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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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Cites
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V., Rowell, D. P., Kent, E. C., & Kaplan, A. (2003) · Journal of Geophysical Research Atmospheres · doi:10.1029/2002jd002670 · Cited by 11,133
Daily High-Resolution-Blended Analyses for Sea Surface Temperature
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., & Schlax, M. G. (2007) · Journal of Climate · doi:10.1175/2007jcli1824.1 · Cited by 4,435
A new dynamical core for the Met Office's global and regional modelling of the atmosphere
Davies, T., Cullen, M., Malcolm, A. J., Mawson, M. H., Staniforth, A. N., White, A. A., & Wood, N. (2005) · Quarterly Journal of the Royal Meteorological Society · doi:10.1256/qj.04.101 · Cited by 1,000
Comparative performance of AVHRR‐based multichannel sea surface temperatures
McClain, E. P., Pichel, W. G., & Walton, C. C. (1985) · Journal of Geophysical Research Atmospheres · doi:10.1029/jc090ic06p11587 · Cited by 969
The Global Monitoring for Environment and Security (GMES) Sentinel-3 mission
Donlon, C. J., Berruti, B., Buongiorno, A., Ferreira, M.-H., Féménias, P., Frerick, J., Goryl, P., Klein, U., Laur, H., Mavrocordatos, C., et al. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2011.07.024 · Cited by 848
Self-citationAir–sea interaction over ocean fronts and eddies
Small, J., de Szoeke, S. P., Xie, S., O’Neill, L. W., Seo, H., Song, Q., Cornillon, P., Spall, M. A., & Minobe, S. (2008) · Dynamics of Atmospheres and Oceans · doi:10.1016/j.dynatmoce.2008.01.001 · Cited by 834
Satellite measurements of sea surface temperature through clouds
Wentz, F., Gentemann, C., Smith, D. K., & Chelton, D. (2000) · Science · doi:10.1126/science.288.5467.847 · Cited by 766
Quality control of ocean temperature and salinity profiles — Historical and real-time data
Ingleby, B., & Huddleston, M. R. (2006) · Journal of Marine Systems · doi:10.1016/j.jmarsys.2005.11.019 · Cited by 512
Skill Assessment for Coupled Biological/Physical Models of Marine Systems.
Stow, C., Jolliff, J., McGillicuddy, D. J., Doney, S., Allen, J., Friedrichs, M. A. M., Rose, K., & Wallhead, P. (2009) · Journal of Marine Systems · doi:10.1016/j.jmarsys.2008.03.011 · Cited by 487
The Global Ocean Data Assimilation Experiment High-resolution Sea Surface Temperature Pilot Project
Donlon, C. J., Robinson, I. S., Casey, K. S., Vázquez, J., Armstrong, E., Arinò, O., Gentemann, C. L., May, D., Borgne, P. L., Piollé, J., et al. (2007) · Bulletin of the American Meteorological Society · doi:10.1175/bams-88-8-1197 · Cited by 415
Self-citation
Research works printed but not linked: 5
- Cayula, 2004, Reliability estimates for real-time sea surface temperature, Sea Technology, 45, 67
- Edwards, 2000, Metop: The space segment for Eumetsat's polar system, ESA Bulletin, 102, 6
- Lobl, 2001, Joint advanced microwave scanning radiometer (AMSR) science team meeting, Earth Observer, 13, 3
- Mironov, 2010, Towards improved representation of lakes in numerical weather prediction and climate models: Introduction to the special edition of Boreal Environmental Research, Boreal Environmental Research, 15, 97
- Reynolds, 2002, An improved in situ and satellite SST analysis for climate, Journal of Climate, 15, 1609, 10.1175/1520-0442(2002)015<1609:AIISAS>2.0.CO;2 · DOI
Cited by
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Brossier, C. L., Léger, F., Giordani, H., Beuvier, J., Bouin, M., Ducrocq, V., & Fourrié, N. (2017) · Journal of Geophysical Research Oceans · doi:10.1002/2016jc012526 · Cited by 25
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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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