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Satellite data retrieval algorithms almost always involve a large degree of model or simulation input. As an example, the satellite might provide a radiance or transmittance measurement that has to be unfolded to provide temperature or mass density. In order to convert transmittance into mass density, the operator must make some assumptions on the mass extinction coefficient and particle size distribution. These assumptions are often based upon climatological averages or upon simulation results. The Operational Multiscale Environment model with Grid Adaptivity (OMEGA) is a new atmospheric simulation system that merges state-of-the-art computational fluid dynamics techniques with a comprehensive non-hydrostatic equation set that includes both explicit and parameterized microphysics. OMEGA is based upon an unstructured triangular prism grid that permits a horizontal grid resolution ranging from 100 km down to 1 km and a vertical resolution from a few tens of meters in the boundary layer to 1 km in the free troposphere. OMEGA also contains an embedded aerosol transport algorithm that permits the simulation at high resolution of the transport and diffusion of either grid based aerosols or of Lagrangian parcels. OMEGA represents a significant advance in the field of weather prediction and aerosol transport. Current operational forecast models are scale- specific and have a limit to their resolution caused by their fixed rectangular grid structure. OMEGA, on the other hand, is naturally scale spanning and its unstructured grid permits the addition of grid elements at any point in space and time. This means that OMEGA can readily adapt its grid to fixed surface or terrain features, or dynamic features in the evolving weather. This feature also makes OMEGA a useful tool for satellite data retrieval and for the generation of synthetic satellite data. Synthetic satellite data is generated by recognizing that it is easier, in some ways, to simulate the performance of a sensor using the simulated environment and the sensor characteristics than to extract environmental information from the sensor data. This technique has been applied to generate simulated radar data as well as to produce a simulated photograph of an isolated cloud where the primary discrimination was the color contrast provided by the obscuration of the blue diffuse backscattered illumination by the cloud. The flexible grid adaptivity of OMEGA permits the accurate simulation of the satellite field of view thereby reducing the beam-filling problem that can cause major discrepancies in the data retrieval algorithm. Given the interaction of the model forecast and the data retrieval, the very high resolution forecasts possible with OMEGA also could improve existing retrieval algorithms. In this paper, we will present an overview of our concept of an analog sensor (or synthetic satellite data generation), and how the unique simulation capabilities of OMEGA factor into this concept.
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