Global Three-Dimensional Water Vapor Feature-Tracking For Horizontal Winds Using Hyper-Spectral Infrared Sounder Data From Overlapped Tracks of Two Satellites

Amir Ouyed, Department of Hydrology and Atmospheric Sciences, University of Arizona

  • Nadia Smith, Science and Technology Corporation

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  • Xubin Zeng, Department of Hydrology and Atmospheric Sciences, University of Arizona

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  • Thomas Galarneau Jr., NOAA/OAR National Severe Storms Laboratory

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  • Hui Su, Department of Atmospheric and Oceanic Sciences, University of California—Los Angeles

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  • Ross D. Dixon, Department of Earth and Atmospheric Sciences, University of Nebraska—Lincoln

The lack of measurements of three-dimensional (3D) distribution of horizontal wind vectors is a major challenge in atmospheric science. Here we develop an algorithm to retrieve winds for 9 pressure levels at 1◦ grid spacing from 70◦N to 70◦S. The retrieval is done by tracking water vapor from the hyper-spectral Cross-track Infrared Sounder aboard two polar satellites (NOAA-20 and Suomi-NPP) that have overlapped tracks separated by 50 minutes. We impose a gross error check by flagging retrievals that are too different from ERA-5 reanalysis. Testing the algorithm for the first week of January and July 2020 indicates that our algorithm yields 104 wind profiles per day and these 3D winds qualitatively agree with ERA-5. Compared with radiosonde data, the errors are within the range of reported errors of cloud-tracking winds.