L. Carr, J.; L. Wu, D.; A. Kelly, M.; Gong, J. MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds. Remote Sens.2018, 10, 1885.
L. Carr, J.; L. Wu, D.; A. Kelly, M.; Gong, J. MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds. Remote Sens. 2018, 10, 1885.
L. Carr, J.; L. Wu, D.; A. Kelly, M.; Gong, J. MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds. Remote Sens.2018, 10, 1885.
L. Carr, J.; L. Wu, D.; A. Kelly, M.; Gong, J. MISR-GOES 3D Winds: Implications for Future LEO-GEO and LEO-LEO Winds. Remote Sens. 2018, 10, 1885.
Abstract
Global wind observations are fundamental for studying weather and climate dynamics. 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 around the planetary boundary layer (PBL) and with tropopause folding. 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 GEO-GEO 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.
Environmental and Earth Sciences, Atmospheric Science and Meteorology
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