Volume 50,Issue 6,2022 Table of Contents
2022, 50(6):751-758.
DOI: 10.19517/j.1671-6345.20210503
Abstract:
Hangzhou Xiasha SA weather radar adds sophisticated detection technology based on the dual polarization upgrade. In order to further improve the accuracy of radar quantitative precipitation estimation, this paper, referring to the hourly rain gauge data, corrects the radar precipitation estimation algorithm model. It establishes a model based on the real-time QPE rain intensity correction method for minute-level rain gauge data (QPE-ADJUST method for short) and uses rain gauge data to correct the radar’s QPE data body-by-body scan in real-time. Accumulatively complete 1-hour and 3-hours precipitation estimation products, which improves the radar precipitation estimation accuracy. Through the evaluation of radar products and automatic station data, the precipitation estimation effect of the QPE-ADJUST method is statistically analyzed from three aspects: the precipitation estimation algorithm, the influence of the radar resolution and the influence of the body scan cycle speed. The results show that the QPE-ADJUST method is better in the temporal and spatial distribution of precipitation than other algorithms under the conditions of high radar resolution and fast body scanning period, and the reduced error of radar hourly quantitative precipitation estimation from 50% to 20%, which has high estimation accuracy and stability, and operation application value.
Hangzhou Xiasha SA weather radar adds sophisticated detection technology based on the dual polarization upgrade. In order to further improve the accuracy of radar quantitative precipitation estimation, this paper, referring to the hourly rain gauge data, corrects the radar precipitation estimation algorithm model. It establishes a model based on the real-time QPE rain intensity correction method for minute-level rain gauge data (QPE-ADJUST method for short) and uses rain gauge data to correct the radar’s QPE data body-by-body scan in real-time. Accumulatively complete 1-hour and 3-hours precipitation estimation products, which improves the radar precipitation estimation accuracy. Through the evaluation of radar products and automatic station data, the precipitation estimation effect of the QPE-ADJUST method is statistically analyzed from three aspects: the precipitation estimation algorithm, the influence of the radar resolution and the influence of the body scan cycle speed. The results show that the QPE-ADJUST method is better in the temporal and spatial distribution of precipitation than other algorithms under the conditions of high radar resolution and fast body scanning period, and the reduced error of radar hourly quantitative precipitation estimation from 50% to 20%, which has high estimation accuracy and stability, and operation application value.
2022, 50(6):759-765.
DOI: 10.19517/j.1671-6345.20210507
Abstract:
Due to the ageing of the hydrophobic layer of the radome, the ground-based microwave radiometer is prone to form water accumulation on the radome during rainy weather detection, resulting in unstable detection performance, which is one of the key problems affecting its wide application in scientific research and business. This study uses the actual observation data of 6 microwave radiometers in Beijing during the rainfall period from 2017 to 2018. It analyzes the influence of the ageing of the hydrophobic layer of the radome on the observed brightness temperature of the microwave radiometer. The results show that increasing with the use time, especially after three months, the magnitude of the increase in the brightness temperature during precipitation becomes significantly larger, and the duration of the increase in the brightness temperature after the precipitation also increases. At the same time, the rain test of the radome is carried out using the microwave radiometer in Beijing Nanjiao Station. The results show that after the radome is used for 40 days, with the pollution and ageing of the radome, the observed brightness temperature increases in a jumping manner during rain, and the brightness temperature is still high after the rain, even after more than 2 hours. Therefore, in order to improve the availability of microwave radiometer observation data, it is recommended to replace the radome every quarter during actual use. For heavily polluted areas such as Beijing, Tianjin and Hebei, the replacement frequency can be appropriately increased according to the actual situation.
Due to the ageing of the hydrophobic layer of the radome, the ground-based microwave radiometer is prone to form water accumulation on the radome during rainy weather detection, resulting in unstable detection performance, which is one of the key problems affecting its wide application in scientific research and business. This study uses the actual observation data of 6 microwave radiometers in Beijing during the rainfall period from 2017 to 2018. It analyzes the influence of the ageing of the hydrophobic layer of the radome on the observed brightness temperature of the microwave radiometer. The results show that increasing with the use time, especially after three months, the magnitude of the increase in the brightness temperature during precipitation becomes significantly larger, and the duration of the increase in the brightness temperature after the precipitation also increases. At the same time, the rain test of the radome is carried out using the microwave radiometer in Beijing Nanjiao Station. The results show that after the radome is used for 40 days, with the pollution and ageing of the radome, the observed brightness temperature increases in a jumping manner during rain, and the brightness temperature is still high after the rain, even after more than 2 hours. Therefore, in order to improve the availability of microwave radiometer observation data, it is recommended to replace the radome every quarter during actual use. For heavily polluted areas such as Beijing, Tianjin and Hebei, the replacement frequency can be appropriately increased according to the actual situation.
2022, 50(6):766-775.
DOI: 10.19517/j.1671-6345.20210530
Abstract:
Numerical model has become the main direction of the development of weather forecasting. The numerical model calculation produces a variety of meteorological grid products. Meteorological grid products have the characteristics of a large amount of data, fast update frequency and strong professionalism. They need to be processed with the help of professional tool software, which can not meet the needs of enterprises and social users, and the application scope is greatly limited. Facing the contradiction between the specialization of meteorological grid products and the simplification of meteorological data application requirements, this paper proposes to apply WebGIS technology to meteorological grid products and services by means of Internet service, discrete processing of grid data and spatial management. Users only need to carry out simple text retrieval or GIS graphics retrieval on the client, and the system can realize the fine extraction of effective data in meteorological grid products and finally realize the fine service. This data processing method proposed in this paper plays a guiding role in applying meteorological grid products in different industries.
Numerical model has become the main direction of the development of weather forecasting. The numerical model calculation produces a variety of meteorological grid products. Meteorological grid products have the characteristics of a large amount of data, fast update frequency and strong professionalism. They need to be processed with the help of professional tool software, which can not meet the needs of enterprises and social users, and the application scope is greatly limited. Facing the contradiction between the specialization of meteorological grid products and the simplification of meteorological data application requirements, this paper proposes to apply WebGIS technology to meteorological grid products and services by means of Internet service, discrete processing of grid data and spatial management. Users only need to carry out simple text retrieval or GIS graphics retrieval on the client, and the system can realize the fine extraction of effective data in meteorological grid products and finally realize the fine service. This data processing method proposed in this paper plays a guiding role in applying meteorological grid products in different industries.
2022, 50(6):776-782.
DOI: 10.19517/j.1671-6345.20220018
Abstract:
The overall architecture and operation flow of the high-frequency refined meteorological grid data real-time processing system are designed and implemented taking high-frequency massive meteorological grid data as the research object, focusing on the low data processing efficiency of the traditional real-time processing system. Based on the analysis of the characteristics of massive high-frequency meteorological grid data, a distributed storage model is designed and implemented to meet the needs of the meteorological service. Multi-channel dynamic sensing technology is used to implement dynamic multi-channel file processing and fast sensing triggers of file arrival. The fast data block positioning algorithm based on accurate location addressing is implemented using real-time data fast processing technology to realize the accurate positioning of data blocks. The data on-demand real-time interception technology is used to realize the interception algorithm, which can intercept the data on-demand, and then realize the data ondemand extraction. The practical application shows that the system can effectively improve the real-time processing efficiency of unstructured meteorological data.
The overall architecture and operation flow of the high-frequency refined meteorological grid data real-time processing system are designed and implemented taking high-frequency massive meteorological grid data as the research object, focusing on the low data processing efficiency of the traditional real-time processing system. Based on the analysis of the characteristics of massive high-frequency meteorological grid data, a distributed storage model is designed and implemented to meet the needs of the meteorological service. Multi-channel dynamic sensing technology is used to implement dynamic multi-channel file processing and fast sensing triggers of file arrival. The fast data block positioning algorithm based on accurate location addressing is implemented using real-time data fast processing technology to realize the accurate positioning of data blocks. The data on-demand real-time interception technology is used to realize the interception algorithm, which can intercept the data on-demand, and then realize the data ondemand extraction. The practical application shows that the system can effectively improve the real-time processing efficiency of unstructured meteorological data.
2022, 50(6):783-792.
DOI: 10.19517/j.1671-6345.20210525
Abstract:
Based on stational observations and retrieved sea fog products by the Kuihua-8 satellite from January to June 2020, this paper have evaluated the performance of the independent researched and developed GRAPES-TYM model to forecast sea fogs over the Eastern China Seas. Results indicate that sea fog forecasting for the Eastern China Seas by GRAPES-TYM is relatively promising, for TS of 48 h and 72 h is 0.40 and 0.36, respectively. Especially the model shows the best ability to predict the Yellow Sea sea fogs with TS of most stations in the sea area between 34°N and 37°N higher than 0.50. The further assessment indicates that the fog area forecast under the uniformed pressure field is more accurate, with an average CSI of 0.35. The model often gives false alarms when under the back of the cyclone. It appears that deviations between observed and forecasted surface air temperature and relative humidity are relative to locality. The hit rate and TS are lower with underestimating relative humidity, and vice versa. Our results also suggest that for successful cases, the model accurately captures the near-surface meteorological conditions, which are favourable for fog formation. In contrast, the model shows a large error in near-surface relative humidity and temperature for false alarm cases compared to successful cases. The predicted near-surface wind direction is often in the southeast of the actual wind direction, which is prone to introduce cold bias and overprediction of relative humidity. False favourable temperature and humidity conditions lead to false sea fog alarms.
Based on stational observations and retrieved sea fog products by the Kuihua-8 satellite from January to June 2020, this paper have evaluated the performance of the independent researched and developed GRAPES-TYM model to forecast sea fogs over the Eastern China Seas. Results indicate that sea fog forecasting for the Eastern China Seas by GRAPES-TYM is relatively promising, for TS of 48 h and 72 h is 0.40 and 0.36, respectively. Especially the model shows the best ability to predict the Yellow Sea sea fogs with TS of most stations in the sea area between 34°N and 37°N higher than 0.50. The further assessment indicates that the fog area forecast under the uniformed pressure field is more accurate, with an average CSI of 0.35. The model often gives false alarms when under the back of the cyclone. It appears that deviations between observed and forecasted surface air temperature and relative humidity are relative to locality. The hit rate and TS are lower with underestimating relative humidity, and vice versa. Our results also suggest that for successful cases, the model accurately captures the near-surface meteorological conditions, which are favourable for fog formation. In contrast, the model shows a large error in near-surface relative humidity and temperature for false alarm cases compared to successful cases. The predicted near-surface wind direction is often in the southeast of the actual wind direction, which is prone to introduce cold bias and overprediction of relative humidity. False favourable temperature and humidity conditions lead to false sea fog alarms.
2022, 50(6):793-801.
DOI: 10.19517/j.1671-6345.20220075
Abstract:
The key roles of the Marine Atmospheric Boundary Layer Height (MABLH) in pollution, climate, and model forecasting have long been recognized. The paper describes the vertical distribution of water vapour, heat, and matter in the atmosphere over the ocean. However, the observed MABLH has rarely been used to evaluate numerical weather prediction models. Therefore, we compare the temporal and spatial characteristics of the bias in the MABLH in the ocean predicted by the CMA-GFS model with Global Positioning System occultation data from 2019 to 2020. We find that: (1) The MABLH predicted by the CMA-GFS global model in the Western Pacific, South Pacific, and South Atlantic is reasonable. (2) There is an overestimation of the MABLH over the Intertropical Convergence Zone (ITCZ) and the South Pacific Convergence Zone (SPCZ). Preliminary analyses indicate that it may be due to the overestimation of the Lifting Condensation Level (LCL) by the Tropical deep Convection of the CMA-GFS model. (3) MABLH in the Southern Hemisphere Cumulus Region is underestimated by the CMA-GFS model, which may be due to inaccurate physical processes in the boundary layer parameterization. (4) There is an overestimation of the MABLH in a cloudy atmosphere, and the average bias is 200 m. The model forecast is more reasonable in a clear atmosphere, and ERA5 has a similar bias.
The key roles of the Marine Atmospheric Boundary Layer Height (MABLH) in pollution, climate, and model forecasting have long been recognized. The paper describes the vertical distribution of water vapour, heat, and matter in the atmosphere over the ocean. However, the observed MABLH has rarely been used to evaluate numerical weather prediction models. Therefore, we compare the temporal and spatial characteristics of the bias in the MABLH in the ocean predicted by the CMA-GFS model with Global Positioning System occultation data from 2019 to 2020. We find that: (1) The MABLH predicted by the CMA-GFS global model in the Western Pacific, South Pacific, and South Atlantic is reasonable. (2) There is an overestimation of the MABLH over the Intertropical Convergence Zone (ITCZ) and the South Pacific Convergence Zone (SPCZ). Preliminary analyses indicate that it may be due to the overestimation of the Lifting Condensation Level (LCL) by the Tropical deep Convection of the CMA-GFS model. (3) MABLH in the Southern Hemisphere Cumulus Region is underestimated by the CMA-GFS model, which may be due to inaccurate physical processes in the boundary layer parameterization. (4) There is an overestimation of the MABLH in a cloudy atmosphere, and the average bias is 200 m. The model forecast is more reasonable in a clear atmosphere, and ERA5 has a similar bias.
2022, 50(6):802-811.
DOI: 10.19517/j.1671-6345.20220012
Abstract:
Based on the regional high-temperature process’s classification standards and by using the daily maximum temperature data, the regional high-temperature events in Shandong Province are objectively identified. The spatio-temporal distribution and variation characteristics of regional high-temperature events and their response to climate warming are also analyzed. The results show that there are 154 regional high-temperature events in Shandong Province from 1961 to 2020, with an average of about 2.6 times per year. These events, in general, occur from June to July. Over the space, regional high-temperature events are mainly distributed in the western region of Shandong Province and less in the mountainous and coastal areas. There are obvious inter-annual and inter-decadal changes in the occurence frequence of regional high-temperature events, with a shift from a downtrend to an uptrend. The occurence frequence of regional high-temperature events decrease significantly from the 1960s to the 1980s and increase after the mid-1990s, with a significant increase in the 21st century. These events’ duration, region and intensity also increase and enhance significantly in the 21st century. Regional high-temperature events have a significant response to climate warming. With the intensification of warming, the annual latest occurrence time of regional high temperature is obviously delayed. Regional hightemperature events become more frequent, longer and stronger, with a larger influence range. And the longer and stronger regional high-temperature events are also more likely.
Based on the regional high-temperature process’s classification standards and by using the daily maximum temperature data, the regional high-temperature events in Shandong Province are objectively identified. The spatio-temporal distribution and variation characteristics of regional high-temperature events and their response to climate warming are also analyzed. The results show that there are 154 regional high-temperature events in Shandong Province from 1961 to 2020, with an average of about 2.6 times per year. These events, in general, occur from June to July. Over the space, regional high-temperature events are mainly distributed in the western region of Shandong Province and less in the mountainous and coastal areas. There are obvious inter-annual and inter-decadal changes in the occurence frequence of regional high-temperature events, with a shift from a downtrend to an uptrend. The occurence frequence of regional high-temperature events decrease significantly from the 1960s to the 1980s and increase after the mid-1990s, with a significant increase in the 21st century. These events’ duration, region and intensity also increase and enhance significantly in the 21st century. Regional high-temperature events have a significant response to climate warming. With the intensification of warming, the annual latest occurrence time of regional high temperature is obviously delayed. Regional hightemperature events become more frequent, longer and stronger, with a larger influence range. And the longer and stronger regional high-temperature events are also more likely.
2022, 50(6):812-821.
DOI: 10.19517/j.1671-6345.20210387
Abstract:
The characteristics and mechanisms of typhoon rainstorms in the Tianmu Mountain area are researched in this paper based on the automatic weather station data and ERA5 analysis dataset from classification, rainfall distribution, weather system and topography conditions during the process. The results show that: (1) The rainfall in the Tianmu Mountain area has been more in the northeast and northwest parts and less in the south part as a whole, and concentrates in the north of East Tianmu Mountain and Western Zhejiang Tianchi. (2) When the upper-level trough is the northwest-southeast type, the cold air behind the trough invades from the northwest to the south side of the typhoon in a cyclonic manner. It encircles the centre of the typhoon in a semi-encircling shape, which makes the typhoon appear an obvious relative warm centre again. It is conducive to the excitation of cyclonic vorticity and the enhancement of rainfall. (3) For the Tianmu Mountain area, the most favourable condition for triggering convective weather is the weak cold air with an intensity of 2 ℃, which intrudes into the bottom of the warm and humid air along the topography and makes the warm and humid airflow rise. (4) Affected by the windward slope effect, when the northwest wind in Western Zhejiang Tianchi has the most obvious increase in precipitation. The topography of East Tianmu Mountain is the northeastsouthwest valley type. The main reasons for the increase in precipitation are the windward slope effect and narrow tube effect, and the convergence line forms in front of the mountain due to the flow around and rebound when the airflow meets the mountain. The northward-moving typhoon is easy to induce the rainfall centre in the north of the Tianmu Mountain area, while the westwardmoving typhoon rainfall centre is in the east of the Tianmu Mountain area.
The characteristics and mechanisms of typhoon rainstorms in the Tianmu Mountain area are researched in this paper based on the automatic weather station data and ERA5 analysis dataset from classification, rainfall distribution, weather system and topography conditions during the process. The results show that: (1) The rainfall in the Tianmu Mountain area has been more in the northeast and northwest parts and less in the south part as a whole, and concentrates in the north of East Tianmu Mountain and Western Zhejiang Tianchi. (2) When the upper-level trough is the northwest-southeast type, the cold air behind the trough invades from the northwest to the south side of the typhoon in a cyclonic manner. It encircles the centre of the typhoon in a semi-encircling shape, which makes the typhoon appear an obvious relative warm centre again. It is conducive to the excitation of cyclonic vorticity and the enhancement of rainfall. (3) For the Tianmu Mountain area, the most favourable condition for triggering convective weather is the weak cold air with an intensity of 2 ℃, which intrudes into the bottom of the warm and humid air along the topography and makes the warm and humid airflow rise. (4) Affected by the windward slope effect, when the northwest wind in Western Zhejiang Tianchi has the most obvious increase in precipitation. The topography of East Tianmu Mountain is the northeastsouthwest valley type. The main reasons for the increase in precipitation are the windward slope effect and narrow tube effect, and the convergence line forms in front of the mountain due to the flow around and rebound when the airflow meets the mountain. The northward-moving typhoon is easy to induce the rainfall centre in the north of the Tianmu Mountain area, while the westwardmoving typhoon rainfall centre is in the east of the Tianmu Mountain area.
2022, 50(6):822-829.
DOI: 10.19517/j.1671-6345.20210518
Abstract:
Based on the AWS (Automatic Weather Stations) data, the sounding data of two arenas (Genting Snow Park and Guyangshu Cluster) in the Zhangjiakou competition area of the 2022 Beijing Winter Olympic Games, and the ECMWF ERA5 global 0.25°×0.25° reanalysis data in the winter of 2019 and 2020 (November to next February), the characteristics of the temporal and spatial distribution of snowfall and the circulation patterns in the Zhangjiakou competition area are analyzed. This study isolates the distinct synoptic types of snowfall into three patterns: low vortex-cyclone, cold front, and northwest airflow. The amount and duration of snowfall are distinct from one synoptic pattern to another. The low vortex-cyclone pattern causes the heaviest snowfall and the longest duration among the three patterns. The snowfall amount in Genting Snow Park is 16.9% larger than that in Guyangshu Cluster. The mean snowfall amount caused by the cold front pattern takes second place. Under this condition, the snowfall amount in Genting Snow Park is 44.4% larger than that in Guyangshu Cluster. The northwest airflow pattern results in the least snowfall amount and shortest duration, but the largest difference between the two clusters is that the snowfall amount in Genting Snow Park is 140% larger than that in Guyangshu Cluster.
Based on the AWS (Automatic Weather Stations) data, the sounding data of two arenas (Genting Snow Park and Guyangshu Cluster) in the Zhangjiakou competition area of the 2022 Beijing Winter Olympic Games, and the ECMWF ERA5 global 0.25°×0.25° reanalysis data in the winter of 2019 and 2020 (November to next February), the characteristics of the temporal and spatial distribution of snowfall and the circulation patterns in the Zhangjiakou competition area are analyzed. This study isolates the distinct synoptic types of snowfall into three patterns: low vortex-cyclone, cold front, and northwest airflow. The amount and duration of snowfall are distinct from one synoptic pattern to another. The low vortex-cyclone pattern causes the heaviest snowfall and the longest duration among the three patterns. The snowfall amount in Genting Snow Park is 16.9% larger than that in Guyangshu Cluster. The mean snowfall amount caused by the cold front pattern takes second place. Under this condition, the snowfall amount in Genting Snow Park is 44.4% larger than that in Guyangshu Cluster. The northwest airflow pattern results in the least snowfall amount and shortest duration, but the largest difference between the two clusters is that the snowfall amount in Genting Snow Park is 140% larger than that in Guyangshu Cluster.
2022, 50(6):830-841.
DOI: 10.19517/j.1671-6345.20220040
Abstract:
Using Qingdao dual-polarization CINRAD/SA data, sounding and automatic meteorological station data, the polarimetric signatures of a supercell storm occurred in Gaomi, Shandong Province on 3 August 2020 are analyzed. The results show that: (1) The key environmental factors to the development and maintenance of the Gaomi supercell were the strong CAPE, strong low-level vertical wind shear, 200 hPa strong divergence and high humidity. (2) The ZDR arcs and KDP high-value areas were important characteristics of the lower layer. The ZDR arcs matched the high-value region of reflectivity factor gradient on one side of the inflow and correspond to smaller KDP, which were caused by a few large particles. The KDP high-value area in the middle of the storm, corresponding to the smaller ZDR (1-3 dB), larger CC, caused by the high concentration of smaller particles, was the heavy rainfall area. (3) TheZDR ring around BWER, corresponding to smaller KDP, indicate that a small number of large droplets were distributed around BWER. The deep and wide ZDR and KDP columns above the BWER indicate that the higher concentration of large droplets was distributed above the BWER. (4) Abundant liquid particles under the -20 ℃ layer and abundant graupel and ice crystal particles above the -20 ℃ layer were the typical vertical characteristics of the microphysics of the Gaomi supercell.
Using Qingdao dual-polarization CINRAD/SA data, sounding and automatic meteorological station data, the polarimetric signatures of a supercell storm occurred in Gaomi, Shandong Province on 3 August 2020 are analyzed. The results show that: (1) The key environmental factors to the development and maintenance of the Gaomi supercell were the strong CAPE, strong low-level vertical wind shear, 200 hPa strong divergence and high humidity. (2) The ZDR arcs and KDP high-value areas were important characteristics of the lower layer. The ZDR arcs matched the high-value region of reflectivity factor gradient on one side of the inflow and correspond to smaller KDP, which were caused by a few large particles. The KDP high-value area in the middle of the storm, corresponding to the smaller ZDR (1-3 dB), larger CC, caused by the high concentration of smaller particles, was the heavy rainfall area. (3) TheZDR ring around BWER, corresponding to smaller KDP, indicate that a small number of large droplets were distributed around BWER. The deep and wide ZDR and KDP columns above the BWER indicate that the higher concentration of large droplets was distributed above the BWER. (4) Abundant liquid particles under the -20 ℃ layer and abundant graupel and ice crystal particles above the -20 ℃ layer were the typical vertical characteristics of the microphysics of the Gaomi supercell.
2022, 50(6):842-850.
DOI: 10.19517/j.1671-6345.20220064
Abstract:
Using the observation data of a certain wind farm in Gansu, an ultra short-term fast rolling wind speed forecast method is proposed based on the Long Short-Term Memory (LSTM) neural network model by evaluating the forecast accuracy under different input variables and model time window lengths. The results show that the change in wind speed itself plays a leading role in the ultra short-term wind speed forecast. Better simulation results can be obtained when input variables only include the wind speed data at different altitudes. By evaluating the impact of time window lengthL of LSTM on simulation capability, it is found that when L≤24 h, the model works well, which means that the change of ultra short-term wind speed is mainly related to the change of its own near time. When L>24 h, the simulation effect of all schemes decreases, which means overly long L reduces the simulation accuracy. By evaluating the wind speed forecast capability of LSTM in the next 4 hours, it is found that the simulation accuracy decreases gradually while the prediction time increases. The forecast ability is ideal in the next 2 hours, and the RMSE is less than 2 m·s-1. LSTM proves economical and practical with low requirements for computing resources and has high application potential in operational wind speed forecast practice.
Using the observation data of a certain wind farm in Gansu, an ultra short-term fast rolling wind speed forecast method is proposed based on the Long Short-Term Memory (LSTM) neural network model by evaluating the forecast accuracy under different input variables and model time window lengths. The results show that the change in wind speed itself plays a leading role in the ultra short-term wind speed forecast. Better simulation results can be obtained when input variables only include the wind speed data at different altitudes. By evaluating the impact of time window lengthL of LSTM on simulation capability, it is found that when L≤24 h, the model works well, which means that the change of ultra short-term wind speed is mainly related to the change of its own near time. When L>24 h, the simulation effect of all schemes decreases, which means overly long L reduces the simulation accuracy. By evaluating the wind speed forecast capability of LSTM in the next 4 hours, it is found that the simulation accuracy decreases gradually while the prediction time increases. The forecast ability is ideal in the next 2 hours, and the RMSE is less than 2 m·s-1. LSTM proves economical and practical with low requirements for computing resources and has high application potential in operational wind speed forecast practice.
2022, 50(6):851-858.
DOI: 10.19517/j.1671-6345.20210312
Abstract:
Accurate estimation of wind speed is essential for many meteorological applications. A novel shortterm wind speed prediction method of the BLSTM-TRA model is proposed by combining the Transformer model and LSTM model. Six stations along the southern coast of the Shandong Peninsula are selected as the research area. After comparing and analyzing the 6 h prediction results of the 2018 ECMWF model, the following conclusions are drawn: The BLSTM-TRA multi-step prediction model can reduce the error of wind speed prediction. Compared with the ECMWF prediction model results, the RMSE and MAE of BLSTM-TRA are decreased by 58.9% and 63.2% on average. The analysis of wind speed error and wind statistical process shows that the BLSTM-TRA model has a certain anti-interference ability and can capture the sensitive information of short-term wind, etc., which is obviously better than the ECWMF model and traditional LSTM model for wind prediction.
Accurate estimation of wind speed is essential for many meteorological applications. A novel shortterm wind speed prediction method of the BLSTM-TRA model is proposed by combining the Transformer model and LSTM model. Six stations along the southern coast of the Shandong Peninsula are selected as the research area. After comparing and analyzing the 6 h prediction results of the 2018 ECMWF model, the following conclusions are drawn: The BLSTM-TRA multi-step prediction model can reduce the error of wind speed prediction. Compared with the ECMWF prediction model results, the RMSE and MAE of BLSTM-TRA are decreased by 58.9% and 63.2% on average. The analysis of wind speed error and wind statistical process shows that the BLSTM-TRA model has a certain anti-interference ability and can capture the sensitive information of short-term wind, etc., which is obviously better than the ECWMF model and traditional LSTM model for wind prediction.
2022, 50(6):859-869.
DOI: 10.19517/j.1671-6345.20220058
Abstract:
Currently, most of the researches based on dualpolarization weather radar focus on the way to identify the various phases of particles and detect the vertical structure of the clouds, and the researches on the identification and characteristics of ZDR column are few. In order to strengthen the application of dual-polarization radar in Hainan, the identification algorithm of the ZDR column based on the dual-polarization radar (2020－2021) is proposed according to the characteristics of convective cloud systems on the Hainan Island. Based on the method, combined with multi-sources data, two convective weather processes in Hainan are analyzed and studied to verify the ZDR column. The results show that the algorithm can identify the ZDR column on the Hainan Island; the algorithm could obtain the spatial distribution of the ZDR column in real-time to analyze the convective weather processes, weather modification and short-term disaster warning. The ZDR column is usually deep in the early and middle stages of the convective clouds, and the maximum can reach 3 to 5 km above the 0 ℃ layer; the ZDR column with deeper spatial distribution is more likely to appear in the direction of the convective cloud movement. The position of the leading edge has a corresponding relationship with the area with large radar reflectivity (≥50 dBz), which continues to deepen with the evolution of the clouds. The average ZDR column depth variation trend has a weak correlation with the radar echo top height and the vertical accumulated liquid water content. The changes of the radar echo top height and the vertical accumulated liquid water content usually lag the ZDR column depth (12 to 15 min).
Currently, most of the researches based on dualpolarization weather radar focus on the way to identify the various phases of particles and detect the vertical structure of the clouds, and the researches on the identification and characteristics of ZDR column are few. In order to strengthen the application of dual-polarization radar in Hainan, the identification algorithm of the ZDR column based on the dual-polarization radar (2020－2021) is proposed according to the characteristics of convective cloud systems on the Hainan Island. Based on the method, combined with multi-sources data, two convective weather processes in Hainan are analyzed and studied to verify the ZDR column. The results show that the algorithm can identify the ZDR column on the Hainan Island; the algorithm could obtain the spatial distribution of the ZDR column in real-time to analyze the convective weather processes, weather modification and short-term disaster warning. The ZDR column is usually deep in the early and middle stages of the convective clouds, and the maximum can reach 3 to 5 km above the 0 ℃ layer; the ZDR column with deeper spatial distribution is more likely to appear in the direction of the convective cloud movement. The position of the leading edge has a corresponding relationship with the area with large radar reflectivity (≥50 dBz), which continues to deepen with the evolution of the clouds. The average ZDR column depth variation trend has a weak correlation with the radar echo top height and the vertical accumulated liquid water content. The changes of the radar echo top height and the vertical accumulated liquid water content usually lag the ZDR column depth (12 to 15 min).
14 Risk Zoning of Rainstorm Disaster along Shuohuang Railway Based on Meteorological Geography Method
2022, 50(6):870-877.
DOI: 10.19517/j.1671-6345.20210393
Abstract:
Based on the precipitation data of automatic weather stations along Shuohuang Railway from 2016 to 2020, combined with the geographical information and socioeconomic information of administrative districts and counties, the risk zoning model of Shuohuang Railway rainstorm disasters is constructed by using the Analytic Hierarchy Process (AHP), expert scoring method and weighted comprehensive evaluation method from four factors: the risk of rainstorm disaster, the sensitivity of disaster pregnant environment, the vulnerability of bearing body and the ability of disaster prevention and mitigation. The comprehensive risk zoning map of the rainstorm disaster on the Shuohuang Railway is drawn. The results show that: the rainstorm disaster risk along the Shuohuang Railway is divided into four grades: high, secondary high, medium and low, and the risk in the East is higher than that in the West. The four high-risk sections are basically consistent with the high-frequency rainstorm information collected in each work section along the Shuohuang Railway. The results will play a good role in decision-making on risk prevention.
Based on the precipitation data of automatic weather stations along Shuohuang Railway from 2016 to 2020, combined with the geographical information and socioeconomic information of administrative districts and counties, the risk zoning model of Shuohuang Railway rainstorm disasters is constructed by using the Analytic Hierarchy Process (AHP), expert scoring method and weighted comprehensive evaluation method from four factors: the risk of rainstorm disaster, the sensitivity of disaster pregnant environment, the vulnerability of bearing body and the ability of disaster prevention and mitigation. The comprehensive risk zoning map of the rainstorm disaster on the Shuohuang Railway is drawn. The results show that: the rainstorm disaster risk along the Shuohuang Railway is divided into four grades: high, secondary high, medium and low, and the risk in the East is higher than that in the West. The four high-risk sections are basically consistent with the high-frequency rainstorm information collected in each work section along the Shuohuang Railway. The results will play a good role in decision-making on risk prevention.
2022, 50(6):878-884.
DOI: 10.19517/j.1671-6345.20210519
Abstract:
Using the observation of CE-318 sunphotometer at Lhasa and QOMS_CAS stations in Tibet Plateau, the impact of biomass burning transportation on the aerosol optical radiation properties over the Tibet Plateau is studied during a case of April 2 to 5, 2012. Besides, the possible aerosol sources are analyzed with the satellite remote sensing products and backward trajectory model. The results show that the dominant aerosol types at Lhasa and QOMS_CAS stations changed to biomass-burning aerosol. The extinction of aerosol particles increased,AOD (Aerosol Optical Depth) increased, and the maximum AOD of Lhasa and QOMS_CAS sites were 0.4 and 0.29. Aerosol size decreased, EAE(Extinction Angstrom Exponent)>1.5, aerosol absorption increased, AAE (Absorption Angstrom Exponent) >1.3, and the volume concentration of fine mode particles increased. The peak radius of fine mode particles decreased. The aerosol direct radiation forcing shows that aerosol effect of cooling the top of the atmosphere and the surface at Lhasa and QOMS_CAS stations strengthened, and the effect of heating the atmosphere also strengthened. The possible sources of smoke aerosol were the transportation of biomass burning from Northeast India, Nepal and Bhutan in South Asia.
Using the observation of CE-318 sunphotometer at Lhasa and QOMS_CAS stations in Tibet Plateau, the impact of biomass burning transportation on the aerosol optical radiation properties over the Tibet Plateau is studied during a case of April 2 to 5, 2012. Besides, the possible aerosol sources are analyzed with the satellite remote sensing products and backward trajectory model. The results show that the dominant aerosol types at Lhasa and QOMS_CAS stations changed to biomass-burning aerosol. The extinction of aerosol particles increased,AOD (Aerosol Optical Depth) increased, and the maximum AOD of Lhasa and QOMS_CAS sites were 0.4 and 0.29. Aerosol size decreased, EAE(Extinction Angstrom Exponent)>1.5, aerosol absorption increased, AAE (Absorption Angstrom Exponent) >1.3, and the volume concentration of fine mode particles increased. The peak radius of fine mode particles decreased. The aerosol direct radiation forcing shows that aerosol effect of cooling the top of the atmosphere and the surface at Lhasa and QOMS_CAS stations strengthened, and the effect of heating the atmosphere also strengthened. The possible sources of smoke aerosol were the transportation of biomass burning from Northeast India, Nepal and Bhutan in South Asia.
2022, 50(6):885-890.
DOI: 10.19517/j.1671-6345.20210495
Abstract:
Taking advantage of the 67 national meteorological station data from 1971 to 2020, geographic information data and other literature review data, authors construct the index system of climatic suitability zoning of jasmine. According to the Analytic Hierarchy Process (AHP), the index weight value is calculated, and the climate suitability index of each station is calculated by the membership function and fuzzy comprehensive evaluation method. The weight superposition analysis obtains the climate suitability zoning of jasmine planting. The map of the suitability zoning of jasmine planting is drawn on the GIS platform with the aid of spatial analysis techniques. The results show that Fujian’s central and southern coastal areas are the most suitable planting area. The northern coastal and inland low-altitude areas are suitable planting areas. The distribution of sub-suitable planting areas is scattered and distributed in all cities of Fujian. The unsuitable planting areas are mainly distributed in high-altitude areas along the mountains. The zoning results are consistent with the existing planting areas by comparing the zoning results and the jasmine planting situation in Fujian over the years.
Taking advantage of the 67 national meteorological station data from 1971 to 2020, geographic information data and other literature review data, authors construct the index system of climatic suitability zoning of jasmine. According to the Analytic Hierarchy Process (AHP), the index weight value is calculated, and the climate suitability index of each station is calculated by the membership function and fuzzy comprehensive evaluation method. The weight superposition analysis obtains the climate suitability zoning of jasmine planting. The map of the suitability zoning of jasmine planting is drawn on the GIS platform with the aid of spatial analysis techniques. The results show that Fujian’s central and southern coastal areas are the most suitable planting area. The northern coastal and inland low-altitude areas are suitable planting areas. The distribution of sub-suitable planting areas is scattered and distributed in all cities of Fujian. The unsuitable planting areas are mainly distributed in high-altitude areas along the mountains. The zoning results are consistent with the existing planting areas by comparing the zoning results and the jasmine planting situation in Fujian over the years.
External LinksChina Meteorological AdministrationCMA Meteorological Observation CentreChinese Academy of Meteorological SciencesBeijing Meteorological ServiceNational Satellite Meteorological Center
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Supported by:Beijing E-Tiller Technology Development Co., Ltd.
Supported by:Beijing E-Tiller Technology Development Co., Ltd.