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2018 Atmospheric Motion Vector (AMV): intercomparison study
Title: 2018 Atmospheric Motion Vector (AMV): intercomparison study
Authors: Santek, DavidDworak, RichardNebuda, SharonWanzong, SteveBorde, RégisGenkova, IlianaGarcía Pereda, JavierAutor AEMETGalante Negri, RenatoCarranza, ManuelNonaka, KenichiShimoji, KazukiOh, Soo MinLee, Byung-IlChung, Sung-RaeDaniels, JaimeBresky, Wayne
Keywords: Atmospheric Motion Vectors (AMVs); Intercomparison; Himawari; CPTEC/INPE; EUMETSAT; JMA; KMA; NOAA; NWCSAF
Issue Date: 2019
Publisher: Multidisciplinary Digital Publishing Institute
Citation: Remote Sensing. 2019, 11(19), 2240
Publisher version:
Abstract: Atmospheric Motion Vectors (AMVs) calculated by six different institutions (Brazil Center for Weather Prediction and Climate Studies/CPTEC/INPE, European Organization for the Exploitation of Meteorological Satellites/EUMETSAT, Japan Meteorological Agency/JMA, Korea Meteorological Administration/KMA, Unites States National Oceanic and Atmospheric Administration/NOAA, and the Satellite Application Facility on Support to Nowcasting and Very short range forecasting/NWCSAF) with JMA’s Himawari-8 satellite data and other common input data are here compared. The comparison is based on two different AMV input datasets, calculated with two different image triplets for 21 July 2016, and the use of a prescribed and a specific configuration. The main results of the study are summarized as follows: (1) the differences in the AMV datasets depend very much on the ‘AMV height assignment’ used and much less on the use of a prescribed or specific configuration; (2) the use of the ‘Common Quality Indicator (CQI)’ has a quantified skill in filtering collocated AMVs for an improved statistical agreement between centers; (3) Among the six AMV operational algorithms verified by this AMV Intercomparison, JMA AMV algorithm has the best overall performance considering all validation metrics, mainly due to its new height assignment method: ‘Optimal estimation method considering the observed infrared radiances, the vertical profile of the Numerical Weather Prediction wind, and the estimated brightness temperature using a radiative transfer model’.
Sponsorship : The “Space Science and Engineering Center” (SSEC) of the “University ofWisconsin-Madison” (UW) was funded to do this research by the “European Organization for the Exploitation of Meteorological Satellites (EUMETSAT)”, through the “Satellite Application Facility on Support to Nowcasting and Very short range forecasting (NWCSAF)” “Visiting Scientist Activity (VSA)” program.
ISSN: 2072-4292
Appears in Collections:Artículos científicos 2019-2022

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