对2006年7月中下旬由西太平洋地区生成,登陆我国,并对我国造成严重影响的强热带风暴"碧利斯"(0604号)和台风"格美"(0605号)的基本情况做了详细的总结,并基于武汉暴雨所AREM(Advanced Regional Eta Model)模式预报的...对2006年7月中下旬由西太平洋地区生成,登陆我国,并对我国造成严重影响的强热带风暴"碧利斯"(0604号)和台风"格美"(0605号)的基本情况做了详细的总结,并基于武汉暴雨所AREM(Advanced Regional Eta Model)模式预报的700hPa流场、900hPa风场及降水量场,就模式对台风登陆时间、登陆地点、移动路径及其引发的附近最大风力和降水过程的预报情况做了分析。结果表明:"碧利斯"达强热带风暴强度,于7月14日12:50在福建霞浦登陆,后西行,造成位于21°N以北、28°N以南东西向的带状雨区,"格美"为台风强度,于7月25日15:50在福建晋江围头镇登陆,后西行,造成华东南地区近西南-东北走向的雨带,两台风给沿途及附近省份造成严重的气象灾害和人、财损失;AREM模式总体上对两台风附近最大风速,风雨带的基本位置、形态、走势、强度预报较好,对一些强降水中心的预报较为理想,但多数强中心的预报与实况存在位置和强度上的偏差;模式对于台风登陆时间和地点的预报较好,偏差较小,对于两台风西行走势的预报也基本符合实况,但也存在一定的预报位置偏差。展开更多
分析了2005年6月1日至11月31日以T213分析场为背景场和以AVN(Aviation)分析场为背景场条件下AREM(Advanced Regional Eta Model)模式降水预报效果,并对两分析场计算日平均偏差和均方根标准差,分析偏差分布、总结两者之间的差别。结果表...分析了2005年6月1日至11月31日以T213分析场为背景场和以AVN(Aviation)分析场为背景场条件下AREM(Advanced Regional Eta Model)模式降水预报效果,并对两分析场计算日平均偏差和均方根标准差,分析偏差分布、总结两者之间的差别。结果表明:AREM模式在其他条件完全相同,分别使用两种分析场做背景场条件下,出现了降水预报效果的较明显差异,总体上以AVN分析场为背景场条件下AREM模式的预报效果好于以T213分析场为背景场;对两分析场进行统计学对比,发现两分析场在高度、温度和相对湿度3个要素上存在较大的差异,两分析场在新疆北侧的西伯利亚、内蒙古东北部及俄罗斯东南部区域、孟加拉湾、青藏高原等地区存在较大偏差,而这些地区的天气系统对我国天气有重要的影响。展开更多
In this paper, based on heavy rain numerical forecast model AREM(Advanced Regional Eta Model), two different initialization schemes, LAPS and GRAPES-3DVAR, are used to run assimilation experiments of AREM-LAPS and ARE...In this paper, based on heavy rain numerical forecast model AREM(Advanced Regional Eta Model), two different initialization schemes, LAPS and GRAPES-3DVAR, are used to run assimilation experiments of AREM-LAPS and AREM-3DVAR with the same data source(NCEP forecast field, surface data and radio-soundings) during the period from 21 May to 30 July 2008 to investigate the effect of the two initialization schemes on the rainfall simulation. The result suggests that:(1) the forecast TS score by the AREM-LAPS is higher than that by the AREM-3DVAR for rainfall in different areas, at different valid time and with different intensity, especially for the heavy rain, rainstorm and extremely heavy rain;(2) the AREM-3DVAR can generally simulate the average rainfall distribution, but the forecast area is smaller and rainfall intensity is weaker than the observation, while the AREM-LAPS significantly improves the forecast;(3) the AREM-LAPS gives a better forecast for the south-north shift of rainfall bands and the rainfall intensity variation than the AREM-3DVAR;(4) the AREM-LAPS can give a better reproduction for the daily change in the mean-rainfall-rate of the main rain band, and rainfall intensity changes in the eastern part of Southwest China, the coastal area in South China, the middle-lower valleys of Yangtze river, the Valleys of Huaihe river, and Shandong peninsula, with the rainfall intensity roughly close to the observation, while the rainfall intensity simulated by the AREM-3DVAR is clearly weaker than the observation, especially in the eastern part of Southwest China; and(5) the comparison verification between the AREM-LAPS and AREM-3DVAR for more than 10 typical rainfall processes in the summer of 2008 indicates that the AREM-LAPS gives a much better forecast than AREM-3DVAR in rain-band area, rainfall location and intensity, and in particular, the rainfall intensity forecast is improved obviously.展开更多
文摘对2006年7月中下旬由西太平洋地区生成,登陆我国,并对我国造成严重影响的强热带风暴"碧利斯"(0604号)和台风"格美"(0605号)的基本情况做了详细的总结,并基于武汉暴雨所AREM(Advanced Regional Eta Model)模式预报的700hPa流场、900hPa风场及降水量场,就模式对台风登陆时间、登陆地点、移动路径及其引发的附近最大风力和降水过程的预报情况做了分析。结果表明:"碧利斯"达强热带风暴强度,于7月14日12:50在福建霞浦登陆,后西行,造成位于21°N以北、28°N以南东西向的带状雨区,"格美"为台风强度,于7月25日15:50在福建晋江围头镇登陆,后西行,造成华东南地区近西南-东北走向的雨带,两台风给沿途及附近省份造成严重的气象灾害和人、财损失;AREM模式总体上对两台风附近最大风速,风雨带的基本位置、形态、走势、强度预报较好,对一些强降水中心的预报较为理想,但多数强中心的预报与实况存在位置和强度上的偏差;模式对于台风登陆时间和地点的预报较好,偏差较小,对于两台风西行走势的预报也基本符合实况,但也存在一定的预报位置偏差。
文摘分析了2005年6月1日至11月31日以T213分析场为背景场和以AVN(Aviation)分析场为背景场条件下AREM(Advanced Regional Eta Model)模式降水预报效果,并对两分析场计算日平均偏差和均方根标准差,分析偏差分布、总结两者之间的差别。结果表明:AREM模式在其他条件完全相同,分别使用两种分析场做背景场条件下,出现了降水预报效果的较明显差异,总体上以AVN分析场为背景场条件下AREM模式的预报效果好于以T213分析场为背景场;对两分析场进行统计学对比,发现两分析场在高度、温度和相对湿度3个要素上存在较大的差异,两分析场在新疆北侧的西伯利亚、内蒙古东北部及俄罗斯东南部区域、孟加拉湾、青藏高原等地区存在较大偏差,而这些地区的天气系统对我国天气有重要的影响。
基金Scientific Research Projects Specially for Public Welfare Industries(GYHY200906010)National Natural Science Foundation of China(41075034)Project 1009 for Wuhan Heavy Rain Institute
文摘In this paper, based on heavy rain numerical forecast model AREM(Advanced Regional Eta Model), two different initialization schemes, LAPS and GRAPES-3DVAR, are used to run assimilation experiments of AREM-LAPS and AREM-3DVAR with the same data source(NCEP forecast field, surface data and radio-soundings) during the period from 21 May to 30 July 2008 to investigate the effect of the two initialization schemes on the rainfall simulation. The result suggests that:(1) the forecast TS score by the AREM-LAPS is higher than that by the AREM-3DVAR for rainfall in different areas, at different valid time and with different intensity, especially for the heavy rain, rainstorm and extremely heavy rain;(2) the AREM-3DVAR can generally simulate the average rainfall distribution, but the forecast area is smaller and rainfall intensity is weaker than the observation, while the AREM-LAPS significantly improves the forecast;(3) the AREM-LAPS gives a better forecast for the south-north shift of rainfall bands and the rainfall intensity variation than the AREM-3DVAR;(4) the AREM-LAPS can give a better reproduction for the daily change in the mean-rainfall-rate of the main rain band, and rainfall intensity changes in the eastern part of Southwest China, the coastal area in South China, the middle-lower valleys of Yangtze river, the Valleys of Huaihe river, and Shandong peninsula, with the rainfall intensity roughly close to the observation, while the rainfall intensity simulated by the AREM-3DVAR is clearly weaker than the observation, especially in the eastern part of Southwest China; and(5) the comparison verification between the AREM-LAPS and AREM-3DVAR for more than 10 typical rainfall processes in the summer of 2008 indicates that the AREM-LAPS gives a much better forecast than AREM-3DVAR in rain-band area, rainfall location and intensity, and in particular, the rainfall intensity forecast is improved obviously.
