Abstract
The distribution of tropospheric moisture in the environment is highly associated with storm development. Therefore, it is important to evaluate the uncertainty of moisture fields from numerical weather prediction (NWP) models for better understanding and enhancing storm prediction. With water vapor absorption band radiance measurements from the advanced imagers onboard the new generation of geostationary weather satellites, it is possible to quantitatively evaluate the environmental moisture fields from NWP models. Three NWP models—Global Forecast System (GFS), Unified Model (UM), Weather Research and Forecasting (WRF)—are evaluated with brightness temperature (BT) measurements from the three moisture channels of Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite for Typhoon Linfa (2015) case. It is found that the three NWP models have similar performance for lower tropospheric moisture, and GFS has a smaller bias for middle tropospheric moisture. Besides, there is a close relationship between moisture forecasts in the environment and the tropical cyclone (TC) track forecasts in GFS, while regional WRF does not show this pattern. When the infrared and microwave sounder radiance measurements from polar orbit satellite are assimilated in regional WRF, it is clearly shown that the environment moisture fields are improved compared with that with only conventional data are assimilated.
Highlights
Atmospheric water vapor is one of the major contributors to the Earth’s energy balance, severe weather forecasting and climate studies [1,2,3,4]
An assessment based on bias analysis between moisture field in numerical weather prediction (NWP) models and observations from multiple water vapor (WV) bands of GEO satellite is performed in this study
This study developed a methodology using Advanced Himawari Imager (AHI) data to evaluate environmental moisture from NWP models
Summary
Atmospheric water vapor is one of the major contributors to the Earth’s energy balance, severe weather forecasting and climate studies [1,2,3,4]. The WV absorption IR bands can provide useful moisture information for improving weather monitoring, nowcasting, and numerical weather prediction (NWP) model-based forecasting. They can be used for detecting tropospheric moisture features associated with low-level thermodynamic conditions and evaluation of NWP model performance. An assessment based on bias analysis between moisture field in NWP models and observations from multiple WV bands of GEO satellite is performed in this study. ((bb)) TThhee bbeesstt ttrraacckk ooff ttyypphhoooonn LLiinnffaa. IImmaaggeess ffrroomm tthhee CCooooppeerraattiivvee IInnssttiittuuttee ffoorr MMeetteeoorroollooggiiccaall SSaatteelllliittee SSttuuddiieess ((CCIIMMSSSS))//SSppaaccee SScciieennccee aanndd EEnnggiinneeeerriinngg CCeenntteerr ((SSSSEECC))//UUnniivveerrssiittyy ooff WWiissccoonnssiinn--MMaaddiissoonn
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