby providing dynamical lifting and organizational mechanism over snowfall echo structures,ultimately shaping the dynamical structure of snowfall. For forecasting applications, it is essential to make an integrated dynamic analysis of cold advection developmental stages, three-dimensional spatial structure and intensity evolution on low-level. Focus on sea-air temperature difference,absolute moisture content within the boundary layer, inversion layer height, thickness of the conditionally(or neutral) unstablelayer and steering wind direction. Diagnostics of mesoscale characteristics such as the position, orientation and intensity of low-level warm tongue and shear line are imperative.
Abstract:On 17th (hereinafter referred to as “1217”)and from 24th to 26th December 2021 (hereinafter referred to as “1225”), Shandong Peninsula experienced two Bohai sea-effect snowfall events.Compared with “1217”,the cold air intensity was stronger and snowfall duration was longer for “1225”, but the total snowfall amount was less and intensity of snowfall was weaker than “1217”. In order to clarify the reasons, thermodynamic and dynamical characters were analyzed and compared by using data of moored buoy station,S-band Doppler weather radar,conventional sounding, hourly snowfall observation data from ground automatic meteorological stations and ERA5( ECMWF Reanalysis v5). The main results are as follows:During the first snowfall phase of "1225", sea-air temperature difference(temperature difference between sea surface and 850hPa air) was 28°C, which exceeded "1217" (24°C). During the second snowfall phase, both events exhibited comparable sea-air temperature between 24°C and 25°C. However, throughout the snowfall period,"1225" displayed an?intermittent weakening of low-level cold advection, with?advection intensities consistently weaker than "1217". This weaker thermal advection?impaired the development of?lower-level thermal and moisture conditions?for the "1225". During "1217", the intense core of cold advection extended vertically to 700～500 hPa, whereas during "1225" it was confined to 875～750 hPa and was weaker than"1217". Consequently, the inversion layer developed above the cold advection center in "1225" displayed both lower height and reduced thickness relative to "1217". This structural difference further suppressed depth of the conditionally unstable (or neutral) layer beneath the inversion,thereby limiting the vertical extent of shallow convective clouds and ultimately diminishing snowfall intensity. During the second snowfall phase of "1225", steering wind direction (mean wind direction from 1000 hPa to 700 hPa) over the Bohai Sea and its upstream regions was 327°, deviating by 11° from "1217" with a larger westerly component. Consequently, the low-level tongue, mesoscale shear line and heavy snow echo band all displayed larger zonal component and positioned predominantly offshore resulting in inconspicuous snowfall over the peninsula ultimately. Cold advection constitutes a primary physical driver modulating the thermal structure of sea-effect snowfall. Simultaneously, it indirectly governs the initiation and evolution of mesoscale shear lines by inducing a low-level warm tongue, thereby providing dynamical lifting and organizational mechanism over snowfall echo structures,ultimately shaping the dynamical structure of snowfall. For forecasting applications, it is essential to make an integrated dynamic analysis of cold advection developmental stages, three-dimensional spatial structure and intensity evolution on low-level. Focus on sea-air temperature difference,absolute moisture content within the boundary layer, inversion layer height, thickness of the conditionally(or neutral) unstablelayer and steering wind direction. Diagnostics of mesoscale characteristics such as the position, orientation and intensity of low-level warm tongue and shear line are imperative.
Available online: February 25, 2026 , DOI: 10.7519/j.issn.1000-0526.2025.081201
Abstract:
To investigate the impact of meteorological conditions on the key quality components (protein, fat, starch, and amino acids) of maize grains, stepwise regression-based quality prediction models were constructed based on interval sowing tests and tested. The values calculated by the models were converted into quality grades and compared with the actual grades. The results showed that all stepwise regression-based prediction models passed the significance test, establishing a relationship between grain quality and meteorological factors from tasseling to milk stage and from milk stage to maturity. The linear relationship between grain quality and meteorological factors was quantified. The results of the model test and forecasting test indicated that the mean absolute percentage errors for all four quality components were less than 15 % and the predictions for starch and protein were closer to the actual values compared to those for fat and amino acids. The actual and predicted contents of grain quality components (regardless of cropping system) were converted into grades for validation. For protein, fat, and starch, the combined proportion of samples with predicted grades matching or within one grade of actual grades exceeded 90 % (reaching 100 % for starch), and was 76.67 % for amino acids. The predicted grades aligned well with the actual grades, indicating that the prediction models exhibited high accuracy and can be used for forecasting and evaluating grain quality. The findings can offer an objective and quantitative basis for optimizing environmental resource utilization to improve maize quality and for informing maize ecological zoning.
To investigate the impact of meteorological conditions on the key quality components (protein, fat, starch, and amino acids) of maize grains, stepwise regression-based quality prediction models were constructed based on interval sowing tests and tested. The values calculated by the models were converted into quality grades and compared with the actual grades. The results showed that all stepwise regression-based prediction models passed the significance test, establishing a relationship between grain quality and meteorological factors from tasseling to milk stage and from milk stage to maturity. The linear relationship between grain quality and meteorological factors was quantified. The results of the model test and forecasting test indicated that the mean absolute percentage errors for all four quality components were less than 15 % and the predictions for starch and protein were closer to the actual values compared to those for fat and amino acids. The actual and predicted contents of grain quality components (regardless of cropping system) were converted into grades for validation. For protein, fat, and starch, the combined proportion of samples with predicted grades matching or within one grade of actual grades exceeded 90 % (reaching 100 % for starch), and was 76.67 % for amino acids. The predicted grades aligned well with the actual grades, indicating that the prediction models exhibited high accuracy and can be used for forecasting and evaluating grain quality. The findings can offer an objective and quantitative basis for optimizing environmental resource utilization to improve maize quality and for informing maize ecological zoning.
Available online: February 10, 2026 , DOI: 10.7519/j.issn.1000-0526.2025.080501
Abstract:
A rare weather event featuring a long-lived period of freezing rain and ice pellets transitioning to snow occurred in the southern Shandong region from February 20-21, 2024. Using conventional observational data, wind profiler radar data, raindrop spectrum data, and ERA5 reanalysis data to analyze this event, the results indicate:?(1)? The event was characterized by return flow precipitation. A southwest warm and humid airflow ahead of the upper-level trough slid upwards along a cold pad caused by a significant temperature drop due to the low-level strong cold air. The interaction between the mid-level warm and humid airflow and the low-level northeastern airflow formed a strong inversion, and the "cold-warm-cold" vertical temperature structure was maintained for a long time, leading to a 12-hour period of freezing rain and ice pellets??(2)? Both freezing rain and ice pellets exhibit typical characteristics of ice-phase melting. The ground temperature during freezing rain is higher, the starting height of the warm layer is lower, and both the thickness and intensity of the warm layer are greater, while the thickness and intensity of the cold layer are smaller. ??(3)? Raindrop spectrum data showed no significant differences in the particle size distribution characteristics between freezing rain and ice pellets. Both had features of small particle size, low number concentration, low precipitation intensity, and high falling speed. The velocity curves of both were similar to those of rainfall but with slight differences. Freezing rain had slightly larger particles and fewer particle numbers than ice pellets. During the snowfall phase, the spectrum widened, characterized by large particle size, high number concentration, high precipitation intensity, and low falling speed.
A rare weather event featuring a long-lived period of freezing rain and ice pellets transitioning to snow occurred in the southern Shandong region from February 20-21, 2024. Using conventional observational data, wind profiler radar data, raindrop spectrum data, and ERA5 reanalysis data to analyze this event, the results indicate:?(1)? The event was characterized by return flow precipitation. A southwest warm and humid airflow ahead of the upper-level trough slid upwards along a cold pad caused by a significant temperature drop due to the low-level strong cold air. The interaction between the mid-level warm and humid airflow and the low-level northeastern airflow formed a strong inversion, and the "cold-warm-cold" vertical temperature structure was maintained for a long time, leading to a 12-hour period of freezing rain and ice pellets??(2)? Both freezing rain and ice pellets exhibit typical characteristics of ice-phase melting. The ground temperature during freezing rain is higher, the starting height of the warm layer is lower, and both the thickness and intensity of the warm layer are greater, while the thickness and intensity of the cold layer are smaller. ??(3)? Raindrop spectrum data showed no significant differences in the particle size distribution characteristics between freezing rain and ice pellets. Both had features of small particle size, low number concentration, low precipitation intensity, and high falling speed. The velocity curves of both were similar to those of rainfall but with slight differences. Freezing rain had slightly larger particles and fewer particle numbers than ice pellets. During the snowfall phase, the spectrum widened, characterized by large particle size, high number concentration, high precipitation intensity, and low falling speed.
Available online: February 03, 2026 , DOI: 10.7519/j.issn.1000-0526.2025.072402
Abstract:
The complex topography of the hilly and mountainous regions in Fujian Province gives rise to diverse hail cloud structures, notably isolated convective cells and squall lines. This study addresses the lack of comparative research on the microphysical characteristics of these two types of hail-bearing convection. Based on a persistent severe convective event that occurred in March 2023 over the hilly terrain of southeastern coastal China, S-band dual-polarization radar data and surface precipitation particle spectra observations are employed to comparatively analyze the ground-based spectral characteristics of precipitation particles associated with isolated cells and squall-line systems.The results show that isolated convection during the concentrated hailfall stage exhibits larger particle sizes, more complex spectral structures, more pronounced fluctuations in total particle number concentration, and greater dispersion in the velocity–size spectra, indicating more vigorous ice-phase microphysical processes. In contrast, squall-line convection is characterized by high-density hail, a relatively high concentration of small raindrops, and simpler spectral structures. For both convective types, the peak in precipitation particle concentration appears near the front side of the cloud system in the heavy rainfall region following the main hailfall stage, accompanied by a narrowing of the spectral width and a reduction in large particles. The precipitation process is further divided into four distinct stages, each exhibiting markedly different spectral characteristics.These findings enhance the understanding of the microphysical processes of isolated and squall-line hail clouds and provide scientific support for short-term nowcasting and hail suppression operations.
The complex topography of the hilly and mountainous regions in Fujian Province gives rise to diverse hail cloud structures, notably isolated convective cells and squall lines. This study addresses the lack of comparative research on the microphysical characteristics of these two types of hail-bearing convection. Based on a persistent severe convective event that occurred in March 2023 over the hilly terrain of southeastern coastal China, S-band dual-polarization radar data and surface precipitation particle spectra observations are employed to comparatively analyze the ground-based spectral characteristics of precipitation particles associated with isolated cells and squall-line systems.The results show that isolated convection during the concentrated hailfall stage exhibits larger particle sizes, more complex spectral structures, more pronounced fluctuations in total particle number concentration, and greater dispersion in the velocity–size spectra, indicating more vigorous ice-phase microphysical processes. In contrast, squall-line convection is characterized by high-density hail, a relatively high concentration of small raindrops, and simpler spectral structures. For both convective types, the peak in precipitation particle concentration appears near the front side of the cloud system in the heavy rainfall region following the main hailfall stage, accompanied by a narrowing of the spectral width and a reduction in large particles. The precipitation process is further divided into four distinct stages, each exhibiting markedly different spectral characteristics.These findings enhance the understanding of the microphysical processes of isolated and squall-line hail clouds and provide scientific support for short-term nowcasting and hail suppression operations.
包红军, zeng sihai, wangjianwen, yunxiaobo, lin jian, zhangbo, lizhijia, luanchengmei, wangmeng, xufengwen
Available online: January 30, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.011301
Abstract:
In late July 2025, Chaobai River Basin experienced the largest flood since 1959. A flood simulation and forecasting model is developed for Chaobai River Basin based on a distributed hydrological model, aiming to retrospectively analyze the characteristics of the basin’s "25·7" regional flood in this paper. The Zhangjiafen cross section of the Bai River, the Xiahui cross section of the Chao River, and the Putaoyuan cross section of the Qingshui River were taken for test hydrological sections. Flood simulation and forecasting model based on the GMKHM distributed hydrological model was developed with taking hourly precipitation observation data from CMA regional meteorological stations as model forcing input, incorporating terrain curve numbers and terrain indices to develop a DEM-based runoff and production model, adding a deep groundwater module in the water source separation module. Results show that the peak discharge simulation errors is -1.8% for the Zhangjiafen hydrological section, 3.6% for the Xiahui hydrological section. The model determination coefficient is 0.87 for the Zhangjiafen hydrological section, and 0.89 for the Xiahui hydrological section. for the Putaoyuan section of the Qingshui River, the peak discharge error was 0.9%, and the determination coefficient reached 0.92. GMKHM distributed hydrological model perform well for simulation of "25·7" Flood events in the Chaobai Basin.
In late July 2025, Chaobai River Basin experienced the largest flood since 1959. A flood simulation and forecasting model is developed for Chaobai River Basin based on a distributed hydrological model, aiming to retrospectively analyze the characteristics of the basin’s "25·7" regional flood in this paper. The Zhangjiafen cross section of the Bai River, the Xiahui cross section of the Chao River, and the Putaoyuan cross section of the Qingshui River were taken for test hydrological sections. Flood simulation and forecasting model based on the GMKHM distributed hydrological model was developed with taking hourly precipitation observation data from CMA regional meteorological stations as model forcing input, incorporating terrain curve numbers and terrain indices to develop a DEM-based runoff and production model, adding a deep groundwater module in the water source separation module. Results show that the peak discharge simulation errors is -1.8% for the Zhangjiafen hydrological section, 3.6% for the Xiahui hydrological section. The model determination coefficient is 0.87 for the Zhangjiafen hydrological section, and 0.89 for the Xiahui hydrological section. for the Putaoyuan section of the Qingshui River, the peak discharge error was 0.9%, and the determination coefficient reached 0.92. GMKHM distributed hydrological model perform well for simulation of "25·7" Flood events in the Chaobai Basin.
Available online: January 23, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.010602
Abstract:
This study is based on LiDAR wind profiler data and uses the Wind Profile Exponent (WPE) method to calculate the wind profile exponent within the 50–500 meter height range under different surface wind conditions. The results were validated using data from 50 meteorological stations, each with observation heights exceeding 40 meters. The findings indicate that the LiDAR wind profile exponent suffers from a systematic overestimation, with errors closely related to the building density and height characteristics of the observation area. To address this issue, the study innovatively introduces urban building parameters and proposes a multi-factor-driven dynamic correction algorithm for the wind profile exponent, overcoming the limitations of the traditional single roughness parameter approach. After correction, 91.7% of the wind speed calculation errors were controlled within a ±1 Beaufort scale range, with 50.1% showing zero error. Building upon this, a three-dimensional high-altitude wind field reconstruction model tailored for urban complex building environments was further developed. This model has a horizontal resolution of 100 meters and vertical coverage from 50 to 500 meters, enabling real-time monitoring every 5 minutes and forecast outputs up to 168 hours. The model provides a low-cost, high-precision wind disaster prevention and control technology pathway for urban high-altitude operations, offering significant business application potential and engineering value.
This study is based on LiDAR wind profiler data and uses the Wind Profile Exponent (WPE) method to calculate the wind profile exponent within the 50–500 meter height range under different surface wind conditions. The results were validated using data from 50 meteorological stations, each with observation heights exceeding 40 meters. The findings indicate that the LiDAR wind profile exponent suffers from a systematic overestimation, with errors closely related to the building density and height characteristics of the observation area. To address this issue, the study innovatively introduces urban building parameters and proposes a multi-factor-driven dynamic correction algorithm for the wind profile exponent, overcoming the limitations of the traditional single roughness parameter approach. After correction, 91.7% of the wind speed calculation errors were controlled within a ±1 Beaufort scale range, with 50.1% showing zero error. Building upon this, a three-dimensional high-altitude wind field reconstruction model tailored for urban complex building environments was further developed. This model has a horizontal resolution of 100 meters and vertical coverage from 50 to 500 meters, enabling real-time monitoring every 5 minutes and forecast outputs up to 168 hours. The model provides a low-cost, high-precision wind disaster prevention and control technology pathway for urban high-altitude operations, offering significant business application potential and engineering value.
Available online: January 21, 2026 , DOI: 10.7519/j.issn.1000-0526.2026.011602
Abstract:
Fixed-hourly precipitation data may underestimate the characteristics of heavy rainfall at the hourly scale. To gain a deeper understanding of the variation patterns of hourly heavy rainfall, this study utilizes minute-level precipitation observations from 123 national meteorological stations in Shandong Province from June to September during the flood seasons of 2004–2024. It compares the differences between the 60-minute sliding window and fixed-hourly statistical methods in identifying heavy rainfall events, aiming to quantitatively assess the impact of different methods on the frequency, intensity, and spatio-temporal distribution of heavy rainfall. The results indicate that the 60-minute sliding window method captures heavy rainfall events more comprehensively than the fixed-hourly method. The average frequency of heavy rainfall across the province was 124.3 times using the sliding method, which is 1.48 times that of the fixed-hourly method (84.3 times), with regional ratios ranging between 1.31 and 1.81. The maximum precipitation captured by the sliding method was on average 10.0 mm higher, exceeding 30.0 mm at some stations. While the spatial distributions of the two methods are generally consistent, the sliding method exhibits greater spatial variability and extremity. It also more clearly reveals increasing trends in both the frequency and intensity of heavy rainfall, with climatic tendency rates of 1.31 times·(10a)?1 and 4.514 mm·(10a)?1, respectively. Moreover, monthly and diurnal variation characteristics are more distinct with the sliding method, particularly during the high-frequency periods from July to August and from afternoon to early morning. The traditional fixed-hourly statistical system underestimates the frequency and extreme intensity of short-duration heavy rainfall. The 60-minute sliding window method provides a more accurate representation of heavy rainfall characteristics, offering important applications for improving the accuracy of storm monitoring and enhancing early warning capabilities for disaster risk.
Fixed-hourly precipitation data may underestimate the characteristics of heavy rainfall at the hourly scale. To gain a deeper understanding of the variation patterns of hourly heavy rainfall, this study utilizes minute-level precipitation observations from 123 national meteorological stations in Shandong Province from June to September during the flood seasons of 2004–2024. It compares the differences between the 60-minute sliding window and fixed-hourly statistical methods in identifying heavy rainfall events, aiming to quantitatively assess the impact of different methods on the frequency, intensity, and spatio-temporal distribution of heavy rainfall. The results indicate that the 60-minute sliding window method captures heavy rainfall events more comprehensively than the fixed-hourly method. The average frequency of heavy rainfall across the province was 124.3 times using the sliding method, which is 1.48 times that of the fixed-hourly method (84.3 times), with regional ratios ranging between 1.31 and 1.81. The maximum precipitation captured by the sliding method was on average 10.0 mm higher, exceeding 30.0 mm at some stations. While the spatial distributions of the two methods are generally consistent, the sliding method exhibits greater spatial variability and extremity. It also more clearly reveals increasing trends in both the frequency and intensity of heavy rainfall, with climatic tendency rates of 1.31 times·(10a)?1 and 4.514 mm·(10a)?1, respectively. Moreover, monthly and diurnal variation characteristics are more distinct with the sliding method, particularly during the high-frequency periods from July to August and from afternoon to early morning. The traditional fixed-hourly statistical system underestimates the frequency and extreme intensity of short-duration heavy rainfall. The 60-minute sliding window method provides a more accurate representation of heavy rainfall characteristics, offering important applications for improving the accuracy of storm monitoring and enhancing early warning capabilities for disaster risk.
Available online: January 06, 2026 , DOI: 10.7519/j.issn.1000-0526.2025.072803
Abstract:
Based on the operational real-time typhoon data of National Meteorological Centre and other sources of observations including the ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasting, we analyzed the characteristics of typhoon activities in western North Pacific in 2024. We revealed the different features of typhoons between summer and autumn in 2024 from three aspects: typhoon genesis, typhoon activity, and typhoon landfall. In the summer of 2024, the typhoons genesis number was lower than normal, with the genesis region shifted northward and eastward, and weaker maximum intensities. No typhoons were generated from June 1 to July 18, while the peak summer season saw frequent typhoon occurrences, mostly following northwestward and northward tracks. The number of typhoons landing in China was less than usual, with weaker landfall intensities. However, typhoons were more active in autumn. The typhoon genesis number ranked the third highest in history, with their genesis location shifting northward and westward, and their intensities being unusually strong. Typhoon activities were characterized by distinct periodicity and clustering, with most following westward or northwestward tracks. The number of typhoon landfalls was relatively higher, and the landfall intensities were stronger than the average. Further research showed that the significant differences between summer and autumn typhoons in 2024 were closely related to multiple factors such as the lag effect of sea surface temperature in the year following El Ni?o, the abnormal Western Pacific subtropical high, the phase transition of the tropical intraseasonal oscillation, the onset and withdrawal of the South China Sea summer monsoon, etc.
Based on the operational real-time typhoon data of National Meteorological Centre and other sources of observations including the ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasting, we analyzed the characteristics of typhoon activities in western North Pacific in 2024. We revealed the different features of typhoons between summer and autumn in 2024 from three aspects: typhoon genesis, typhoon activity, and typhoon landfall. In the summer of 2024, the typhoons genesis number was lower than normal, with the genesis region shifted northward and eastward, and weaker maximum intensities. No typhoons were generated from June 1 to July 18, while the peak summer season saw frequent typhoon occurrences, mostly following northwestward and northward tracks. The number of typhoons landing in China was less than usual, with weaker landfall intensities. However, typhoons were more active in autumn. The typhoon genesis number ranked the third highest in history, with their genesis location shifting northward and westward, and their intensities being unusually strong. Typhoon activities were characterized by distinct periodicity and clustering, with most following westward or northwestward tracks. The number of typhoon landfalls was relatively higher, and the landfall intensities were stronger than the average. Further research showed that the significant differences between summer and autumn typhoons in 2024 were closely related to multiple factors such as the lag effect of sea surface temperature in the year following El Ni?o, the abnormal Western Pacific subtropical high, the phase transition of the tropical intraseasonal oscillation, the onset and withdrawal of the South China Sea summer monsoon, etc.
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2012,38(12):1482-1491, DOI: 10.7519/j.issn.1000-0526.2012.12.005
Abstract:
By using the conventional meteorological data, Doppler radar data and NCEP/NCAR reanalysis data, the characteristics of Doppler radar’s reflectivity, environmental condition and trigger mechanism of the heavy rain are analyzed and compared between two abrupt heavy rain processes occurring in Sichuan Basin on 3 July (7.3) and 23 July (7.23) 2011. The results show that: the “7.3” heavy rain happened under a typical circulation background, and moisture transporting to the heavy rain area from the South China Sea was smoothly, thus the heavy rainfall maintained so long, but the “7.23” heavy rain occurred behind the upper cold vortex, and convective unstable energy was abundant and vertical wind shear was strong, thus this heavy rain process happened with hail and thunderstorm weather accompanied, its radar reflectivity was 5 dBz stronger than “7.3” case and had the characteristics of severe storms such as the low level weak reflectivity and the upper echo overhang. As a whole, the non equilibrium force is contributed to the occurrence of heavy rain and it is the excited mechanism of the two heavy rainfalls, and the change of the divergence evolvement is consistent with the strength and the position of the heavy rain which would happen 6 hours later．
By using the conventional meteorological data, Doppler radar data and NCEP/NCAR reanalysis data, the characteristics of Doppler radar’s reflectivity, environmental condition and trigger mechanism of the heavy rain are analyzed and compared between two abrupt heavy rain processes occurring in Sichuan Basin on 3 July (7.3) and 23 July (7.23) 2011. The results show that: the “7.3” heavy rain happened under a typical circulation background, and moisture transporting to the heavy rain area from the South China Sea was smoothly, thus the heavy rainfall maintained so long, but the “7.23” heavy rain occurred behind the upper cold vortex, and convective unstable energy was abundant and vertical wind shear was strong, thus this heavy rain process happened with hail and thunderstorm weather accompanied, its radar reflectivity was 5 dBz stronger than “7.3” case and had the characteristics of severe storms such as the low level weak reflectivity and the upper echo overhang. As a whole, the non equilibrium force is contributed to the occurrence of heavy rain and it is the excited mechanism of the two heavy rainfalls, and the change of the divergence evolvement is consistent with the strength and the position of the heavy rain which would happen 6 hours later．
2017,43(7):769-780, DOI: 10.7519/j.issn.1000-0526.2017.07.001
Abstract:
The spatial distributions of severe convective wind (SCW) and nonsevere thunderstorms (NT) over South China, occurring between 08:00 BT and 20:00 BT during spring and summer in 2010-2014, were analyzed by using the observational data from China Meteorological Administration. And then, their environmental characteristics were compared between SCW and NT in spring and summer. It was found that SCW in summer is more frequently than that in spring and that NT in summer is about 3.6 times the counts of NT in spring. SCW events mainly concentrate in the western Guangdong to the Pearl River Delta Region. Compared to NT, SCW is generally associated with stronger baroclinity, instability and stronger dynamic forcing. The precipitable water and averaged relative humidity between 700-500 hPa of SCW tend to be higher than those of NT in spring, while the opposite is the case for the pattern in summer. In conclusion, it is obvious that the dynamic forcing for SCW in spring is much better than these in summer, while the thermal condition is more significant in summer.
The spatial distributions of severe convective wind (SCW) and nonsevere thunderstorms (NT) over South China, occurring between 08:00 BT and 20:00 BT during spring and summer in 2010-2014, were analyzed by using the observational data from China Meteorological Administration. And then, their environmental characteristics were compared between SCW and NT in spring and summer. It was found that SCW in summer is more frequently than that in spring and that NT in summer is about 3.6 times the counts of NT in spring. SCW events mainly concentrate in the western Guangdong to the Pearl River Delta Region. Compared to NT, SCW is generally associated with stronger baroclinity, instability and stronger dynamic forcing. The precipitable water and averaged relative humidity between 700-500 hPa of SCW tend to be higher than those of NT in spring, while the opposite is the case for the pattern in summer. In conclusion, it is obvious that the dynamic forcing for SCW in spring is much better than these in summer, while the thermal condition is more significant in summer.
2010,36(3):9-18, DOI: 10.7519/j.issn.1000-0526.2010.3.002
Abstract:
Potential vorticity (PV) is one of the important concepts in advanced synoptic and dynamic meteorology. This paper is a brief introduction to the theory of potential vorticity, including the concept of PV, the conservation and invertibility of PV, PV thinking, moist PV (MPV), and the application of PV theory.
Potential vorticity (PV) is one of the important concepts in advanced synoptic and dynamic meteorology. This paper is a brief introduction to the theory of potential vorticity, including the concept of PV, the conservation and invertibility of PV, PV thinking, moist PV (MPV), and the application of PV theory.
FU Jiaolan, MA Xuekuan, CHEN Tao, ZHANG Fang, ZHANG Xidi, SUN Jun, QUAN Wanqing, YANG Shunan, SHEN Xiaolin
2017,43(5):528-539, DOI: 10.7519/j.issn.1000-0526.2017.05.002
Abstract:
An extremely severe precipitation event took place in North China in 19-20 July 2016. It was characterized by large rainfall, persistent rainfall, warm cloud rainfall, strong local rainfall intensity and orographic precipitation. Its rainfall was larger than that of the extreme rainfall in 3-5 August 1996, and only next to the amount of the 2-7 August 1963 extreme rainfall event. It occurred under the circulation background of the South Asia high moving eastward, the West Pacific subtropical high moving northwestward and the low vortex in the westerlies developing in mid high latitude. The abnormal development of Huanghuai cyclone, southwest and southeast low level jets, and the abnormally abundant moisture indicates that the dynamic lifting and moisture conditions favored this severe rainfall process significantly. The whole rainfall event presented clearly the phase characteristics, and could be divided into two stages. The first stage was the orographic rainfall caused by the easterly winds ahead of the trough from the early morning to the daytime of 19 July, while the second part was produced by spiral rain bands in the north side of Huanghuai cyclone from the night of 19 to the daytime of 20 July. In the first stage, the easterly low level jet was lifted by the Taihang Mountains, which continuously triggered the convective cells along the east edge of the mountains. The weak dry and cold advection at mid level and the strong warm and wet advection at low level jointly maintained the convective instability. The cold pool generated by heavy rainfall and the mesoscale frontogenesis process created by local orographic effect provided favorable conditions for severe convections to occur continuously. The second stage rainfall was mainly related to the development of cut off vortex and Huanghuai cyclone. The blocking of the high pressure system slowed the steps of Huanghuai cyclone in North China, thus leading to the long lasting rainfall process.
An extremely severe precipitation event took place in North China in 19-20 July 2016. It was characterized by large rainfall, persistent rainfall, warm cloud rainfall, strong local rainfall intensity and orographic precipitation. Its rainfall was larger than that of the extreme rainfall in 3-5 August 1996, and only next to the amount of the 2-7 August 1963 extreme rainfall event. It occurred under the circulation background of the South Asia high moving eastward, the West Pacific subtropical high moving northwestward and the low vortex in the westerlies developing in mid high latitude. The abnormal development of Huanghuai cyclone, southwest and southeast low level jets, and the abnormally abundant moisture indicates that the dynamic lifting and moisture conditions favored this severe rainfall process significantly. The whole rainfall event presented clearly the phase characteristics, and could be divided into two stages. The first stage was the orographic rainfall caused by the easterly winds ahead of the trough from the early morning to the daytime of 19 July, while the second part was produced by spiral rain bands in the north side of Huanghuai cyclone from the night of 19 to the daytime of 20 July. In the first stage, the easterly low level jet was lifted by the Taihang Mountains, which continuously triggered the convective cells along the east edge of the mountains. The weak dry and cold advection at mid level and the strong warm and wet advection at low level jointly maintained the convective instability. The cold pool generated by heavy rainfall and the mesoscale frontogenesis process created by local orographic effect provided favorable conditions for severe convections to occur continuously. The second stage rainfall was mainly related to the development of cut off vortex and Huanghuai cyclone. The blocking of the high pressure system slowed the steps of Huanghuai cyclone in North China, thus leading to the long lasting rainfall process.
2012,38(10):1255-1266, DOI: 10.7519/j.issn.1000-0526.2012.10.012
Abstract:
Precipitation characteristics, environment conditions, generation and development of the mesoscale convective system that brought about the extreme torrential rain in Beijing on 21 July 2012 were analyzed comprehensively in this paper by using various conventional and unconventional data. The results showed that the extreme torrential rain had the characteristics of long duration, great rainfall and wide coverage area and its process consisted of warm area precipitation and frontal precipitation. The warm area rainfall started earlier, the severe precipitation center was scattered and lasted long while the frontal rainfallprocess contained several severe rainfall centers with high precipitation efficiency, lasting a short time.Environment conditions of the mesoscale convective system that triggered this extreme severe rainfall were analyzed. The results showed that interactions of high level divergence, the wind shear and convergence with the vortex in the lower troposphere and the surface wind convergence line provided favorable environment to the severe extreme rain. The warm humid airs from the tropical and sub tropical zones converged over the torrential rain region, continuous and sufficient water vapor manifested as high atmospheric column of precipitable water and strong low level water vapor convergence and other extreme vapor conditions for the torrential rain. In addition, the intense precipitation was triggered by the vortex wind shear, wind disturbance on low level jet, surface wind convergence line and the effect of terrain under the condition of the plentiful water vapour and maintained. With the cold front moved eastward, heavy frontal rainfall was brought by the development and evolution of convective system made by the cold air and the suitable vertical wind shear.Generation and development processes of the mesoscale convective system were also studied. The findings suggested that stratiform cloud precipitation and dispersed convective precipitation occurred firstly in the precipitation process. The warm and steady stratiform cloud precipitation changed to be highly organized convectional precipitation as the cold dry air invaded. Many small scale and mesoscale convective clusters developed into mesoscale convective complex (MCC), leading to the extreme severe precipitation. Since all the directions of the echo long axis, terrain and echo movement were parallel, train effect was obviously seen in the radar echo imegery during this precipitation process. Meanwhile, the radar echo had the characteristics of backward propagation and low centroid which was similar to tropical heavy rainfalls. Finally, a series of scientific problems were proposed according to the integrated analysis on the observation data of this rare torrential rain event, such as the causes for the extreme torrential rain and the extreme rich water vapor, mechanisms for the warm area torrential rain in the north of China, the mechanism for the train effect and backward propagation, mechanisms for the organization and maintenance of the convective cells, the simulation and analysis ability of the numerical models to extreme torrential rains and so on.
Precipitation characteristics, environment conditions, generation and development of the mesoscale convective system that brought about the extreme torrential rain in Beijing on 21 July 2012 were analyzed comprehensively in this paper by using various conventional and unconventional data. The results showed that the extreme torrential rain had the characteristics of long duration, great rainfall and wide coverage area and its process consisted of warm area precipitation and frontal precipitation. The warm area rainfall started earlier, the severe precipitation center was scattered and lasted long while the frontal rainfallprocess contained several severe rainfall centers with high precipitation efficiency, lasting a short time.Environment conditions of the mesoscale convective system that triggered this extreme severe rainfall were analyzed. The results showed that interactions of high level divergence, the wind shear and convergence with the vortex in the lower troposphere and the surface wind convergence line provided favorable environment to the severe extreme rain. The warm humid airs from the tropical and sub tropical zones converged over the torrential rain region, continuous and sufficient water vapor manifested as high atmospheric column of precipitable water and strong low level water vapor convergence and other extreme vapor conditions for the torrential rain. In addition, the intense precipitation was triggered by the vortex wind shear, wind disturbance on low level jet, surface wind convergence line and the effect of terrain under the condition of the plentiful water vapour and maintained. With the cold front moved eastward, heavy frontal rainfall was brought by the development and evolution of convective system made by the cold air and the suitable vertical wind shear.Generation and development processes of the mesoscale convective system were also studied. The findings suggested that stratiform cloud precipitation and dispersed convective precipitation occurred firstly in the precipitation process. The warm and steady stratiform cloud precipitation changed to be highly organized convectional precipitation as the cold dry air invaded. Many small scale and mesoscale convective clusters developed into mesoscale convective complex (MCC), leading to the extreme severe precipitation. Since all the directions of the echo long axis, terrain and echo movement were parallel, train effect was obviously seen in the radar echo imegery during this precipitation process. Meanwhile, the radar echo had the characteristics of backward propagation and low centroid which was similar to tropical heavy rainfalls. Finally, a series of scientific problems were proposed according to the integrated analysis on the observation data of this rare torrential rain event, such as the causes for the extreme torrential rain and the extreme rich water vapor, mechanisms for the warm area torrential rain in the north of China, the mechanism for the train effect and backward propagation, mechanisms for the organization and maintenance of the convective cells, the simulation and analysis ability of the numerical models to extreme torrential rains and so on.
2006,32(10):64-69, DOI: 10.7519/j.issn.1000-0526.2006.10.010
Abstract:
Based on the data of CINRAD Doppler Radar which located at Xinle of Hebei Province,the hail,strong wind and heavy rainfall weather events in mid-south Hebei in 2004 are statistically analyzed.The routine radar products,such as echo reflectivity,radial velocity,Vertically Integrated Liquid(VIL)Water,hail index,mesocyclone,velocity azimuth display wind profile,etc.are used in this statistics.The results show that hail's VIL value is larger than generic thunder storm's.At the same time,greater VIL value and longer sustaining will bring about greater diameter hail and larger effect area.It is the very useful index to indicate strong wind in mesocyclone products and the wind direction sudden change in radial velocity products.A reference based on analyzing this type synoptic forecast with radar system in future is proposed.
Based on the data of CINRAD Doppler Radar which located at Xinle of Hebei Province,the hail,strong wind and heavy rainfall weather events in mid-south Hebei in 2004 are statistically analyzed.The routine radar products,such as echo reflectivity,radial velocity,Vertically Integrated Liquid(VIL)Water,hail index,mesocyclone,velocity azimuth display wind profile,etc.are used in this statistics.The results show that hail's VIL value is larger than generic thunder storm's.At the same time,greater VIL value and longer sustaining will bring about greater diameter hail and larger effect area.It is the very useful index to indicate strong wind in mesocyclone products and the wind direction sudden change in radial velocity products.A reference based on analyzing this type synoptic forecast with radar system in future is proposed.
Zhou Yuquan, Chen Yingying, Li Juan, Huang Yimei, He Xiaodong, Zhou Feifei, Wu Menxin, Hu Bo, Mao Jietai
2008,34(12):27-35, DOI: 10.7519/j.issn.1000-0526.2008.12.004
Abstract:
Cloud macro and micro physical characteristic parameters play an important role not only in the field of the analysis and forecast of the weather and climate, but also in the field of weather modification to identify the seeding c ondition. Based on the data from FY-2C/D stationary satellite and SBDART radiati on transfer model, associated with the sounding data and surface information, a method retrieving cloud macro and micro physical parameters is established in th is research. These parameters include cloud top height, cloud top temperature, d epth of super-cooled layer, depth of warm layer, cloud bottom height, depth of c loud, cloud optical thickness, cloud effective particle radius and cloud liquid water content. It has been run operationally. In this paper, the correlated info rmation such as physical meaning, retrieving method and technology, retrieving p rocess and data format are simply introduced. Furthermore, comparing with the ob servation of Cloudsat up to the minute, the retrieving results of main cloud par ameters are proved to be reasonable and usable. By contrast with same kind produ cts of MODIS, it also shows good corresponding relationship.
Cloud macro and micro physical characteristic parameters play an important role not only in the field of the analysis and forecast of the weather and climate, but also in the field of weather modification to identify the seeding c ondition. Based on the data from FY-2C/D stationary satellite and SBDART radiati on transfer model, associated with the sounding data and surface information, a method retrieving cloud macro and micro physical parameters is established in th is research. These parameters include cloud top height, cloud top temperature, d epth of super-cooled layer, depth of warm layer, cloud bottom height, depth of c loud, cloud optical thickness, cloud effective particle radius and cloud liquid water content. It has been run operationally. In this paper, the correlated info rmation such as physical meaning, retrieving method and technology, retrieving p rocess and data format are simply introduced. Furthermore, comparing with the ob servation of Cloudsat up to the minute, the retrieving results of main cloud par ameters are proved to be reasonable and usable. By contrast with same kind produ cts of MODIS, it also shows good corresponding relationship.
ZHANG Xiaoling, ZHANG Tao, LIU Xinhua, ZHOU Qingliang, CHEN Yun, ZHOU Xiaoxia, ZHENG Yongguang, ZHAO Surong
2010,36(7):143-150, DOI: 10.7519/j.issn.1000-0526.2010.7.021
Abstract:
Mesoscale severe weather forecasting ability is limited, in some sense for a lack of valid analysis on mesoscale convective systems and its favorable environments. This paper introduces the mesoscale weather chart analysis techniq ue which was tested in the National Meteorological Center (NMC). Mesoscale weath er chart analyzes the favorable environmental conditions of mesoscale convective systems based on observational data and numerical weather forecast outputs. It includes upper air composite chart and surface chart. In the upper air composite ch art, by analyzing wind, temperature, moisture, temperature change and height change, the diagnostic systems and features in all the lower, middle and upper t roposphere isobaric layers are combined into one plot, which can clearly displa y the available environments and synoptic pattern of severe convective weather. In the surface chart, the analysis contents are pressure, wind, temperature, moi sture, convective weather phenomena and all kinds of boundaries (fronts). The te st in NMC shows that mesoscale weather chart analysis is a dependable means for severe convective weather outlook forecasting.
Mesoscale severe weather forecasting ability is limited, in some sense for a lack of valid analysis on mesoscale convective systems and its favorable environments. This paper introduces the mesoscale weather chart analysis techniq ue which was tested in the National Meteorological Center (NMC). Mesoscale weath er chart analyzes the favorable environmental conditions of mesoscale convective systems based on observational data and numerical weather forecast outputs. It includes upper air composite chart and surface chart. In the upper air composite ch art, by analyzing wind, temperature, moisture, temperature change and height change, the diagnostic systems and features in all the lower, middle and upper t roposphere isobaric layers are combined into one plot, which can clearly displa y the available environments and synoptic pattern of severe convective weather. In the surface chart, the analysis contents are pressure, wind, temperature, moi sture, convective weather phenomena and all kinds of boundaries (fronts). The te st in NMC shows that mesoscale weather chart analysis is a dependable means for severe convective weather outlook forecasting.
2013,39(10):1284-1292, DOI: 10.7519/j.issn.1000-0526.2013.10.006
Abstract:
Based on the fog observation data during 24-27 December 2006 (advection radiation fog), NCEP NC reanalysis data (2.5°×2.5°) and GDAS global meteorological data (1°×1°), detailed trajectory analysis of the boundary layer characteristics and water vapor transport of the fog is investigated, combined with the weather condition, meteorological elements and physical quantity field. The results show that: (1) there is thick inversion layer, even multi layer inversion throughout the dense fog event. Temperatures of different inversion tops in the middle and high levels are 2-5℃ higher than the surface temperature. The thickness of inversion layer is more than 200 m, and it gets to 500 m at 08:00 BT 26 December, indicating the atmosphere is very stable and conducive to the convergence of water vapor before the fog forms. However, it is not favorable for the divergence of water vapor after the formation of fog, which helps the development and maintenance of the fog, causing the fog to last about 64 hours with dense fog (visibility <50 m) about 37 hours; (2) The divergence of water vapor flux in low level is negative in the advection fog event. The upper air has persistent moisture convergence and the strongest moisture convergence appears at 02:00 BT 25 December, being -30×10-7 g·s-1·cm-2·hPa-1. The accumulation of low level water vapor makes fog form and develop while the divergence of water vapor flux speeds up its dissipation. 〖JP2〗The long lasting advection radiation fog is mainly caused by the continuous water vapor convergence; (3) The water vapor path is from the coastal area in easten China to Nanjing. The water vapor is continuously supplied from sea during the fog event, with the water vapor flux maximum getting to 2 g·s-1·hPa-1·cm-1. The sufficient supply and supplementary of water vapor determines the duration of the fog.
Based on the fog observation data during 24-27 December 2006 (advection radiation fog), NCEP NC reanalysis data (2.5°×2.5°) and GDAS global meteorological data (1°×1°), detailed trajectory analysis of the boundary layer characteristics and water vapor transport of the fog is investigated, combined with the weather condition, meteorological elements and physical quantity field. The results show that: (1) there is thick inversion layer, even multi layer inversion throughout the dense fog event. Temperatures of different inversion tops in the middle and high levels are 2-5℃ higher than the surface temperature. The thickness of inversion layer is more than 200 m, and it gets to 500 m at 08:00 BT 26 December, indicating the atmosphere is very stable and conducive to the convergence of water vapor before the fog forms. However, it is not favorable for the divergence of water vapor after the formation of fog, which helps the development and maintenance of the fog, causing the fog to last about 64 hours with dense fog (visibility <50 m) about 37 hours; (2) The divergence of water vapor flux in low level is negative in the advection fog event. The upper air has persistent moisture convergence and the strongest moisture convergence appears at 02:00 BT 25 December, being -30×10-7 g·s-1·cm-2·hPa-1. The accumulation of low level water vapor makes fog form and develop while the divergence of water vapor flux speeds up its dissipation. 〖JP2〗The long lasting advection radiation fog is mainly caused by the continuous water vapor convergence; (3) The water vapor path is from the coastal area in easten China to Nanjing. The water vapor is continuously supplied from sea during the fog event, with the water vapor flux maximum getting to 2 g·s-1·hPa-1·cm-1. The sufficient supply and supplementary of water vapor determines the duration of the fog.
2014,40(4):400-411, DOI: 10.7519/j.issn.1000-0526.2014.04.002
Abstract:
Based on the synoptic environment analysis of about 100 severe convection cases in China since 2000 and the reference of related literatures, from the perspectives of the three essential conditions for the development of severe convection, namely the thermal instability, lift and moisture, five basic synoptic situation configurations of severe convection in China are proposed and expounded. They are cold advection forcing category, warm advection forcing category, baroclinic frontogenesis category, quasi barotropic category and elevated thunderstorm category. The typical characteristics of the upper cold advection forcing category is that the mid upper strong cold advection above 500 hPa strengthens and reaches the boundary warm convergence zone. The warm advection forcing category is characterized by trough with special structure moving over low level strong warm and moist advection. The deep convection produced by the mid lower layer convergence of cold and warm air features the baroclinic frontogenesis category. The quasi barotropic category mostly occurs at the northern and the southern edges or the interior of summer subtropical high and the area with weak baroclinicity, where the dynamic forcing and the surface inhomogeneous local heating play major roles. The features of elevated thunderstorms are the southwest jet in 700-500 hPa lifted by boundary cold wedge and the instable energy is from above 700 hPa. The classification based on the difference of the formation mechanisms can grasp accurately the synoptic characteristics, the situation configurations, the dynamic and thermal properties and the key points in analyzing short term potential forecast, providing more technical support to further enhance the level of weather prediction.
Based on the synoptic environment analysis of about 100 severe convection cases in China since 2000 and the reference of related literatures, from the perspectives of the three essential conditions for the development of severe convection, namely the thermal instability, lift and moisture, five basic synoptic situation configurations of severe convection in China are proposed and expounded. They are cold advection forcing category, warm advection forcing category, baroclinic frontogenesis category, quasi barotropic category and elevated thunderstorm category. The typical characteristics of the upper cold advection forcing category is that the mid upper strong cold advection above 500 hPa strengthens and reaches the boundary warm convergence zone. The warm advection forcing category is characterized by trough with special structure moving over low level strong warm and moist advection. The deep convection produced by the mid lower layer convergence of cold and warm air features the baroclinic frontogenesis category. The quasi barotropic category mostly occurs at the northern and the southern edges or the interior of summer subtropical high and the area with weak baroclinicity, where the dynamic forcing and the surface inhomogeneous local heating play major roles. The features of elevated thunderstorms are the southwest jet in 700-500 hPa lifted by boundary cold wedge and the instable energy is from above 700 hPa. The classification based on the difference of the formation mechanisms can grasp accurately the synoptic characteristics, the situation configurations, the dynamic and thermal properties and the key points in analyzing short term potential forecast, providing more technical support to further enhance the level of weather prediction.
2012,38(2):164-173, DOI: 10.7519/j.issn.1000-0526.2012.02.004
Abstract:
Many weather forecasters seem to have acquaintance with most of basic concepts or fundamental theories which are connected with severe convection, but some of them are misapplied frequently by some forecasters when they are engaged in severe convective weather analysis or forecasting argumentation. Due to the above problem, some basic concepts and fundamental theories should be explained from the view of forecasting application. The following issues are discussed in this paper. They are the relationship between humidity and water vapor content, the role of clod air during the precipitation process, the fundamental theories connected with thermal and dynamic instability, the sounding analysis related to instability parameters, the relationship between helicity or moist potential vorticity and instability, the relationship among the convergence line, lifting velocity and convective vertical movement, and the essential connection between the synoptic patterns and severe convective phenomena.
Many weather forecasters seem to have acquaintance with most of basic concepts or fundamental theories which are connected with severe convection, but some of them are misapplied frequently by some forecasters when they are engaged in severe convective weather analysis or forecasting argumentation. Due to the above problem, some basic concepts and fundamental theories should be explained from the view of forecasting application. The following issues are discussed in this paper. They are the relationship between humidity and water vapor content, the role of clod air during the precipitation process, the fundamental theories connected with thermal and dynamic instability, the sounding analysis related to instability parameters, the relationship between helicity or moist potential vorticity and instability, the relationship among the convergence line, lifting velocity and convective vertical movement, and the essential connection between the synoptic patterns and severe convective phenomena.
2015,41(2):212-218, DOI: 10.7519/j.issn.1000-0526.2015.02.009
Abstract:
From 1 May to 8 June 2013 CMA Meteorological Observation Centre conducted an experiment of cloud height observations by using cloud radar (35 GHz), whose observation data are the echo power value and temporal resolution is 1 min and a ceilometer whose observation data are the back scattering intens data with 1 min temporal resolution. The result of analyzing the data observed from the 39 d experiment indicates that: (1) the data acquisition ratio of cloud radar is 26% larger than that of ceilometer; (2) the ratio is 51% in fog haze weather; (3) relatively, precipitation has more significant effect on cloud base height measured by laser ceilometer than that by cloud radar; (4) height of cloud base measured by cloud radar is almost consistent with the height by ceilometer because their average deviation is less than 300 m.
From 1 May to 8 June 2013 CMA Meteorological Observation Centre conducted an experiment of cloud height observations by using cloud radar (35 GHz), whose observation data are the echo power value and temporal resolution is 1 min and a ceilometer whose observation data are the back scattering intens data with 1 min temporal resolution. The result of analyzing the data observed from the 39 d experiment indicates that: (1) the data acquisition ratio of cloud radar is 26% larger than that of ceilometer; (2) the ratio is 51% in fog haze weather; (3) relatively, precipitation has more significant effect on cloud base height measured by laser ceilometer than that by cloud radar; (4) height of cloud base measured by cloud radar is almost consistent with the height by ceilometer because their average deviation is less than 300 m.
2009,35(1):55-64, DOI: 10.7519/j.issn.1000-0526.2009.1.007
Abstract:
A strong rainstorm is analysis which occurred in Xinghua located the north of Ji angsu province on 25 July 2007. Results show that wind disaster originated from two kinds of rainstorm. One kind was the gust front which occurred at the front of the storm. Strong wind of grade 7-9 was attained when it happened. Another ki nd was the downburst arose in the multi cell storm. The original height of refl ectivity core was higher than -20℃ isotherm. It had the characteristics of conv ergence on the mid level and descending of reflectivity core. The strong wind ab ove grade 10 was attained, when the descending airflow diverged strongly on the ground. A new cell was combined with the former storm above the gust front, thus the storm enhanced. When the downburst happened, the storm weakened, and another new cell was combin ed with the former storm. The downburst happened continuously, and the impact of gust front persisted.
A strong rainstorm is analysis which occurred in Xinghua located the north of Ji angsu province on 25 July 2007. Results show that wind disaster originated from two kinds of rainstorm. One kind was the gust front which occurred at the front of the storm. Strong wind of grade 7-9 was attained when it happened. Another ki nd was the downburst arose in the multi cell storm. The original height of refl ectivity core was higher than -20℃ isotherm. It had the characteristics of conv ergence on the mid level and descending of reflectivity core. The strong wind ab ove grade 10 was attained, when the descending airflow diverged strongly on the ground. A new cell was combined with the former storm above the gust front, thus the storm enhanced. When the downburst happened, the storm weakened, and another new cell was combin ed with the former storm. The downburst happened continuously, and the impact of gust front persisted.
2014,40(2):133-145, DOI: 10.7519/j.issn.1000-0526.2014.02.001
Abstract:
By using the NCEP reanalysis data, the vapor budget of the area covered by the severe torrential rain over the northeast of North China on 21 July, 2012 is calculated according to the vapor budget equation. The results show that meridional water vapor transportation is dominant while the extremely heavy rain hits Beijing Region, where most moist vapor comes from the southern boundary below 500 hPa. The low level regional moisture convergence is consistent with the time and space when the torrential rain breaks out and develops. Above the middle level the vertical vapor transport is more prominent. Then the variation features of the vapor transport corridors and their moisture contributions are got through the HYSPLIT mode. The backward trajectory analyses illustrate two major vapor transport corridors. The moistest vapor derived from Yellow Sea and East China Sea along the low level make the main moisture contribution during the heavy precipitation. Moisture from the South China Sea and the Bay of Bengal strengthens the water vapor in the region when the heavy rain starts and develops. Also the drier vapor corridor along the high level from the northwest of China plays an important role in this case.
By using the NCEP reanalysis data, the vapor budget of the area covered by the severe torrential rain over the northeast of North China on 21 July, 2012 is calculated according to the vapor budget equation. The results show that meridional water vapor transportation is dominant while the extremely heavy rain hits Beijing Region, where most moist vapor comes from the southern boundary below 500 hPa. The low level regional moisture convergence is consistent with the time and space when the torrential rain breaks out and develops. Above the middle level the vertical vapor transport is more prominent. Then the variation features of the vapor transport corridors and their moisture contributions are got through the HYSPLIT mode. The backward trajectory analyses illustrate two major vapor transport corridors. The moistest vapor derived from Yellow Sea and East China Sea along the low level make the main moisture contribution during the heavy precipitation. Moisture from the South China Sea and the Bay of Bengal strengthens the water vapor in the region when the heavy rain starts and develops. Also the drier vapor corridor along the high level from the northwest of China plays an important role in this case.
2014,40(4):389-399, DOI: 10.7519/j.issn.1000-0526.2014.04.001
Abstract:
Thunderstorm potential forecasting based on three ingredients has been widely accepted. This article aims to discuss some basical questions in operational forecast applications, and clarify some easily confused concepts. The content includes atmospheric instablility and convection, thunderstorms trigger mechanism and lifting and its relationship with snoptical weather system, how to deal with the three elements of the thunderstorm “enough”, the combination of pattern recognition and ingredients based forecasting methodology. Atmospheric instablility is one of the three ingredients of convection initiation, and it is also very important to thunderstorm short time forecasting and analysis. This paper discusses various mesoscale instability related to the thunderstorm, and inicates how to estimate the spatial and temporal evolution of CAPE. In addition, the definition and criterion for potential instability and symmetric instability are discussed profoundly.
Thunderstorm potential forecasting based on three ingredients has been widely accepted. This article aims to discuss some basical questions in operational forecast applications, and clarify some easily confused concepts. The content includes atmospheric instablility and convection, thunderstorms trigger mechanism and lifting and its relationship with snoptical weather system, how to deal with the three elements of the thunderstorm “enough”, the combination of pattern recognition and ingredients based forecasting methodology. Atmospheric instablility is one of the three ingredients of convection initiation, and it is also very important to thunderstorm short time forecasting and analysis. This paper discusses various mesoscale instability related to the thunderstorm, and inicates how to estimate the spatial and temporal evolution of CAPE. In addition, the definition and criterion for potential instability and symmetric instability are discussed profoundly.
2012,38(1):1-16, DOI: 10.7519/j.issn.1000-0526.2012.01.001
Abstract:
In this paper, the modulation of atmospheric MJO on typhoon generation over the northwestern Pacific and its mechanism are first studied by using the MJO index. The results show that the MJO plays an important modulation role in typhoon generation over the northwestern Pacific: The proportion of typhoon number is 21 between active period and inactive period; During the MJO active period, the proportion of typhoon number is also 2:1 between phases 5-6 and phases 2-3 of MJO. The composite analyses of atmospheric circulation show that there are different circulation patterns over the northwestern Pacific in different phases of the MJO, which will affect the typhoon generation. In phases 5-6 (2-3), the dynamic factor and convective heating patterns over western Pacific are favorable (unfavorable) for typhoon generation. Then， the comparing analyses of the 30-60 day low frequency kinetic energy in lower and higher levels of the troposphere show that the atmospheric intraseasonal oscillation over the northwestern Pacific has a clear impact on the typhoon generation. There is an evident positive (negative) anomaly area of 30-60 day low frequency kinetic energy in the more (less) typhoon years over the northwestern Pacific east of the Philippines, which means that strong (weak) atmospheric intraseasonal oscillation (ISO) over the northwestern Pacific is favorable (unfavorable) for typhoon generation. The analyses of 200 hPa velocity potential show that there is a clear divergence (convergence) pattern over the northwestern Pacific in the more (less) typhoon years, which is favorable (unfavorable) for typhoon generation. The modulation of the intraseasonal oscillation on the typhoon tracks over the northwestern Pacific is studied by observational data analyses. We classified the main classes of typhoon tracks into 5 types as straight west moving typhoons (I), northwest moving typhoons (II), recurving to Korea/west of Japan typhoons (III), landing on Japan typhoons (IV) and recurving to the east of Japan typhoons (V). Then the composite analyses of atmospheric low-frequency wind fields at 850, 500 and 200 hPa, corresponding to the typhoon forming date, for every typhoon track are completed. The analysis results of relationships between the low-frequency (ISO) wind fields and typhoon tracks have indicated that the typhoon tracks will be affected by wind pattern of the ISO. The low frequency positive vorticity belt (the maximum value line of cyclonic vorticity) associated with low-frequency cyclone (LFC) at 850 hPa is so closely related to the typhoon track, that the maximum value line (belt) of low frequency cyclonic vorticity can be an important factor to predicate the typhoon tracks over the northwestern Pacific. And the typhoon tracks will be also affected by the ISO circulation pattern at 200 hPa, particularly the strong low frequency wind associated with low frequency anticyclone (LFAC).
In this paper, the modulation of atmospheric MJO on typhoon generation over the northwestern Pacific and its mechanism are first studied by using the MJO index. The results show that the MJO plays an important modulation role in typhoon generation over the northwestern Pacific: The proportion of typhoon number is 21 between active period and inactive period; During the MJO active period, the proportion of typhoon number is also 2:1 between phases 5-6 and phases 2-3 of MJO. The composite analyses of atmospheric circulation show that there are different circulation patterns over the northwestern Pacific in different phases of the MJO, which will affect the typhoon generation. In phases 5-6 (2-3), the dynamic factor and convective heating patterns over western Pacific are favorable (unfavorable) for typhoon generation. Then， the comparing analyses of the 30-60 day low frequency kinetic energy in lower and higher levels of the troposphere show that the atmospheric intraseasonal oscillation over the northwestern Pacific has a clear impact on the typhoon generation. There is an evident positive (negative) anomaly area of 30-60 day low frequency kinetic energy in the more (less) typhoon years over the northwestern Pacific east of the Philippines, which means that strong (weak) atmospheric intraseasonal oscillation (ISO) over the northwestern Pacific is favorable (unfavorable) for typhoon generation. The analyses of 200 hPa velocity potential show that there is a clear divergence (convergence) pattern over the northwestern Pacific in the more (less) typhoon years, which is favorable (unfavorable) for typhoon generation. The modulation of the intraseasonal oscillation on the typhoon tracks over the northwestern Pacific is studied by observational data analyses. We classified the main classes of typhoon tracks into 5 types as straight west moving typhoons (I), northwest moving typhoons (II), recurving to Korea/west of Japan typhoons (III), landing on Japan typhoons (IV) and recurving to the east of Japan typhoons (V). Then the composite analyses of atmospheric low-frequency wind fields at 850, 500 and 200 hPa, corresponding to the typhoon forming date, for every typhoon track are completed. The analysis results of relationships between the low-frequency (ISO) wind fields and typhoon tracks have indicated that the typhoon tracks will be affected by wind pattern of the ISO. The low frequency positive vorticity belt (the maximum value line of cyclonic vorticity) associated with low-frequency cyclone (LFC) at 850 hPa is so closely related to the typhoon track, that the maximum value line (belt) of low frequency cyclonic vorticity can be an important factor to predicate the typhoon tracks over the northwestern Pacific. And the typhoon tracks will be also affected by the ISO circulation pattern at 200 hPa, particularly the strong low frequency wind associated with low frequency anticyclone (LFAC).
2014,40(7):816-826, DOI: 10.7519/j.issn.1000-0526.2014.07.005
Abstract:
In term of precipitation data of 2400 stations from 1981 to 2010, annual, seasonal and monthly distribution and evolution characteristics of rainstorm were analyzed. The results show that the processes of rainstorm have been increased evidently since 21 century especially in the south of China, but the duration is relatively short. Rainstorm days have been increased, but the amount of precipitation is not as much as in 1990s. Variation trend of the annual (monthly) precipitation amount is in accordance with that of rainstorm days, but rainfall is averagely more while the rainstorm days are less during spring rainfall phase over the south of Yangtze River. Distribution of the maximum annual rainstorm days is very similar with that of the annual mean rainstorm days, revealing the feature of more in south and east but less in north and west. Maximum annual rainstorm days are more than double of annual average rainstorm days with multi centers due to the effect of topography. The months of maximum monthly rainstorm days over different regions of the same province are incompletely same as the result of the impact of different weather systems. Generally, rainstorm days have been increased since 2000, rainstorm begins earlier, ends latter and lasts longer than before. Nowadays, as the extreme rainfall events and secondary disasters happen frequently, it is conducive for the forecast of quantitative precipitation forecast (QPF) to learn the spatio temporal distribution and evolution features of rainstorm.
In term of precipitation data of 2400 stations from 1981 to 2010, annual, seasonal and monthly distribution and evolution characteristics of rainstorm were analyzed. The results show that the processes of rainstorm have been increased evidently since 21 century especially in the south of China, but the duration is relatively short. Rainstorm days have been increased, but the amount of precipitation is not as much as in 1990s. Variation trend of the annual (monthly) precipitation amount is in accordance with that of rainstorm days, but rainfall is averagely more while the rainstorm days are less during spring rainfall phase over the south of Yangtze River. Distribution of the maximum annual rainstorm days is very similar with that of the annual mean rainstorm days, revealing the feature of more in south and east but less in north and west. Maximum annual rainstorm days are more than double of annual average rainstorm days with multi centers due to the effect of topography. The months of maximum monthly rainstorm days over different regions of the same province are incompletely same as the result of the impact of different weather systems. Generally, rainstorm days have been increased since 2000, rainstorm begins earlier, ends latter and lasts longer than before. Nowadays, as the extreme rainfall events and secondary disasters happen frequently, it is conducive for the forecast of quantitative precipitation forecast (QPF) to learn the spatio temporal distribution and evolution features of rainstorm.
2011,37(10):1262-1269, DOI: 10.7519/j.issn.1000-0526.2011.10.009
Abstract:
Based on the daily precipitation data at 110 observational stations during 1961-2008 in South China， the climatic characteristics and variation of torrential rain days， rainstorm intensity and contribution which is in annual， the first and second flood seasons in South China were studied by using statistical and diagnostic methods， such as linear regression analysis， Mann Kendall test， wavelet analysis and the computation of trend coefficients. The results have shown that the annual mean torrential rain days have a decreasing trend from coastal regions to inland in South China in recent 48 years， the highest center is in Dongxing of Guangxi （14.9 d）， and the lowest center is in Longlin of Guangxi （3.2 d）. About 72% of the total torrential rain days occurred in the flood seasons with about 45% in the first season and 27% in the second season. The mean torrential rain days have increased faintly in annual， the first and second flood seasons in South China， but it is not obvious. There are the characteristics of interannual and interdecadal changes. The mean rainstorm intensity has increased faintly in annual and in the first flood season in South China. However, since 2005 it has become obviously. The mean rainstorm intensity has declined in the second flood season， but it is not obvious. The annual mean rainstorm contribution to the total rainfall has increased obviously， but the mean contribution is not obvious in the first and second flood seasons. The wavelet analysis has shown that the changes of torrential rain days， intensity and contribution which is in annual， the first and second flood seasons in South China have two significant periods of 2-3 a and 3-4 a.
Based on the daily precipitation data at 110 observational stations during 1961-2008 in South China， the climatic characteristics and variation of torrential rain days， rainstorm intensity and contribution which is in annual， the first and second flood seasons in South China were studied by using statistical and diagnostic methods， such as linear regression analysis， Mann Kendall test， wavelet analysis and the computation of trend coefficients. The results have shown that the annual mean torrential rain days have a decreasing trend from coastal regions to inland in South China in recent 48 years， the highest center is in Dongxing of Guangxi （14.9 d）， and the lowest center is in Longlin of Guangxi （3.2 d）. About 72% of the total torrential rain days occurred in the flood seasons with about 45% in the first season and 27% in the second season. The mean torrential rain days have increased faintly in annual， the first and second flood seasons in South China， but it is not obvious. There are the characteristics of interannual and interdecadal changes. The mean rainstorm intensity has increased faintly in annual and in the first flood season in South China. However, since 2005 it has become obviously. The mean rainstorm intensity has declined in the second flood season， but it is not obvious. The annual mean rainstorm contribution to the total rainfall has increased obviously， but the mean contribution is not obvious in the first and second flood seasons. The wavelet analysis has shown that the changes of torrential rain days， intensity and contribution which is in annual， the first and second flood seasons in South China have two significant periods of 2-3 a and 3-4 a.
2014,40(11):1372-1379, DOI: 10.7519/j.issn.1000-0526.2014.11.010
Abstract:
The hourly precipitation observation data from 2447 rain gauge records are used to verify and evaluate the satellite precipitation estimation products of Climate Prediction Center Morphing Technique (CMORPH) and Tropical Rainfall Measuring Mission (TRMM) 3B42 during 2007-2010 in China. The results show that the two satellite precipitation data are similar to ground gain gauge data in revealing the spatial patterns of daily mean precipitation amount. The pattern correlation coefficients of 3 h rainfall amount are over 0.5 and 0.4 in most areas, respectively. Bias of two satellite precipitation products are both between the positive and negative 0.25 mm, but there are significant difference between the north and the south. And the mean absolute error, relative error and root mean square error all have a significant seasonal periodic variations. The two satellite precipitation products can reflect the summer rainfall diurnal variation well in most parts of China, but there are also clear distinctions in some areas. The overall vacancy retrieval rate of CMORPH and TRMM 3B42 products are 7.23% and 2.63%, overall missing retrieval rate are 3.25% and 5.5%, respectively.
The hourly precipitation observation data from 2447 rain gauge records are used to verify and evaluate the satellite precipitation estimation products of Climate Prediction Center Morphing Technique (CMORPH) and Tropical Rainfall Measuring Mission (TRMM) 3B42 during 2007-2010 in China. The results show that the two satellite precipitation data are similar to ground gain gauge data in revealing the spatial patterns of daily mean precipitation amount. The pattern correlation coefficients of 3 h rainfall amount are over 0.5 and 0.4 in most areas, respectively. Bias of two satellite precipitation products are both between the positive and negative 0.25 mm, but there are significant difference between the north and the south. And the mean absolute error, relative error and root mean square error all have a significant seasonal periodic variations. The two satellite precipitation products can reflect the summer rainfall diurnal variation well in most parts of China, but there are also clear distinctions in some areas. The overall vacancy retrieval rate of CMORPH and TRMM 3B42 products are 7.23% and 2.63%, overall missing retrieval rate are 3.25% and 5.5%, respectively.
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