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Unmanned aerial system (UAS) for improving forecast accuracy of high-impact weather systems has been studied under the Sensing Hazards with Operational Unmanned Technology (SHOUT) project in the NOAA joint OSSE system. Due to the limited number of dropsondes, adaptive observation schemes have to be considered in these experiments in order to fully take advantages of this observing system. Among the existing adaptive observation schemes, we investigated ensemble transform (ET) methods and proposed a new ET based method for better performance in computational efficiency. An ET-based sensitivity (ETS) method, which calculates the gradient of forecast error variance reduction to analysis error variance reduction, is proposed to specify regions for possible adaptive observations. The ETS method will be descripted and results from an OSSE case study will be presented.
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