Impacts of Improved Quality Control for GOES Imager Radiance Assimilation on Tropical Cyclone Forecasts Using HWRF

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Wednesday, 7 January 2015: 9:30 AM
230 (Phoenix Convention Center - West and North Buildings)
Zhengkun Qin, Nanjing University of Information Science and Technology, Nanjing, China; and X. Zou

The Geostationary Operational Environmental Satellites (GOES), GOES-13, GOES-15 and GOES-R, have been and will be providing high temporal- and spatial-resolution image radiance observations, which allows the structural evolution of extreme weather systems to be captured in real time. The direct radiance assimilation of four imager channels from GOES-13 and -15 using the current state-of-art the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) analysis system resulted a positive impact on hurricane track and intensity forecasts. A detailed analysis of GOES imager data assimilation revealed a systematic increase of analysis increments (O-A) compared with background innovations (O-B) for those data that have small O-B values, especially for GOES-13 and -15 channels 2 and 4 over ocean. Such a phenomena is found to be associated with either an existence of some large outliers in these surface-sensitive channels or a cancellation of radiance contributions from clouds and water vapor content. An improved quality control algorithm is proposed, which results in a more significant positive impact of GOES imager radiance assimilation on hurricane forecasts when the new quality control algorithm is incorporated into HWRF.