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The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system

The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system
The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system
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 10 km and 100 km. 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° (~ 6 km) although the smallest analysis feature resolution is based on the correlation length scale of 10 km. 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 diurnal variability and AATSR data are adjusted to represent the SST at the same depth as drifting buoy measurements (0.2–1 m) before bias adjustments are made. Global coverage outputs are provided each day in GHRSST L4 netCDF format. A variety of secondary products are also provided including weekly and monthly mean data sets. OSTIA products are continuously monitored and validation/verification activities demonstrate that SST products have zero mean bias and an accuracy of ~ 0.57 K compared to in situ measurements. OSTIA is now used operationally as a boundary condition for all weather forecast models at the Met Office and at European Centre for Medium-range Weather Forecasting (ECMWF). OSTIA is produced by the Met Office as part of the European Union Global Monitoring for Environment and Security (GMES) MyOcean project.
0034-4257
140-158
Donlon, Craig J.
b81d748d-4c2e-42d0-94c1-befc9cecf732
Martin, Matthew
85d62a4b-8bab-44ab-9d7a-810acaa60f89
Stark, John
cf8da964-ba02-4d93-b9d6-096fba5a31ab
Roberts-Jones, Jonah
4d267782-afae-4a3c-bcf0-a720dc142853
Fiedler, Emma
f9234242-185c-434e-8043-373f0f486149
Wimmer, Werenfrid
7b66c35e-5f83-4f95-82e3-5ced9614f28d
Donlon, Craig J.
b81d748d-4c2e-42d0-94c1-befc9cecf732
Martin, Matthew
85d62a4b-8bab-44ab-9d7a-810acaa60f89
Stark, John
cf8da964-ba02-4d93-b9d6-096fba5a31ab
Roberts-Jones, Jonah
4d267782-afae-4a3c-bcf0-a720dc142853
Fiedler, Emma
f9234242-185c-434e-8043-373f0f486149
Wimmer, Werenfrid
7b66c35e-5f83-4f95-82e3-5ced9614f28d

Donlon, Craig J., Martin, Matthew, Stark, John, Roberts-Jones, Jonah, Fiedler, Emma and Wimmer, Werenfrid (2012) The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system. Remote Sensing of Environment, 116, 140-158. (doi:10.1016/j.rse.2010.10.017).

Record type: Article

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 10 km and 100 km. 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° (~ 6 km) although the smallest analysis feature resolution is based on the correlation length scale of 10 km. 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 diurnal variability and AATSR data are adjusted to represent the SST at the same depth as drifting buoy measurements (0.2–1 m) before bias adjustments are made. Global coverage outputs are provided each day in GHRSST L4 netCDF format. A variety of secondary products are also provided including weekly and monthly mean data sets. OSTIA products are continuously monitored and validation/verification activities demonstrate that SST products have zero mean bias and an accuracy of ~ 0.57 K compared to in situ measurements. OSTIA is now used operationally as a boundary condition for all weather forecast models at the Met Office and at European Centre for Medium-range Weather Forecasting (ECMWF). OSTIA is produced by the Met Office as part of the European Union Global Monitoring for Environment and Security (GMES) MyOcean project.

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More information

Published date: 15 January 2012
Organisations: Physical Oceanography

Identifiers

Local EPrints ID: 208499
URI: https://eprints.soton.ac.uk/id/eprint/208499
ISSN: 0034-4257
PURE UUID: 5d3d0232-2fc0-4dab-8cf0-3030c2e2e602
ORCID for Werenfrid Wimmer: ORCID iD orcid.org/0000-0003-4693-1161

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Date deposited: 19 Jan 2012 13:33
Last modified: 15 Aug 2019 00:44

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Contributors

Author: Craig J. Donlon
Author: Matthew Martin
Author: John Stark
Author: Jonah Roberts-Jones
Author: Emma Fiedler

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