Tuesday, 14 January 2020: 11:30 AM
257AB (Boston Convention and Exhibition Center)
The Japan Meteorological Agency (JMA) plans to upgrade its operational global NWP system by introducing a revised version of its Global Spectral Model (GSM; JMA 2019). The revision involved the refinement of various parametrized processes, including gravity wave, land surface, cloud, and radiation. In this presentation, we will show the improvements and the impact experiment results, especially for the land surface processes.
In GSM, the land surface processes are composed of vegetation canopy, grass, snow, and soil components to provide lower boundary conditions of fluxes to the atmospheric model.
The upgrade of the land surface processes consists of various changes such as ones for diagnostic schemes of soil thermal conductivity and fraction of snow coverage to address several biases, which may be caused partially by the processes. As a preliminary result, the former change relatively suppresses excessive diurnal amplitude of soil heat flux, and the latter appropriately decreases the diagnosed fraction of snow coverage. The comparisons with SYNOP observations indicate reductions in the targeted biases, including summer nighttime warm bias of surface temperature in dry area and winter low-level cold bias in high latitudes.
References
Japan Meteorological Agency, 2019: Outline of the Operational Numerical Weather Prediction at the Japan Meteorological Agency. 229pp, URL https://www.jma.go.jp/jma/jma-eng/jma-center/nwp/outline2019-nwp/index.htm
In GSM, the land surface processes are composed of vegetation canopy, grass, snow, and soil components to provide lower boundary conditions of fluxes to the atmospheric model.
The upgrade of the land surface processes consists of various changes such as ones for diagnostic schemes of soil thermal conductivity and fraction of snow coverage to address several biases, which may be caused partially by the processes. As a preliminary result, the former change relatively suppresses excessive diurnal amplitude of soil heat flux, and the latter appropriately decreases the diagnosed fraction of snow coverage. The comparisons with SYNOP observations indicate reductions in the targeted biases, including summer nighttime warm bias of surface temperature in dry area and winter low-level cold bias in high latitudes.
References
Japan Meteorological Agency, 2019: Outline of the Operational Numerical Weather Prediction at the Japan Meteorological Agency. 229pp, URL https://www.jma.go.jp/jma/jma-eng/jma-center/nwp/outline2019-nwp/index.htm
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