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The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system
Abstract
This paper describes a new Sea surface temperature (SST) analysis that is produced with global coverage on a daily basis at the Met Office called the Operational SST and Sea Ice Analysis (OSTIA) system. OSTIA uses satellite SST data provided by international agencies via the Group for High Resolution SST (GHRSST) Regional/Global Task Sharing (R/GTS) framework. GHRSST products include data from microwave and infrared satellite instruments with accompanying uncertainty estimates. The system also uses in situ SST data available over the Global Telecommunications System (GTS) and a sea-ice concentration product from the EUMETSAT Ocean and Sea Ice Satellite Applications Facility (OSI-SAF). The SST analysis is a multi-scale optimal interpolation that is designed for applications in numerical weather prediction and ocean forecasting systems. The background error covariance matrix is specified using ocean model data and the analysis uses correlation length scales of 10km and 100km. The OSTIA system produces a foundation SST estimate (SSTfnd, which is the SST free of diurnal variability) at an output grid resolution of 1/20° (~6km) although the smallest analysis feature resolution is based on the correlation length scale of 10km. All satellite SST data are adjusted for bias errors based on a combination of ENVISAT Advanced Along Track Scanning Radiometer (AATSR) SST data and in situ SST measurements from drifting buoys. Data are filtered (based on surface wind speed data) to remove di…
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“Uncertainty information is also provided in the L4 products, which is estimated using an analysis quality method46.”
From Satellite-based time-series of sea-surface temperature since 1981 for climate applications (2019) · cites this paper as [46]
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Metadata
- Authors
- Donlon, C. J., Martin, M., Stark, J., Roberts-Jones, J., Fiedler, E., & Wimmer, W.
- Affiliations
- Met Office (GB)
- National Oceanography Centre (GB)
- Corresponding author
- Donlon, Craig J.
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 116
- Pages
- 140-158
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W1978648105
- Cited by
- 1,394
- References
- 66
- Citations by year
- 2026: 91 · 2025: 101 · 2024: 163 · 2023: 122 · 2022: 143 · 2021: 124 · 2020: 135 · 2019: 116 · 2018: 92 · 2017: 69 · 2016: 72 · 2015: 59 · 2014: 54 · 2013: 33 · 2012: 13
- FWCI
- 23.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Remote Sensing of Environment (publishedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- Topics
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Ocean Waves and Remote Sensing
- Keywords
- Ostia, sea ice concentration, optimal interpolation, satellite SST, GHRSST, AATSR, drifting buoys, background error covariance, ocean forecasting, SST validation
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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