气候变化领域集成服务门户(CCPortal): A Satellite-Derived Upper-Ocean Stratification Data Set for the Tropical North Atlantic With Potential Applications for Hurricane Intensity Prediction

CCPortal

DOI	10.1029/2019JC015980
	A Satellite-Derived Upper-Ocean Stratification Data Set for the Tropical North Atlantic With Potential Applications for Hurricane Intensity Prediction
	Da N.D.; Foltz G.R.; Balaguru K.
发表日期	2020
ISSN	21699275
卷号	125 期号:10
英文摘要	Upper-ocean stratification strongly impacts vertical mixing and the heat flux between the ocean and atmosphere, especially under extreme conditions of tropical cyclones (TCs). Knowledge of prestorm stratification is important for accurate TC intensity prediction. In situ observations of the tropical ocean have significantly increased in the past decade. However, they are still too sparse to resolve ocean stratification variability in near-real time and on small spatial scales. In this study, based on long-term observations and an ocean reanalysis data set from 2004–2017, we investigate the possibility of retrieving upper-ocean stratification from sea surface temperature (SST), sea surface salinity (SSS), and sea surface height (SSH) using a simple regression method. It is found that more than 90% of the mean seasonal cycle and about 30% to 80% of temperature and salinity stratification anomalies can be reconstructed using surface data from either observations or an ocean reanalysis. Simple regression can be used with satellite observations to create a high-resolution, near-real-time-gridded ocean stratification data set that successfully reproduces both the large and mesoscale variability of ocean stratification. When used in a simple expression for TC-induced SST cooling, the satellite-derived stratification shows improvements over an ocean analysis in terms of variance explained of SST cooling, offering promise as a near-real-time indicator of the ocean's impact on TC intensification. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	ocean stratification data set; SMOS satellite salinity; tropical cyclone
语种	英语
来源期刊	Journal of Geophysical Research: Oceans
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/186655
作者单位	Cooperative Institute for Marine and Atmospheric Studies (CIMAS), Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, United States; Atlantic Oceanographic and Meteorological Laboratory (AOML), National Oceanic and Atmospheric Administration, Miami, FL, United States; Marine Sciences Laboratory, Pacific Northwest National Laboratory (PNNL), Seattle, WA, United States
推荐引用方式 GB/T 7714	Da N.D.,Foltz G.R.,Balaguru K.. A Satellite-Derived Upper-Ocean Stratification Data Set for the Tropical North Atlantic With Potential Applications for Hurricane Intensity Prediction[J],2020,125(10).
APA	Da N.D.,Foltz G.R.,&Balaguru K..(2020).A Satellite-Derived Upper-Ocean Stratification Data Set for the Tropical North Atlantic With Potential Applications for Hurricane Intensity Prediction.Journal of Geophysical Research: Oceans,125(10).
MLA	Da N.D.,et al."A Satellite-Derived Upper-Ocean Stratification Data Set for the Tropical North Atlantic With Potential Applications for Hurricane Intensity Prediction".Journal of Geophysical Research: Oceans 125.10(2020).