Journal of Geophysical Research Atmospheres · 2018 · 65 citations · 59 references
Natural SciencesEarth SciencesMeteorologyAtmospheric ScienceClimatologyWeather ForecastingConvective MeteorologyConvective WeatherData AssimilationForecast VerificationNumerical Weather Prediction Data AssimilationPrecipitation ForecastingConvection Permitting ForecastingConvective Storm ForecastingConvective-scale Data AssimilationData Assimilation For Severe WeatherData Assimilation For Weather ForecastingHumidityRainstorm ClimatologySatellite Data Assimilation
Abstract Himawari‐8 is the first launched and operational new‐generation geostationary meteorological satellite. The Advanced Himawari Imager (AHI) on board Himawari‐8 provides continuous high‐resolution observations of severe weather phenomena in space and time. In this study, the capability to assimilate AHI radiances has been developed within the Weather Research and Forecasting (WRF) model's data assimilation system. As the first attempt to assimilate AHI using WRF data assimilation at convective scales, the added value of hourly AHI clear‐sky radiances from three water vapor channels on convection‐permitting (3 km) analyses and forecasts of the “7.19” severe rainstorm that occurred over north China during 18–21 July 2016 was investigated. Analyses were produced hourly, and 24 h forecasts were produced every 6 h. The results showed that improved wind and humidity fields were obtained in analyses and forecasts verified against conventional observations after assimilating AHI water vapor radiances when compared to the control experiment which assimilated only conventional observations. It was also found that the assimilation of AHI water vapor radiances had a clearly positive impact on the rainfall forecast for the first 6 h lead time, especially for heavy rainfall exceeding 100 mm when verified against the observed rainfall. Furthermore, the horizontal and vertical distribution of features in the moisture fields were improved after assimilating AHI water vapor radiances, eventually contributing to a better forecast of the severe rainstorm.
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A Description of the Advanced Research WRF Version 3
Jimy Dudhia, Dale Barker, Wei Wang et al. · UCAR/NCAR · 2008 · 9.4K citations · Full text