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Observing Typhoons from Satellite-Derived Images

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Part of the book series: Springer Natural Hazards ((SPRINGERNAT))

Abstract

This chapter compares the typhoon centers from the tropical cyclone best track (BT) datasets of three meteorological agencies and those from synthetic aperture radar (SAR) and infrared (IR) images. First, we carried out algorithm comparison, using two newly developed and one existing wavelet-based algorithms, which were used to extract typhoon eyes in six SAR images and two IR images. These case studies showed that the extracted eyes by the three algorithms are consistent with each other. The differences among them are relatively small. However, there is a systematic difference between these extracted centers and the typhoon centers from the three BT datasets, which are interpolated to the imaging times first. We then compared the typhoon centers determined from 25 SAR and 43 IR images with those from the three BT datasets to investigate the performance of the latter at the sea surface and at the cloud top, respectively. We found the typhoon centers from the three BT datasets are generally closer to the locations extracted from the SAR images showing sea surface imprints of the typhoons than those from the IR images showing cloud top structures of the typhoons. We also evaluate the effect caused by rain to the SAR wind field retrieval. By using RADARSAT-2 data, National Centers for Environmental Prediction (NCEP) reanalysis data and Tropical Rainfall Measuring Mission satellite (TRMM) precipitation radar rainfall data, rain-induced attenuation, raindrop volumetric scattering are calculated and the perturbation of the water surface is simulated by rainfall and incident angle. The performance of this model is further proved by one typhoon case.

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Correspondence to Gang Zheng .

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Zheng, G. et al. (2017). Observing Typhoons from Satellite-Derived Images. In: Li, X. (eds) Hurricane Monitoring With Spaceborne Synthetic Aperture Radar. Springer Natural Hazards. Springer, Singapore. https://doi.org/10.1007/978-981-10-2893-9_9

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