AMSR2 all-sky radiance assimilation and its impact on the analysis and forecast of Hurricane Sandy with a limited-area data assimilation system

Abstract

A method to assimilate all-sky radiances from the Advanced Microwave Scanning Radiometer 2 (AMSR2) was developed within the Weather Research and Forecasting (WRF) model's data assimilation (WRFDA) system. The four essential elements are: (1) extending the community radiative transform model's (CRTM) interface to include hydrometeor profiles; (2) using total water Q t as the moisture control variable; (3) using a warm-rain physics scheme for partitioning the Q t increment into individual increments of water vapour, cloud liquid water and rain; and (4) adopting a symmetric observation error model for all-sky radiance assimilation. Compared to a benchmark experiment with no AMSR2 data, the impact of assimilating clear-sky or allsky AMSR2 radiances on the analysis and forecast of Hurricane Sandy (2012) was assessed through analysis/ forecast cycling experiments using WRF and WRFDA's three-dimensional variational (3DVAR) data assimilation scheme. With more cloud/precipitation-affected data being assimilated around tropical cyclone (TC) core areas in the all-sky AMSR2 assimilation experiment, better analyses were obtained in terms of the TC's central sea level pressure (CSLP), warm-core structure and cloud distribution. Substantial (!20 %) error reduction in track and CSLP forecasts was achieved from both clear-sky and all-sky AMSR2 assimilation experiments, and this improvement was consistent from the analysis time to 72-h forecasts. Moreover, the allsky assimilation experiment consistently yielded better track and CSLP forecasts than the clear-sky did for all forecast lead times, due to a better analysis in the TC core areas. Positive forecast impact from assimilating AMSR2 radiances is also seen when verified against the European Center for Medium-Range Weather Forecasts (ECMWF) analysis and the Stage IV precipitation analysis, with an overall larger positive impact from the all-sky assimilation experiment.

All‐Sky Assimilation of the MWHS‐2 Observations and Evaluation the Impacts on the Analyses and Forecasts of Binary Typhoons

“…These improvements in the surrounding environment have considerable potential to improve the forecasts of typhoons. Note that the improvement in humidity in the all‐sky assimilation was not significant compared with the clear‐sky assimilation, which has also been reported by Yang et al (). According to D. Xu et al (), the forecasts of the moisture field in the clear‐sky assimilation of the MWHS radiance data using the flow‐dependent ensemble background covariance error with the Hybrid (ensemble/3D‐VAR) method agreed best with the observations.…”

Impact of assimilating GOES imager clear‐sky radiance with a rapid refresh assimilation system for convection‐permitting forecast over Mexico

“…The same bias correction method, variational bias correction (VarBC) [ Dee , ], described in Yang et al [] is used for GOES imager data to correct the systematic error before they are assimilated. The cost function J to be minimized with respect to the bias parameters and model state becomes where β ′ is the increment of bias correction coefficient vector and B β is the bias parameter background error covariance, respectively [ Auligné et al , ].…”

“…It provides 90–95% of the actively assimilated data [ Bauer et al , ]. As the development of fast radiative transfer models and their adjoint models, a number of clear‐sky or all‐sky infrared and microwave channel radiance observations from satellite instruments have been assimilated directly into most operational centers, such as the National Centers for Environmental Prediction (NCEP), European Centre for Medium‐Range Weather Forecasts (ECMWF), Met Office, Japan Meteorological Agency, Météo‐France, and Environment Canada [ Greenwald et al , ; Heilliette and Garand , ; Pavelin et al , ; McNally , ; Pangaud et al , ; Heilliette , ; Bauer et al , ; Geer et al , ; Geer and Bauer , ; Guidard et al , ; Lupu and McNally , ; Okamoto , ; Zhu et al , ; Kazumori , ; Yang et al , ]. These infrared and microwave instruments are carried on different geostationary and polar‐orbiting satellites.…”

Impacts of Observation Errors on Hurricane Forecasts When Assimilating Hyperspectral Infrared Sounder Radiances in Partially Cloudy Skies

“…Satellite information has become one of the dominant sources for improving numerical weather prediction (NWP) model‐based forecasts. In the last few years, all‐sky satellite‐based microwave sounder data have shown great benefit to forecast improvement at operational NWP systems (Bauer et al, ; Geer et al, ; Zhu et al, ) and in the research community (Li et al, ; Yang et al, ; Zhang et al, ). Infrared (IR) radiances, however, are often not fed into the assimilation system because a large percentage of those data are contaminated with clouds (Eresmaa, ; Wang et al, ).…”