1. Global Observing System Simulation Experiments (Global OSSEs) How It Works Nature Run 13-month uninterrupted forecast produces alternative atmosphere. Extract simulated observations at realistic times and locations. Add realistic errors to the simulated observations. The European Centre for Medium Range Weather Forecasts has the best global model anywhere. It runs at a very high resolution (T599). Assess the realism of nature run by comparison with known atmospheric behavior (various statistics describing the general circulation and climate). Errors can be random or systematic and are spatially correlated. ECMWF Global Model Global Forecast System (GFS): for global prediction, and data assimilation with the GSI (Grid-point Statistical Interpolation) Use a model for assimilating synthetic data that is different from the nature run model in order to avoid overly optimistic results. The National Centers for Environmental Prediction (NCEP) run the GFS. Assimilate synthetic observations. Include or withhold observations from proposed new system. Assimilate real observations, the same mix as used in simulation. Generate prediction valid at the next analysis time. First guess Continue the forecast out to 1-5 days. Continue the forecast out to 1-5 days. Verify forecast against nature run fields or simulated observations. Verify forecast against operational analyses or real observations. Compare If the statistical behavior of the assimilation system is similar in the simulated and real worlds, success! Distinguish between runs in which the prospective new observing system was included in or withheld from the analysis. Differences show the effect of the new observing system on forecast accuracy — the most basic result of the OSSE. Participants in a collaborative global OSSE program The National Centers for Environmental Prediction NASA’s Global Assimilation and Modeling Office Joint Center for Satellite Data Assimilation NOAA’s Earth System Research Lab, Global Systems Division European Centre for Medium-Range Weather Forecasts Others The purposes of this program are to Evaluate the nature run Generate simulated observations from the nature run Perform specific OSSEs SimulationCalibration Thomas W. Schlatter 1,2 1 NOAA Earth System Research Laboratory (ESRL) – Boulder, Colorado 2 Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado – Boulder, Colorado Include all of the observation sources currently assimilated in operational models, e.g., surface: land and ocean, sounders: radiosondes, profilers, aircraft, etc., satellites: geosynchronous and in low-earth orbit, plus proposed new sources. All infrastructure that is used in operational data assimilation and numerical weather prediction, plus specialized software. An OSSE simulates the effect of a hypothetical (perhaps future) ob- serving system on the accuracy of operational forecasts. For ~1% of the cost of an expensive observing system, one can assess in advance of procurement its impact on forecast services. Moreover, a properly executed OSSE ensures that the capability to assimilate the new data source is in place before instrument deployment. DefinitionMotivationResources Needed