Abstract
¶Cloud Motion Vector wind (CMV) data is one of the major products derived from current day operational geostationary satellites and continues to be a useful source of information for global data assimilation systems. The CMV fields result basically from the apparent cloud motion estimated through a sequence of very high resolution radiometer (VHRR) images and the corresponding cloud level is inferred from observed brightness temperatures (BT) in the infrared window channel. The main problem in CMV production is associated with the assignment of correct height to the cloud tracked motions in view of the known limitations associated with the cloud emissivity characteristics and estimation of BTs. Despite these inherent uncertainties satellite derived CMVs are widely used to augment the conventional upper air wind data especially over the oceanic regions. In this study, an attempt is made to improve the quality of INSAT derived CMVs through an appropriate height re-assignment by employing first guess fields (short range forecasts) of a global forecast model.
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