ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 48,Issue 1,2022 Table of Contents
2022, 48(1):1-13.
DOI: 10.7519/j.issn.1000-0526.2021.010401
Abstract:
By virtue of the daily temperature observations of 2 〖KG-*5〗400 stations in China from 1960 to 2019, the climatological characteristics of the cold event in China are systematically analyzed. The results show that the cold wave and cold air process in China mainly occur in autumn, winter and spring, and the frequency and intensity have obvious monthly and seasonal differences. Regional cold wave has the highest frequency in autumn, and national cold wave and all types 〖JP2〗of cold air have the highest frequency in winter. The average〖JP〗 intensity of regional cold event is the largest in February, and the average intensity of national cold event is the largest in November. Based on the analysis of winter temperature in China, the past 60 years can be divided into two stages, that is, the cold period from 1960 to 1986 and the warm period from 1987 to 2019. In the winter of cold period, the frequency of the national cold wave shows a significant decrease trend ［-0.57 times·（10 a）-1］, and the frequency of regional cold air and alltype (the sum of national type and regional type) cold air processes in winter shows a significant upward trend of 1.37 times·（10 a）-1 and 1.28 times·（10 a）-1, respectively. In the warm period, there is a significantly decreasing trend of national cold wave frequency ［-0.17 times·（10 a)-1］ and a significantly increasing trend of regional cold air frequency ［0.53 times·（10 a）-1］ in January.
By virtue of the daily temperature observations of 2 〖KG-*5〗400 stations in China from 1960 to 2019, the climatological characteristics of the cold event in China are systematically analyzed. The results show that the cold wave and cold air process in China mainly occur in autumn, winter and spring, and the frequency and intensity have obvious monthly and seasonal differences. Regional cold wave has the highest frequency in autumn, and national cold wave and all types 〖JP2〗of cold air have the highest frequency in winter. The average〖JP〗 intensity of regional cold event is the largest in February, and the average intensity of national cold event is the largest in November. Based on the analysis of winter temperature in China, the past 60 years can be divided into two stages, that is, the cold period from 1960 to 1986 and the warm period from 1987 to 2019. In the winter of cold period, the frequency of the national cold wave shows a significant decrease trend ［-0.57 times·（10 a）-1］, and the frequency of regional cold air and alltype (the sum of national type and regional type) cold air processes in winter shows a significant upward trend of 1.37 times·（10 a）-1 and 1.28 times·（10 a）-1, respectively. In the warm period, there is a significantly decreasing trend of national cold wave frequency ［-0.17 times·（10 a)-1］ and a significantly increasing trend of regional cold air frequency ［0.53 times·（10 a）-1］ in January.
2022, 48(1):14-27.
DOI: 10.7519/j.issn.1000-0526.2021.093001
Abstract:
Convective temperature (Tc) can be utilized to estimate the likelihood of local thermal convection and convective cloud (CC). However, its application in operational cloud forecasting is restricted to some extent due to the limited sounding time and certain preconditions. Addressing this problem, we propose a numerical computation scheme of Tc, as well as an idea for CC forecast on the basis of model-forecasted sounding. Firstly, Tc at each forecasting time can be calculated by using dew point temperature at 2 m height, surface pressure, and temperature on pressure levels from numerical weather prediction (NWP) model. Then, an index of thermal convection (Icv), which is defined as the difference between temperature at 2 m height (T2 m) and Tc, can be easily got as T2 m is usually provided by NWP operational models. If Icv meets certain threshold value, CC will be predicted to occur. In this study, this idea is successfully used to explain the false negative prediction of CC in Shandong on 27 April 2020. Besides, Icv has been quasi-operationally applied in the forecast of CC since May 2020, and it performs quite well in predicting both the thermal cumulus on the land and the wintertime cold airflow-induced low-level cloud over the sea. In order to forecast the occurrence of thermal convective cloud, we suggest that emphasis be paid on the condition analysis of thermal convection, rather than that of dynamical lifting or water vapor. In addition, the influences of a couple of special atmospheric profile scenarios, both of which are characterized by the existence of temperature inversion, on the computing of Tc are discussed, and the corresponding solutions are given.
Convective temperature (Tc) can be utilized to estimate the likelihood of local thermal convection and convective cloud (CC). However, its application in operational cloud forecasting is restricted to some extent due to the limited sounding time and certain preconditions. Addressing this problem, we propose a numerical computation scheme of Tc, as well as an idea for CC forecast on the basis of model-forecasted sounding. Firstly, Tc at each forecasting time can be calculated by using dew point temperature at 2 m height, surface pressure, and temperature on pressure levels from numerical weather prediction (NWP) model. Then, an index of thermal convection (Icv), which is defined as the difference between temperature at 2 m height (T2 m) and Tc, can be easily got as T2 m is usually provided by NWP operational models. If Icv meets certain threshold value, CC will be predicted to occur. In this study, this idea is successfully used to explain the false negative prediction of CC in Shandong on 27 April 2020. Besides, Icv has been quasi-operationally applied in the forecast of CC since May 2020, and it performs quite well in predicting both the thermal cumulus on the land and the wintertime cold airflow-induced low-level cloud over the sea. In order to forecast the occurrence of thermal convective cloud, we suggest that emphasis be paid on the condition analysis of thermal convection, rather than that of dynamical lifting or water vapor. In addition, the influences of a couple of special atmospheric profile scenarios, both of which are characterized by the existence of temperature inversion, on the computing of Tc are discussed, and the corresponding solutions are given.
2022, 48(1):28-43.
DOI: 10.7519/j.issn.1000-0526.2021.061001
Abstract:
Using conventional observation data, Doppler radar data of Xi’an Station, surface densely observed weather data and ERA5 reanalysis data (0.25°×0.25°), the environmental conditions and triggering mechanism of four severe convection weather processes in Guanzhong Area of Shaanxi Province, under the influence of subtropical high from 2015 to 2018 are comparatively analyzed. These four cases resulted in local geological disasters and urban flooding, but the global model failed to forecast the short-term rainstorms. Results show that the severe convection in Guanzhong Area under the control of subtropical high often coexists with the hot weather. When severe convection occurs, low-level atmospheric water vapor content is large and the atmospheric precipitable water can be more than 50 mm. Relative to the systemic rainstorm that occurs in the peripheral of the subtropical high, the water vapor transmission in such weather is relatively weak. The strength of the water vapor transmission determines the total rainfall in the severe convection process. The convergence center is located at the height from the surface to 800 hPa. Compared with the systemic rainstorm, the convergence center position is lower. The main role of low-level convergence is to overcome convection suppression, and to release unstable energy. Favorable environmental conditions for the occurrence of severe convection including intense geopotential unstable layer, low level of free convection, medium intensity of convective available potential energy and thick warm clouds. The triggering mechanism is mainly cold front and low-level wind convergence line. When there is a cold front in the upwind, the cooling effect of precipitation behind the cold front increases the temperature gradient to enhance the cold front, and cold air in the lower layer invades the atmosphere with high temperature and high humidity controlled by subtropical high, triggering severe convection. The convection in warm sectors is usually triggered by ground convergence line. The convection induced cold pools can form gusty front and trigger new convection. The terrain of Qinling Mountains has a significant impact on the movement and spread of the severe convection. The convection that occurs in north of Guanzhong Area and moves southward can easily cause rainstorm because of the rain belt blocked by Qinling Mountains. The new convection along the terrain convergence line in the northern Qinling Mountains triggers new convective development in Guanzhong Area, as the potential energy is converted to kinetic energy during the descending process. The convection system moves faster and the duration of heavy precipitation is shorter, which is easier to produce large-scale thunderstorm and gale weather.
Using conventional observation data, Doppler radar data of Xi’an Station, surface densely observed weather data and ERA5 reanalysis data (0.25°×0.25°), the environmental conditions and triggering mechanism of four severe convection weather processes in Guanzhong Area of Shaanxi Province, under the influence of subtropical high from 2015 to 2018 are comparatively analyzed. These four cases resulted in local geological disasters and urban flooding, but the global model failed to forecast the short-term rainstorms. Results show that the severe convection in Guanzhong Area under the control of subtropical high often coexists with the hot weather. When severe convection occurs, low-level atmospheric water vapor content is large and the atmospheric precipitable water can be more than 50 mm. Relative to the systemic rainstorm that occurs in the peripheral of the subtropical high, the water vapor transmission in such weather is relatively weak. The strength of the water vapor transmission determines the total rainfall in the severe convection process. The convergence center is located at the height from the surface to 800 hPa. Compared with the systemic rainstorm, the convergence center position is lower. The main role of low-level convergence is to overcome convection suppression, and to release unstable energy. Favorable environmental conditions for the occurrence of severe convection including intense geopotential unstable layer, low level of free convection, medium intensity of convective available potential energy and thick warm clouds. The triggering mechanism is mainly cold front and low-level wind convergence line. When there is a cold front in the upwind, the cooling effect of precipitation behind the cold front increases the temperature gradient to enhance the cold front, and cold air in the lower layer invades the atmosphere with high temperature and high humidity controlled by subtropical high, triggering severe convection. The convection in warm sectors is usually triggered by ground convergence line. The convection induced cold pools can form gusty front and trigger new convection. The terrain of Qinling Mountains has a significant impact on the movement and spread of the severe convection. The convection that occurs in north of Guanzhong Area and moves southward can easily cause rainstorm because of the rain belt blocked by Qinling Mountains. The new convection along the terrain convergence line in the northern Qinling Mountains triggers new convective development in Guanzhong Area, as the potential energy is converted to kinetic energy during the descending process. The convection system moves faster and the duration of heavy precipitation is shorter, which is easier to produce large-scale thunderstorm and gale weather.
2022, 48(1):44-60.
DOI: 10.7519/j.issn.1000-0526.2021.061801
Abstract:
Based on the ground observation， NCEP 1°×1° reanalysis， FY-2G TBB， model data and radar mosic data of two type severe precipitations under the influence of low vortex shear in the Qinghai Hehuang Valley in the past three years， the comparative analysis is conducted about the environmental conditions and causes of different types of severe precipitation under the influence of the same circulation background， and also about the preliminary assessment of the model’s forecasting capabilities. The results show that the mixed severe precipitation weather with thunderstorm， hail， thunderstorm and gale is called severe precipitation type Ⅰ， and the severe precipitation weather dominated by pure short-term severe precipitation is called severe precipitation type Ⅱ. The low vortex shear was the impact system of the two types of severe precipitation. The severe precipitation type Ⅰ 400-300 hPa high-altitude cold advection intrusion promoted the eastward movement of the low vortex shear system， and the development of the ground cold front formed an occluded front in the Hehuang Valley. The severe precipitation type Ⅱ was blocked by the westward advance of the subtropical high, and the low vortex shear system and the ground cold front weakened and disappeared. Severe precipitation type I mainly had strong high-altitude dry-cold jets， high sinking convective effective potential energy， high temperature difference between 700 hPa and 400 hPa， and strong vertical wind shear all provided power conditions for the occurrence of severe convection， and the severe weather produced was mainly gale and hail. The severe precipitation type Ⅱ had a higher height of 0℃ layer and -20℃ layer， a higher uplift and condensation height， and the severe weather produced was dominated by short-term severe precipitation. The characteristics of the severe precipitation type Ⅰ cloud map were mainly manifested in the cold vortex cloud system with a high degree of organization developed in the afternoon.The initial center value of TBB was between -45℃ and -35℃， and the TBB dropped to -75℃ to -40℃ in the developing stage. In the meantime， the type Ⅱ cloud image of severe precipitation was mainly characterized by scattered massive convective cloud system. The initial center value of TBB was around -35℃， and TBB dropped to -70℃ to -50℃ in the developing stage. Ground convergence lines were two types of severe precipitation trigger systems.The pseudo-equivalent potential temperature value of the severe precipitation type Ⅱ was greater than that of the severe precipitation type Ⅰ， and was dominated by thermal forcing.The vertical velocity of the severe precipitation type Ⅰ was greater than that of the severe precipitation type Ⅱ， which was dominated by dynamic forcing. The global model assimilation forecasst system had more advantages than the mesoscale weather numerical forecast system. The two models of ECMWF and CMA-MESO could better characterize the 500 hPa low vortex shear. The ECMWF model could better simulate the effective convective potential energy， and the three models could predict precipitation magnitude obviously larger and the center of precipitation was more northward and westward， and the mesoscale weather numerical forecast system of China Meteorological Administration CMA-MESO had a slight advantage in precipitation forecasting.
Based on the ground observation， NCEP 1°×1° reanalysis， FY-2G TBB， model data and radar mosic data of two type severe precipitations under the influence of low vortex shear in the Qinghai Hehuang Valley in the past three years， the comparative analysis is conducted about the environmental conditions and causes of different types of severe precipitation under the influence of the same circulation background， and also about the preliminary assessment of the model’s forecasting capabilities. The results show that the mixed severe precipitation weather with thunderstorm， hail， thunderstorm and gale is called severe precipitation type Ⅰ， and the severe precipitation weather dominated by pure short-term severe precipitation is called severe precipitation type Ⅱ. The low vortex shear was the impact system of the two types of severe precipitation. The severe precipitation type Ⅰ 400-300 hPa high-altitude cold advection intrusion promoted the eastward movement of the low vortex shear system， and the development of the ground cold front formed an occluded front in the Hehuang Valley. The severe precipitation type Ⅱ was blocked by the westward advance of the subtropical high, and the low vortex shear system and the ground cold front weakened and disappeared. Severe precipitation type I mainly had strong high-altitude dry-cold jets， high sinking convective effective potential energy， high temperature difference between 700 hPa and 400 hPa， and strong vertical wind shear all provided power conditions for the occurrence of severe convection， and the severe weather produced was mainly gale and hail. The severe precipitation type Ⅱ had a higher height of 0℃ layer and -20℃ layer， a higher uplift and condensation height， and the severe weather produced was dominated by short-term severe precipitation. The characteristics of the severe precipitation type Ⅰ cloud map were mainly manifested in the cold vortex cloud system with a high degree of organization developed in the afternoon.The initial center value of TBB was between -45℃ and -35℃， and the TBB dropped to -75℃ to -40℃ in the developing stage. In the meantime， the type Ⅱ cloud image of severe precipitation was mainly characterized by scattered massive convective cloud system. The initial center value of TBB was around -35℃， and TBB dropped to -70℃ to -50℃ in the developing stage. Ground convergence lines were two types of severe precipitation trigger systems.The pseudo-equivalent potential temperature value of the severe precipitation type Ⅱ was greater than that of the severe precipitation type Ⅰ， and was dominated by thermal forcing.The vertical velocity of the severe precipitation type Ⅰ was greater than that of the severe precipitation type Ⅱ， which was dominated by dynamic forcing. The global model assimilation forecasst system had more advantages than the mesoscale weather numerical forecast system. The two models of ECMWF and CMA-MESO could better characterize the 500 hPa low vortex shear. The ECMWF model could better simulate the effective convective potential energy， and the three models could predict precipitation magnitude obviously larger and the center of precipitation was more northward and westward， and the mesoscale weather numerical forecast system of China Meteorological Administration CMA-MESO had a slight advantage in precipitation forecasting.
2022, 48(1):61-72.
DOI: 10.7519/j.issn.1000-0526.2021.072901
Abstract:
An numerical simulation experiment was conducted on a large-scale hail weather process in Guizhou on 2 April 2018 to assimilate C-band Doppler radar reflectivity data by using the Newton continuous relaxation approximation method (nudging) based on the high-resolution numerical model in South China. The analysis results show that the hydrometeor information and the thermal field structure got adjusted after the nudging assimilated the radar reflectivity factor in the model. The content of rainwater and ice particles in the middle troposphere increased, and the latent heat release of the hydrometeor heated the cloud body and adjusted the positive temperature disturbance for the atmospheric thermal field. This kind of positive temperature disturbance plays an important role in maintaining the development of convection. The cloud analysis system was used in reversing the microphysical quantity, then the nudging assimilated the reverved cloud microphysical quantity into the initial field of the model. Thus, the hail cloud development and evolution, hail cloud life and hail cloud intensity have all improved significantly. The conversion process of cloud water to ice-phase particles in the cloud has been promoted, which has made a significant contribution to the improvement of precipitation forecast effect. Therefore, the assimilation of radar reflectivity factor is of great significance to the forecasting ability of the hail cloud weather system, and could provide an important reference for nowcasting hail clouds.
An numerical simulation experiment was conducted on a large-scale hail weather process in Guizhou on 2 April 2018 to assimilate C-band Doppler radar reflectivity data by using the Newton continuous relaxation approximation method (nudging) based on the high-resolution numerical model in South China. The analysis results show that the hydrometeor information and the thermal field structure got adjusted after the nudging assimilated the radar reflectivity factor in the model. The content of rainwater and ice particles in the middle troposphere increased, and the latent heat release of the hydrometeor heated the cloud body and adjusted the positive temperature disturbance for the atmospheric thermal field. This kind of positive temperature disturbance plays an important role in maintaining the development of convection. The cloud analysis system was used in reversing the microphysical quantity, then the nudging assimilated the reverved cloud microphysical quantity into the initial field of the model. Thus, the hail cloud development and evolution, hail cloud life and hail cloud intensity have all improved significantly. The conversion process of cloud water to ice-phase particles in the cloud has been promoted, which has made a significant contribution to the improvement of precipitation forecast effect. Therefore, the assimilation of radar reflectivity factor is of great significance to the forecasting ability of the hail cloud weather system, and could provide an important reference for nowcasting hail clouds.
2022, 48(1):73-83.
DOI: 10.7519/j.issn.1000-0526.2021.111001
Abstract:
Based on ECMWF high resolution model grid precipitation forecast data from January 2019 to February 2020 and 388 meteorological stations precipitation observation data, the forecast performance of the model precipitation frequency is objectively verified, and the ECMWF grid precipitation forecast is corrected by using the Kalman dynamic frequency. The main conclusions are as follows. The ECMWF model has significantly higher forecast frequency for small-scale precipitation than the observation, but lower frequency for torrential rain. The frequency of model forecast and observed precipitation are significantly different in different seasons. Matching the frequency of forecast precipitation with that of observed precipitation does not get the highest precipitation forecast score. Based on the Kalman filtering method, the forecast and observed precipitation frequency can be dynamically matched, the model forecast frequency can be revised to be basically consistent with the observation, the standard deviation of the model forecast precipitation can be improved, and the phenomenon that the model forecast errors are more for light precipitation but less for severe precipitation can be significantly adjusted. Due to the position or time deviation of precipitation forecasted by the model, appropriate coefficients are selected so that the frequency of torrential rain forecast is slightly higher than the observed frequency, and the light rain frequency is slightly lower than the observed frequency, thus, a better precipitation forecast score can be obtained. According to the precipitation characteristics of different regions, the Kalman precipitation dynamic frequency is calculated separately to correct the precipitation, which can effectively improve the TS forecast score of torrential rain, but the accuracy of sunny and rain forecast is not significantly improved.
Based on ECMWF high resolution model grid precipitation forecast data from January 2019 to February 2020 and 388 meteorological stations precipitation observation data, the forecast performance of the model precipitation frequency is objectively verified, and the ECMWF grid precipitation forecast is corrected by using the Kalman dynamic frequency. The main conclusions are as follows. The ECMWF model has significantly higher forecast frequency for small-scale precipitation than the observation, but lower frequency for torrential rain. The frequency of model forecast and observed precipitation are significantly different in different seasons. Matching the frequency of forecast precipitation with that of observed precipitation does not get the highest precipitation forecast score. Based on the Kalman filtering method, the forecast and observed precipitation frequency can be dynamically matched, the model forecast frequency can be revised to be basically consistent with the observation, the standard deviation of the model forecast precipitation can be improved, and the phenomenon that the model forecast errors are more for light precipitation but less for severe precipitation can be significantly adjusted. Due to the position or time deviation of precipitation forecasted by the model, appropriate coefficients are selected so that the frequency of torrential rain forecast is slightly higher than the observed frequency, and the light rain frequency is slightly lower than the observed frequency, thus, a better precipitation forecast score can be obtained. According to the precipitation characteristics of different regions, the Kalman precipitation dynamic frequency is calculated separately to correct the precipitation, which can effectively improve the TS forecast score of torrential rain, but the accuracy of sunny and rain forecast is not significantly improved.
2022, 48(1):84-95.
DOI: 10.7519/j.issn.1000-0526.2021.061701
Abstract:
Based on ECMWF ensemble forecast, the optimal percentile fusion product of typhoon rainfall in Guangdong Province is developed by using customized fusion parameters. Verification indicates that threat score (TS) of severe precipitation is significantly improved than the ensemble average product. The longer the forecast lead time, the greater the increment, but Bias and false alarm ratio (FAR) also become greater accordingly. The over-estimation of severe precipitation forecast is related to the divergence of typhoon path forecast. Since the fusion product uses high percentile field for mapping in large rainfall grades, the fusion result of severe precipitation is close to the union of severe rainfall locations of each member. When the typhoon paths are more dispersed, the spatial location of the severe precipitation area of each member is generally more divergent, resulting in the large range error of the severe rainfall area predicted by the fusion product. In order to solve this problem, a forecast index describing the probability of forecasting a certain precipitation threshold is introduced, which can effectively identify the heavy rainfall forecast samples with large false alarms but few hit alarms. Using the index, we are likely able to improve the optimal percentile fusion product. Under the condition of maintaining TS, the improved fusion products have Bias decreasing from 1.27 to 1.03 and FAR from 0.51 to 0.43 during the test period. Meanwhile, the longer the forecast time, the greater the improvement effect of Bias and TS of the fusion products. Therefore, the revised products can provide grid quantitative precipitation forecast with more appropriate severe precipitation scope and more accurate rainfall location in forecasting operation.
Based on ECMWF ensemble forecast, the optimal percentile fusion product of typhoon rainfall in Guangdong Province is developed by using customized fusion parameters. Verification indicates that threat score (TS) of severe precipitation is significantly improved than the ensemble average product. The longer the forecast lead time, the greater the increment, but Bias and false alarm ratio (FAR) also become greater accordingly. The over-estimation of severe precipitation forecast is related to the divergence of typhoon path forecast. Since the fusion product uses high percentile field for mapping in large rainfall grades, the fusion result of severe precipitation is close to the union of severe rainfall locations of each member. When the typhoon paths are more dispersed, the spatial location of the severe precipitation area of each member is generally more divergent, resulting in the large range error of the severe rainfall area predicted by the fusion product. In order to solve this problem, a forecast index describing the probability of forecasting a certain precipitation threshold is introduced, which can effectively identify the heavy rainfall forecast samples with large false alarms but few hit alarms. Using the index, we are likely able to improve the optimal percentile fusion product. Under the condition of maintaining TS, the improved fusion products have Bias decreasing from 1.27 to 1.03 and FAR from 0.51 to 0.43 during the test period. Meanwhile, the longer the forecast time, the greater the improvement effect of Bias and TS of the fusion products. Therefore, the revised products can provide grid quantitative precipitation forecast with more appropriate severe precipitation scope and more accurate rainfall location in forecasting operation.
2022, 48(1):96-106.
DOI: 10.7519/j.issn.1000-0526.2021.061501
Abstract:
Based on the observation data of air quality, meteorological elements, and reanalysis data, the evolution characteristics of air quality in Hubei Province and its adjacent areas from 1 to 30 October 2019, the impacts of meteorological conditions on the air quality during the 7th CISM Military World Games and before and after of this time are analyzed. The concentrations of PM2.5, PM10 in control period Ⅱ (from 17 to 28 October) were lower than the average concentrations in past five years and in other surrounding cities. Control measures were effective in decreasing concentration and restraining ascending velocity. O3 and NO2 were the primary pollutants in control periods (Ⅰ and Ⅱ) (from 13 to 16 October, and 17 to 28 October). Compared with the past five years, the concentration of O3 in Wuhan increased. However, under the background of excessive O3 in other nearby cities, pollution in Wuhan did not reach the polluted level, which indicates the control still took some effects. Actually, the concentration of NO2 was lower than normal years, but higher than that in other cities. Compared with control period Ⅰ, precipitation was less and wind speed was small in control period Ⅱ, thus the meteorological condition was not good for pollutant concentration to decrease. Anticyclonic circulation was dominant from 17 to 21 October, and sunlight and radiation was high with intense photochemical reaction, so concentrations of O3 and NO2 raised obviously. Based on evaluation on meteorological condition index (EMI), EMI was a positive value in 2019 compared with 2013-2017, which indicates that the meteorological conditions in 2019 were not conducive to the reduction of PM2.5, so emission reduction did the most significant contribution to the decreased concentration.
Based on the observation data of air quality, meteorological elements, and reanalysis data, the evolution characteristics of air quality in Hubei Province and its adjacent areas from 1 to 30 October 2019, the impacts of meteorological conditions on the air quality during the 7th CISM Military World Games and before and after of this time are analyzed. The concentrations of PM2.5, PM10 in control period Ⅱ (from 17 to 28 October) were lower than the average concentrations in past five years and in other surrounding cities. Control measures were effective in decreasing concentration and restraining ascending velocity. O3 and NO2 were the primary pollutants in control periods (Ⅰ and Ⅱ) (from 13 to 16 October, and 17 to 28 October). Compared with the past five years, the concentration of O3 in Wuhan increased. However, under the background of excessive O3 in other nearby cities, pollution in Wuhan did not reach the polluted level, which indicates the control still took some effects. Actually, the concentration of NO2 was lower than normal years, but higher than that in other cities. Compared with control period Ⅰ, precipitation was less and wind speed was small in control period Ⅱ, thus the meteorological condition was not good for pollutant concentration to decrease. Anticyclonic circulation was dominant from 17 to 21 October, and sunlight and radiation was high with intense photochemical reaction, so concentrations of O3 and NO2 raised obviously. Based on evaluation on meteorological condition index (EMI), EMI was a positive value in 2019 compared with 2013-2017, which indicates that the meteorological conditions in 2019 were not conducive to the reduction of PM2.5, so emission reduction did the most significant contribution to the decreased concentration.
2022, 48(1):107-121.
DOI: 10.7519/j.issn.1000-0526.2021.120201
Abstract:
The anomaly characteristics of the weather and climate in China were outstanding in the summer of 2021. During this summer, many extreme weather and climate events tookplace with much more precipi- tation in North China. The intraseasonal variation of summer climate was significant. The pre-monsoonal rainfall season in South China started later, and the Meiyu in Yangtze-Huaihe River Valley and the North China rainy season started earlier than normal. The spatial distribution of monthly precipitation anomaly and its possible causes varied greatly in the summer of 2021. In June, the Northeast China cold vortex activity was very frequent, bringing more precipitation in North China and Northeast China. Severe floods occurred in Heilongjiang and Nenjiang River basins. The anomalous activity of the Northeast China cold vortex was mainly influenced by the positive phase of the North Atlantic triple from spring to June 2021. In July, the longitudinal rainy belt from the lower reaches of the Yangtze River to the eastern part of Inner Mongolia and the extremely severe rainfall in Henan were mainly affected by the long-term activity of the strong Typhoon In-Fa, the strong continental high and the Western Pacific subtropical high (WPSH). La Ni〖AKn~D〗a was an important external forcing factor for the above circulation anomalies. In August, the WPSH was much stronger and more southward. The associated anomalous low-level northwestern Pacific anticyclone resulted in anomalous convergence of moisture flux over the Yangtze River and “reoccurrence of Meiyu” weather. Further analysis indicates that the unusually active Madden-Julian Oscillation (MJO) in August was the critical cause for the significant turning of the tropical and subtropical circulations. MJO located in the Indian Ocean (Phase 2) lasted for 22 days with stronger average intensity, which was rare in history.
The anomaly characteristics of the weather and climate in China were outstanding in the summer of 2021. During this summer, many extreme weather and climate events tookplace with much more precipi- tation in North China. The intraseasonal variation of summer climate was significant. The pre-monsoonal rainfall season in South China started later, and the Meiyu in Yangtze-Huaihe River Valley and the North China rainy season started earlier than normal. The spatial distribution of monthly precipitation anomaly and its possible causes varied greatly in the summer of 2021. In June, the Northeast China cold vortex activity was very frequent, bringing more precipitation in North China and Northeast China. Severe floods occurred in Heilongjiang and Nenjiang River basins. The anomalous activity of the Northeast China cold vortex was mainly influenced by the positive phase of the North Atlantic triple from spring to June 2021. In July, the longitudinal rainy belt from the lower reaches of the Yangtze River to the eastern part of Inner Mongolia and the extremely severe rainfall in Henan were mainly affected by the long-term activity of the strong Typhoon In-Fa, the strong continental high and the Western Pacific subtropical high (WPSH). La Ni〖AKn~D〗a was an important external forcing factor for the above circulation anomalies. In August, the WPSH was much stronger and more southward. The associated anomalous low-level northwestern Pacific anticyclone resulted in anomalous convergence of moisture flux over the Yangtze River and “reoccurrence of Meiyu” weather. Further analysis indicates that the unusually active Madden-Julian Oscillation (MJO) in August was the critical cause for the significant turning of the tropical and subtropical circulations. MJO located in the Indian Ocean (Phase 2) lasted for 22 days with stronger average intensity, which was rare in history.
2022, 48(1):122-128.
DOI: 10.7519/j.issn.1000-0526.2021.120301
Abstract:
The main characteristics of the general atmospheric circulation in October 2021 are as follows. The polar vortex presented a unipolar pattern, with location shifting from the North Polar to Siberia. The circulation at 500 hPa showed a five-wave pattern in middle-high latitudes, with negative anomaly of geopotential height over the region from Northeastern Asia to Northeast Pacific, and positive anomaly over the North America to Arctic region. The subtropical high presented a long and narrow strip shape and almost surrounded the Northern Hemisphere. The Northwest Pacific subtropical high was smaller than those in recent years in the same period. The monthly mean precipitation was 52.1 mm, which is 45.4% more than normal, ranking the top 4th since 1961. Moreover, the distribution of the precipitation was unevenly. The monthly mean temperature was 10.7 ℃, 0.4 ℃ higher than normal. Three heavy rainfall processes and two cold air processes occurred in October, while four typhoons and one tropical depress were generated and developed. Among them the first heavy rainfall process was jointly caused by the northeast cold vortex, the low-level jet and the low-layer shear line, and became a long-term, heavy and extreme rainstorm process with a large amount of accumulated precipitation. Another two heavy rainfall processes were produced by Typhoon Lionlock (No.2117) and Kompasu (No.2118), both of which landed on Qionghai City of Hainan Province and brought heavy precipitation to the coastal area of southeastern and southern China.
The main characteristics of the general atmospheric circulation in October 2021 are as follows. The polar vortex presented a unipolar pattern, with location shifting from the North Polar to Siberia. The circulation at 500 hPa showed a five-wave pattern in middle-high latitudes, with negative anomaly of geopotential height over the region from Northeastern Asia to Northeast Pacific, and positive anomaly over the North America to Arctic region. The subtropical high presented a long and narrow strip shape and almost surrounded the Northern Hemisphere. The Northwest Pacific subtropical high was smaller than those in recent years in the same period. The monthly mean precipitation was 52.1 mm, which is 45.4% more than normal, ranking the top 4th since 1961. Moreover, the distribution of the precipitation was unevenly. The monthly mean temperature was 10.7 ℃, 0.4 ℃ higher than normal. Three heavy rainfall processes and two cold air processes occurred in October, while four typhoons and one tropical depress were generated and developed. Among them the first heavy rainfall process was jointly caused by the northeast cold vortex, the low-level jet and the low-layer shear line, and became a long-term, heavy and extreme rainstorm process with a large amount of accumulated precipitation. Another two heavy rainfall processes were produced by Typhoon Lionlock (No.2117) and Kompasu (No.2118), both of which landed on Qionghai City of Hainan Province and brought heavy precipitation to the coastal area of southeastern and southern China.
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ISSN:1000-0526 CN:11-2282/P