Editorial for Special Issue "Tropical Cyclones Remote Sensing and Data Assimilation"

被引:0
作者
Stiles, Bryan W. [1 ]
Portabella, Marcos [2 ]
Yang, Xiaofeng [3 ]
Zheng, Gang [4 ]
机构
[1] CALTECH, Prop Lab, 4800 Oak Grove Dr, Pasadena, CA 91109 USA
[2] Inst Marine Sci ICM CSIC, Pg Maritim Barceloneta 37-49, Barcelona 08003, Spain
[3] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Aerosp Informat Res Inst, 20A Datun Rd, Beijing 100101, Peoples R China
[4] Minist Nat Resources, Inst Oceanog 2, State Key Lab Satellite Ocean Environm Dynam, 36 Baochubei Rd, Hangzhou 310012, Peoples R China
关键词
D O I
10.3390/rs12183067
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Tropical cyclones (TCs) are essential for many reasons, including their destruction of human lives and property and their effect on heat and nutrient fluxes between the ocean's surface and its depths. A better understanding of ocean fluxes is needed to predict the impact of global climate change on the oceans and to quantify how ocean heat content modulates the dynamics of global climate change. Similarly, improved modeling of nutrient fluxes is crucial for maintaining fisheries and preserving crucial marine ecosystems to benefit both humanity and marine life. Numerous remote sensors measure crucial geophysical quantities before, during, and after TCs, including sea surface temperature (SST), ocean color, chlorophyll concentration, ocean surface winds, sea surface height, and significant wave height. In this special issue, an international group of researchers have written articles describing (1) novel techniques and remote sensors for measuring the aforementioned quantities in tropical cyclones, (2) methods for validating and improving the accuracy of those measurements and harmonizing them among different sensors, (3) scientific analyses that investigate the relationships between remote-sensed ocean surface measurements and in situ measurements of vertical profiles of ocean temperature, salinity, and current, and (4) strategies for utilizing remote-sensed measurements to improve operational forecasts in order to provide better tropical cyclone warnings to human populations.
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页数:4
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