华东区域模式对河南“7·19”特大暴雨的数值检验与分析
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摘要
采用9 km分辨率的华东区域模式预报产品,对2016年7月19日发生在河南省的极端暴雨过程进行天气学检验与分析,结果表明:1)华东区域模式提前60 h对本次暴雨过程做出了较好预报,能反映出该暴雨过程的降水中心、强度及强降水发生时段。对临近时效和极端暴雨中心极值,该区域模式表现出优于全球模式的预报能力。2)华东区域模式能较好预报出本次过程中对流层中低层主要影响系统,但对系统位置、强度和移速预报与实况的差异导致了降水落区预报的偏差;西南急流预报较实况偏强是导致豫东南暴雨区空报的原因之一。3)华东区域模式对暴雨发生前K指数分布及不稳定层结有较好预报,对暴雨预报业务有重要指示意义。4)模式能较好地刻画出地面辐合线及气旋位置。
Using the 9 km resolution data of SMS-WARMS v2.0, the forecast results of the extreme process in Henan on 19 July 2016 were tested and analyzed by synoptic verification, the results show as follows. 1)The model has made a good forecast of this process for 60 hours in advance, while it reflects the center, intensity of the precipitation and the period of strong precipitation in this process. For near-time forecast and extreme value of the extreme rainstorm, the regional model is superior to the global model in forecasting ability. 2)The model forecasts the main influence systems of this process in the middle and lower troposphere accurately. The difference of position, intensity and moving speed for the main influence system between forecast and observation lead the forecast error of the precipitation area.The forecast southwest jet forecast is stronger than observation, which is one of reasons for false forecast of the rainstorm area in southeastern Henan. 3)The model forecasts K index distribution and the unstable stratification before rainstorm well, which are important indicators for rainstorm. 4)The model forecasts the position of surface convergence line and cyclone quite well.
Using the 9 km resolution data of SMS-WARMS v2.0, the forecast results of the extreme process in Henan on 19 July 2016 were tested and analyzed by synoptic verification, the results show as follows. 1)The model has made a good forecast of this process for 60 hours in advance, while it reflects the center, intensity of the precipitation and the period of strong precipitation in this process. For near-time forecast and extreme value of the extreme rainstorm, the regional model is superior to the global model in forecasting ability. 2)The model forecasts the main influence systems of this process in the middle and lower troposphere accurately. The difference of position, intensity and moving speed for the main influence system between forecast and observation lead the forecast error of the precipitation area.The forecast southwest jet forecast is stronger than observation, which is one of reasons for false forecast of the rainstorm area in southeastern Henan. 3)The model forecasts K index distribution and the unstable stratification before rainstorm well, which are important indicators for rainstorm. 4)The model forecasts the position of surface convergence line and cyclone quite well.
引文
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[2]景怀玺,徐科展,石圆圆,等.T213数值预报产品在白银市盛夏中雨以上降水中的释用技术[J].干旱气象,2008,26(1):83-88.
[3]张宏芳,潘留杰,杨新.ECMWF、日本高分辨率模式降水预报能力的对比分析[J].气象,2014,40(4):424-432.
[4]许敏,丛波,刘艳杰,等.廊坊地区5种数值模式降水预报性能检验与评估[J].气象与环境学报,2016,32(1):9-15.
[5]朱占云,潘娅英,骆月珍,等.浙江省水库流域面雨量的多模式预报效果分析与检验[J].气象与环境科学,2017,40(3):93-100.
[6]刘世祥,陶健红,张铁军,等.西北区秋季短期气象要素客观预报检验评估[J].干旱气象,2010,28(3):346-351.
[7]史恒斌,梁俊平.动力模式产品在河南省夏季降水预测中的降尺度应用[J].气象与环境科学,2017,40(1):35-39.
[8]崔强,王春明,岳甫璐,等.江淮地区一次强飑线系统结构特征的数值模拟研究[J].气象与环境科学,2018,41(3):21-28.
[9]刘武,李耀东,史小康.FY-2G地表温度反演产品改变模式初值对一次台风暴雨模拟的影响[J].气象与环境科学,2017,40(1):26-34.
[10]袁冬美,何文,钟思奕,等.4种数值模式的降水预报检验分析[J].江西科技,2017,35(6):956-965.
[11]潘留杰,张宏芳,王建鹏,等.日本高分辨率模式对中国降水预报能力的客观检验[J].高原气象,2014,33(2):483-494.
[12]张霞,梁钰,史一丛,等.ECMWF集合预报产品在河南省暴雨预报中的应用[J].河南科学,2018,36(4):616-620.
[13]王雨,公颖,陈法敬,等.区域业务模式6 h降水预报检验方案比较[J].应用气象学报,2013,24(2):171-178.
[14]曹萍萍,肖递祥,王佳津,等.SWCWARMS及ECMWF模式对四川盆地暖区型和斜压锋生型暴雨预报检验分析[J].高原山地气象研究,2018,38(1):22-29.
[15]范水勇,陈敏,仲跻芹,等.北京地区高分辨率快速循环同化预报系统性能检验和评估[J].暴雨灾害,2009,28(2):119-125.
[16]漆梁波.高分辨率数值模式在强对流天气预警中的业务应用进展[J].气象,2015,41(6):661-673.
[17]王雨,李莉.GRAPES_MesoV3.0模式预报效果检验[J].应用气象学报,2010,21(5):524-534.
[18]何光碧,张利红,屠妮妮.区域中尺度模式对西南地区一次强降水过程的预报分析[J].高原山地气象研究,2014,34(2):1-7.
[19]漆梁波,徐珺.豫北“7·9”特大暴雨的短期预报分析和反思[J].气象,2018,44(1):1-14.
[20]刘建文,郭虎,李耀东,等.天气分析预报物理量计算基础[M].北京:气象出版社,2008:217.