Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

2018 Atmospheric Motion Vector (AMV) Intercomparison Study

David Santek
* ,
Richard Dworak
* ,
Sharon Nebuda
* ,
Steve Wanzong
* ORCID logo ,
Régis Borde
* ,
Iliana Genkova
* ,
Javier García-Pereda
* ,
Renato Galante Negri
* ,
Manuel Carranza
* ,
Kenichi Nonaka
* ,
Kazuki Shimoji
* ,
Soo Min Oh
* ORCID logo ,
Byung-Il Lee
* ,
Sung-Rae Chung
* ,
Jaime Daniels
* ORCID logo ,
Wayne Bresky
*
Version 1 : Received: 31 July 2019 / Approved: 2 August 2019 / Online: 2 August 2019 (05:44:19 CEST)

A peer-reviewed article of this Preprint also exists.

Santek, D.; Dworak, R.; Nebuda, S.; Wanzong, S.; Borde, R.; Genkova, I.; García-Pereda, J.; Galante Negri, R.; Carranza, M.; Nonaka, K.; Shimoji, K.; Oh, S.M.; Lee, B.-I.; Chung, S.-R.; Daniels, J.; Bresky, W. 2018 Atmospheric Motion Vector (AMV) Intercomparison Study. Remote Sens. 2019, 11, 2240. Santek, D.; Dworak, R.; Nebuda, S.; Wanzong, S.; Borde, R.; Genkova, I.; García-Pereda, J.; Galante Negri, R.; Carranza, M.; Nonaka, K.; Shimoji, K.; Oh, S.M.; Lee, B.-I.; Chung, S.-R.; Daniels, J.; Bresky, W. 2018 Atmospheric Motion Vector (AMV) Intercomparison Study. Remote Sens. 2019, 11, 2240.

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/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) JMA AMV algorithm has the best overall performance considering all validation metrics, most likely due to its height assignment: “optimal estimation using observed radiance and NWP wind vertical profile”.

Keywords

atmospheric motion vectors; AMVs; intercomparison; himawari; CPTEC/INPE; EUMETSAT; JMA; KMA; NOAA; NWCSAF

Subject

Environmental and Earth Sciences, Atmospheric Science and Meteorology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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