MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds

Global wind observations are fundamental for studying weather and climate dynamics and for operational forecasting. Most wind measurements come from atmospheric motion vectors (AMVs) by tracking the displacement of cloud or water vapor features. These AMVs generally rely on thermal infrared (IR) tec...

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Main Authors: James L. Carr, Dong L. Wu, Michael A. Kelly, Jie Gong
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/10/12/1885
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spelling doaj-6496d1ad85774d76a2524c790110893d2020-11-24T22:58:24ZengMDPI AGRemote Sensing2072-42922018-11-011012188510.3390/rs10121885rs10121885MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO WindsJames L. Carr0Dong L. Wu1Michael A. Kelly2Jie Gong3Carr Astronautics, 6404 Ivy Lane, Suite 333, Greenbelt, MD 20770, USANASA Goddard Space Flight Center, Greenbelt, MD 20770, USAJohns Hopkins Applied Physics Laboratory, Laurel, MD 20723, USANASA Goddard Space Flight Center, Greenbelt, MD 20770, USAGlobal wind observations are fundamental for studying weather and climate dynamics and for operational forecasting. Most wind measurements come from atmospheric motion vectors (AMVs) by tracking the displacement of cloud or water vapor features. These AMVs generally rely on thermal infrared (IR) techniques for their height assignments, which are subject to large uncertainties in the presence of weak or reversed vertical temperature gradients near the planetary boundary layer (PBL) and tropopause folds. Stereo imaging can overcome the height assignment problem using geometric parallax for feature height determination. In this study we develop a stereo 3D-Wind algorithm to simultaneously retrieve AMV and height from geostationary (GEO) and low Earth orbit (LEO) satellite imagery and apply it to collocated Geostationary Operational Environmental Satellite (GOES) and Multi-angle Imaging SpectroRadiometer (MISR) imagery. The new algorithm improves AMV and height relative to products from GOES or MISR alone, with an estimated accuracy of <0.5 m/s in AMV and <200 m in height with 2.2 km sampling. The algorithm can be generalized to other LEO-GEO or LEO-LEO combinations for greater spatiotemporal coverage. The technique demonstrated with MISR and GOES has important implications for future high-quality AMV observations, for which a low-cost constellation of CubeSats can play a vital role.https://www.mdpi.com/2072-4292/10/12/18853D-Windsatmospheric motion vectors (AMVs)MISRGOES-Rplanetary boundary layer (PBL)stereo imagingparallaxCubeSats
collection DOAJ
language English
format Article
sources DOAJ
author James L. Carr
Dong L. Wu
Michael A. Kelly
Jie Gong
spellingShingle James L. Carr
Dong L. Wu
Michael A. Kelly
Jie Gong
MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds
Remote Sensing
3D-Winds
atmospheric motion vectors (AMVs)
MISR
GOES-R
planetary boundary layer (PBL)
stereo imaging
parallax
CubeSats
author_facet James L. Carr
Dong L. Wu
Michael A. Kelly
Jie Gong
author_sort James L. Carr
title MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds
title_short MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds
title_full MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds
title_fullStr MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds
title_full_unstemmed MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds
title_sort misr-goes 3d winds: implications for future leo-geo and leo-leo winds
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2018-11-01
description Global wind observations are fundamental for studying weather and climate dynamics and for operational forecasting. Most wind measurements come from atmospheric motion vectors (AMVs) by tracking the displacement of cloud or water vapor features. These AMVs generally rely on thermal infrared (IR) techniques for their height assignments, which are subject to large uncertainties in the presence of weak or reversed vertical temperature gradients near the planetary boundary layer (PBL) and tropopause folds. Stereo imaging can overcome the height assignment problem using geometric parallax for feature height determination. In this study we develop a stereo 3D-Wind algorithm to simultaneously retrieve AMV and height from geostationary (GEO) and low Earth orbit (LEO) satellite imagery and apply it to collocated Geostationary Operational Environmental Satellite (GOES) and Multi-angle Imaging SpectroRadiometer (MISR) imagery. The new algorithm improves AMV and height relative to products from GOES or MISR alone, with an estimated accuracy of <0.5 m/s in AMV and <200 m in height with 2.2 km sampling. The algorithm can be generalized to other LEO-GEO or LEO-LEO combinations for greater spatiotemporal coverage. The technique demonstrated with MISR and GOES has important implications for future high-quality AMV observations, for which a low-cost constellation of CubeSats can play a vital role.
topic 3D-Winds
atmospheric motion vectors (AMVs)
MISR
GOES-R
planetary boundary layer (PBL)
stereo imaging
parallax
CubeSats
url https://www.mdpi.com/2072-4292/10/12/1885
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