Journal article 51 views 36 downloads
Satellite-based time-series of sea-surface temperature since 1980 for climate applications
Owen Embury 
,
Christopher J. Merchant ,
Simon A. Good ,
Nick A. Rayner ,
Jacob L. Høyer ,
Chris Atkinson ,
Thomas Block ,
Emy Alerskans ,
Kevin Pearson ,
Mark Worsfold ,
Niall McCarroll,
Craig Donlon
,
Christopher J. Merchant ,
Simon A. Good ,
Nick A. Rayner ,
Jacob L. Høyer ,
Chris Atkinson ,
Thomas Block ,
Emy Alerskans ,
Kevin Pearson ,
Mark Worsfold ,
Niall McCarroll,
Craig Donlon
Scientific Data, Volume: 11, Issue: 1
Swansea University Author:
Kevin Pearson
-
PDF | Version of Record
© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License.
Download (2.99MB)
DOI (Published version): 10.1038/s41597-024-03147-w
Abstract
A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high degree of independence from in situ measurements. Observations from twenty infrared and two microwave radiometers are used, and are adjusted for thei...
| Published in: | Scientific Data |
|---|---|
| ISSN: | 2052-4463 |
| Published: |
Springer Science and Business Media LLC
2024
|
| Online Access: |
Check full text
|
| URI: | https://cronfa.swan.ac.uk/Record/cronfa69081 |
| Abstract: |
A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high degree of independence from in situ measurements. Observations from twenty infrared and two microwave radiometers are used, and are adjusted for their differing times of day of measurement to avoid aliasing and ensure observational stability. A total of 1.5 × 1013 locations are processed, yielding 1.4 × 1012 SST observations deemed to be suitable for climate applications. The corresponding observation density varies from less than 1 km−2 yr−1 in 1980 to over 100 km−2 yr−1 after 2007. Data are provided at their native resolution, averaged on a global 0.05° latitude-longitude grid (single-sensor with gaps), and as a daily, merged, gap-free, SST analysis at 0.05°. The data include the satellite-based SSTs, the corresponding time-and-depth standardised estimates, their standard uncertainty and quality flags. Accuracy, spatial coverage and length of record are all improved relative to a previous version, and the timeseries is routinely extended in time using consistent methods. |
|---|---|
| College: |
Faculty of Science and Engineering |
| Funders: |
Te authors gratefully acknowledge funding for this work as follows. Te European Space Agency supported three phases of the Climate Change Initiative for Sea Surface Temperature, and has provided the majority of the support leading to the outcomes herein described, via contracts 4000101570/10/I-AM, 4000109848/13/I-NB and 4000126471/19/I-NB. Te Copernicus Climate Change Service funded ICDR developments between 2017 and 2022 under frameworks: 2016/C3S_312a_Lot3_TVUK, 2018/C3S_312b_Lot3_CLS, and 2021/C3S2_312a_Lot3_
METNorway. From 2023 onwards the ICDR is funded by the Natural Environment Research Council (NERC) under grant NE/X019071/1 (EOCIS) and the UK Marine and Climate Advisory Service (UKMCAS), beneftting from the Earth Observation Investment Package of the Department of Science, Innovation and Technology.
Additional development of the SLSTR algorithms was funded by the European Organization for the Exploitation of Meteorological Satellites, grant numbers EUM/CO/20/4600002392/GKC and EUM/CO/21/4600002531/AOC, and ESA under grant 4000111836/14/I-LG. Development of the AVHRR bias-aware method was supported by: the National Centre for Earth Observation (UK) core science programme; the Visiting Scientist programme of the Ocean and Sea Ice Satellite Application Facility of EUMETSAT (OSI_VS18_03); and UK EPSRC Grant No. EP/P002331/1 “Data Assimilation for the Resilient City” (DARE). Foundational work has been supported by the Natural Environment Research Council (NERC) grants: NE/C508893/1, NE/D001129/1, NE/H004130/1 and NE/D011582/1. Use of the Centre for Environmental Data Analysis computational facilities been supported in part by the NERC National Centre for Earth Observation. |
| Issue: |
1 |