JpGU-AGU Joint Meeting 2020

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[E] Poster

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI33] Data assimilation: A fundamental approach in geosciences

convener:Shin ya Nakano(The Institute of Statistical Mathematics), Yosuke Fujii(Meteorological Research Institute, Japan Meteorological Agency), Takemasa Miyoshi(RIKEN), SHINICHI MIYAZAKI(Graduate School of Science, Kyoto University)

[MGI33-P06] Observation impact study in global numerical weather prediction

*Toshiyuki Ishibashi1 (1.Meteorological Research Institute/Japan Meteorological Agency)

Keywords:data assimilation, observation impact, adjoint operator

To improve the accuracy of global numerical weather prediction (NWP), it is necessary to assimilate more observation information with a data assimilation system (DAS). To know impact of each assimilated observation on analyses and forecasts is essential for this. In this study, we estimate observation impacts using the adjoint based impact estimation method, which used an adjoint operators of a DAS and a NWP model. Various properties of observation impact such as nonlinearity, probabilistic nature, system dependency are also considered.