本文通过耦合AFWA(Air Force Weather Agency)冻雨参数化方案的WRF模式,对2020年冬季因暖锋引发的中国北方严重冻雨灾害个例进行了模拟,结果显示模式能够很好地模拟此次冻雨过程中降水相态的空间分布。通过分析暖锋的演变、水成物云微...本文通过耦合AFWA(Air Force Weather Agency)冻雨参数化方案的WRF模式,对2020年冬季因暖锋引发的中国北方严重冻雨灾害个例进行了模拟,结果显示模式能够很好地模拟此次冻雨过程中降水相态的空间分布。通过分析暖锋的演变、水成物云微物理特征以及降水相态的变化,得到:在辽宁中北部—吉林中东部地区,暖锋导致中低空形成“冷—暖—冷”的温度层结,该区冻雨形成机制以“冰相机制”为主,即高空的雪花落入大于0℃暖层内融化、再降落到次冻结层后形成冻雨。同时,发现存在高空无固态水成物、逆温层内暖雨下落到次冻结层在地面形成冻雨的现象,这种新机制被定义为“暖雨机制”,更多水成物垂直剖面与同期地面观测降水相态的比对,验证了新机制的存在,并解释了该机制形成的可能原因。为更深入理解冻雨形成机理以及北方冻雨的预报、预警提供科学支撑。展开更多
Fires,including wildfires,harm air quality and essential public services like transportation,communication,and utilities.These fires can also influence atmospheric conditions,including temperature and aerosols,potenti...Fires,including wildfires,harm air quality and essential public services like transportation,communication,and utilities.These fires can also influence atmospheric conditions,including temperature and aerosols,potentially affecting severe convective storms.Here,we investigate the remote impacts of fires in the western United States(WUS)on the occurrence of large hail(size:≥2.54 cm)in the central US(CUS)over the 20-year period of 2001–20 using the machine learning(ML),Random Forest(RF),and Extreme Gradient Boosting(XGB)methods.The developed RF and XGB models demonstrate high accuracy(>90%)and F1 scores of up to 0.78 in predicting large hail occurrences when WUS fires and CUS hailstorms coincide,particularly in four states(Wyoming,South Dakota,Nebraska,and Kansas).The key contributing variables identified from both ML models include the meteorological variables in the fire region(temperature and moisture),the westerly wind over the plume transport path,and the fire features(i.e.,the maximum fire power and burned area).The results confirm a linkage between WUS fires and severe weather in the CUS,corroborating the findings of our previous modeling study conducted on case simulations with a detailed physics model.展开更多
文摘本文通过耦合AFWA(Air Force Weather Agency)冻雨参数化方案的WRF模式,对2020年冬季因暖锋引发的中国北方严重冻雨灾害个例进行了模拟,结果显示模式能够很好地模拟此次冻雨过程中降水相态的空间分布。通过分析暖锋的演变、水成物云微物理特征以及降水相态的变化,得到:在辽宁中北部—吉林中东部地区,暖锋导致中低空形成“冷—暖—冷”的温度层结,该区冻雨形成机制以“冰相机制”为主,即高空的雪花落入大于0℃暖层内融化、再降落到次冻结层后形成冻雨。同时,发现存在高空无固态水成物、逆温层内暖雨下落到次冻结层在地面形成冻雨的现象,这种新机制被定义为“暖雨机制”,更多水成物垂直剖面与同期地面观测降水相态的比对,验证了新机制的存在,并解释了该机制形成的可能原因。为更深入理解冻雨形成机理以及北方冻雨的预报、预警提供科学支撑。
基金supported by the U.S.Department of Energy,Office of Science,Office of Biological and Environmental Research program as part of the Regional and Global Model Analysis and Multi-Sector Dynamics program areas(Award Number DE-SC0016605)Argonne National Laboratory is operated for the DOE by UChicago Argonne,LLC,under contract DE-AC02-06CH11357+1 种基金the National Energy Research Scientific Computing Center(NERSC)NERSC is a U.S.DOE Office of Science User Facility operated under Contract DE-AC02-05CH11231.
文摘Fires,including wildfires,harm air quality and essential public services like transportation,communication,and utilities.These fires can also influence atmospheric conditions,including temperature and aerosols,potentially affecting severe convective storms.Here,we investigate the remote impacts of fires in the western United States(WUS)on the occurrence of large hail(size:≥2.54 cm)in the central US(CUS)over the 20-year period of 2001–20 using the machine learning(ML),Random Forest(RF),and Extreme Gradient Boosting(XGB)methods.The developed RF and XGB models demonstrate high accuracy(>90%)and F1 scores of up to 0.78 in predicting large hail occurrences when WUS fires and CUS hailstorms coincide,particularly in four states(Wyoming,South Dakota,Nebraska,and Kansas).The key contributing variables identified from both ML models include the meteorological variables in the fire region(temperature and moisture),the westerly wind over the plume transport path,and the fire features(i.e.,the maximum fire power and burned area).The results confirm a linkage between WUS fires and severe weather in the CUS,corroborating the findings of our previous modeling study conducted on case simulations with a detailed physics model.
