Prediction and Predictability of Tropical Cyclones over Oceanic and Coastal Regions and Advanced Assimilation of Radar and Satellite Data for the Navy Coupled Ocean-Atmosphere Mesoscale Prediction System. Annual Report

摘要

This project addresses tropical cyclone (TC) structure and intensity prediction improvement problem by (a) developing and testing advanced data assimilation (DA) capabilities for use by the Navy's COAMPS model and other community mesoscale prediction systems; and (b) by studying the effects of DA and initial condition and model errors at the convective scales on the predictability of TCs, which will in turn provide guidance to optimal ensemble prediction system design and DA improvement. OBJECTIVES: The project seeks to help fill some gaps of the Navy, DoD and NOAA's weather forecasting research and development. The research will accelerate our nation's capability to accurately predict hurricane intensity, thereby potentially reducing hurricane- related losses through better preparedness and response. Reduction in the uncertainty in track and intensity forecasting can directly translate into huge economic savings. The project will directly contribute to Navy's goal of reducing TC structure and intensity prediction error by 50% within a decade. The software developed has a direct path of transition to Navy's operations.