Ensemble Data Assimilation and Predictability of Tropical Cyclones
Abstract
The ultimate goal is to improve tropical cyclone track and intensity prediction through further development of ensemble-based data assimilation at the regional scale. More specifically, the objective is to make better use of in-situ and remotely-sensed observations in cloud-resolving models. In collaboration with scientists at the Naval Research Lab (NRL), we would like to develop an ensemble-based data assimilation system for the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) that is capable of assimilating remotely sensed data, as well as observations from conventional meteorological networks, to improve tropical cyclone prediction. This work will build upon a protype COAMPS-based ensemble Kalman filter (COAMPS-EnKF) that has been recently developed at NRL following the success of the ensemble data assimilation system developed at the Pennsylvania State University (PSU) for the Weather Research and Forecasting (WRF) model.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2012
- Accession Number
- ADA574591
Entities
People
- Fuqing Zhang
Organizations
- Pennsylvania State University