"Meso-scale Hybrid-4DVar using Adjoint-model including 3-ice Microphysics Scheme"　

［ 2017年02月27日 ］

RIKEN International Symposium on Data Assimilation 2017
"Meso-scale Hybrid-4DVar using Adjoint-model including 3-ice Microphysics Scheme"

A new meso-scale hybrid-4DVar data assimilation system has been developing to improve short-range precipitation forecasts. One of the purposes of this system is to enable the assimilation of high temporal resolution observations. Some important data among such observations are radar reflectivity and satellite radiance, for whose assimilation the detailed information of hydrometeors is necessary. In this regard, I have developed a tangent-linear and an adjoint model including simplified 6-class 3-ice 1-moment bulk cloud microphysics scheme. The simplification of microphysics scheme provides that the growth of perturbation in this tangent-linear model becomes similar to the growth of nonlinear perturbation during 3-hour assimilation window. In addition, the background error covariance of hydrometeors is estimated from ensemble perturbations in this system because the vertical error correlation is strongly dependent on meteorological situations. The impact of the assimilation of radar reflectivity and satellite radiance data using the meso-scale hybrid-4DVar data assimilation system will be presented at the symposium.
http://www.data-assimilation.riken.jp/risda2017/

講師プロフィール
名前:Yasutaka Ikuta	所属:Japan Meteorological Agency

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