Satellite radiance assimilation using a 3DVAR assimilation system for hurricane Sandy forecasts

Tanvir Islam (), Prashant K. Srivastava, Dinesh Kumar, George P. Petropoulos, Qiang Dai and Lu Zhuo
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Tanvir Islam: California Institute of Technology
Prashant K. Srivastava: NASA Goddard Space Flight Center
Dinesh Kumar: Central University of Jammu
George P. Petropoulos: Aberystwyth University
Qiang Dai: Nanjing Normal University
Lu Zhuo: University of Bristol

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2016, vol. 82, issue 2, No 6, 845-855

Abstract: Abstract In this article, we present an assimilation impact study for forecasting hurricane Sandy using a three‐dimensional variational data assimilation system (3DVAR). In particular, we employ the 3DVAR component of the Weather Research and Forecasting Model and conduct analysis/forecast cycling experiments for “control” and “radiance” assimilation cases for the hurricane Sandy period. In “control” assimilation experiment, only conventional air and surface observations data are assimilated, while, in “radiance” assimilation experiment, along with the conventional air and surface observations data, the satellite radiance data from the Advanced Microwave Sounding Unit-A (AMSU-A) and the Microwave Humidity Sounder (MHS) sensors are also assimilated. For the radiance assimilation, we employ the community radiative transfer model as the forward operator and perform quality control and bias correction procedure before the radiance data are assimilated. In order to assess the impact of the assimilation experiments, we produce 132-h deterministic forecast starting on 00 UTC October 25, 2012. The results reveal that, in particular, the assimilation of AMSU-A satellite radiances helps to improve the short- to medium-range forecast (up to ~60-h lead time). The forecast skill is degraded in the long-range forecast (beyond 60 h) with the AMSU-A assimilation.

Keywords: Variational data assimilation; Numerical weather prediction (NWP); Cyclone forecast; Track propagation; WRF 3DVAR; Radiative transfer; ATOVS; AMSU-A; AMSU-B; MHS (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11069-016-2221-4

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