Identifying the Uncertainty in Determining Satellite-Derived Atmospheric Motion Vector Height AttributionSource: Journal of Applied Meteorology and Climatology:;2009:;volume( 048 ):;issue: 003::page 450DOI: 10.1175/2008JAMC1957.1Publisher: American Meteorological Society
Abstract: This study investigates the assignment of pressure heights to satellite-derived atmospheric motion vectors (AMVs), commonly known as cloud-drift and water vapor?motion winds. Large volumes of multispectral AMV datasets are compared with collocated rawinsonde wind profiles collected by the U.S. Department of Energy Atmospheric Radiation Measurement Program at three geographically disparate sites: the southern Great Plains, the North Slope of Alaska, and the tropical western Pacific Ocean. From a careful analysis of these comparisons, the authors estimate that mean AMV observation errors are ?5?5.5 m s?1 and that vector height assignment is the dominant factor in AMV uncertainty, contributing up to 70% of the error. These comparisons also reveal that in most cases the RMS differences between matched AMVs and rawinsonde wind values are minimized if the rawinsonde values are averaged over specified layers. In other words, on average, the AMV values better correlate to a motion over a mean tropospheric layer rather than to a traditionally assigned discrete level. The height assignment behavioral characteristics are specifically identified according to AMV height (high cloud vs low cloud), type (spectral bands; clear vs cloudy), geolocation, height assignment method, and amount of environmental vertical wind shear present. The findings have potentially important implications for data assimilation of AMVs, and these are discussed.
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contributor author | Velden, Christopher S. | |
contributor author | Bedka, Kristopher M. | |
date accessioned | 2017-06-09T16:22:29Z | |
date available | 2017-06-09T16:22:29Z | |
date copyright | 2009/03/01 | |
date issued | 2009 | |
identifier issn | 1558-8424 | |
identifier other | ams-66700.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4208064 | |
description abstract | This study investigates the assignment of pressure heights to satellite-derived atmospheric motion vectors (AMVs), commonly known as cloud-drift and water vapor?motion winds. Large volumes of multispectral AMV datasets are compared with collocated rawinsonde wind profiles collected by the U.S. Department of Energy Atmospheric Radiation Measurement Program at three geographically disparate sites: the southern Great Plains, the North Slope of Alaska, and the tropical western Pacific Ocean. From a careful analysis of these comparisons, the authors estimate that mean AMV observation errors are ?5?5.5 m s?1 and that vector height assignment is the dominant factor in AMV uncertainty, contributing up to 70% of the error. These comparisons also reveal that in most cases the RMS differences between matched AMVs and rawinsonde wind values are minimized if the rawinsonde values are averaged over specified layers. In other words, on average, the AMV values better correlate to a motion over a mean tropospheric layer rather than to a traditionally assigned discrete level. The height assignment behavioral characteristics are specifically identified according to AMV height (high cloud vs low cloud), type (spectral bands; clear vs cloudy), geolocation, height assignment method, and amount of environmental vertical wind shear present. The findings have potentially important implications for data assimilation of AMVs, and these are discussed. | |
publisher | American Meteorological Society | |
title | Identifying the Uncertainty in Determining Satellite-Derived Atmospheric Motion Vector Height Attribution | |
type | Journal Paper | |
journal volume | 48 | |
journal issue | 3 | |
journal title | Journal of Applied Meteorology and Climatology | |
identifier doi | 10.1175/2008JAMC1957.1 | |
journal fristpage | 450 | |
journal lastpage | 463 | |
tree | Journal of Applied Meteorology and Climatology:;2009:;volume( 048 ):;issue: 003 | |
contenttype | Fulltext |