Impact of moisture information from advanced Himawari Imager measurements on heavy precipitation forecasts in a regional NWP model

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.

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Copyright 2018 American Geophysical Union.


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Author Wang, Pei
Li, Jun
Lu, Bing
Schmit, Timothy J.
Lu, Jiazhen
Lee, Yong-Keun
Li, Jinlong
Liu, Zhiquan
Publisher UCAR/NCAR - Library
Publication Date 2018-06-12T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T19:19:36.553809
Metadata Record Identifier edu.ucar.opensky::articles:21771
Metadata Language eng; USA
Suggested Citation Wang, Pei, Li, Jun, Lu, Bing, Schmit, Timothy J., Lu, Jiazhen, Lee, Yong-Keun, Li, Jinlong, Liu, Zhiquan. (2018). Impact of moisture information from advanced Himawari Imager measurements on heavy precipitation forecasts in a regional NWP model. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7h41v71. Accessed 15 June 2025.

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