Due to global warming, extreme weather and climate events are becoming more frequent, highlighting the need to explore the changing characteristics of precipitation in China, including extreme precipitation. A cluster...Due to global warming, extreme weather and climate events are becoming more frequent, highlighting the need to explore the changing characteristics of precipitation in China, including extreme precipitation. A clustering algorithm was developed to classify summer(June, July, and August) daily precipitation in China from 1961 to 2020, considering spatial distribution, standard deviations, and frequency of extreme precipitation events. The results reveal six distinct precipitation climate zones, a classification that differs from previous divisions. While overall precipitation has decreased in most regions, the frequency of extreme precipitation events has increased across all clusters, indicating a shift in precipitation distribution patterns. Analysis shows that the weakened Lake Baikal blocking high and strengthened Mongolian cyclone influence the arid region in northwest China(Cluster 1), which is characterized by the lowest precipitation.The transition zone between the monsoon and arid region(Cluster 2) is affected by the Mongolian cyclone, water vapor transport from the Indian Ocean, and shifts in the monsoon boundary. Clusters 3 and 4 represent areas associated with advancement and retreat of the summer monsoon. In the Meiyu region, two distinct subregions have been identified exist.Cluster 4 is primarily influenced by the East Asia-Pacific wave train. Despite sharing similar climate drivers and proximity,Clusters 4 and 5 differ significantly due to topographic variations and disparate levels of urbanization. Cluster 5 exhibits a higher average precipitation, greater variability, and more frequent extreme events. Cluster 6 exhibits the highest overall precipitation in the coastal areas of Guangdong and Guangxi, where abundant water vapor contributes to a higher frequency of extreme precipitation. In addition, anthropogenic activities and urbanization significantly influence precipitation in Beijing-Tianjin-Hebei and Yangtze River Delta regions. This research proposes a precipitation classification scheme integrating multiple precipitation parameters, providing support for risk management and mitigation strategies in the face of increasing extreme precipitation events.展开更多
Accurate and fine-scale short-term precipitation forecasting is crucial for disaster prevention,mitigation,and socioeconomic development.Currently,the direct precipitation forecasts of numerical weather prediction oft...Accurate and fine-scale short-term precipitation forecasting is crucial for disaster prevention,mitigation,and socioeconomic development.Currently,the direct precipitation forecasts of numerical weather prediction often face great challenges and correction methods are still needed to further improve the forecast accuracy.By utilizing the 500-m resolution fusion precipitation data from the Rapid-refresh Integrated Seamless Ensemble(RISE)system in the Beijing-Tianjin-Hebei(BTH)region,this study proposes a new Segmented Classification and Regression machine learning model based on the extreme gradient boosting(XGBoost)algorithm,termed SCR-XGBoost,which can be applied to correct hourly precipitation forecasts in areas with a dense network of weather stations at lead times of 4-6 h.The performance of the model is evaluated according to six metrics:the accuracy(AC),mean absolute error(MAE),root mean square error(RMSE),correlation coefficient(CC),threat score(TS),and bias score(BS).The results indicate that,although the XGBoost algorithm is almost ineffective for directly forecasting precipitation,the SCR-XGBoost model can significantly improve the forecast performance compared with the original RISE forecast,and the segmented correction method for torrential rainfall(≥20 mm h^(-1))outperforms other precipitation grades,which can effectively alleviate the problem of false alarms in the RISE system for heavy rainfall and above(≥10 mm h^(-1)).The optimization rates after applying the SCR-XGBoost model correction in precipitation forecasts can be improved by 6.49%-23.21%in terms of RMSE and MAE reduction,and the CC and AC can be greatly improved by 35.38%-84.39%.Therefore,the SCR-XGBoost algorithm,which introduces precipitation grade classification and multi-layer piecewise machine learning corrections,can significantly improve the 4-6-h precipitation forecast skill,especially for heavy rainfall.The results of this study not only provide new insights for machine learning-based precipitation forecasting,but also help improve rainfall forecasts and the level of disaster prevention and reduction in the BTH region.展开更多
The characteristics of raindrop size distribution （DSD） over the Tibetan Plateau and southern China are studied in this paper, using the DSD data from April to August 2014 collected by HSC-PS32 disdrometers in Nagqu...The characteristics of raindrop size distribution （DSD） over the Tibetan Plateau and southern China are studied in this paper, using the DSD data from April to August 2014 collected by HSC-PS32 disdrometers in Nagqu and Yangjiang, com- prising a total of 9430 and 63661-rain raindrop spectra, respectively. The raindrop spectra, characteristics of parameter variations with rainfall rate, and the relationships between reflectivity factor （Z） and rainfall rate （R） are analyzed, as well as their DSD changes with precipitation type and rainfall rate. The results show that the average raindrop spectra appear to be one-peak curves, the number concentration for larger drops increase significantly with rainfall rate, and its value over southern China is much higher, especially in convective rain larger drops, especially for convective rain in southern China. Standardized Gamma distributions better describe DSD for All three Gamma parameters for stratiform precipitation over the Tibetan Plateau are much higher, while its shape parameter （,u） and mass-weighted mean diameter （Dm）, for convective precipitation, are less. In terms of parameter variation with rainfall rate, the normalized intercept parameter （Nw） over the Tibetan Plateau for stratiform rain increases with rainfall rate, which is opposite to the situation in convective rain. The/1 over the Tibetan Plateau for stratiform and convective precipitation types decreases with an increase in rainfall rate, which is opposite to the case for Dm variation. In Z-R relationships, like ＂Z = ARb＇＇, the coefficient A over the Tibetan Plateau is smaller, while its b is higher, when the rain type transfers from stratiform to convective ones. Furthermore, with an increase in rainfall rate, parameters A and b over southern China increase gradually, while A over the Tibetan Plateau decreases sub- stantially, which differs from the findings of previous studies. In terms of geographic location and climate over the Tibetan Plateau and southern China, the precipitation in the pre-flood seasons is dominated by strong convective rain, while weak convective rain occurs frequently in northern Tibet with lower humidity and higher altitude.展开更多
Based on observational precipitation at 63 stations in South China and NCEP NCAR reanalysis data during 1951 2010,a cluster analysis is performed to classify large-scale circulation patterns responsible for persistent...Based on observational precipitation at 63 stations in South China and NCEP NCAR reanalysis data during 1951 2010,a cluster analysis is performed to classify large-scale circulation patterns responsible for persistent precipitation extremes（PPEs） that are independent of the influence of tropical cyclones（TCs）.Conceptual schematics depicting configurations among planetary-scale systems at different levels are established for each type.The PPEs free from TCs account for 38.6%of total events,and they tend to occur during April August and October,with the highest frequency observed in June.Corresponding circulation patterns during June August can be mainly categorized into two types,i.e.,summer-Ⅰ type and summer-Ⅱtype.In summer-Ⅰ type,the South Asian high takes the form of a zonal-belt type.The axis of upstream westerly jets is northwest-oriented.At the middle level,the westerly jets at midlatitudes extend zonally.Along the southern edge of the westerly jet,synoptic eddies steer cold air to penetrate southward;the Bay of Bengal（BOB） trough is located to the north;a shallow trough resides over coastal areas of western South China;and an intensified western Pacific subtropical high（WPSH） extends westward.The anomalous moisture is mainly contributed by horizontal advection via southwesterlies around 20°N and southeasterlies from the southern flange of the WPSH.Moisture convergence maximizes in coastal regions of eastern South China,which is the very place recording extreme precipitation.In summer-Ⅱ type,the South Asian high behaves as a western-center type.The BOB trough is much deeper,accompanied by a cyclone to its north;and a lower-level trough appears in northwestern parts of South China.Different to summer-Ⅰ type,moisture transport via southwesterlies is mostly responsible for the anomalous moisture in this type.The moisture convergence zones cover Guangdong,Guangxi,and Hainan,matching well with the areas of flooding.It is these set combinations among different systems at different levels that trigger PPEs in South China.展开更多
基金National Natural Science Foundation of China(U2442202, 42274217, 62441501)Key Innovation Team of China Meteorological Administration (CMA2024ZD01)Scientific Research Foundation of CUIT (376278, KYTZ202158)。
文摘Due to global warming, extreme weather and climate events are becoming more frequent, highlighting the need to explore the changing characteristics of precipitation in China, including extreme precipitation. A clustering algorithm was developed to classify summer(June, July, and August) daily precipitation in China from 1961 to 2020, considering spatial distribution, standard deviations, and frequency of extreme precipitation events. The results reveal six distinct precipitation climate zones, a classification that differs from previous divisions. While overall precipitation has decreased in most regions, the frequency of extreme precipitation events has increased across all clusters, indicating a shift in precipitation distribution patterns. Analysis shows that the weakened Lake Baikal blocking high and strengthened Mongolian cyclone influence the arid region in northwest China(Cluster 1), which is characterized by the lowest precipitation.The transition zone between the monsoon and arid region(Cluster 2) is affected by the Mongolian cyclone, water vapor transport from the Indian Ocean, and shifts in the monsoon boundary. Clusters 3 and 4 represent areas associated with advancement and retreat of the summer monsoon. In the Meiyu region, two distinct subregions have been identified exist.Cluster 4 is primarily influenced by the East Asia-Pacific wave train. Despite sharing similar climate drivers and proximity,Clusters 4 and 5 differ significantly due to topographic variations and disparate levels of urbanization. Cluster 5 exhibits a higher average precipitation, greater variability, and more frequent extreme events. Cluster 6 exhibits the highest overall precipitation in the coastal areas of Guangdong and Guangxi, where abundant water vapor contributes to a higher frequency of extreme precipitation. In addition, anthropogenic activities and urbanization significantly influence precipitation in Beijing-Tianjin-Hebei and Yangtze River Delta regions. This research proposes a precipitation classification scheme integrating multiple precipitation parameters, providing support for risk management and mitigation strategies in the face of increasing extreme precipitation events.
基金Supported by the National Natural Science Foundation of China(42275012)National Key Research and Development Program of China(2022YFC3004103)+1 种基金Beijing Municipal Science and Technology Project(Z221100005222012)Key Innovation Team Fund of China Meteorological Administration(CMA2022ZD07).
文摘Accurate and fine-scale short-term precipitation forecasting is crucial for disaster prevention,mitigation,and socioeconomic development.Currently,the direct precipitation forecasts of numerical weather prediction often face great challenges and correction methods are still needed to further improve the forecast accuracy.By utilizing the 500-m resolution fusion precipitation data from the Rapid-refresh Integrated Seamless Ensemble(RISE)system in the Beijing-Tianjin-Hebei(BTH)region,this study proposes a new Segmented Classification and Regression machine learning model based on the extreme gradient boosting(XGBoost)algorithm,termed SCR-XGBoost,which can be applied to correct hourly precipitation forecasts in areas with a dense network of weather stations at lead times of 4-6 h.The performance of the model is evaluated according to six metrics:the accuracy(AC),mean absolute error(MAE),root mean square error(RMSE),correlation coefficient(CC),threat score(TS),and bias score(BS).The results indicate that,although the XGBoost algorithm is almost ineffective for directly forecasting precipitation,the SCR-XGBoost model can significantly improve the forecast performance compared with the original RISE forecast,and the segmented correction method for torrential rainfall(≥20 mm h^(-1))outperforms other precipitation grades,which can effectively alleviate the problem of false alarms in the RISE system for heavy rainfall and above(≥10 mm h^(-1)).The optimization rates after applying the SCR-XGBoost model correction in precipitation forecasts can be improved by 6.49%-23.21%in terms of RMSE and MAE reduction,and the CC and AC can be greatly improved by 35.38%-84.39%.Therefore,the SCR-XGBoost algorithm,which introduces precipitation grade classification and multi-layer piecewise machine learning corrections,can significantly improve the 4-6-h precipitation forecast skill,especially for heavy rainfall.The results of this study not only provide new insights for machine learning-based precipitation forecasting,but also help improve rainfall forecasts and the level of disaster prevention and reduction in the BTH region.
基金supported jointly by the China Meteorological Administration Special Public Welfare Research Fund (Grant No. GYHY201406001)the National (Key) Basic Research and Development (973) Program of China (Grant No. 2012CB417202)the National Natural Science Foundation of China (Grant No. 41175038)
文摘The characteristics of raindrop size distribution （DSD） over the Tibetan Plateau and southern China are studied in this paper, using the DSD data from April to August 2014 collected by HSC-PS32 disdrometers in Nagqu and Yangjiang, com- prising a total of 9430 and 63661-rain raindrop spectra, respectively. The raindrop spectra, characteristics of parameter variations with rainfall rate, and the relationships between reflectivity factor （Z） and rainfall rate （R） are analyzed, as well as their DSD changes with precipitation type and rainfall rate. The results show that the average raindrop spectra appear to be one-peak curves, the number concentration for larger drops increase significantly with rainfall rate, and its value over southern China is much higher, especially in convective rain larger drops, especially for convective rain in southern China. Standardized Gamma distributions better describe DSD for All three Gamma parameters for stratiform precipitation over the Tibetan Plateau are much higher, while its shape parameter （,u） and mass-weighted mean diameter （Dm）, for convective precipitation, are less. In terms of parameter variation with rainfall rate, the normalized intercept parameter （Nw） over the Tibetan Plateau for stratiform rain increases with rainfall rate, which is opposite to the situation in convective rain. The/1 over the Tibetan Plateau for stratiform and convective precipitation types decreases with an increase in rainfall rate, which is opposite to the case for Dm variation. In Z-R relationships, like ＂Z = ARb＇＇, the coefficient A over the Tibetan Plateau is smaller, while its b is higher, when the rain type transfers from stratiform to convective ones. Furthermore, with an increase in rainfall rate, parameters A and b over southern China increase gradually, while A over the Tibetan Plateau decreases sub- stantially, which differs from the findings of previous studies. In terms of geographic location and climate over the Tibetan Plateau and southern China, the precipitation in the pre-flood seasons is dominated by strong convective rain, while weak convective rain occurs frequently in northern Tibet with lower humidity and higher altitude.
基金Supported by the National(Key)Basic Research and Developmet(973)Program of China(2012CB417204)Natural Science Foundation of Hainan Province(414197)Program of Key Technology Integration and Application(CMAGJ2013M39)
文摘Based on observational precipitation at 63 stations in South China and NCEP NCAR reanalysis data during 1951 2010,a cluster analysis is performed to classify large-scale circulation patterns responsible for persistent precipitation extremes（PPEs） that are independent of the influence of tropical cyclones（TCs）.Conceptual schematics depicting configurations among planetary-scale systems at different levels are established for each type.The PPEs free from TCs account for 38.6%of total events,and they tend to occur during April August and October,with the highest frequency observed in June.Corresponding circulation patterns during June August can be mainly categorized into two types,i.e.,summer-Ⅰ type and summer-Ⅱtype.In summer-Ⅰ type,the South Asian high takes the form of a zonal-belt type.The axis of upstream westerly jets is northwest-oriented.At the middle level,the westerly jets at midlatitudes extend zonally.Along the southern edge of the westerly jet,synoptic eddies steer cold air to penetrate southward;the Bay of Bengal（BOB） trough is located to the north;a shallow trough resides over coastal areas of western South China;and an intensified western Pacific subtropical high（WPSH） extends westward.The anomalous moisture is mainly contributed by horizontal advection via southwesterlies around 20°N and southeasterlies from the southern flange of the WPSH.Moisture convergence maximizes in coastal regions of eastern South China,which is the very place recording extreme precipitation.In summer-Ⅱ type,the South Asian high behaves as a western-center type.The BOB trough is much deeper,accompanied by a cyclone to its north;and a lower-level trough appears in northwestern parts of South China.Different to summer-Ⅰ type,moisture transport via southwesterlies is mostly responsible for the anomalous moisture in this type.The moisture convergence zones cover Guangdong,Guangxi,and Hainan,matching well with the areas of flooding.It is these set combinations among different systems at different levels that trigger PPEs in South China.
