Tuesday, 24 January 2017
4E (Washington State Convention Center )
Two goals of global Observing System Simulation Experiments (OSSEs) are 1) for the observation error for control observations to closely resemble those in the real world and 2) for the forecast skill for the control dataset to closely resemble that for the real world as well. In pursuit of these goals, the authors worked on simulating control observations from the GEOS-5 Nature Run (G5NR) based on observations used operationally in August-September 2014, as well as adding reasonable errors. Upon the realization that the Global Forecast System (GFS) was better able to predict the G5NR than it could predict the real world, forecast system parameters were also identified that could be used to degrade the forecast. This poster will describe both of these approaches, and tuning procedures to create a control dataset/forecast system for OSSEs using prospective new observation systems.
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