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Data Assimilation Seminar Series

Prof. Fuqing Zhang (Jan. 13, 2017, 16:00-)

Affiliation Penn State U
Title Promises and Challenges in Assimilation of Infrared and Microwave All-sky Satellite Radiances for Convection-Permitting Analysis and Prediction
Abstract The impacts of assimilating GOES-R all-sky infrared brightness temperatures on tropical cyclone analysis and prediction were demonstrated through a series of convection-permitting observing system simulation experiments using an ensemble Kalman filter under both perfect and imperfect model scenarios. Assimilation of the high temporal and spatial resolution infrared radiances not only constrained well the thermodynamic variables, including temperature, moisture and hydrometeors, but also considerably reduced analysis and forecast errors in the wind fields. The potential of all-sky radiances is further demonstrated through an additional proof-of-concept experiment assimilating real-data infrared brightness temperatures from GOES-13 and Himawara-8. An empirical flow-dependent adaptive observation error inflation (AOEI) method is proposed for assimilating all-sky satellite brightness temperatures with an ensemble Kalman filter. The AOEI method adaptively inflates the observation error when the absolute difference (innovation) between the observed and simulated brightness temperatures is greater than the square root of the combined variance of the uninflated observational error variance and ensemble-estimated background error variance. This adaptive method is designed to limit erroneous analysis increments where there are large representativeness errors, as is often the case for cloudy-affected radiance observations. To better assimilate all-sky microwave radiance from polar-orbiting satellites, we begin to modify the Community Radiative Transfer Model (CRTM) to ensure that the cloud and precipitation particle scattering properties for calculating microwave radiances are consistent with the particle properties and size distributions internal to microphysics parameterization schemes. Using microphysics-consistent cloud scattering properties generates much greater variety in the simulated brightness temperature fields across the different microphysics schemes than the traditional use of effective radius. It is our expectation that the use of microphysics-consistent cloud scattering properties in the CRTM will help developing a more self-consistent tool for analyzing and constraining microphysics schemes, and to improve all-sky microwave radiance assimilation for convection-permitting analysis and prediction.
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