气候变化领域集成服务门户(CCPortal): Construction of a climate data record of sea surface temperature from passive microwave measurements

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DOI	10.1016/j.rse.2019.111485
	Construction of a climate data record of sea surface temperature from passive microwave measurements
	Alerskans E.; Høyer J.L.; Gentemann C.L.; Pedersen L.T.; Nielsen-Englyst P.; Donlon C.
发表日期	2020
ISSN	00344257
卷号	236
英文摘要	A statistical regression-based microwave sea surface temperature (SST) retrieval algorithm has been developed within the European Space Agency Climate Change Initiative (ESA-CCI) SST project. The retrieval algorithm was used to generate a climate data record (CDR) of passive microwave (PMW) SST from the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) and its follow-on instrument AMSR2 for the period June 2002–October 2017. Multisensor Matchup Datasets (MMDs), which includes satellite orbital data collocated with in situ and auxiliary data, was used to derive consistent algorithms for AMSR-E and AMSR2. The retrieval algorithms consist of wind speed (WS) retrievals and SST retrievals, with corresponding uncertainty retrievals. The WS retrieval consists of a two-step regression model, where the second step is a localized algorithm, trained to perform well over restricted WS intervals. A two-step multiple linear regression retrieval with localized algorithms is used to retrieve SST. The first-stage algorithm is trained to perform well over restricted latitude intervals for ascending and descending orbit, respectively, whereas the second-stage retrieval uses localized SST and WS algorithms. Furthermore, a new and effective method for detecting and screening for Radio Frequency Interference (RFI) was developed. Validation of the PMW SSTs against drifter in situ SSTs shows an overall bias of −0.02 K for quality level (QL) 4 and 5 AMSR-E retrievals with a standard deviation of 0.46 K. Validation results for QL 4 and 5 AMSR2 retrievals against drifter in situ SSTs give a bias of 0.002 K and a standard deviation of 0.45 K. The corresponding mean modelled SST uncertainties, including in situ and sampling uncertainties, are estimated to 0.45 K for QL 4 and 5 AMSR-E retrievals and 0.44 K for QL 4 and 5 AMSR2 retrievals. Validation against near-surface temperature measurements from Argo floats yielded comparable results, confirming the drifting-buoy validation. The validation results demonstrate a consistent PMW SST CDR with accurate SST observations and reliable uncertainty estimates. © 2019 Elsevier Inc.
英文关键词	AMSR-E; AMSR2; Climate data record; Microwave; Remote sensing; Sea surface temperature
语种	英语
scopus关键词	Atmospheric temperature; Climate change; Clock and data recovery circuits (CDR circuits); Linear regression; Microwaves; Orbits; Radio interference; Remote sensing; Search engines; Statistics; Submarine geophysics; Surface properties; Surface waters; Temperature measurement; Uncertainty analysis; Wind; Advanced microwave scanning radiometer; AMSR2; Climate data records; Multiple linear regressions; Near surface temperature; Passive microwave measurements; Radio frequency interference; Sea surface temperature (SST); Oceanography; air sampling; algorithm; AMSR-E; Argo; data set; drifter; EOS; in situ measurement; measurement method; multiple regression; remote sensing; sampling; satellite data; sea surface temperature; uncertainty analysis
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179571
作者单位	Danish Meteorological Institute, Lyngbyvej 100, Copenhagen Ø, DK-2100, Denmark; Earth and Space Research, Seattle, WA 98121, United States; DTU-Space, Technical University of Denmark, Lyngby, DK-2800, Denmark; European Space Agency/European Space Research and Technology Centre (ESA/ESTEC), Noordwijk, AZ 2201, Netherlands
推荐引用方式 GB/T 7714	Alerskans E.,Høyer J.L.,Gentemann C.L.,et al. Construction of a climate data record of sea surface temperature from passive microwave measurements[J],2020,236.
APA	Alerskans E.,Høyer J.L.,Gentemann C.L.,Pedersen L.T.,Nielsen-Englyst P.,&Donlon C..(2020).Construction of a climate data record of sea surface temperature from passive microwave measurements.Remote Sensing of Environment,236.
MLA	Alerskans E.,et al."Construction of a climate data record of sea surface temperature from passive microwave measurements".Remote Sensing of Environment 236(2020).