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.