Significant and steady progress has been made in understanding and predicting tropical cyclone (TC) motion over the past 15-20 years. In contrast, only modest improvements in intensity prediction have been made over the same period. The primary objective of this study is to improve understanding and prediction of intensity change of tropical cyclones by assimilating satellite microwave observations into atmospheric prediction models. Unlike visible and infrared channel observations, microwave satellite data convey especially rich information originated from deep in the cloud/precipitation layers, therefore, reflect the distributions of hydrometeors within TCs. This makes microwave observations particularly advantageous in overcast and rainy TC areas.
Many meteorological satellites that are currently in operation carry sensors operating at microwave frequencies. Passive radiance observations at frequencies lower than 80 GHz are more sensitive to cloud liquid and raindrops, while those at higher frequencies are more sensitive to cloud ice, snowflake, and graupel. In this project, we investigate how these satellite microwave observations can effectively be assimilated into hurricane forecasting models (WRF and MM5) to provide improve analyses of cloud ice, snow, cloud liquid, and raindrop distributions within TCs, which may, in turn, pose a positive impact on hurricane intensity forecasts.
Intellectual merits. New and effective ways of applying these hydrometeor-sensitive data to TC analysis and forecast at different resolutions will be developed. In particular, we will: (i) develop and refine forward observation operators of microwave radiances through model verification with observations; (ii) design and test an effective quality control algorithm for these data; (iii) incorporate the new observation operators and the satellite microwave data into a hurricane data assimilation system; and (iv) assess the role of accurate analysis of ice, snow, liquid water, and raindrops in TC rapid intensification forecasts.
Broader impacts. The research activity will impose a significant scientific, technological, and societal impact. Improvement of forecasts of hurricane intensity and convective processes are important and challenging. The assessment of the impact of the satellite hydrometeor data on these forecasts and the development of new techniques to use these data will advance the science of hurricane research and prediction. The work will also provide benefit to the society by minimizing damages caused by hurricanes. The research activity will train two graduate students.
