ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 49,Issue 6,2023 Table of Contents
2023, 49(6):641-656.
DOI: 10.7519/j.issn.1000-0526.2022.121201
Abstract:
A relatively large number of the convective storms which affect Beijing and Hebei can often be traced to the Taihang Mountains. This study analyzes warm-season convective storms developing in the eastern foothills of the Taihang Mountains during 2011-2020. The statistical analysis is based on the national composite radar reflectivity factor data mosaics to increase the understanding of the evolution of these convective storms, including the changing of intensity, lifespan and so on. The results show that there are four high-frequency centers with strong echoes ≥45 dBz located in northern Shijiazhuang, southern Beijing, south-central Baoding and western Cangzhou. The storms often strengthen significantly in the foothills of northern Shijiazhuang and western Cangzhou. For the strengthened convective storms, they are most active in mountainous areas around 17:00 BT and mainly affect plain areas between 18:00 BT and 02:00 BT. The more westerly the path, the more cases of mountain-to-plain convective storms, the higher the percentage of convective intensification, and the greater the moving speed. During the downhill process, most convective storms become stronger and more organized. For the convective storms whose echo strength ≥45 dBz at the initial moment of going downhill, more than 86% of them can successfully reach the plains, and more than 90% of them with horizontal scale exceeding 100 km and solidly connected structures can successfully reach the plains. The strong echo areas of the strengthened convective storms expand dramatically as they go downhill. Strong echo areas expand to about 2 times larger than their initial echo areas when they reach the foothill, and the average areas in the plains can reach 4.6 times as big as their initial echo areas. Most of the strengthened convective storms take only 1-2 hours to go downhill and last 4-8 hours on the plains. The storm types of the convective storms which last 4-8 hours on the plains are dominated by linear MCS (47%) and nonlinear MCS (30%).
A relatively large number of the convective storms which affect Beijing and Hebei can often be traced to the Taihang Mountains. This study analyzes warm-season convective storms developing in the eastern foothills of the Taihang Mountains during 2011-2020. The statistical analysis is based on the national composite radar reflectivity factor data mosaics to increase the understanding of the evolution of these convective storms, including the changing of intensity, lifespan and so on. The results show that there are four high-frequency centers with strong echoes ≥45 dBz located in northern Shijiazhuang, southern Beijing, south-central Baoding and western Cangzhou. The storms often strengthen significantly in the foothills of northern Shijiazhuang and western Cangzhou. For the strengthened convective storms, they are most active in mountainous areas around 17:00 BT and mainly affect plain areas between 18:00 BT and 02:00 BT. The more westerly the path, the more cases of mountain-to-plain convective storms, the higher the percentage of convective intensification, and the greater the moving speed. During the downhill process, most convective storms become stronger and more organized. For the convective storms whose echo strength ≥45 dBz at the initial moment of going downhill, more than 86% of them can successfully reach the plains, and more than 90% of them with horizontal scale exceeding 100 km and solidly connected structures can successfully reach the plains. The strong echo areas of the strengthened convective storms expand dramatically as they go downhill. Strong echo areas expand to about 2 times larger than their initial echo areas when they reach the foothill, and the average areas in the plains can reach 4.6 times as big as their initial echo areas. Most of the strengthened convective storms take only 1-2 hours to go downhill and last 4-8 hours on the plains. The storm types of the convective storms which last 4-8 hours on the plains are dominated by linear MCS (47%) and nonlinear MCS (30%).
2023, 49(6):657-670.
DOI: 10.7519/j.issn.1000-0526.2023.021701
Abstract:
Using the precipitation data of dense automatic weather stations, ERA5 reanalysis data and radar data, we analyze a local rainstorm process influenced by the parallel ridge-valley topography in western Chongqing from 16 to 17 June 2020. The results show that the rainstorm process happened under the combined influence of the stable low vortex shear formed by the southwest warm and humid low-level airflow around the subtropical high and the northward air flow intruding into the Sichuan Basin under the guidance of the high trough in western Chongqing, and the maintaining mesoscale convergence line under the influence of the parallel ridge-valley topography. From 00 UTC to 03 UTC 17 June 2020, there existed obvious moisture convergence, ascending motion and strong instability center in the boundary layer below 850 hPa in the ridge-valley region, which triggered the localized severe heavy rainfall. Due to the ridge-valley topography, the cold front and the convergence center moving northward along the convergence line lifted on the windward slope, strengthening the vertical ascending motion that enhanced the vertical circulation wind speed ahead of the front. This is an important cause for the rainstorm amplification in the southern end of Huaying Mountain and the eastern transition area of wide valleys and hills. The development and evolution of the mesoscale convective systems were closely related to the postion change of the surface convergence line. The convergence uplift of the parallel ridge-valley made the mesoscale convective systems stagnate near the Huaying Mountain and strengthen twice at its southern end.
Using the precipitation data of dense automatic weather stations, ERA5 reanalysis data and radar data, we analyze a local rainstorm process influenced by the parallel ridge-valley topography in western Chongqing from 16 to 17 June 2020. The results show that the rainstorm process happened under the combined influence of the stable low vortex shear formed by the southwest warm and humid low-level airflow around the subtropical high and the northward air flow intruding into the Sichuan Basin under the guidance of the high trough in western Chongqing, and the maintaining mesoscale convergence line under the influence of the parallel ridge-valley topography. From 00 UTC to 03 UTC 17 June 2020, there existed obvious moisture convergence, ascending motion and strong instability center in the boundary layer below 850 hPa in the ridge-valley region, which triggered the localized severe heavy rainfall. Due to the ridge-valley topography, the cold front and the convergence center moving northward along the convergence line lifted on the windward slope, strengthening the vertical ascending motion that enhanced the vertical circulation wind speed ahead of the front. This is an important cause for the rainstorm amplification in the southern end of Huaying Mountain and the eastern transition area of wide valleys and hills. The development and evolution of the mesoscale convective systems were closely related to the postion change of the surface convergence line. The convergence uplift of the parallel ridge-valley made the mesoscale convective systems stagnate near the Huaying Mountain and strengthen twice at its southern end.
2023, 49(6):671-681.
DOI: 10.7519/j.issn.1000-0526.2023.030801
Abstract:
As an important parameter in representing precipitation anomalies, water vapor flux divergence (Qv) is decomposed into three components based on the Helmholtz theorem, i.e., flow convergence caused by rotating winds (Qr), moisture advections by divergent winds (Qd) and water vapor flux divergence by large-scale airflow convergence and divergence (Qdiv). Taking the severe rainfall event caused by Typhoon Rumbia (No.18) in 2018 as an example, this paper analyzes the temporal evolutions and spatial distributions of the three components from the perspective of water vapor flux divergence and its three decomposed components. The results show that Qv only indicates water vapor accumulations, while the decomposed components can better represent their individual leading roles at different precipitating stages. The value of Qv mainly originates from Qdiv, while the positive contribution of Qr caused by the rotational wind component is better when heavy precipitation occurs. The decrease in precipitation is often caused by the inhibition effect of Qd caused by the divergent wind component. Further applications of this decomposition technique of water vapor flux divergence will potentially improve the diagnosis and prediction of typhoon rainstorms in the future.
As an important parameter in representing precipitation anomalies, water vapor flux divergence (Qv) is decomposed into three components based on the Helmholtz theorem, i.e., flow convergence caused by rotating winds (Qr), moisture advections by divergent winds (Qd) and water vapor flux divergence by large-scale airflow convergence and divergence (Qdiv). Taking the severe rainfall event caused by Typhoon Rumbia (No.18) in 2018 as an example, this paper analyzes the temporal evolutions and spatial distributions of the three components from the perspective of water vapor flux divergence and its three decomposed components. The results show that Qv only indicates water vapor accumulations, while the decomposed components can better represent their individual leading roles at different precipitating stages. The value of Qv mainly originates from Qdiv, while the positive contribution of Qr caused by the rotational wind component is better when heavy precipitation occurs. The decrease in precipitation is often caused by the inhibition effect of Qd caused by the divergent wind component. Further applications of this decomposition technique of water vapor flux divergence will potentially improve the diagnosis and prediction of typhoon rainstorms in the future.
2023, 49(6):682-696.
DOI: 10.7519/j.issn.1000-0526.2023.011601
Abstract:
Using observation data from automatic weather station (AWS), ERA5 reanalysis data, Himawari-8 satellite data and multi-source observation data at Xiang’an Station, we analyze the circulation situation, evolution characteristics and microphysical structure of a sea fog event that occurred in southern Fujian Coastal Area (SFCA) on 1 April 2021. The results show that this was a typical advection fog process. Multiple weather conditions provided stable circulation situation and abundant water vapor conditions for the occurrence and development of sea fog. In other words, when the fog was formed, there was west-southwest airflow at 500 hPa, the lower troposphere was controlled by consistent southwest airflow and anticyclonic sinking airflow, and the temperature inversion layer and wet layer existed near surface. Low-level cloud and sea fog conversed into each other during the whole fog process. Daytime was dominated by low-level cloud, but after sunset, the low-level cloud changes into fog with dropping temperature and slowing wind. Next morning, fog changed into low-level cloud under the effect of west wind. The fog height is deduced by aerosol lidar. The fog thickness was relatively low and fluctuated greatly in the initial and developing stages, and the fog top height was about 100 m in the mature stage. Microphysical analysis shows that average fog droplet number concentration (N) was 52.4 cm-3, the average fog droplet liquid water content (LWC) was 0.084 g·m-3, and the mean diameter (MD) was 9.4 μm during this event. The maxima of the average N per minute and the average LWC per minute were 132.6 cm-3 and 0.7321 g·m-3, respectively. Spectrums of N and LWC at different stages exhibited quite different characteristics, of which the size distribution of N was mainly a unimodal structure with the peak diameter at 4-6 μm in the preliminary, development and dissipation stages, but it was a bimodal structure with the main peak at 4-5 μm and the secondary peak at 24-26 μm in the mature stage. The LWC also had a bimodal structure, with the main peak at 24-26 μm and the secondary peak at 5-6 μm. Thus, the N should be dominantly influenced by small particles, but the greatest influence to LWC is fog droplets of 20-30 μm. Comparative analysis of size distribution at the development and mature stages shows that the main reason for the further deterioration of visibility should be the significant increase in LWC which resulted from the increase in the particles of 20-30 μm.
Using observation data from automatic weather station (AWS), ERA5 reanalysis data, Himawari-8 satellite data and multi-source observation data at Xiang’an Station, we analyze the circulation situation, evolution characteristics and microphysical structure of a sea fog event that occurred in southern Fujian Coastal Area (SFCA) on 1 April 2021. The results show that this was a typical advection fog process. Multiple weather conditions provided stable circulation situation and abundant water vapor conditions for the occurrence and development of sea fog. In other words, when the fog was formed, there was west-southwest airflow at 500 hPa, the lower troposphere was controlled by consistent southwest airflow and anticyclonic sinking airflow, and the temperature inversion layer and wet layer existed near surface. Low-level cloud and sea fog conversed into each other during the whole fog process. Daytime was dominated by low-level cloud, but after sunset, the low-level cloud changes into fog with dropping temperature and slowing wind. Next morning, fog changed into low-level cloud under the effect of west wind. The fog height is deduced by aerosol lidar. The fog thickness was relatively low and fluctuated greatly in the initial and developing stages, and the fog top height was about 100 m in the mature stage. Microphysical analysis shows that average fog droplet number concentration (N) was 52.4 cm-3, the average fog droplet liquid water content (LWC) was 0.084 g·m-3, and the mean diameter (MD) was 9.4 μm during this event. The maxima of the average N per minute and the average LWC per minute were 132.6 cm-3 and 0.7321 g·m-3, respectively. Spectrums of N and LWC at different stages exhibited quite different characteristics, of which the size distribution of N was mainly a unimodal structure with the peak diameter at 4-6 μm in the preliminary, development and dissipation stages, but it was a bimodal structure with the main peak at 4-5 μm and the secondary peak at 24-26 μm in the mature stage. The LWC also had a bimodal structure, with the main peak at 24-26 μm and the secondary peak at 5-6 μm. Thus, the N should be dominantly influenced by small particles, but the greatest influence to LWC is fog droplets of 20-30 μm. Comparative analysis of size distribution at the development and mature stages shows that the main reason for the further deterioration of visibility should be the significant increase in LWC which resulted from the increase in the particles of 20-30 μm.
5 Objective Correction Schemes on the Forecast of Torrential Rain During the Meiyu Period in Zhejiang
2023, 49(6):697-707.
DOI: 10.7519/j.issn.1000-0526.2023.040901
Abstract:
Based on the 2019-2021 rainfall observation and forecasts from multiple NWP models in Zhejiang Province, the performances of five operational models in forecasting torrential rains during the Meiyu period are analyzed. The 12 objective correction schemes are used to hindcast forecasts for the 2020 and 2021 Meiyu periods in Zhejiang, and are comparatively analyzed through the compressive evaluation. The results demonstrate that the skills of ECMWF, CMA-SH9 and CMA-MESO models are better than NCEP-GFS and CMA-GFS models in forecasting the torrential rains in the Meiyu period, and they have stable frequency bias relationships, therefore picked out for objective correction. Frequency matching fails to improve torrential rain quality because of the significant interannual variation in characteristics of torrential rains in the Meiyu period. The optimal score method (OTS) can improve the TS score of ECMWF rainfall forecast obviously, but its false alarm ratio is raised. The probability 〖JP2〗matching correction based on ECMWF〖JP〗 ensemble average and corrected forecast by OTS performs good skills in improving the forecast quality of the torrential rains in Meiyu period when steady torrential rain events with large rain bands are the dominant, but its correction is not effective for the convective-dominated torrential rain events. Various multi-model fusion schemes of preferred models, including multi-model averaging, adaptive integration and time-lagged ensemble forecast, can effectively improve the forecast quality of convective-dominated torrential rain events in the 2020 and 2021 Meiyu periods. Those schemes of multi-model fusion integrating OTS corrected models further improve the forecast skill for both steady and convective-dominated torrential rain events. Among them, the time-lagged ensemble algorithm integrating OTS corrected models has the best skill.
Based on the 2019-2021 rainfall observation and forecasts from multiple NWP models in Zhejiang Province, the performances of five operational models in forecasting torrential rains during the Meiyu period are analyzed. The 12 objective correction schemes are used to hindcast forecasts for the 2020 and 2021 Meiyu periods in Zhejiang, and are comparatively analyzed through the compressive evaluation. The results demonstrate that the skills of ECMWF, CMA-SH9 and CMA-MESO models are better than NCEP-GFS and CMA-GFS models in forecasting the torrential rains in the Meiyu period, and they have stable frequency bias relationships, therefore picked out for objective correction. Frequency matching fails to improve torrential rain quality because of the significant interannual variation in characteristics of torrential rains in the Meiyu period. The optimal score method (OTS) can improve the TS score of ECMWF rainfall forecast obviously, but its false alarm ratio is raised. The probability 〖JP2〗matching correction based on ECMWF〖JP〗 ensemble average and corrected forecast by OTS performs good skills in improving the forecast quality of the torrential rains in Meiyu period when steady torrential rain events with large rain bands are the dominant, but its correction is not effective for the convective-dominated torrential rain events. Various multi-model fusion schemes of preferred models, including multi-model averaging, adaptive integration and time-lagged ensemble forecast, can effectively improve the forecast quality of convective-dominated torrential rain events in the 2020 and 2021 Meiyu periods. Those schemes of multi-model fusion integrating OTS corrected models further improve the forecast skill for both steady and convective-dominated torrential rain events. Among them, the time-lagged ensemble algorithm integrating OTS corrected models has the best skill.
2023, 49(6):708-720.
DOI: 10.7519/j.issn.1000-0526.2023.032001
Abstract:
Based on the new data such as mooring launch sounding, lidar and surface densely observed data of the Winter Olympic Games in Zhangjiakou Area, the NCEP 0.25°×0.25° reanalysis data, and the field observation of the cold-air-pool (CAP) process from 15 to 16 January 2020, this paper analyzes the temperature, humidity and three-dimensional wind field of the CAP, and constructs the conceptual model of the formation, development, maintenance and breakup process of the CAP. The results show that this CAP process occurred under the background of stable-static weather with weak high-pressure ridge control, middle-level warming, significantly reduced wind speed in the upper air, less cloud in the sky and breeze near the ground. The CAP began to build up gradually from sunset in the evening when atmosphere was neutral, the strong fall wind on both sides of the valley slopes carried the cold air, stacked up and converged at the bottom of the valley, producing updraft and replacing the warm air in the valley, lifting it up. Temperature inversion formed and rapidly developed upward. Around midnight about 4-5 hours after sunset, the CAP developed to the height of about 300 m, which is about 3/5 of the valley height, 300 m above which was the isothermal layer, i.e., warm zone. During the development of the CAP, obvious east-west wind shear layer appeared under the inversion layer. With the continuous rise of the inversion layer top, the wind shear layer also gradually rose. From midnight to sunrise, the CAP developed into maintenance period, with little change at the height of inversion layer top and temperature, while the temperature at the bottom of the CAP continued to decline slowly. In this period, the down-slope wind and down-valley wind failed to penetrate into the valley floor, and the cooling was mainly of long-wave radiation cooling. The CAP break up about four hours after sunrise. First, solar radiation heated the western slope of the valley, causing the air in the middle and upper levels of the valley to heat up rapidly, and then with the increase of solar altitude angle, up-slope wind and up-valley wind appeared on the eastern and western slopes of the valley, transporting the cold air from the valley bottom to the eastern and western slopes and out of the valley. The warm air in the middle and upper levels of the valley sank, the convective boundary layer decreased, and the inversion dissipated from top to bottom, which was obviously different from the inversion disappearing from bottom to top in the plain area.
Based on the new data such as mooring launch sounding, lidar and surface densely observed data of the Winter Olympic Games in Zhangjiakou Area, the NCEP 0.25°×0.25° reanalysis data, and the field observation of the cold-air-pool (CAP) process from 15 to 16 January 2020, this paper analyzes the temperature, humidity and three-dimensional wind field of the CAP, and constructs the conceptual model of the formation, development, maintenance and breakup process of the CAP. The results show that this CAP process occurred under the background of stable-static weather with weak high-pressure ridge control, middle-level warming, significantly reduced wind speed in the upper air, less cloud in the sky and breeze near the ground. The CAP began to build up gradually from sunset in the evening when atmosphere was neutral, the strong fall wind on both sides of the valley slopes carried the cold air, stacked up and converged at the bottom of the valley, producing updraft and replacing the warm air in the valley, lifting it up. Temperature inversion formed and rapidly developed upward. Around midnight about 4-5 hours after sunset, the CAP developed to the height of about 300 m, which is about 3/5 of the valley height, 300 m above which was the isothermal layer, i.e., warm zone. During the development of the CAP, obvious east-west wind shear layer appeared under the inversion layer. With the continuous rise of the inversion layer top, the wind shear layer also gradually rose. From midnight to sunrise, the CAP developed into maintenance period, with little change at the height of inversion layer top and temperature, while the temperature at the bottom of the CAP continued to decline slowly. In this period, the down-slope wind and down-valley wind failed to penetrate into the valley floor, and the cooling was mainly of long-wave radiation cooling. The CAP break up about four hours after sunrise. First, solar radiation heated the western slope of the valley, causing the air in the middle and upper levels of the valley to heat up rapidly, and then with the increase of solar altitude angle, up-slope wind and up-valley wind appeared on the eastern and western slopes of the valley, transporting the cold air from the valley bottom to the eastern and western slopes and out of the valley. The warm air in the middle and upper levels of the valley sank, the convective boundary layer decreased, and the inversion dissipated from top to bottom, which was obviously different from the inversion disappearing from bottom to top in the plain area.
2023, 49(6):721-732.
DOI: 10.7519/j.issn.1000-0526.2022.092601
Abstract:
Alpine skiing is extremely sensitive to wind, and especially extreme wind speed is often one of the key factors that determine the smooth progress of the Winter Olympic Games. The numerical model data from the European Center for Medium-Range Weather Forecasts (ECMWF) and corresponding extreme wind observations at eight key stations in Yanqing Competition Zone of the Winter Olympic Games from January to March during 2018-2021 are used. The objective forecasting models of extreme wind speed are constructed based on three types of machine learning algorithms: decision tree (DT), random forest (RF) and gradient boosting decision tree (GBDT). The comparative evaluation results show that the best predictors of extreme wind speed mainly focus on the wind speed and direction at different levels, and additionally include the vertical velocity at individual stations. Removing the wind direction leads to the decrease of accuracy and increase of mean absolute error (MAE) in most of models. On the whole, the GBDT and RF models based on the decision tree ensemble learning are superior to the single decision tree model (DT). The GBDT model has the least MAE ranging from 1.56 m·s-1 to 3.57 m·s-1, and the maximum improvement rate is up to 8.7% compared with the DT model. Besides, the GBDT model is also skillful in the forecasts of super threshold extreme wind speed. All models have the increasing trend in the MAE and decreasing trend in the accuracy with the rising elevation of stations. As the forecasting lead time extends, the MAE of each model shows a periodic diurnal variation. Based on the stacking ensemble learning method, the RGL model is established using the two outstanding models, GBDT and RF, as the primary learner and the support vector machine as the secondary learner. The results indicate that compared with the single model, the RGL model has a certain ability to improve the prediction of extreme wind speed, especially at the high-altitude stations with relatively high winds. The MAE can be reduced by a maximum of 0.13 m·s-1, and the accuracy can be increased by a maximum of 0.022. The relevant research results have been well applied to the 2022 Beijing Winter Olympic and Paralympic Games.
Alpine skiing is extremely sensitive to wind, and especially extreme wind speed is often one of the key factors that determine the smooth progress of the Winter Olympic Games. The numerical model data from the European Center for Medium-Range Weather Forecasts (ECMWF) and corresponding extreme wind observations at eight key stations in Yanqing Competition Zone of the Winter Olympic Games from January to March during 2018-2021 are used. The objective forecasting models of extreme wind speed are constructed based on three types of machine learning algorithms: decision tree (DT), random forest (RF) and gradient boosting decision tree (GBDT). The comparative evaluation results show that the best predictors of extreme wind speed mainly focus on the wind speed and direction at different levels, and additionally include the vertical velocity at individual stations. Removing the wind direction leads to the decrease of accuracy and increase of mean absolute error (MAE) in most of models. On the whole, the GBDT and RF models based on the decision tree ensemble learning are superior to the single decision tree model (DT). The GBDT model has the least MAE ranging from 1.56 m·s-1 to 3.57 m·s-1, and the maximum improvement rate is up to 8.7% compared with the DT model. Besides, the GBDT model is also skillful in the forecasts of super threshold extreme wind speed. All models have the increasing trend in the MAE and decreasing trend in the accuracy with the rising elevation of stations. As the forecasting lead time extends, the MAE of each model shows a periodic diurnal variation. Based on the stacking ensemble learning method, the RGL model is established using the two outstanding models, GBDT and RF, as the primary learner and the support vector machine as the secondary learner. The results indicate that compared with the single model, the RGL model has a certain ability to improve the prediction of extreme wind speed, especially at the high-altitude stations with relatively high winds. The MAE can be reduced by a maximum of 0.13 m·s-1, and the accuracy can be increased by a maximum of 0.022. The relevant research results have been well applied to the 2022 Beijing Winter Olympic and Paralympic Games.
2023, 49(6):733-744.
DOI: 10.7519/j.issn.1000-0526.2023.041701
Abstract:
In this study, to meet the fine meteorological service requirements proposed by the Organizing Committee for the Beijing Winter Olympic Games, a real-time forecasting system with 100 m horizontal grid spacing RMAPS-LES which was coupled with mesoscale meteorological model and large eddy simulation was especially built for the Yanqing and Zhangjiakou competition zones. Based on the observation data of Winter Olympics zones and the 3 km×3 km horizontal grid spacing from “CMA-BJ” mesoscale forecast system, the RMAPS-LES results of the competion months (February to March) from 2020 to 2022 are compared and verified at different space-time scales. The results show that the high-resolution microscale RMAPS-LES has a higher prediction in forecasting wind and temperature than the CMA-BJ mesoscale model. The mean absolute error (MAE) of average hourly 2 m temperature of all stations in the three years for the Winter Olympic Games is 1.85℃, which is 28% less than the CMA-BJ model, the MAE of the hourly average 10 m wind speed is 2.11 m·s-1, which is 23.6% less and the instantaneous wind direction MAE is 44.43°, 30.33% lower. Relative to the CMA-BJ model, RMAPS-LES has the advantage of obtaining high-frequency data that can describe the atmospheric microscale turbulent motion in detail. The verification results indicate that the probability density distribution of wind speed fluctuation is basically close to the normal distribution, nearing the observations. It is also found that when dynamic downscaling is used, the inflow turbulence generation method needs to be used for different-scale simulation to accelerate the rapid generation of atmospheric turbulence in the large eddy simulation region. The RMAPS-LES uses the turbulence generation scheme based on random disturbance of grid potential temperature, which can substantially reduce the transitional zone and achieve fully developed turbulence. The technical route of RMAPS-LES can also be widely used in the wind power generators selection， forest fires， outdoor activities， and other scenes that have high requirements for fine local meteorological forecasts.
In this study, to meet the fine meteorological service requirements proposed by the Organizing Committee for the Beijing Winter Olympic Games, a real-time forecasting system with 100 m horizontal grid spacing RMAPS-LES which was coupled with mesoscale meteorological model and large eddy simulation was especially built for the Yanqing and Zhangjiakou competition zones. Based on the observation data of Winter Olympics zones and the 3 km×3 km horizontal grid spacing from “CMA-BJ” mesoscale forecast system, the RMAPS-LES results of the competion months (February to March) from 2020 to 2022 are compared and verified at different space-time scales. The results show that the high-resolution microscale RMAPS-LES has a higher prediction in forecasting wind and temperature than the CMA-BJ mesoscale model. The mean absolute error (MAE) of average hourly 2 m temperature of all stations in the three years for the Winter Olympic Games is 1.85℃, which is 28% less than the CMA-BJ model, the MAE of the hourly average 10 m wind speed is 2.11 m·s-1, which is 23.6% less and the instantaneous wind direction MAE is 44.43°, 30.33% lower. Relative to the CMA-BJ model, RMAPS-LES has the advantage of obtaining high-frequency data that can describe the atmospheric microscale turbulent motion in detail. The verification results indicate that the probability density distribution of wind speed fluctuation is basically close to the normal distribution, nearing the observations. It is also found that when dynamic downscaling is used, the inflow turbulence generation method needs to be used for different-scale simulation to accelerate the rapid generation of atmospheric turbulence in the large eddy simulation region. The RMAPS-LES uses the turbulence generation scheme based on random disturbance of grid potential temperature, which can substantially reduce the transitional zone and achieve fully developed turbulence. The technical route of RMAPS-LES can also be widely used in the wind power generators selection， forest fires， outdoor activities， and other scenes that have high requirements for fine local meteorological forecasts.
2023, 49(6):745-756.
DOI: 10.7519/j.issn.1000-0526.2023.050801
Abstract:
Taking the small- and medium-sized river basins in the upper reaches of Xiong’an New Area as a study area, selecting maximum precipitation for three consecutive days as flood hazard factor and using a combination of HBV hydrological model and FloodArea hydrodynamic model, we simulated the flood inundation range and depth and assessed the economic loss risk of flood disaster through building vulnerability curve of direct economic loss rate in combination with population and economic projections under SSPs. The results show that in the small- and medium-sized river basins in the upper reaches of Xiong’an New Area, the maximum precipitation for three consecutive days during 1961-2019 was 335 mm, with a return period of once in 200 years. Under the SSP2-4.5 scenario, this precipitation return period will decrease to once in 150 years from 2021 to 2050, which will cause more than 60% of the Xiong’an New Area to be inundated by floods, with an average inundated water depth of 1.1 m. The area of urban-rural industrial and mining residential land affected by floods in Xiong’an New Area will be 119 km2, and more than 50% of the population and GDP will be exposed to floods. The largest amount of population and GDP exposed to floods will be mostly located in the southeastern part of the starting area and most of Xiongxian County, which will be more than 10 〖KG-*5〗000 people per km2 and 500 million Yuan per km2 respectively. The economic loss of flood in Xiong’an New Area will be about 36.4 billion Yuan, accounting for about 8% of GDP. Moreover, 85% of the whole region will belong to the low-risk area of economic loss, the areas with high risk of economic loss will be concentrated in the southeast of the starting area, and also in the urban and rural residential areas in Xiongxian County and Zangang Town, which will take up 2% of the total area.
Taking the small- and medium-sized river basins in the upper reaches of Xiong’an New Area as a study area, selecting maximum precipitation for three consecutive days as flood hazard factor and using a combination of HBV hydrological model and FloodArea hydrodynamic model, we simulated the flood inundation range and depth and assessed the economic loss risk of flood disaster through building vulnerability curve of direct economic loss rate in combination with population and economic projections under SSPs. The results show that in the small- and medium-sized river basins in the upper reaches of Xiong’an New Area, the maximum precipitation for three consecutive days during 1961-2019 was 335 mm, with a return period of once in 200 years. Under the SSP2-4.5 scenario, this precipitation return period will decrease to once in 150 years from 2021 to 2050, which will cause more than 60% of the Xiong’an New Area to be inundated by floods, with an average inundated water depth of 1.1 m. The area of urban-rural industrial and mining residential land affected by floods in Xiong’an New Area will be 119 km2, and more than 50% of the population and GDP will be exposed to floods. The largest amount of population and GDP exposed to floods will be mostly located in the southeastern part of the starting area and most of Xiongxian County, which will be more than 10 〖KG-*5〗000 people per km2 and 500 million Yuan per km2 respectively. The economic loss of flood in Xiong’an New Area will be about 36.4 billion Yuan, accounting for about 8% of GDP. Moreover, 85% of the whole region will belong to the low-risk area of economic loss, the areas with high risk of economic loss will be concentrated in the southeast of the starting area, and also in the urban and rural residential areas in Xiongxian County and Zangang Town, which will take up 2% of the total area.
10 Application of Loss Rate Evaluation Model in Meteorological Disaster Loss Evaluation in Guangdong
2023, 49(6):757-764.
DOI: 10.7519/j.issn.1000-0526.2023.052202
Abstract:
Using the data of the 1995-2021 Guangdong Disaster Prevention and Reduction Yearbook and the 2021 Guangdong Statistical Yearbook, based on the loss rate assessment model for meteorological disaster losses, we quantitatively analyze and assess the annual losses and total losses of five major meteorological disasters caused by rainstorm, flood, typhoon, low temperature freezing, drought and severe convection (including lightning strike) in Guangdong in the past 27 years. The results show that the peak values of annual loss rate indexes of typhoon, rainstorm, low temperature freezing, severe convection and total loss all appeared in the middle and late 1990s, while the peak value of drought loss rate index was seen in 2002. The total losses of meteorological disasters in Guangdong were extremely heavy in 6 years, of which the loss rate index in 1994 reached 7.62, so 1994 is the year with the highest total loss of meteorological disasters during the research periods. In the past 27 years, the loss rate index of the total losses caused by meteorological disasters in Guangdong has shown a significant decreasing trend. The average index value during the period from 2000 to 2020 was 0.17, a decrease of 92.54% compared to the average value from 1994 to 1999, and a decrease of 60.83% in the index of deaths and missing persons.
Using the data of the 1995-2021 Guangdong Disaster Prevention and Reduction Yearbook and the 2021 Guangdong Statistical Yearbook, based on the loss rate assessment model for meteorological disaster losses, we quantitatively analyze and assess the annual losses and total losses of five major meteorological disasters caused by rainstorm, flood, typhoon, low temperature freezing, drought and severe convection (including lightning strike) in Guangdong in the past 27 years. The results show that the peak values of annual loss rate indexes of typhoon, rainstorm, low temperature freezing, severe convection and total loss all appeared in the middle and late 1990s, while the peak value of drought loss rate index was seen in 2002. The total losses of meteorological disasters in Guangdong were extremely heavy in 6 years, of which the loss rate index in 1994 reached 7.62, so 1994 is the year with the highest total loss of meteorological disasters during the research periods. In the past 27 years, the loss rate index of the total losses caused by meteorological disasters in Guangdong has shown a significant decreasing trend. The average index value during the period from 2000 to 2020 was 0.17, a decrease of 92.54% compared to the average value from 1994 to 1999, and a decrease of 60.83% in the index of deaths and missing persons.
2023, 49(6):765-772.
DOI: 10.7519/j.issn.1000-0526.2023.052201
Abstract:
The main characteristics of the general atmospheric circulation in March 2023 are as follows. There was one polar vortex center in the Northern Hemisphere, which was stronger than usual. The 500 hPa geopotential height presented the distribution of an anomalous four-wave pattern in the mid-high latitudes of the Northern Hemisphere and the airflow was relatively straight and flat in Asia. The strength of Western Pacific subtropical high was a little weaker than that in normal years, and the south branch trough was weaker slightly with position more westward than normal. During this month, most regions of China experienced warmer temperatures with the averaged value reaching 6.8℃, which is 2.0℃ higher than the normal, and was recorded the third highest mean temperature in the same period since 1961. The monthly mean precipitation amount was 26.5 mm, 9.9% less than in normal periods (29.4 mm). A large-scale rainfall process occurred in the month, accompanied by significant severe convective weather such as heavy rain and thunderstorm, and many provinces were even hit by hail. Meanwhile, the cold airs affecting China were generally weak, and only two main cold air processes posed influence on the whole country. The northern part of China was caught by four sand-dust weather processes, one of which reached the level of a strong sandstorm. In addition, drought conditions appeared in the East China, the southern part of Central China, the South China and the southern part of Southwest China.
The main characteristics of the general atmospheric circulation in March 2023 are as follows. There was one polar vortex center in the Northern Hemisphere, which was stronger than usual. The 500 hPa geopotential height presented the distribution of an anomalous four-wave pattern in the mid-high latitudes of the Northern Hemisphere and the airflow was relatively straight and flat in Asia. The strength of Western Pacific subtropical high was a little weaker than that in normal years, and the south branch trough was weaker slightly with position more westward than normal. During this month, most regions of China experienced warmer temperatures with the averaged value reaching 6.8℃, which is 2.0℃ higher than the normal, and was recorded the third highest mean temperature in the same period since 1961. The monthly mean precipitation amount was 26.5 mm, 9.9% less than in normal periods (29.4 mm). A large-scale rainfall process occurred in the month, accompanied by significant severe convective weather such as heavy rain and thunderstorm, and many provinces were even hit by hail. Meanwhile, the cold airs affecting China were generally weak, and only two main cold air processes posed influence on the whole country. The northern part of China was caught by four sand-dust weather processes, one of which reached the level of a strong sandstorm. In addition, drought conditions appeared in the East China, the southern part of Central China, the South China and the southern part of Southwest China.
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ISSN:1000-0526 CN:11-2282/P