Open AccessImpact of Four-Dimensional Variational Data Assimilation of Atmospheric Motion Vectors on Tropical Cyclone Track Forecasts
Author(s) -
Dongliang Wang,
Xudong Liang,
Yihong Duan,
Johnny C. L. Chan
Publication year - 2006
Publication title -
weather and forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.393
H-Index - 106
eISSN - 1520-0434
pISSN - 0882-8156
DOI - 10.1175/waf940.1
Subject(s) - tropical cyclone , data assimilation , mesoscale meteorology , meteorology , environmental science , satellite , geostationary orbit , track (disk drive) , numerical weather prediction , atmospheric research , geostationary operational environmental satellite , climatology , weather research and forecasting model , geology , computer science , geography , physics , operating system , astronomy
The fifth-generation Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model is employed to evaluate the impact of the Geostationary Meteorological Satellite-5 water vapor and infrared atmospheric motion vectors (AMVs), incorporated with the four-dimensional variational (4DVAR) data assimilation technique, on tropical cyclone (TC) track predictions. Twenty-two cases from eight different TCs over the western North Pacific in 2002 have been examined. The 4DVAR assimilation of these satellite-derived wind observations leads to appreciable improvements in the track forecasts, with average reductions in track error of ∼5% at 12 h, 12% at 24 h, 10% at 36 h, and 7% at 48 h. Preliminary results suggest that the improvement depends on the quantity of the AMV data available for assimilation.