The Impact of Assimilation of GPM Clear Sky Radiance on HWRF Hurricane Track and Intensity Forecasts

The impact of GPM microwave imager (GMI) clear sky radiances on hurricane predication is examined by assimilating GMI level 1C recalibrated brightness temperature into the NCEP Gridpoint Statistical Interpolation (GSI)- based ensemble-variational hybrid data assimilation system for the operational Hurricane Weather Research and Forecast (HWRF) system. A quality control scheme is applied to filtered out cloud and precipitation contaminated radiance observations. Since biases are found in various channels, a regression method is used to compute the appropriate bias correction coefficients for GMI data in GSI system. Forecast results with and without assimilation of GMI radiance are compared using hurricane cases from recent hurricane seasons (e.g., hurricane Joaquin in 2015).

Diagnoses of data assimilation results show that the bias correction coefficients obtained from the regression method are able to significantly reduced the inherent biases in GMI radiance data. The removal of biases also allows more data to pass GSI quality control and hence to be assimilated into the model. Forecast results for hurricane Joaquin demonstrates that the quality of analysis from the data assimilation is sensitive to the bias correction, with positive impacts on the hurricane track forecast when systematic biases are removed from the radiance data. Details will be presented in the symposium.