ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 47,Issue 7,2021 Table of Contents
2021, 47(7):773-780.
DOI: 10.7519/j.issn.1000-0526.2021.07.001
Abstract:
The year 2020 is the centenary of Mr. Gu Zhenchao’s birth. Mr. Gu was one of the main foun-ders and creators of modern Chinese synoptic meteorology, having made outstanding contributions to Chinese synoptic research and modern weather forecasting operation. He had a profound theoretical foundation of meteorological research, good at grasping the essence from complex weather phenomena, and had insight into the world frontiers and the development direction of weather forecasting operations at that time. He adapted the western synoptic theory and research results to Chinese actual needs, managing to work out the creative solutions to the theoretical and practical problems of synoptic science in China and putting forward many original ideas and facts. He also further applied scientific research results to the operational forecasting practice, which effectively promoted the development and modernization of China’s weather forecasting services. This article reviews and sorts out Mr. Gu Zhenchao’s outstanding contributions to Chinese synoptic meteorology from seven aspects in order to commemorate and remember him.
The year 2020 is the centenary of Mr. Gu Zhenchao’s birth. Mr. Gu was one of the main foun-ders and creators of modern Chinese synoptic meteorology, having made outstanding contributions to Chinese synoptic research and modern weather forecasting operation. He had a profound theoretical foundation of meteorological research, good at grasping the essence from complex weather phenomena, and had insight into the world frontiers and the development direction of weather forecasting operations at that time. He adapted the western synoptic theory and research results to Chinese actual needs, managing to work out the creative solutions to the theoretical and practical problems of synoptic science in China and putting forward many original ideas and facts. He also further applied scientific research results to the operational forecasting practice, which effectively promoted the development and modernization of China’s weather forecasting services. This article reviews and sorts out Mr. Gu Zhenchao’s outstanding contributions to Chinese synoptic meteorology from seven aspects in order to commemorate and remember him.
2021, 47(7):781-790.
DOI: 10.7519/j.issn.1000-0526.2021.07.002
Abstract:
Prof. Gu Zhenchao has been away from us for 45 years, but our yearning for him has not decreased at all. Now a short article is written to express the deep nostalgia for him. Prof. Gu Zhenchao was born in Shanghai in 1920 and died in 1976. He graduated from the Graduate School of Southwest United University and then studied for a doctorate in meteorology at Stockholm University in 1947, under the international famous meteorologist C.G. Rossby. Due to the urgent need of the motherland’s meteorological development he returned China in May 1950. He was appointed as the director of “Joint Weather Analysis and Forecast Center”, and then the first director of the Institute of Atmospheric Physics, Chinese Academy of Sciences. He worked hard for the country and the people, and dedicated his life. As an excellent scientist, he has made great contributions to the development of meteorology and atmospheric science, including synoptic meteorology, dynamic meteorology, numerical weather forecast, Qinghai-Tibet Plateau meteorology, cloud and precipitation physics, weather modification and atmospheric physics and so on. He was one of the main pioneers and founders of Chinese meteorology. His academic thought is a valuable wealth, which is of great significance today and in the future.
Prof. Gu Zhenchao has been away from us for 45 years, but our yearning for him has not decreased at all. Now a short article is written to express the deep nostalgia for him. Prof. Gu Zhenchao was born in Shanghai in 1920 and died in 1976. He graduated from the Graduate School of Southwest United University and then studied for a doctorate in meteorology at Stockholm University in 1947, under the international famous meteorologist C.G. Rossby. Due to the urgent need of the motherland’s meteorological development he returned China in May 1950. He was appointed as the director of “Joint Weather Analysis and Forecast Center”, and then the first director of the Institute of Atmospheric Physics, Chinese Academy of Sciences. He worked hard for the country and the people, and dedicated his life. As an excellent scientist, he has made great contributions to the development of meteorology and atmospheric science, including synoptic meteorology, dynamic meteorology, numerical weather forecast, Qinghai-Tibet Plateau meteorology, cloud and precipitation physics, weather modification and atmospheric physics and so on. He was one of the main pioneers and founders of Chinese meteorology. His academic thought is a valuable wealth, which is of great significance today and in the future.
2021, 47(7):791-804.
DOI: 10.7519/j.issn.1000-0526.2021.07.003
Abstract:
Using the WRF mesoscale numerical model, the dynamic and thermodynamic mechanisms of cold dry air intensity change on distribution and intensity of rainstorm are revealed by conducting numerical experiments on a continuous rainstorm caused by tropical depression inverted trough in Jiangsu Province during 11-13 July 2011. The conclusions drawn from this study are as follows. The enhancement of cold air in the upper troposphere leads to precipitation reduction, and the dry cold air with a certain humidity is favorable for precipitation. Enhancement of dry cold air in the middle troposphere is good for the increase of heavy rain, but the low relative humidity is not conducive to the continuation of heavy precipitation. The stronger the dry cold air in the lower troposphere, the more intensification of heavy rain. Besides, the intensity of rainstorm is not only related to the intensity of coupling dynamic configuration of convergence in the lower troposphere and divergence in the upper troposphere, but also related to its maintenance time. The enhancement of dry cold air in the middle troposphere and lower troposphere both benefit the enhancement and maintenance of configuration, corresponding to the heavy rain. Moreover, the enhancement of dry cold air in the middle troposphere contributes to the strengthening of the lower front area and precipitation. As the dry cold air in the low troposphere strengthens (weakens), the front area strengthens (weakens), corresponding to the precipitation increase (reduction) and the southeast (northwest) movement of the rainstorm center. In addition, the coupling effects of positive MPV1 at 500 hPa and negative MPV2 at 800 hPa above the rainstorm center positively enhance the rainfall. When the dry cold air in upper and middle troposphere strengthens, the extreme values of MPV1 and MPV2 both appear before the maximum precipitation. When dry cold air in the lower troposphere strengthens, the maximum MPV1 appears before the maximum precipitation, and the maximum MPV2 appears at the same time as the maximum precipitation, which respectively has leading and increasing effects on precipitation enhancement. The greater the maximum values of MPV1 and MPV2, the heavier the precipitation.
Using the WRF mesoscale numerical model, the dynamic and thermodynamic mechanisms of cold dry air intensity change on distribution and intensity of rainstorm are revealed by conducting numerical experiments on a continuous rainstorm caused by tropical depression inverted trough in Jiangsu Province during 11-13 July 2011. The conclusions drawn from this study are as follows. The enhancement of cold air in the upper troposphere leads to precipitation reduction, and the dry cold air with a certain humidity is favorable for precipitation. Enhancement of dry cold air in the middle troposphere is good for the increase of heavy rain, but the low relative humidity is not conducive to the continuation of heavy precipitation. The stronger the dry cold air in the lower troposphere, the more intensification of heavy rain. Besides, the intensity of rainstorm is not only related to the intensity of coupling dynamic configuration of convergence in the lower troposphere and divergence in the upper troposphere, but also related to its maintenance time. The enhancement of dry cold air in the middle troposphere and lower troposphere both benefit the enhancement and maintenance of configuration, corresponding to the heavy rain. Moreover, the enhancement of dry cold air in the middle troposphere contributes to the strengthening of the lower front area and precipitation. As the dry cold air in the low troposphere strengthens (weakens), the front area strengthens (weakens), corresponding to the precipitation increase (reduction) and the southeast (northwest) movement of the rainstorm center. In addition, the coupling effects of positive MPV1 at 500 hPa and negative MPV2 at 800 hPa above the rainstorm center positively enhance the rainfall. When the dry cold air in upper and middle troposphere strengthens, the extreme values of MPV1 and MPV2 both appear before the maximum precipitation. When dry cold air in the lower troposphere strengthens, the maximum MPV1 appears before the maximum precipitation, and the maximum MPV2 appears at the same time as the maximum precipitation, which respectively has leading and increasing effects on precipitation enhancement. The greater the maximum values of MPV1 and MPV2, the heavier the precipitation.
2021, 47(7):805-816.
DOI: 10.7519/j.issn.1000-0526.2021.07.004
Abstract:
Previous literatures suggest that El Ni〖AKn~D〗o is a dominant factor causing spring drought in Yunnan Province. Under the background of super-strong El Ni〖AKn~D〗o event during 2015, the spring (March-May) precipitation in most parts of western Yunnan Province was below normal, and the rainy season started late or even very late. However, the precipitation in eastern part was more than normal generally, and the rainy seasons in some regions started early or even very early, presenting a sharp contrast between the east and west. By using daily rain gauge precipitation of Yunnan Province, the CPC (Climate Prediction Center, USA) global unified gauge-based analysis of daily precipitation and NCEP/NCAR (National Centers for Environmental Prediction/ National Center for Atmospheric Research) reanalysis data, the influence of 10-30 d atmospheric oscillation on the spring abnormal precipitation over eastern Yunnan was studied by statistical and dynamical diagnosis methods. The analysis shows that the 10-30 d oscillation was active in the areas to the east of 100°E from mid-March to late-April, which is a major reason for the abnormal abundant precipitation over eastern Yunnan. 〖JP2〗Three distinct precipitation processes in eastern Yunnan happened associated closely with the southward approaching of the low-frequency cold phase embedded in the Eurasian pattern (EU) wave train from the mid- and high-latitudes of East Asia. Namely, when the upward branch of the secondary circulation around the subtropical westerly jet entrance interacted with the reflux vapor on the southwestern fringe of the cold high, the rainfall process was formed.
Previous literatures suggest that El Ni〖AKn~D〗o is a dominant factor causing spring drought in Yunnan Province. Under the background of super-strong El Ni〖AKn~D〗o event during 2015, the spring (March-May) precipitation in most parts of western Yunnan Province was below normal, and the rainy season started late or even very late. However, the precipitation in eastern part was more than normal generally, and the rainy seasons in some regions started early or even very early, presenting a sharp contrast between the east and west. By using daily rain gauge precipitation of Yunnan Province, the CPC (Climate Prediction Center, USA) global unified gauge-based analysis of daily precipitation and NCEP/NCAR (National Centers for Environmental Prediction/ National Center for Atmospheric Research) reanalysis data, the influence of 10-30 d atmospheric oscillation on the spring abnormal precipitation over eastern Yunnan was studied by statistical and dynamical diagnosis methods. The analysis shows that the 10-30 d oscillation was active in the areas to the east of 100°E from mid-March to late-April, which is a major reason for the abnormal abundant precipitation over eastern Yunnan. 〖JP2〗Three distinct precipitation processes in eastern Yunnan happened associated closely with the southward approaching of the low-frequency cold phase embedded in the Eurasian pattern (EU) wave train from the mid- and high-latitudes of East Asia. Namely, when the upward branch of the secondary circulation around the subtropical westerly jet entrance interacted with the reflux vapor on the southwestern fringe of the cold high, the rainfall process was formed.
2021, 47(7):817-829.
DOI: 10.7519/j.issn.1000-0526.2021.07.005
Abstract:
At 14:00 BT 18 June 2017, a flash flood happened in the Shiyanggou Watershed of Mentougou District, Beijing, causing casualties. The station precipitation, combined precipitation of station and satellite, radar precipitation and satellite precipitation are used to drive the WRF-Hydro hydrological model to evaluate the performance of these different precipitation data in the flash flood simulation. The results show that the spatial distribution and temporal variation of these data are similar. Except radar precipitation, other precipitation data underestimate the precipitation. In these flash flood simulation experiments, the flash flood simulated by radar precipitation is most similar to the actual flash flood in terms of occurrence time and peak flow. The flash floods simulated based on other precipitation data are close to the actual streamflow in terms of occurrence time but the peak flow is underestimated. At present, conventional precipitation products by routine observation stations can not meet the requirements of research and early warning of small-scale abrupt flash floods. So, it is urgent to integrate radar and satellite precipitation products with observation station precipitation to get real-time high-resolution precipitation products.
At 14:00 BT 18 June 2017, a flash flood happened in the Shiyanggou Watershed of Mentougou District, Beijing, causing casualties. The station precipitation, combined precipitation of station and satellite, radar precipitation and satellite precipitation are used to drive the WRF-Hydro hydrological model to evaluate the performance of these different precipitation data in the flash flood simulation. The results show that the spatial distribution and temporal variation of these data are similar. Except radar precipitation, other precipitation data underestimate the precipitation. In these flash flood simulation experiments, the flash flood simulated by radar precipitation is most similar to the actual flash flood in terms of occurrence time and peak flow. The flash floods simulated based on other precipitation data are close to the actual streamflow in terms of occurrence time but the peak flow is underestimated. At present, conventional precipitation products by routine observation stations can not meet the requirements of research and early warning of small-scale abrupt flash floods. So, it is urgent to integrate radar and satellite precipitation products with observation station precipitation to get real-time high-resolution precipitation products.
2021, 47(7):830-842.
DOI: 10.7519/j.issn.1000-0526.2021.07.006
Abstract:
Due to the influence of surface and other factors, the raindrop size distribution characteristics of rainfall in mountainous and plain areas have significant differences in some cases. Understanding their differences in mountain and plain is useful to deeply learn the microphysical characteristics of rainfall and improve the accuracy of radar quantitative precipitation estimation (QPE) with different underlying surfaces.Based on the raindrop spectrum data from laser optical disdrometer and the rainfall data from automatic weather stations over Beijing during summers of 2017 and 2018, the representative mountain-area Yanqing Station and plain-area Daxing Station were selected. The raindrop size distribution characteristics of convective and stratiform rain types at the two stations were studied by the rain type classification method.〖JP〗 The results show that the contribution of rainfall intensity (R) greater than 5 mm·h-1 with lower frequency to the total rainfall is dramatically larger than that (mountain/plain station is 33%/29%) less than or eaqual to 5 mm·h-1 with higher frequency （both stations are 86%） in the Beijing summer. Further research indicates that convective rain spectra has larger mass-weighted mean diameter Dm, logarithmic generalized intercept parameter lgNw and distribution spectrum width than the stratiform rain spectra. Comparing the two stations, we find the Dm (lgNw) of different rain types at Yanqing Station (mountain station) is larger than (less than) that at Daxing Station (plain station), indicating that the mountain area raindrop size is larger while number concentration is lower. Compared to foreign classical convective spectra, the convective rain spectrum at mountain (plain) area is more inclined to the continental (maritime) convection. Relationships among Dm-R, lgNw-R, μ (shape)-Λ (slope) and Z-R are in accordance with the classical findings, but the fitted parameters are different from those of other areas, which means the variations by different researches. The Z-R fitted relationships between Yanqing and Daxing are Z=764R1.20 and Z=386R1.32, of which the Z-R relationship at Daxing Station is consistent with Z=300R1.40, which represents the summer convective precipitation while the Z-R relationship at Yanqing is distinct from Z=300R1.40, revealing the rainfall difference between mountain and plain.
Due to the influence of surface and other factors, the raindrop size distribution characteristics of rainfall in mountainous and plain areas have significant differences in some cases. Understanding their differences in mountain and plain is useful to deeply learn the microphysical characteristics of rainfall and improve the accuracy of radar quantitative precipitation estimation (QPE) with different underlying surfaces.Based on the raindrop spectrum data from laser optical disdrometer and the rainfall data from automatic weather stations over Beijing during summers of 2017 and 2018, the representative mountain-area Yanqing Station and plain-area Daxing Station were selected. The raindrop size distribution characteristics of convective and stratiform rain types at the two stations were studied by the rain type classification method.〖JP〗 The results show that the contribution of rainfall intensity (R) greater than 5 mm·h-1 with lower frequency to the total rainfall is dramatically larger than that (mountain/plain station is 33%/29%) less than or eaqual to 5 mm·h-1 with higher frequency （both stations are 86%） in the Beijing summer. Further research indicates that convective rain spectra has larger mass-weighted mean diameter Dm, logarithmic generalized intercept parameter lgNw and distribution spectrum width than the stratiform rain spectra. Comparing the two stations, we find the Dm (lgNw) of different rain types at Yanqing Station (mountain station) is larger than (less than) that at Daxing Station (plain station), indicating that the mountain area raindrop size is larger while number concentration is lower. Compared to foreign classical convective spectra, the convective rain spectrum at mountain (plain) area is more inclined to the continental (maritime) convection. Relationships among Dm-R, lgNw-R, μ (shape)-Λ (slope) and Z-R are in accordance with the classical findings, but the fitted parameters are different from those of other areas, which means the variations by different researches. The Z-R fitted relationships between Yanqing and Daxing are Z=764R1.20 and Z=386R1.32, of which the Z-R relationship at Daxing Station is consistent with Z=300R1.40, which represents the summer convective precipitation while the Z-R relationship at Yanqing is distinct from Z=300R1.40, revealing the rainfall difference between mountain and plain.
2021, 47(7):843-853.
DOI: 10.7519/j.issn.1000-0526.2021.07.007
Abstract:
To improve the quality of quantitative precipitation estimation (QPE), the characteristics of local precipitation are analyzed using the measured raindrop size distribution (DSD) data of Nanjing Area in two consecutive summers. The precipitation estimators (PEs) including the relationship of microwave rainfall attenuation and rain rate and the relationship of weather radar intensity and rain rate are calculated based on the DSD data. The relationships obtained are different from ITU-R rain attenuation relationships and commonly used Z-R relationships. The radar Z-R relationship for convective precipitation is Z=161.63R1.55 and Z=227.23R1.53 for stratiform precipitation. Using these PEs, the rain rate distributions in two rainfall cases of different types are retrieved with a microwave link and a weather radar. The results are as follows. The rainfall is overestimated in stratiform precipitation and underestimated in convective precipitation when using ITU-R rain attenuation relationship. The rain rates are obviously underestimated when using commonly used Z-R relationship. The rain rates retrieved with the rain attenuation relationship and the Z-R relationships obtained from the DSD data are more consistent with the rain rates measured by the rain gauges. The mean absolute errors are reduced, and the correlations are significantly improved. The results show that the accuracy of QPE can be improved effectively by using the local PEs calculated by the DSD data.
To improve the quality of quantitative precipitation estimation (QPE), the characteristics of local precipitation are analyzed using the measured raindrop size distribution (DSD) data of Nanjing Area in two consecutive summers. The precipitation estimators (PEs) including the relationship of microwave rainfall attenuation and rain rate and the relationship of weather radar intensity and rain rate are calculated based on the DSD data. The relationships obtained are different from ITU-R rain attenuation relationships and commonly used Z-R relationships. The radar Z-R relationship for convective precipitation is Z=161.63R1.55 and Z=227.23R1.53 for stratiform precipitation. Using these PEs, the rain rate distributions in two rainfall cases of different types are retrieved with a microwave link and a weather radar. The results are as follows. The rainfall is overestimated in stratiform precipitation and underestimated in convective precipitation when using ITU-R rain attenuation relationship. The rain rates are obviously underestimated when using commonly used Z-R relationship. The rain rates retrieved with the rain attenuation relationship and the Z-R relationships obtained from the DSD data are more consistent with the rain rates measured by the rain gauges. The mean absolute errors are reduced, and the correlations are significantly improved. The results show that the accuracy of QPE can be improved effectively by using the local PEs calculated by the DSD data.
2021, 47(7):854-861.
DOI: 10.7519/j.issn.1000-0526.2021.07.008
Abstract:
In view of the difficulty in hail monitoring and hail disaster estimation, combined with the characteristics of acoustic signal in time and frequency domain, this paper proposes a generalized regression neural network (GRNN) hail detection method based on entropy method by combining the entropy method with the GRNN. The time domain feature, frequency domain feature and wavelet packet energy spectrum feature are extracted from the collected hail and rain sound signals. The entropy method is used to determine the weight of each feature. The feature items with smaller weight are eliminated and fused to form a 〖JP2〗new feature subset. The feature subset is input into GRNN for prediction and recognition. The experimental results show that the method can effectively identify hail, and the recognition rate after feature screening is as high as 97.827 〖KG-*5〗6%, which is nearly 10% higher than that of the feature set without feature screening.
In view of the difficulty in hail monitoring and hail disaster estimation, combined with the characteristics of acoustic signal in time and frequency domain, this paper proposes a generalized regression neural network (GRNN) hail detection method based on entropy method by combining the entropy method with the GRNN. The time domain feature, frequency domain feature and wavelet packet energy spectrum feature are extracted from the collected hail and rain sound signals. The entropy method is used to determine the weight of each feature. The feature items with smaller weight are eliminated and fused to form a 〖JP2〗new feature subset. The feature subset is input into GRNN for prediction and recognition. The experimental results show that the method can effectively identify hail, and the recognition rate after feature screening is as high as 97.827 〖KG-*5〗6%, which is nearly 10% higher than that of the feature set without feature screening.
2021, 47(7):862-871.
DOI: 10.7519/j.issn.1000-0526.2021.07.009
Abstract:
In April, the pollen and flying fruit hair from Platanus acerifolia endanger human health and bring pressure to city cleaning. The prediction of the firstflowering date （FFD) is conducive to the protection of allergy groups, and can provide theoretical basis for the timely spraying of plant growth inhibitor by the garden department. Taking the FFD of Platanus acerifolia in Xinghua, Jiangsu Province as the research object, this paper analyzes the annual variation trend from 1990 to 2020 and selects the leading meteorological factors which are significantly related to the FFD by using the observation data and synchronous meteorological date. Moreover, the effect of the leading meteorological factors is quantitatively specified by path analysis and the regression prediction model is constructed. In addition， the effective accumulated temperature threshold is statistically analyzed， and the prediction is made based on the SW accumulative temperature model. Finally， the prediction effects of the two models are evaluated. The results show that under the background of climate warming, the FFD shows a tendency of advancing year by year, about 2 days every 10 years. Light, wind speed and precipitation have little impact on the FFD, but in late February, plenty of rain and moist air are conducive to early flowering. Temperature is the main impact factor. The impact of daily maximum temperature on the FFD is higher than that of daily minimum temperature, and the impact of average surface temperature is higher than that of average temperature. However, the situation is opposite when temperature begins to warm up from March. The average winter surface temperature, the average winter air temperature and the number of days in midMarch with daily minimum air temperature <10℃ all have the significant impact on the FFD directly or indirectly. The fitting result of the regression prediction model which is established based on these factors is 89.3%. Therefore, this prediction model has high reliability and operational application value.
In April, the pollen and flying fruit hair from Platanus acerifolia endanger human health and bring pressure to city cleaning. The prediction of the firstflowering date （FFD) is conducive to the protection of allergy groups, and can provide theoretical basis for the timely spraying of plant growth inhibitor by the garden department. Taking the FFD of Platanus acerifolia in Xinghua, Jiangsu Province as the research object, this paper analyzes the annual variation trend from 1990 to 2020 and selects the leading meteorological factors which are significantly related to the FFD by using the observation data and synchronous meteorological date. Moreover, the effect of the leading meteorological factors is quantitatively specified by path analysis and the regression prediction model is constructed. In addition， the effective accumulated temperature threshold is statistically analyzed， and the prediction is made based on the SW accumulative temperature model. Finally， the prediction effects of the two models are evaluated. The results show that under the background of climate warming, the FFD shows a tendency of advancing year by year, about 2 days every 10 years. Light, wind speed and precipitation have little impact on the FFD, but in late February, plenty of rain and moist air are conducive to early flowering. Temperature is the main impact factor. The impact of daily maximum temperature on the FFD is higher than that of daily minimum temperature, and the impact of average surface temperature is higher than that of average temperature. However, the situation is opposite when temperature begins to warm up from March. The average winter surface temperature, the average winter air temperature and the number of days in midMarch with daily minimum air temperature <10℃ all have the significant impact on the FFD directly or indirectly. The fitting result of the regression prediction model which is established based on these factors is 89.3%. Therefore, this prediction model has high reliability and operational application value.
2021, 47(7):872-879.
DOI: 10.7519/j.issn.1000-0526.2021.07.010
Abstract:
Meteorological condition is one of important factors in influencing electricity consumption, and is widely used in electricity load forecasting model. This study uses daily electricity load and meteorological data in Tianjin during 2014-2018 and analyzes the relationship between electricity and meteorological elements. The results show that the relationship between daily electricity load and temperature and relative humidity is nonlinear correlation with “U” shape. With the increasing of relative humidity, the temperature threshold between the comfort zone and the cooling zone is obviously offset to the low temperature side. Thus, the relative humidity is joined into the electricity load relational model. Based on the slope of the non-linear fitting curve between electricity load and temperature and relative humidity, a new method which considered the temperature and humidity effect of electricity consumption segmentation is proposed. It is found that the new method can effectively promote the fitting level of electricity load. In liner model, compared with the “V” segmented method, the root mean square error (RMSE) and mean absolute percentage error (MAPE) values decrease by 1.562 GW·h and 0.546%, respectively. For transition area between comfort zone and cooling zone (21.1℃ to 26.2℃), the RMSE and MAPE values decrease by 0.759 GW·h and 0.215% compared with the traditional “U” segmented method, while the RMSE and MAPE values decrease by 0.647 GW·h and 0.209% in the nonlinear model. This shows the stable prediction effect of different models. Thus, this “U” segmented method based on temperature and humidity effect can effectively improve the accuracy of daily electricity load forecasting.
Meteorological condition is one of important factors in influencing electricity consumption, and is widely used in electricity load forecasting model. This study uses daily electricity load and meteorological data in Tianjin during 2014-2018 and analyzes the relationship between electricity and meteorological elements. The results show that the relationship between daily electricity load and temperature and relative humidity is nonlinear correlation with “U” shape. With the increasing of relative humidity, the temperature threshold between the comfort zone and the cooling zone is obviously offset to the low temperature side. Thus, the relative humidity is joined into the electricity load relational model. Based on the slope of the non-linear fitting curve between electricity load and temperature and relative humidity, a new method which considered the temperature and humidity effect of electricity consumption segmentation is proposed. It is found that the new method can effectively promote the fitting level of electricity load. In liner model, compared with the “V” segmented method, the root mean square error (RMSE) and mean absolute percentage error (MAPE) values decrease by 1.562 GW·h and 0.546%, respectively. For transition area between comfort zone and cooling zone (21.1℃ to 26.2℃), the RMSE and MAPE values decrease by 0.759 GW·h and 0.215% compared with the traditional “U” segmented method, while the RMSE and MAPE values decrease by 0.647 GW·h and 0.209% in the nonlinear model. This shows the stable prediction effect of different models. Thus, this “U” segmented method based on temperature and humidity effect can effectively improve the accuracy of daily electricity load forecasting.
2021, 47(7):880-892.
DOI: 10.7519/j.issn.1000-0526.2021.07.011
Abstract:
During the winter of 2020/2021, the climate over China was characterized by “cold and dry” in the first half of winter and “warm and wet” in the latter half of winter. In the cold and warm two periods, the amplitude of surface air temperature (SAT) fluctuated extremely, and the observed daily SATs at many stations in China broke the lowest and highest records, respectively. From 1 December 2020 to 10 January 2021, it was cold and dry over most of China, but turned sharply to warm and wet condition during the period from 13 January to 28 February 2021. The overturning changes of the large-scale circulation systems, including the Ural blocking, Siberian high, East Asian winter monsoon (EAWM), the position of the polar cold air and the western Pacific subtropical high, provided the direct reason for the cold-warm transition in China during this winter. Further analysis shows that the La Ni〖AKn~D〗a event, coupled with the reduced Arctic ice and the warmer North Atlantic currents in the mid-latitudes, met the conditions for the “warm Arctic, cold Eurasian” effect in the earlier winter. They intensified the meridional circulation with stronger Ural blocking, Siberian high and EAWM, and further led to the cold and dry climate in China. In the latter half of winter, the Arctic experienced a sudden stratospheric warming event, favoring the long-lasting negative Arctic Oscillation. The main body of the polar vortex shifted to the Western Hemisphere, while at the same time, the Ural blocking collapsed and the EAWM weakened. As a result, the temperature in most parts of China suddenly increased to be above normal.
During the winter of 2020/2021, the climate over China was characterized by “cold and dry” in the first half of winter and “warm and wet” in the latter half of winter. In the cold and warm two periods, the amplitude of surface air temperature (SAT) fluctuated extremely, and the observed daily SATs at many stations in China broke the lowest and highest records, respectively. From 1 December 2020 to 10 January 2021, it was cold and dry over most of China, but turned sharply to warm and wet condition during the period from 13 January to 28 February 2021. The overturning changes of the large-scale circulation systems, including the Ural blocking, Siberian high, East Asian winter monsoon (EAWM), the position of the polar cold air and the western Pacific subtropical high, provided the direct reason for the cold-warm transition in China during this winter. Further analysis shows that the La Ni〖AKn~D〗a event, coupled with the reduced Arctic ice and the warmer North Atlantic currents in the mid-latitudes, met the conditions for the “warm Arctic, cold Eurasian” effect in the earlier winter. They intensified the meridional circulation with stronger Ural blocking, Siberian high and EAWM, and further led to the cold and dry climate in China. In the latter half of winter, the Arctic experienced a sudden stratospheric warming event, favoring the long-lasting negative Arctic Oscillation. The main body of the polar vortex shifted to the Western Hemisphere, while at the same time, the Ural blocking collapsed and the EAWM weakened. As a result, the temperature in most parts of China suddenly increased to be above normal.
2021, 47(7):893-900.
DOI: 10.7519/j.issn.1000-0526.2021.07.012
Abstract:
The main characteristics of the general atmospheric circulation in April 2021 are as follows. The 500 hPa geopotential height presented a threewave pattern in the high latitude of Northern Hemisphere. There was one polar vortex center in the Northern Hemisphere, stronger than usual. The strength of Western Pacific subtropical high was weaker than that in normal years, but the south branch trough was stronger than usual. The monthly mean temperature was 11.1℃, 0.1℃ higher than normal. The monthly mean precipitation over China was 42.5 mm, which is 5.8% less than normal. However, the mean precipitation in Qinghai Province this month was recorded the most for the same period of history. Four nationwide strong cold air processes happened this month. The drought conditions in Southwest China and eastern part of South China persisted or worsened. Two sanddust events occurred across the northern part of China. Several provinces were attacked by severe thunder storms and hail, and some areas were hit harder.
The main characteristics of the general atmospheric circulation in April 2021 are as follows. The 500 hPa geopotential height presented a threewave pattern in the high latitude of Northern Hemisphere. There was one polar vortex center in the Northern Hemisphere, stronger than usual. The strength of Western Pacific subtropical high was weaker than that in normal years, but the south branch trough was stronger than usual. The monthly mean temperature was 11.1℃, 0.1℃ higher than normal. The monthly mean precipitation over China was 42.5 mm, which is 5.8% less than normal. However, the mean precipitation in Qinghai Province this month was recorded the most for the same period of history. Four nationwide strong cold air processes happened this month. The drought conditions in Southwest China and eastern part of South China persisted or worsened. Two sanddust events occurred across the northern part of China. Several provinces were attacked by severe thunder storms and hail, and some areas were hit harder.
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