探空和飞机观测资料联合同化对台风“苏迪罗”(2015)数值模拟的影响研究
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摘要
基于中尺度数值天气预报模式WRF和WRFDA三维变分同化系统,针对2015年台风"苏迪罗"二次登陆过程,利用NCEP ADP提供的无线电探空、飞机报观测资料,同时同化两种资料,并进行36 h模拟预报,从台风移动路径、强度、降水及模式初始场改进等方面分析了同化模拟效果。结果表明,同时同化两种资料能够有效改善台风移动路径、中心附近最低气压的模拟。对浙闽降水关键区24 h降水的TS评分结果表明,该同化方案对台风降水的预报评分有一定程度的改进,尤其是中雨和特大暴雨的改进最明显。对于模式初始场的温度、相对湿度、纬向风、经向风在各高度上的均方根误差,除湿度外均有不同程度的减小。并且同化对于台风结构的模拟也有所调整。
Based on the mesoscale numerical weather prediction model WRF and WRF-3 DVAR assimilation system, assimilating the aircraft, radiosonde observations provided by NCEP ADP data at the same time and simulating the typhoon "Soudelor" for 36 hours, the assimilation effects are analysed from the aspects of the typhoon path, strength, precipitation and initial field. The results show that the assimilation of two kinds of data can effectively improve the simulation of the minimum pressure near the moving path and center. After assimilation, the root mean square error of the moving path is reduced by 14.846 km(about 17.5%), and the root mean square error of the lowest pressure is reduced by 1.1 hPa, which is improved by about 18.1%. TS scores of 24 hours precipitation in key areas Zhejiang and Fujian provinces shows that the assimilation scheme has a certain degree of improvement in the prediction of typhoon precipitation, especially the improvement of moderate rain and torrential rain. The root mean square error of temperature, relative humidity, zonal wind and meridional wind at different heights of the model initial field is reduced to varying degrees except humidity. The temperature is reduced by 0.13 degrees averagely at all heights, about19%, the relative humidity increased by 0.5%, about 0.6%, the zonal wind decreased by 0.27 m/s, about9.9%, and the meridional wind decreased by 0.38 m/s, about 13.4%. According to the vertical distribution of the mean square root error, the improvement of temperature, relative humidity, zonal wind and meridional wind at the height of 950 hPa and 850 hPa are more obvious. And it also modify the simulated structure of typhoon.
Based on the mesoscale numerical weather prediction model WRF and WRF-3 DVAR assimilation system, assimilating the aircraft, radiosonde observations provided by NCEP ADP data at the same time and simulating the typhoon "Soudelor" for 36 hours, the assimilation effects are analysed from the aspects of the typhoon path, strength, precipitation and initial field. The results show that the assimilation of two kinds of data can effectively improve the simulation of the minimum pressure near the moving path and center. After assimilation, the root mean square error of the moving path is reduced by 14.846 km(about 17.5%), and the root mean square error of the lowest pressure is reduced by 1.1 hPa, which is improved by about 18.1%. TS scores of 24 hours precipitation in key areas Zhejiang and Fujian provinces shows that the assimilation scheme has a certain degree of improvement in the prediction of typhoon precipitation, especially the improvement of moderate rain and torrential rain. The root mean square error of temperature, relative humidity, zonal wind and meridional wind at different heights of the model initial field is reduced to varying degrees except humidity. The temperature is reduced by 0.13 degrees averagely at all heights, about19%, the relative humidity increased by 0.5%, about 0.6%, the zonal wind decreased by 0.27 m/s, about9.9%, and the meridional wind decreased by 0.38 m/s, about 13.4%. According to the vertical distribution of the mean square root error, the improvement of temperature, relative humidity, zonal wind and meridional wind at the height of 950 hPa and 850 hPa are more obvious. And it also modify the simulated structure of typhoon.
引文
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[13]朱磊,万齐林,刘靓珂,等.雷达径向风资料EnKF同化应用对Vicente(2012)登陆台风强度变化过程预报的影响试验研究[J].热带气象学报, 2017, 33(3):345-356.
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[19]莫毅,潘晓滨,臧增亮,等.资料同化对一次华南暴雨影响的数值试验研究[J].暴雨灾害, 2008, 27(4):289-294.
[20]张钊扬,钱贞成,岳甫璐,等.一次台风倒槽暴雨的GPS同化试验[J].暴雨灾害, 2014, 33(3):247-254.
[21]邱学兴,王东勇,江杨. LAPS系统中两种资料融合方法对台风“海葵”的预报对比分析[J].暴雨灾害, 2014, 33(1):41-49.
[22]曲晓波, Julian Heming.下投式探空资料对数值预报初始场影响的个例分析[J].气象与环境学报, 2006, 22(2):34-37.
[23]张诚忠,万齐林,丁伟钰,等.下投探空资料在台风莫拉克路径预报的应用试验[J].气象学报, 2012, 70(1):30-38.
[24] BENJAMIN S G, JAMISON B D, MONINGER W R, et al. Relative short-range forecast impact from Aircraft, Profiler, Radiosonde,VAD, GPS-PW, METAR, and mesonet observations via the RUC hourly assimilation cycle[J]. Mon Wea Rev, 2010, 138(4):1 319-1 343.
[25]陈锋,董美莹,冀春晓.不同资料同化对登陆台风菲特(2013)短时预报的影响研究[J].气象, 2017, 43(9):1 029-1 040.
[26]董海萍,袁炳,罗雨.多源资料循环同化在台风“潭美”预报中的应用[J].热带气象学报, 2017, 33(4):433-441.
[27]叶龙彬,谌芸,李晟祺,等. 1513号台风“苏迪罗”不同阶段降水的中尺度特征分析[J].热带气象学报, 2018, 34(3):371-384.
[28]季晓云,张庆曹,厉海斌.“苏迪罗”台风暴雨洪水浅析[J].水利科技与经济, 2016, 22(3):54-56.
[29]苏传程,毛文书,师春香,等.多种降水融合产品对“苏迪罗”台风的监测效果对比[J].成都信息工程学院学报, 2016, 31(6):614-621.
[30]王瑞文,叶冬,李莉. AMDAR资料质量分析及对GRAPES系统同化和预报影响[J].气候与环境研究, 2014, 19(6):683-692.
[2]徐亚钦,翟国庆,李国平,等. WRF模式对高影响浙江型台风微物理和边界层参数化方案的优化试验[J].热带气象学报, 2017, 33(2):201-211.
[3]黄燕燕,薛纪善,陈子通,等. 2011年"洛克"和"桑卡"双台风预报效果的初值试验研究[J].热带气象学报, 2017, 33(1):30-42.
[4]马旭林,陆续,于月明,等.数值天气预报中集合-变分混合资料同化及其研究进展[J].热带气象学报, 2014, 30(6):1 188-1 195.
[5]周菲凡,张贺.基于CNOP方法的台风目标观测中三种敏感区确定方案的比较研究[J].大气科学, 2014, 38(2):261-272.
[6]王晓雷,周菲凡,朱克云.条件非线性最优扰动方法在台风“风神”和“凤凰”相互作用过程中的应用研究[J].热带气象学报, 2013, 29(2):235-244.
[7]朱国富.数值天气预报中分析同化基本方法的历史发展脉络和评述[J].气象, 2015(8):986-996.
[8]马旭林,李琳琳,周勃旸,等.台风预报误差的流依赖特征及混合资料同化中最优耦合系数[J].大气科学学报, 2015, 38(6):766-775.
[9]邹力,王云峰,姜勇强,等.基于卫星亮温资料同化对2009年热带风暴“浪卡”的数值研究[J].气象科学, 2016, 36(3):366-373.
[10]余意,张卫民,曹小群,等.同化IASI资料对台风“红霞”和“莫兰蒂”预报的影响研究[J].热带气象学报, 2017, 33(4):500-509.
[11] SRIVASTAVA K, BHARDWAJ R. Assimilation of doppler weather radar data in WRF model for simulation of Tropical Cyclone Aila[J].Pure&Applied Geophysics, 2014, 171(8):2 043-2 072.
[12]李昕,王元,明杰,等.雷达径向风和反演风联合同化在台风灿都(2010)数值预报中的研究[J].气象, 2016, 42(6):649-663.
[13]朱磊,万齐林,刘靓珂,等.雷达径向风资料EnKF同化应用对Vicente(2012)登陆台风强度变化过程预报的影响试验研究[J].热带气象学报, 2017, 33(3):345-356.
[14]李跃清,赵兴炳,邓波. 2010年夏季西南涡加密观测科学试验[J].高原山地气象研究, 2010, 30(4):80-84.
[15]李跃清,赵兴炳,张利红,等. 2011年夏季西南涡加密观测科学试验[J].高原山地气象研究, 2011, 31(4):7-11.
[16]李跃清,赵兴炳,张利红,等. 2012年夏季西南涡加密观测科学试验[J].高原山地气象研究, 2012, 32(4):1-8.
[17]宝兴华,杨舒楠. WRF-EnKF系统对中国南方一次暴雨过程确定性预报的试验[J].气象, 2015, 41(5):566-576.
[18]徐同,王晓峰,张蕾,等.加密探空资料在华东区域业务模式中的应用试验[J].暴雨灾害, 2016, 35(4):306-314.
[19]莫毅,潘晓滨,臧增亮,等.资料同化对一次华南暴雨影响的数值试验研究[J].暴雨灾害, 2008, 27(4):289-294.
[20]张钊扬,钱贞成,岳甫璐,等.一次台风倒槽暴雨的GPS同化试验[J].暴雨灾害, 2014, 33(3):247-254.
[21]邱学兴,王东勇,江杨. LAPS系统中两种资料融合方法对台风“海葵”的预报对比分析[J].暴雨灾害, 2014, 33(1):41-49.
[22]曲晓波, Julian Heming.下投式探空资料对数值预报初始场影响的个例分析[J].气象与环境学报, 2006, 22(2):34-37.
[23]张诚忠,万齐林,丁伟钰,等.下投探空资料在台风莫拉克路径预报的应用试验[J].气象学报, 2012, 70(1):30-38.
[24] BENJAMIN S G, JAMISON B D, MONINGER W R, et al. Relative short-range forecast impact from Aircraft, Profiler, Radiosonde,VAD, GPS-PW, METAR, and mesonet observations via the RUC hourly assimilation cycle[J]. Mon Wea Rev, 2010, 138(4):1 319-1 343.
[25]陈锋,董美莹,冀春晓.不同资料同化对登陆台风菲特(2013)短时预报的影响研究[J].气象, 2017, 43(9):1 029-1 040.
[26]董海萍,袁炳,罗雨.多源资料循环同化在台风“潭美”预报中的应用[J].热带气象学报, 2017, 33(4):433-441.
[27]叶龙彬,谌芸,李晟祺,等. 1513号台风“苏迪罗”不同阶段降水的中尺度特征分析[J].热带气象学报, 2018, 34(3):371-384.
[28]季晓云,张庆曹,厉海斌.“苏迪罗”台风暴雨洪水浅析[J].水利科技与经济, 2016, 22(3):54-56.
[29]苏传程,毛文书,师春香,等.多种降水融合产品对“苏迪罗”台风的监测效果对比[J].成都信息工程学院学报, 2016, 31(6):614-621.
[30]王瑞文,叶冬,李莉. AMDAR资料质量分析及对GRAPES系统同化和预报影响[J].气候与环境研究, 2014, 19(6):683-692.