Atmospheric Motion Vector Retrieval Using the Total Variation-Based Optical Flow Method

Igor Yanovsky, Derek Posselt, Longtao Wu, Svetla Hristova-Veleva, Hai Nguyen, Bjorn Lambrigtsen, Xubin Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Atmospheric motion vector (AMV) retrieval from water vapor measurements is important in climate research and weather forecasting. However, conventional feature tracking methods for AMV retrievals generate velocity fields with gaps and large errors. In this work, we test the optical flow algorithm by generating a nature run of a convective weather phenomenon, which provides water vapor variables and wind vector fields at various pressure levels. We show that our optical flow algorithm generates superior performance when compared with traditional feature tracking algorithms used in operational centers, generating dense AMVs with no gaps and significantly improving AMV accuracy. The optical flow algorithm performs well down to very low wind speeds and does not require a low-wind cutoff threshold. In our studies, we considered various measurement configurations, including water vapor retrievals at different temporal resolutions and found that the optical flow algorithm is not sensitive to the time interval between images.

Original languageEnglish (US)
Title of host publicationIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3780-3783
Number of pages4
ISBN (Electronic)9798350320107
DOIs
StatePublished - 2023
Event2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023 - Pasadena, United States
Duration: Jul 16 2023Jul 21 2023

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2023-July

Conference

Conference2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023
Country/TerritoryUnited States
CityPasadena
Period7/16/237/21/23

Keywords

  • Atmospheric motion vector retrieval
  • feature tracking
  • optical flow
  • total variation
  • water vapor

ASJC Scopus subject areas

  • Computer Science Applications
  • General Earth and Planetary Sciences

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