634 Impacts from Assimilation of One Data Stream of AMSU-A and MHS Radiances on Quantitative Precipitation Forecasts

Tuesday, 24 January 2017
4E (Washington State Convention Center )
Zhengkun Qin, Nanjing University of Information Science and Technology, Nanjing, China; and X. Zou and F. Weng

Since the launch of NOAA-15 satellite in 1998, the observations from microwave temperature and humidity sounders have been routinely disseminated to user communities through two separate data streams. In the Advanced Microwave Sounding Unit-A (AMSU-A) data stream, brightness temperatures at 15 channels are available primarily for profiling atmospheric temperature from the earth surface to low stratosphere. In the Advanced Microwave Sounding Unit-B (AMSU-B) or Microwave Humidly Sounder (MHS) data stream, the brightness temperatures at five channels are included for sounding water vapor in the low troposphere. Assimilation of microwave radiance data in numerical weather prediction systems has also been carried out with AMSU-A and AMSU-B (MHS) data in two separate data streams. A new approach is to combine AMSU-A and MHS radiances into one data stream for their assimilation. The National Centers for Environmental Prediction Gridpoint Statistical Interpolation analysis system and the Advanced Research Weather Research and Forecast model are employed for testing the impacts of the combined datasets. It is shown that the spatial collocation between MHS and AMSU-A field of views in the one data stream experiment allows for an improved quality control of MHS data, especially over the conditions where the liquid-phase clouds are dominate. As a result, a closer fit of analyses to AMSU-A and MHS observations is obtained, especially for AMSU-A surface-sensitive channels. The quantitative precipitation forecast skill is improved over a 10-day period when Hurricane Isaac made landfall.
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