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Numerical Assessing Experiments on the Individual Component Impact of the Meteorological Observation Network on the "July 2000" Torrential Rain in Beijing
作者姓名:ZHANG Chaolin  CHEN Min  KUO Ying-Hw  FAN Shuiyong  ZHONG Jiqin
作者单位:Institute of Urban Meteorology China Meteorological Administration,Institute of Urban Meteorology China Meteorological Administration,National Center for Atmospheric Research P.O.Box 3000 Boulder,CO,80307-3000,USA,Institute of Urban Meteorology China Meteorological Administration,Institute of Urban Meteorology China Meteorological Administration,Beijing 100089,China,Beijing 100089,China,Beijing 100089,China,Beijing 100089,China
基金项目:Supported by project of the Ministry of Science and Technology under Nos.2005DIB3J098,2003DFB00011 and 2002BA904B05,project of the Beijing New Star under No.H013610330119,and projects of Beijing Municipal Science Technology Commission under Nos.H010510120119 and H020620250330,and project of GPS application of Beijing Meteorological Bureau.
摘    要:In an effort to assess the impact of the individual component of meteorological observations (ground-based GPS precipitable water vapor,automatic and conventional meteorological observations) on the torrential rain event in 4-5 July 2000 in Beijing (with the 24-h accumulated precipitation reaching 240 mm),24-h observation system experiments are conducted numerically by using the MM5/WRF 3DVAR system and the nonhydrostatic MM5 model.Results indicate that,because the non-conventional GPS observations are directly assimilated into the initial analyses by 3DVAR system,better initial fields and 24-h simulation for the severe precipitation event are achieved than those under the MM5/Litter_R objective analysis scheme. Further analysis also shows that the individual component of meteorological observation network plays their special positive role in the improvement of initial field analysis and forecasting skills.3DVAR scheme with or without radiosonde and pilot observation has the most significant influence on numerical simulation,and automatic and conventional surface meteorological observations rank second.After acquiring the supplement information from the other meteorological observations,the ground-based GPS precipitable water vapor data can more obviously reflect initial field assimilation and precipitation forecast.By incorporating the ground- based GPS precipitable water vapor data into the 3DVAR analyses at the initial time,the threat scores (TS) with thresholds of 1,5,10,and 20 mm are increased by 1%-8% for 6- and 24-h accumulated precipitation observations,respectively.This work gives one helpful example that assesses the impact of individual component of the existing meteorological observation network on the high influence weather event using 3DVAR numerical system.

关 键 词:2000年7月  北京  特大暴雨  气象观测网  个别气象监测资料  数值评估实验
收稿时间:2006/10/30 0:00:00

Numerical Assessing Experiments on the Individual Component Impact of the Meteorological Observation Network on the "July 2000" Torrential Rain in Beijing
ZHANG Chaolin,CHEN Min,KUO Ying-Hw,FAN Shuiyong,ZHONG Jiqin.Numerical Assessing Experiments on the Individual Component Impact of the Meteorological Observation Network on the "July 2000" Torrential Rain in Beijing[J].Acta Meteorologica Sinica,2006,20(4):389-401.
Authors:HANG Chaolin  CHEN Min  KUO Ying-Hwa  FAN Shuiyong  ZHONG Jiqin
Affiliation:[1]Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China [2]National Center for Atmospheric Research, P. O. Box 3000, Boulder, CO, 80307-3000, USA
Abstract:In an effort to assess the impact of the individual component of meteorological observations (ground-based GPS precipitable water vapor,automatic and conventional meteorological observations) on the torrential rain event in 4-5 July 2000 in Beijing (with the 24-h accumulated precipitation reaching 240 mm),24-h observation system experiments are conducted numerically by using the MM5/WRF 3DVAR system and the nonhydrostatic MM5 model.Results indicate that,because the non-conventional GPS observations are directly assimilated into the initial analyses by 3DVAR system,better initial fields and 24-h simulation for the severe precipitation event are achieved than those under the MM5/Litter_R objective analysis scheme. Further analysis also shows that the individual component of meteorological observation network plays their special positive role in the improvement of initial field analysis and forecasting skills.3DVAR scheme with or without radiosonde and pilot observation has the most significant influence on numerical simulation,and automatic and conventional surface meteorological observations rank second.After acquiring the supplement information from the other meteorological observations,the ground-based GPS precipitable water vapor data can more obviously reflect initial field assimilation and precipitation forecast.By incorporating the ground- based GPS precipitable water vapor data into the 3DVAR analyses at the initial time,the threat scores (TS) with thresholds of 1,5,10,and 20 mm are increased by 1%-8% for 6- and 24-h accumulated precipitation observations,respectively.This work gives one helpful example that assesses the impact of individual component of the existing meteorological observation network on the high influence weather event using 3DVAR numerical system.
Keywords:three-dimensional variational data assimilation  global positioning system (GPS)  severe rainfall  observation system experiment  numerical weather prediction (NWP)
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