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

Authors

• Amir Ouyed, University of Arizona
• Nadia Smith, Science and Technology Corporation
• Xubin Zeng, University of Arizona
• Thomas Galarneau Jr., NOAA/OAR National Severe Storms Laboratory
• Hui Su, University of California, Los Angeles
• Ross D. Dixon, University of Nebraska - LincolnFollow

Document Type

Article

Date of this Version

2-26-2023

Citation

Ouyed, A., Smith, N., Zeng, X., Galarneau, T. Jr., Su, H., & Dixon, R. D. (2023). Global three-dimensional water vapor feature-tracking for horizontal winds using hyperspectral infrared sounder data from overlapped tracks of two satellites. Geophysical Research Letters, 50, e2022GL101830. https://doi. org/10.1029/2022GL101830

Comments

Open access.

Abstract

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 nine pressure levels at 1° grid spacing from 70°N to 70°S. The retrieval is done by tracking water vapor from the hyperspectral Cross-track Infrared Sounder aboard two polar satellites (NOAA-20 and Suomi-NPP) that have overlapped tracks separated by 50 min. 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.