The proposed research focuses on improving the predictability and understanding of tropical cyclones through the assimilation of allsky satellite radiances and atmospheric motion vectors (amvs). In…

This is a contract award to The Pennsylvania State University, doing business as Penn State, for $134,795.00 to conduct research focused on improving the predictability and understanding of tropical cyclones. The proposed research will develop methods for assimilating satellite observations from microwave satellites and next-generation geostationary satellites into an ensemble Kalman filter system, with the goal of improving tropical cyclone prediction capabilities. This contract supports the National Aeronautics and Space Administration's (NASA) objectives to improve climate modeling, weather prediction, and natural hazard mitigation through Earth observation from space. The contract has no set-aside designation and was awarded on September 1, 2017, with a completion date of August 31, 2020.

The proposed research focuses on improving the predictability and understanding of tropical cyclones through the assimilation of allsky satellite radiances and atmospheric motion vectors (amvs). In particular, we will develop methods for the assimilation of satellite observations from both microwave satellites and those from the next generation geostationary satellites using an ensemble kalman filter (enkf) system developed specifically for tropical cyclone prediction. We will first examine the structure and dynamics of covariances and correlations between model state variables and satellite radiances and amvs, the predictability of satellite radiances, and the sensitivity to microphysics parameterization scheme. We will next conduct thorough observing system simulation experiments (osses) in which we investigate the impact of assimilating simulated goes-r infrared radiances, microwave radiances, and amvs in order to understand and demonstrate how these observations can complement each other and improve tropical cyclone prediction. Lastly, we will conduct real-data assimilation experiments of future tropical cyclones in which we assimilate all-sky microwave radiances, goes-r radiances, and amvs, in addition to conventional and aircraft observations. These case studies of future tropical storms will also allow US to further investigate the predictability of tropical cyclones and demonstrate increased predictability achieved through this proposed work. The expected outcome of the proposed research is to successfully develop new methods for the assimilation of all-sky satellite observations that result in the improved prediction of tropical cyclones. Improving the prediction of tropical cyclones is important in order to save lives, protect property, and minimize economic loss. In addition, we expect to contribute to the increased understanding of tropical cyclone dynamics and their predictability, while assisting NASA achieve its goal to improve climate modeling, weather prediction, and natural hazard mitigation, through earth observation from space. The methods developed in the proposed research can also be applied to improve the prediction other high impact weather events.