DOI: 10.1029/2017JD028012
Scopus记录号: 2-s2.0-85048995217
论文题名: Impact of Moisture Information From Advanced Himawari Imager Measurements on Heavy Precipitation Forecasts in a Regional NWP Model
作者: Wang P. ; Li J. ; Lu B. ; Schmit T.J. ; Lu J. ; Lee Y.-K. ; Li J. ; Liu Z.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2018
卷: 123, 期: 11 起始页码: 6022
结束页码: 6038
语种: 英语
英文关键词: AHI moisture information
; AHI radiances
; data assimilation
; layered precipitable water
; regional NWP model
Scopus关键词: algorithm
; atmospheric moisture
; climate modeling
; data assimilation
; EOS
; in situ measurement
; instrumentation
; moisture transfer
; precipitation (climatology)
; radiance
; regional climate
; weather forecasting
英文摘要: Information about moisture distribution and transportation in the preconvection environment is very important for nowcasting and forecasting severe weather events. The Advanced Himawari Imager (AHI) onboard the Japanese Himawari-8/-9 provides high temporal and spatial resolution moisture information useful for weather monitoring and forecasting. Algorithms have been developed for three-layered precipitable water (LPW: surface to 0.9, 0.9–0.7, and 0.7–0.3 in sigma vertical coordinate) retrievals from AHI infrared band radiances using a Geostationary Operational Environmental Satellite-R series algorithm working group algorithm. The LPW products from AHI have been validated with in situ measurements. An important application of the AHI LPW product is to improve local severe storm forecasts through assimilating high temporal and spatial resolution moisture information into regional- and storm-scale numerical weather prediction (NWP) models. Assimilation techniques and approaches have been developed; the impact on precipitation forecasts for local severe storm over land from the assimilation of LPWs from AHI shows improvement on heavy precipitation forecasts over those from the assimilation of conventional data. Comparisons between AHI infrared band radiance assimilation and LPW assimilation show overall similar or comparable impact on precipitation forecast. The approaches for assimilating LPW can be applied to the assimilation of data from other advanced imagers such as the Advanced Baseline Imager onboard the U.S. next generation of Geostationary Operational Environmental Satellites-R series, the Advanced Geosynchronous Radiation Imager onboard the Chinese FengYun-4 series, and the Flexible Combined Imager onboard the upcoming European Meteosat Third Generation. ©2018. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/113718
Appears in Collections: 气候减缓与适应
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作者单位: Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison, Madison, WI, United States; Institute of Urban Meteorology, China Meteorological Administration, Beijing, China; Center for Satellite Applications and Research, NESDIS/NOAA, Madison, WI, United States; State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment, Changsha, China; National Center for Atmospheric Research, Boulder, CO, United States
Recommended Citation:
Wang P.,Li J.,Lu B.,et al. Impact of Moisture Information From Advanced Himawari Imager Measurements on Heavy Precipitation Forecasts in a Regional NWP Model[J]. Journal of Geophysical Research: Atmospheres,2018-01-01,123(11)