ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 49,Issue 4,2023 Table of Contents
2023, 49(4):385-399.
DOI: 10.7519/j.issn.1000-0526.2022.050501
Abstract:
In view of the prominent problems in the precipitation and model forecasts of the landfalling typhoons in South China, this paper reviews and analyzes the current researches on the asymmetry of the precipitation distribution of the landfalling typhoons and the mechanism of the persistent torrential rains in the later period of typhoons. Relevant scientific issues that need in-depth study and measures of improving numerical predictions are put forward, in order to provide references for the improvement of the forecast of heavy rainfall associated with tropical cyclone (TC) landfall in South China. The analysis reveals that the vertical shear of the ambient field, the boundary of the low-level air mass (such as the boundary of the cold pool), the intrusion of dry and cold air, mesoscale convective systems (MCSs) and the local topography are important factors causing the asymmetric distribution of precipitation of the landfalling typhoons in South China. The occurrence of persistent torrential rains in South China during the late period of landfalling typhoons is often related to the increase in summer monsoon activity. The active southwest monsoon tends to provide favorable conditions for the development of MCSs in torrential rains. Then, MCSs feed back to the large-scale circulation through latent heat heating, contributing to the maintenance of TC vortex circulation and the southwest monsoon, and cause iterative development of MCSs, resulting in persistent torrential rains. To further improve the forecast of models, it is essential to investigate and evaluate the performance of the current models, carry out in-depth research on the related scientific issues, and then propose effective improvement plans.
In view of the prominent problems in the precipitation and model forecasts of the landfalling typhoons in South China, this paper reviews and analyzes the current researches on the asymmetry of the precipitation distribution of the landfalling typhoons and the mechanism of the persistent torrential rains in the later period of typhoons. Relevant scientific issues that need in-depth study and measures of improving numerical predictions are put forward, in order to provide references for the improvement of the forecast of heavy rainfall associated with tropical cyclone (TC) landfall in South China. The analysis reveals that the vertical shear of the ambient field, the boundary of the low-level air mass (such as the boundary of the cold pool), the intrusion of dry and cold air, mesoscale convective systems (MCSs) and the local topography are important factors causing the asymmetric distribution of precipitation of the landfalling typhoons in South China. The occurrence of persistent torrential rains in South China during the late period of landfalling typhoons is often related to the increase in summer monsoon activity. The active southwest monsoon tends to provide favorable conditions for the development of MCSs in torrential rains. Then, MCSs feed back to the large-scale circulation through latent heat heating, contributing to the maintenance of TC vortex circulation and the southwest monsoon, and cause iterative development of MCSs, resulting in persistent torrential rains. To further improve the forecast of models, it is essential to investigate and evaluate the performance of the current models, carry out in-depth research on the related scientific issues, and then propose effective improvement plans.
2023, 49(4):400-414.
DOI: 10.7519/j.issn.1000-0526.2022.041501
Abstract:
It is important to diagnose and analyze 2 m temperature prediction by CMA-MESO system with 3 km resolution in winter for the Winter Olympics meteorological service and CMA-MESO model system development. The 2 m temperature prediction data from December 2020 to February 2021 are selected and diagnosed. The results show that the daily low temperature prediction is better, but the high temperature prediction is poor. The prediction effect of the model on the heating process in 00-06 UTC is better than that of the cooling process in 06-21 UTC. When the 2 m temperature prediction is corrected by the moving-biweight average method, the correction results show that the 2 m temperature prediction deviation is mainly systematic deviation. The RMSE and standard deviation are reduced, especially in areas with large deviations before correction. According to the large difference of standard deviation before and after temperature correction, individual cases in North China, East China and Southwest China and the continuous test in North China are selected for wave spectrum analysis. It is found that the power spectrum energy gradually increases with the scale. There is a certain correspondence between the 2 m temperature prediction deviation and the power spectrum information of different scales. When value of power spectrum energy is very small or abnormally large, the difference between 2 m temperature prediction and observation is significant.
It is important to diagnose and analyze 2 m temperature prediction by CMA-MESO system with 3 km resolution in winter for the Winter Olympics meteorological service and CMA-MESO model system development. The 2 m temperature prediction data from December 2020 to February 2021 are selected and diagnosed. The results show that the daily low temperature prediction is better, but the high temperature prediction is poor. The prediction effect of the model on the heating process in 00-06 UTC is better than that of the cooling process in 06-21 UTC. When the 2 m temperature prediction is corrected by the moving-biweight average method, the correction results show that the 2 m temperature prediction deviation is mainly systematic deviation. The RMSE and standard deviation are reduced, especially in areas with large deviations before correction. According to the large difference of standard deviation before and after temperature correction, individual cases in North China, East China and Southwest China and the continuous test in North China are selected for wave spectrum analysis. It is found that the power spectrum energy gradually increases with the scale. There is a certain correspondence between the 2 m temperature prediction deviation and the power spectrum information of different scales. When value of power spectrum energy is very small or abnormally large, the difference between 2 m temperature prediction and observation is significant.
2023, 49(4):415-426.
DOI: 10.7519/j.issn.1000-0526.2023.030702
Abstract:
In this paper, based on two commonly used aircraft icing diagnostic indices and ERA5 reanalysis data as the atmospheric environmental field for icing occurrence, an aircraft icing diagnosis and forecasting method is constructed and hindcast for 25 collected spring icing cases over Eastern China. The spatial and temporal distribution characteristics of aircraft icing occurrence over typical cities at different latitudes in China are calculated separately, and the spatial and temporal distribution of icing areas over Xinchang, Zhejiang Province during one cold air activity case is simulated. In addition, several application scenarios of aircraft icing forecasting methods are proposed. The results indicate that among the selected icing cases, the diagnosis accuracy of icing index (IC) method is 80%, while that of the false frost point temperature empirical (TF) method is 92%. The effects of aircraft flight speed and power warming are taken into account by TF method, which has better correlation with ice water particle concentration and cloud cover in medium and low clouds, but the predicted icing intensity is not accurate enough without the real flight speed of the aircraft, and there are more false forecasts of icing intensity above 400 hPa altitude. In general, both the IC and TF methods can effectively diagnose the icingprone altitude layer and the icingprone time, and can effectively forecast the distribution of highaltitude ice accumulation intensity at a certain station. In addition, the TF method can calculate the icing critical flight speed of the aircraft.
In this paper, based on two commonly used aircraft icing diagnostic indices and ERA5 reanalysis data as the atmospheric environmental field for icing occurrence, an aircraft icing diagnosis and forecasting method is constructed and hindcast for 25 collected spring icing cases over Eastern China. The spatial and temporal distribution characteristics of aircraft icing occurrence over typical cities at different latitudes in China are calculated separately, and the spatial and temporal distribution of icing areas over Xinchang, Zhejiang Province during one cold air activity case is simulated. In addition, several application scenarios of aircraft icing forecasting methods are proposed. The results indicate that among the selected icing cases, the diagnosis accuracy of icing index (IC) method is 80%, while that of the false frost point temperature empirical (TF) method is 92%. The effects of aircraft flight speed and power warming are taken into account by TF method, which has better correlation with ice water particle concentration and cloud cover in medium and low clouds, but the predicted icing intensity is not accurate enough without the real flight speed of the aircraft, and there are more false forecasts of icing intensity above 400 hPa altitude. In general, both the IC and TF methods can effectively diagnose the icingprone altitude layer and the icingprone time, and can effectively forecast the distribution of highaltitude ice accumulation intensity at a certain station. In addition, the TF method can calculate the icing critical flight speed of the aircraft.
2023, 49(4):427-438.
DOI: 10.7519/j.issn.1000-0526.2022.080601
Abstract:
The Greater Khingan Mountains Area is an important ecological resource protection area in China due to its complex terrain and various biological species. Understanding and recognizing the microphysical properties of clouds is of great significance for studying the climate change and precipitation characteristics in the region. Based on CloudSat-CALIPSO (CloudSat-Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations) data, the macroscopic and microscopic physical characteristics of the clouds in the Greater Khingan Mountains are analyzed. The results show that the annual average cloud occurrence frequency over the Greater Khingan Mountains is 59.5%, mainly composed of altostratus, cirrus and stratocumulus, and the cloud occurrence frequency in spring and summer is higher than that in autumn and winter. The clouds are mainly thin clouds, and 61.41% of the clouds are less than 2 km thick. The cloud top height and cloud bottom height show the distribution patterns of double peak and single peak, respectively. The occurrence frequency of single-layer cloud is the highest, accounting for 69.19% of the total cloud cover. With the increase of cloud layer, the occurrence frequency of clouds decreases gradually. The cloud liquid water content in the Greater Khingan Mountains is abundant, with an 〖JP2〗annual average value of 244.41 mg·〖JP〗m-3, which is about 4 times the annual average ice water content. There are 83.2% of cloud water resources concentrated in low-altitude areas below 5 km from the ground. The annual mean values of effective particle size and number concentration of water droplets are 15.86 μm and 34.47 cm-3, respectively, which are lower than the average values of ice crystals. The water content and effective particle size in the cloud show a single-peak distribution with height, while the particle number concentration of cloud droplet shows a double-peak distribution at low altitudes.
The Greater Khingan Mountains Area is an important ecological resource protection area in China due to its complex terrain and various biological species. Understanding and recognizing the microphysical properties of clouds is of great significance for studying the climate change and precipitation characteristics in the region. Based on CloudSat-CALIPSO (CloudSat-Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations) data, the macroscopic and microscopic physical characteristics of the clouds in the Greater Khingan Mountains are analyzed. The results show that the annual average cloud occurrence frequency over the Greater Khingan Mountains is 59.5%, mainly composed of altostratus, cirrus and stratocumulus, and the cloud occurrence frequency in spring and summer is higher than that in autumn and winter. The clouds are mainly thin clouds, and 61.41% of the clouds are less than 2 km thick. The cloud top height and cloud bottom height show the distribution patterns of double peak and single peak, respectively. The occurrence frequency of single-layer cloud is the highest, accounting for 69.19% of the total cloud cover. With the increase of cloud layer, the occurrence frequency of clouds decreases gradually. The cloud liquid water content in the Greater Khingan Mountains is abundant, with an 〖JP2〗annual average value of 244.41 mg·〖JP〗m-3, which is about 4 times the annual average ice water content. There are 83.2% of cloud water resources concentrated in low-altitude areas below 5 km from the ground. The annual mean values of effective particle size and number concentration of water droplets are 15.86 μm and 34.47 cm-3, respectively, which are lower than the average values of ice crystals. The water content and effective particle size in the cloud show a single-peak distribution with height, while the particle number concentration of cloud droplet shows a double-peak distribution at low altitudes.
2023, 49(4):439-453.
DOI: 10.7519/j.issn.1000-0526.2022.112201
Abstract:
Based on the observational data and the mesoscale numerical model WRF, a typical low-vortex low-trough snowfall system that occurred in Beijing on 14 February 2019 is analyzed and numerically simulated. The microphysical mechanism and formation process of snowfall are discussed, and the numerical simulation of cloud seeding is analyzed. The results show that the water vapor caused by warm and humid advection near the low vortex front and the strong upward movement near the low vortex shear line gave rise to the regional snowfall event. The sublimation growth of snow, the cloud water rimming on falling snow, the automatic conversion of cloud ice into snow, the ice crystals and snow collisions and aggregation were the main microphysical processes. Seeding simulation shows that after the seeding of silver iodide (AgI), a large number of ice crystals are generated in the cloud, and the increased ice crystals are converted into snow through sublimation growth, collision, aggregation and attachment, etc., which in turn leads to an increase in ground snowfall.
Based on the observational data and the mesoscale numerical model WRF, a typical low-vortex low-trough snowfall system that occurred in Beijing on 14 February 2019 is analyzed and numerically simulated. The microphysical mechanism and formation process of snowfall are discussed, and the numerical simulation of cloud seeding is analyzed. The results show that the water vapor caused by warm and humid advection near the low vortex front and the strong upward movement near the low vortex shear line gave rise to the regional snowfall event. The sublimation growth of snow, the cloud water rimming on falling snow, the automatic conversion of cloud ice into snow, the ice crystals and snow collisions and aggregation were the main microphysical processes. Seeding simulation shows that after the seeding of silver iodide (AgI), a large number of ice crystals are generated in the cloud, and the increased ice crystals are converted into snow through sublimation growth, collision, aggregation and attachment, etc., which in turn leads to an increase in ground snowfall.
2023, 49(4):454-466.
DOI: 10.7519/j.issn.1000-0526.2022.081901
Abstract:
Clouds play an important role in weather forecasting. Accurate identification and segmentation of ground-based cloud images can effectively guide weather forecasting. Now most of the existing datasets are only suitable for single task learning, and ground-based cloud image recognition and segmentation technologies are mostly implemented by single task, thus identification and detection efficiency are low and the robustness of the algorithm is poor. Considering these problems, we construct the ground-based cloud image datasets GBCD and GBCD-GT with labels and suitable for multi-task learning, and then on this basis, a ground-based cloud image recognition and segmentation joint network model GCRSegNet based on multi-task learning is designed. The model firstly extracts shared features through convolutional neural network, then a special network is designed for each task to extract more recognizable features. The segmentation network learns shared features to achieve ground-based cloud image segmentation, and the recognition network combines sharing features and segmentation features to achieve ground-based cloud image recognition. Multiple groups of comparative experiments indicate that the network in this paper can accurately represent the features of ground-based cloud image. Meanwhile, the accuracy of the recognition task can reach 94.28%, the pixel accuracy of segmentation task can reach 93.85%, and mean intersection over union reach 71.58%. These results can provide a possibility for practical application.
Clouds play an important role in weather forecasting. Accurate identification and segmentation of ground-based cloud images can effectively guide weather forecasting. Now most of the existing datasets are only suitable for single task learning, and ground-based cloud image recognition and segmentation technologies are mostly implemented by single task, thus identification and detection efficiency are low and the robustness of the algorithm is poor. Considering these problems, we construct the ground-based cloud image datasets GBCD and GBCD-GT with labels and suitable for multi-task learning, and then on this basis, a ground-based cloud image recognition and segmentation joint network model GCRSegNet based on multi-task learning is designed. The model firstly extracts shared features through convolutional neural network, then a special network is designed for each task to extract more recognizable features. The segmentation network learns shared features to achieve ground-based cloud image segmentation, and the recognition network combines sharing features and segmentation features to achieve ground-based cloud image recognition. Multiple groups of comparative experiments indicate that the network in this paper can accurately represent the features of ground-based cloud image. Meanwhile, the accuracy of the recognition task can reach 94.28%, the pixel accuracy of segmentation task can reach 93.85%, and mean intersection over union reach 71.58%. These results can provide a possibility for practical application.
7 Comparison and Analysis of Verifications for OCF Temperature Forecast Foucsing on Large Error Days
2023, 49(4):467-477.
DOI: 10.7519/j.issn.1000-0526.2022.112101
Abstract:
In order to evaluate the effect of refined multi-model objective consensus forecasting service products (OCF) temperature forecasts which are applied in public weather service, and analyze the causes of forecast errors, this paper makes objective verification on OCF daily maximum and minimum temperature forecasts in China, focuses on large error days with high service impact and the typical case： temperature-drop days, and also makes comparison among OCF, ECMWF and NCEP. The results show that OCF daily maximum and minimum temperature forecasts perform better than models in the consensus generally, and the forecast accuracy is higher in summer but lower in winter. OCF enlarges the range of daily temperature variation and effectively reduces forecast errors. OCF has fewer large error days than models in the consensus, but shows larger errors in 2-3 d forecasting periods and winter half year. The large error days of OCF are related to models in the consensus and obvious temperature-drop. It is found that the forecast performances of OCF, ECMWF and NCEP decline in temperature-drop days, and the error of OCF daily maximum temperature forecast increases rapidly. In temperature-drop days, OCF effectively corrects daily minimum temperature and daily maximum temperature in non-temperature-drop areas, but the daily maximum temperature forecast performs with obvious positive error in temperature-drop areas. Finally, based on analysis above, the improvement direction for OCF consensus methods is proposed. The process verification is conducive to discovering the defects of objective forecasts and methods of temperature consensus and correction.
In order to evaluate the effect of refined multi-model objective consensus forecasting service products (OCF) temperature forecasts which are applied in public weather service, and analyze the causes of forecast errors, this paper makes objective verification on OCF daily maximum and minimum temperature forecasts in China, focuses on large error days with high service impact and the typical case： temperature-drop days, and also makes comparison among OCF, ECMWF and NCEP. The results show that OCF daily maximum and minimum temperature forecasts perform better than models in the consensus generally, and the forecast accuracy is higher in summer but lower in winter. OCF enlarges the range of daily temperature variation and effectively reduces forecast errors. OCF has fewer large error days than models in the consensus, but shows larger errors in 2-3 d forecasting periods and winter half year. The large error days of OCF are related to models in the consensus and obvious temperature-drop. It is found that the forecast performances of OCF, ECMWF and NCEP decline in temperature-drop days, and the error of OCF daily maximum temperature forecast increases rapidly. In temperature-drop days, OCF effectively corrects daily minimum temperature and daily maximum temperature in non-temperature-drop areas, but the daily maximum temperature forecast performs with obvious positive error in temperature-drop areas. Finally, based on analysis above, the improvement direction for OCF consensus methods is proposed. The process verification is conducive to discovering the defects of objective forecasts and methods of temperature consensus and correction.
2023, 49(4):478-486.
DOI: 10.7519/j.issn.1000-0526.2022.081601
Abstract:
This paper proposes a method to calculate the radar detection coverage with a specific altitude corresponding to one point on the surface， and uses the terrain elevation data to analyze the detection capabilities of 23 new-generation weather radars in Shaanxi and surrounding provinces. Additionally， the paper also does the numerical simulation of the negative elevation angle observation mode and obtains the optimal minimum observation elevation angle of the three mountaintop radars. The results show that the primary and secondary coverage rates of the new-generation weather radar at different altitudes over Shaanxi are：48.6% and 2.3% at 0.5 km， 80.0% and 18.9% at 1 km， 98.7% and 74.5% at 2 km, 99.9% and 97.1% at 3 km and 100% at 4 km height. Considered the 3 X-band weather radars of Shaanxi, the primary and secondary coverage rates are increased to 82.7% and 32.1% respectively at 1 km. On this basis, a method using the average annual rainfall, GDP and population data are suggested to calculate the priority of radar coverage in blind areas and counties in Shaanxi Province. The findings of this study could provide a theoretical and technical support for the building of weather radar in the blind area of radar coverage in the future.
This paper proposes a method to calculate the radar detection coverage with a specific altitude corresponding to one point on the surface， and uses the terrain elevation data to analyze the detection capabilities of 23 new-generation weather radars in Shaanxi and surrounding provinces. Additionally， the paper also does the numerical simulation of the negative elevation angle observation mode and obtains the optimal minimum observation elevation angle of the three mountaintop radars. The results show that the primary and secondary coverage rates of the new-generation weather radar at different altitudes over Shaanxi are：48.6% and 2.3% at 0.5 km， 80.0% and 18.9% at 1 km， 98.7% and 74.5% at 2 km, 99.9% and 97.1% at 3 km and 100% at 4 km height. Considered the 3 X-band weather radars of Shaanxi, the primary and secondary coverage rates are increased to 82.7% and 32.1% respectively at 1 km. On this basis, a method using the average annual rainfall, GDP and population data are suggested to calculate the priority of radar coverage in blind areas and counties in Shaanxi Province. The findings of this study could provide a theoretical and technical support for the building of weather radar in the blind area of radar coverage in the future.
2023, 49(4):487-494.
DOI: 10.7519/j.issn.1000-0526.2022.112001
Abstract:
Rainfall attenuation to X-band weather radar measurement is significant, and can lead to the weakening of radar reflectivity factor and inaccuracy in quantitative applications. By using the Z-K〖KG-*4〗DP correction method, the data collected by the X-band dual-polarization Doppler weather radar at Pudong, Shanghai were tested. The specific scheme is as follows. When KDP≥0.3°·km-1, the value of KDP is used to correct the attenuation; when KDP < 0.3°·km-1, the empirical formula between A and Z is used to correct the attenuation. The convective precipitation case (17 September 2020) and the stable precipitation case (26 February 2021) were selected for the test. After attenuation correction and system bias correction, the results show that both the value and the spatial distribution of the X-band’s radar reflectivity factor are close to that of the S-band weather radar. Such Z-KDP method is effective to correct the attenuation from both convective rainfall and stable rainfall.
Rainfall attenuation to X-band weather radar measurement is significant, and can lead to the weakening of radar reflectivity factor and inaccuracy in quantitative applications. By using the Z-K〖KG-*4〗DP correction method, the data collected by the X-band dual-polarization Doppler weather radar at Pudong, Shanghai were tested. The specific scheme is as follows. When KDP≥0.3°·km-1, the value of KDP is used to correct the attenuation; when KDP < 0.3°·km-1, the empirical formula between A and Z is used to correct the attenuation. The convective precipitation case (17 September 2020) and the stable precipitation case (26 February 2021) were selected for the test. After attenuation correction and system bias correction, the results show that both the value and the spatial distribution of the X-band’s radar reflectivity factor are close to that of the S-band weather radar. Such Z-KDP method is effective to correct the attenuation from both convective rainfall and stable rainfall.
2023, 49(4):495-505.
DOI: 10.7519/j.issn.1000-0526.2023.032701
Abstract:
In boreal autumn (September-October-November, SON) of 2022, the climate of China is characterised as “warmer and drier” than normal, and most of southern part has experienced persistent high temperature and drought. The average autumn temperature in China is ranked the highest since 1961. And the intraseasonal variability of precipitation is significant, with less rainfall in most of China in September, less in the south and north of China and more in Central China in October, more in central-eastern China and less in the west of China in November. From September to October, the northerly wind anomaly is strong over southern China with worse than normal moisture transport from South China Sea and Northwesten Pacific. The West Pacific subtropical high (WPSH) is stronger, larger and more westward than normal. Descending motion is dominant over southern China leading to less rainfall and high temperature, and thus drought condition. The influence of tropical sea surface temperature (SST) forcing shows that the warmer warm-pool in Indo-Pacific, colder SST in tropical East-Central Pacific and west equatorial Indian, correspond to the significant coupling characteristics between the zonal monsoon circulation over the equatorial Indian Ocean and the Walker circulation over the Pacific Ocean, which further play important roles in modulating drought over most of southern China. The SST anomalies in equatorial Indian and Pacific are coupled with the air-sea gearing between Indian summer monsoon and Walker circulation in Pacific. The tropical Indian Ocean dipole (TIOD) has significant influence of precipitation over the western part of Jiangnan and the southeastern part of Southwest China, while El Ni〖AKn~D〗o-Southern Oscillation (ENSO) mainly affects most of Jiangnan and northern South China. Therefore, the heavy drought over southern China in autumn 2022 is modulated by both the TIOD negative mode and La Ni〖AKn~D〗a state.
In boreal autumn (September-October-November, SON) of 2022, the climate of China is characterised as “warmer and drier” than normal, and most of southern part has experienced persistent high temperature and drought. The average autumn temperature in China is ranked the highest since 1961. And the intraseasonal variability of precipitation is significant, with less rainfall in most of China in September, less in the south and north of China and more in Central China in October, more in central-eastern China and less in the west of China in November. From September to October, the northerly wind anomaly is strong over southern China with worse than normal moisture transport from South China Sea and Northwesten Pacific. The West Pacific subtropical high (WPSH) is stronger, larger and more westward than normal. Descending motion is dominant over southern China leading to less rainfall and high temperature, and thus drought condition. The influence of tropical sea surface temperature (SST) forcing shows that the warmer warm-pool in Indo-Pacific, colder SST in tropical East-Central Pacific and west equatorial Indian, correspond to the significant coupling characteristics between the zonal monsoon circulation over the equatorial Indian Ocean and the Walker circulation over the Pacific Ocean, which further play important roles in modulating drought over most of southern China. The SST anomalies in equatorial Indian and Pacific are coupled with the air-sea gearing between Indian summer monsoon and Walker circulation in Pacific. The tropical Indian Ocean dipole (TIOD) has significant influence of precipitation over the western part of Jiangnan and the southeastern part of Southwest China, while El Ni〖AKn~D〗o-Southern Oscillation (ENSO) mainly affects most of Jiangnan and northern South China. Therefore, the heavy drought over southern China in autumn 2022 is modulated by both the TIOD negative mode and La Ni〖AKn~D〗a state.
2023, 49(4):506-512.
DOI: 10.7519/j.issn.1000-0526.2023.030701
Abstract:
The main characteristics of the general atmospheric circulation in January 2023 are as follows. There were two polar vortex centers in the Northern Hemisphere. The Northeast Asia low vortex was stronger. The East Asian major trough was more eastward than normal, and the south branch trough was weaker. Meanwhile, the monthly mean precipitation over China was 8.8 mm, which is 38% less than normal (14.3 mm). The monthly mean temperature was -4.4℃, 0.4℃ higher than normal (-4.8℃). There were three cold air processes in the middle and late of the month, and the temperature changed from abnormally warm in the early 10 days to generally cold in the late 10 days. In addition, extremely cold weather appeared in Heilongjiang Province with the lowest temperature in Mohe declining to as low as -53℃, setting a new record of the lowest temperature in China. From 13 to 16 January, the first largescale cold wave of this year occurred, characterised by severe cooling, strong winds and wide range of rain and snow. Xinjiang, Shaanxi, Shanxi, Henan and other provinces experienced heavy snow or blizzard. Besides, the first dust weather affected northern China, and in the first dekad, the atmospheric diffusion and wet clearance conditions were not good so that persistent haze weather stayed for days.
The main characteristics of the general atmospheric circulation in January 2023 are as follows. There were two polar vortex centers in the Northern Hemisphere. The Northeast Asia low vortex was stronger. The East Asian major trough was more eastward than normal, and the south branch trough was weaker. Meanwhile, the monthly mean precipitation over China was 8.8 mm, which is 38% less than normal (14.3 mm). The monthly mean temperature was -4.4℃, 0.4℃ higher than normal (-4.8℃). There were three cold air processes in the middle and late of the month, and the temperature changed from abnormally warm in the early 10 days to generally cold in the late 10 days. In addition, extremely cold weather appeared in Heilongjiang Province with the lowest temperature in Mohe declining to as low as -53℃, setting a new record of the lowest temperature in China. From 13 to 16 January, the first largescale cold wave of this year occurred, characterised by severe cooling, strong winds and wide range of rain and snow. Xinjiang, Shaanxi, Shanxi, Henan and other provinces experienced heavy snow or blizzard. Besides, the first dust weather affected northern China, and in the first dekad, the atmospheric diffusion and wet clearance conditions were not good so that persistent haze weather stayed for days.
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