Improving Parametric Cyclonic Wind Fields Using CYGNSS (Cyclone Global Navigation Satellite System) Data
Abstract
Parametric cyclonic wind fields are widely used worldwide for insurance risk underwriting, coastal planning, or storm surge forecasts. They support high-stakes financial, development, and emergency decisions. Yet, there is still no consensus on the best parametric approach, or relevant guidance to choose among the great variety of published models. We show here that the Cyclone Global Navigation Satellite System (CYGNSS) mission of NASA is able to capture a substantial part of the tropical cyclones structure, and allows identifying systematic biases in a number of parametric models. Our results also suggest that none of the traditional empirical approaches can be considered as the best option in all cases. Rather, the choice of a parametric model depends on several criteria such as cyclone intensity and/or availability of wind radii information. The benefit of using satellite remote sensing data to better select a parametric model for a specific case study is tested here by simulating hurricane Maria (2017). The significant wave heights computed by a wave-current hydrodynamic coupled model are found to be in good accordance with the predictions given by the remote sensing data in terms of bias. The results and approach presented in this study should shed new light on how to handle parametric cyclonic wind models, and help the scientific community to conduct better wind, waves and surge analysis for tropical cyclones.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFMOS51D1279K
- Keywords:
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- 4504 Air/sea interactions;
- OCEANOGRAPHY: PHYSICALDE: 4512 Currents;
- OCEANOGRAPHY: PHYSICALDE: 4534 Hydrodynamic modeling;
- OCEANOGRAPHY: PHYSICALDE: 4564 Tsunamis and storm surges;
- OCEANOGRAPHY: PHYSICAL