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Masahiro Kazumori

Abstract

The direct radiance assimilation scheme used in the Japan Meteorological Agency (JMA) global analysis system is applied to the JMA mesoscale four-dimensional variational data assimilation (4DVAR) system with two modifications. First, the data-thinning distance is shortened, and, second, the atmospheric profiles are extrapolated from the mesoscale model top to the radiative transfer model top using the U.S. Standard Atmosphere lapse rate. Although the variational bias correction method is widely used in many numerical weather prediction centers for global radiance assimilations, a radiance bias correction method for regional models has not been established because of difficulties in estimating the biases within limited regions and times. This paper examined the use of the bias correction coefficients estimated in the global system for the mesoscale system when the radiance data were introduced instead of the retrievals. It was found that the profile extrapolation was necessary to reduce the biases. Moreover, the use of common bias coefficients enables the use of the radiance data in the same way as the global system. The radiance data assimilation experiments in the mesoscale system demonstrated considerable improvements to the tropospheric geopotential height forecasts and precipitation forecasts. The improvements resulted from the introduction of radiance data from multiple satellites into data-sparse regions and times. However, the major effect of the radiance assimilation on the precipitation forecasts was limited to weak precipitation areas over oceans; the effects on deep convective areas and over land were relatively small.

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Masahiro Kazumori, Quanhua Liu, Russ Treadon, and John C. Derber

Abstract

The impact of radiance observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) was investigated in the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS). The GDAS used NCEP’s Gridpoint Statistical Interpolation (GSI) analysis system and the operational NCEP global forecast model. To improve the performance of AMSR-E low-frequency channels, a new microwave ocean emissivity model and its adjoint with respect to the surface wind speed and temperature were developed and incorporated into the assimilation system. The most significant impacts of AMSR-E radiances on the analysis were an increase in temperature of about 0.2 K at 850 hPa at the higher latitudes and a decrease in humidity of about 0.1 g kg−1 at 850 hPa over the ocean when the new emissivity model was used. There was no significant difference in the mean 6-h rainfall in the assimilation cycle. The forecasts made from the assimilation that included the AMSR-E data showed small improvements in the anomaly correlation of geopotential height at 1000 and 500 hPa in the Southern Hemisphere and reductions in the root-mean-square error (RMSE) for 500-hPa geopotential height in the extratropics of both hemispheres. Use of the new emissivity model resulted in improved RMSE for temperature forecasts from 1000 to 100 hPa in the extratropics of both hemispheres. The assimilation of AMSR-E radiances data using the emissivity model improved the track forecast for Hurricane Katrina in the 26 August 2005 case, whereas the assimilation using the NCEP operational emissivity model, FAST Emissivity Model, version 1 (FASTEM-1), degraded it.

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Stephen English, Catherine Prigent, Ben Johnson, Simon Yueh, Emmanuel Dinnat, Jacqueline Boutin, Stuart Newman, Magdalena Anguelova, Thomas Meissner, Masahiro Kazumori, Fuzhong Weng, Alexandre Supply, Lise Kilic, Michael Bettenhausen, Ad Stoffelen, and Christophe Accadia
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