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Remote Sensing for Improved Forecast of Typhoons

  • Yuei-An Liou
  • Ji-Chyun Liu
  • Fabrice Chane-Ming
  • Jing-Shan Hong
  • Ching-Yuang Huang
  • Po-Kuan Chiang
  • Samuel Jolivet
Chapter

Abstract

This chapter presents the advantages of remote sensing in various aspects of tropical cycles or typhoons for the purpose of improved forecasts. A variety of variables influencing the typhoons become our concerns and sequentially investigated. First of all, to effectively predict the rainfall associated with a landfalling typhoon, the ground-based Global Positioning System (GPS) zenith total delay is combined with Doppler radar data through data assimilation algorithms. Subsequently, discussions on a natural phenomenon of interactions among two typhoons with and without tropical depressions (TDs) are elaborated. Remote sensing imagery and image processing techniques are applied to analyze relevant interactions and physical responses, including TDs’ appearance, development, interaction and how they merge. Then, the application of remote sensing observational data in numerical modeling for the study of atmospheric gravity waves, especially during the occurrence of asymmetric tropical cyclones is presented. Finally, a brief introduction is given to the oceanic surface wind measurement from different satellites with already demonstrated or potential impacts on typhoon simulations and predictions. Note that atmospheric and oceanic parameters derived from observations of Global Navigation Satellite System (GNSS) receivers onboard low Earth orbit (LEO) satellites, i.e., FORMOSAT-3/COSMIC and to-be-launched FORMOSAT-7/COSMIC-2, are also discussed within the selected topics. The importance of implementing remote sensing technology in the investigation and forecast of typhoons is the conclusion.

Keywords

Remote sensing Typhoon Forecast Atmospheric gravity wave GPS GNSS-R 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Yuei-An Liou
    • 1
    • 2
  • Ji-Chyun Liu
    • 3
  • Fabrice Chane-Ming
    • 4
  • Jing-Shan Hong
    • 5
  • Ching-Yuang Huang
    • 2
    • 6
  • Po-Kuan Chiang
    • 1
    • 2
  • Samuel Jolivet
    • 7
  1. 1.Center for Space and Remote Sensing ResearchNational Central UniversityTaoyuanTaiwan
  2. 2.Taiwan Group on Earth ObservationsZhubeiTaiwan
  3. 3.Electrical Engineering DepartmentChien Hsin University of Science and TechnologyTaoyuanTaiwan
  4. 4.Laboratoire de l’Atmosphère et des CyclonesUniversité de la RéunionLa RéunionFrance
  5. 5.Central Weather BureauTaipeiTaiwan
  6. 6.Department of Atmospheric SciencesNational Central UniversityTaoyuanTaiwan
  7. 7.MeteobookingBossonnensSwitzerland

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