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 ...
This paper investigates the effects of spatial filtering on the ensemble-based estimate of the background error covariance matrix in an ensemble-based Kalman filter (EnKF). In particular, a novel kernel smoothing method with variable bandwidth is introduced and its performance is compared to that of the widely used Gaspari-Cohn filter, which uses a fifth-order kernel function with a fixed localization length. Numerical experiments are carried out with the 40-variable Lorenz-96 model. ...
The ultimate goals is to improve tropical cyclone track and intensity prediction through further development of the regional-scale, cloud-resolving ensemble-based data assimilation and prediction system capable of efficiently assimilating in-situ and remotely sensed observations.
This study explores the assimilation of Doppler radar radial velocity observations for cloud-resolving hurricane analysis, initialization, and prediction with an ensemble Kalman filter (EnKF). The case studied is Hurricane Humberto (2007), the first landfalling hurricane in the United States since the end of the 2005 hurricane season and the most rapidly intensifying near-landfall storm in U.S. history. The storm caused extensive damage along the southeast Texas coast but was poorly ...
The ultimate goals of the proposed work are to estimate the predictability of mesoscale features embedded within different synoptic-scale flow regimes and to identify key physical processes that control the limit of predictability at the mesoscale through explicit simulations of idealized moist baroclinic waves and case studies of high-impact weather events.
The ultimate goals of the proposed work are to estimate the predictability of mesoscale features embedded within different synoptic-scale flow regimes and to identify key physical processes that control the limit of predictability at the mesoscale through explicit simulations of idealized moist baroclinic waves and case studies of high-impact weather events.
The ultimate goals of the proposed work are to estimate the predictability of mesoscale features embedded within different synoptic-scale flow regimes and to identify key physical processes that control the limit of predictability at the mesoscale through explicit simulations of idealized moist baroclinic waves and case studies of high-impact weather events.
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