
Validation of Satellite-Derived Atmospheric Motion Vectors and Analyses around Tropical Disturbances
Author(s) -
John Sears,
Christopher S. Velden
Publication year - 2012
Publication title -
journal of applied meteorology and climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.079
H-Index - 134
eISSN - 1558-8432
pISSN - 1558-8424
DOI - 10.1175/jamc-d-12-024.1
Subject(s) - dropsonde , geostationary orbit , tropical cyclone , satellite , environmental science , data assimilation , meteorology , numerical weather prediction , tropics , tropical atlantic , climatology , remote sensing , geography , geology , sea surface temperature , physics , astronomy , fishery , biology
Fields of atmospheric motion vectors (AMVs) are routinely derived by tracking features in sequential geostationary satellite infrared, water vapor, and visible-channel imagery. While AMVs produced operationally by global data centers are routinely evaluated against rawinsondes, there is a relative dearth of validation opportunities over the tropical oceans—in particular, in the vicinity of tropical disturbances when anomalous flow fields and strongly sheared environments commonly exist. A field experiment in 2010 called Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) was conducted in the tropical west Atlantic Ocean and provides an opportunity to evaluate the quality of tropical AMVs and analyses derived from them. The importance of such a verification is threefold: 1) AMVs often provide the only input data for numerical weather prediction (NWP) over cloudy areas of the tropical oceans, 2) NWP data assimilation methods are increasingly reliant on accurate flow-dependent observation-error characteristics, and 3) global tropical analysis and forecast centers often rely on analyses and diagnostic products derived from the AMV fields. In this paper, the authors utilize dropsonde information from high-flying PREDICT aircraft to identify AMV characteristics and to better understand their errors in tropical-disturbance situations. It is found that, in general, the AMV observation errors are close to those identified in global validation studies. However, some distinct characteristics are uncovered in certain regimes associated with tropical disturbances. High-resolution analyses derived from the AMV fields are also examined and are found to be more reflective of anomalous flow fields than the respective Global Forecast System global model analyses.