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Remote Sens. 2018, 10(1), 126; https://doi.org/10.3390/rs10010126

Stability Assessment of the (A)ATSR Sea Surface Temperature Climate Dataset from the European Space Agency Climate Change Initiative

1
National Oceanography Centre, University of Southampton Waterfront Campus, European Way, Southampton SO14 3ZH, UK
2
Department of Physics and Astronomy, University of Leicester, University Road, Leicester LE1 7RH, UK
3
National Centre for Earth Observation, University of Leicester, University Road, Leicester LE1 7RH, UK
4
Department of Meteorology, University of Reading, Reading RG6 6AL, UK
5
National Centre for Earth Observation, University of Reading, Reading RG6 6AL, UK
*
Author to whom correspondence should be addressed.
Received: 24 November 2017 / Revised: 11 January 2018 / Accepted: 15 January 2018 / Published: 18 January 2018
(This article belongs to the Collection Sea Surface Temperature Retrievals from Remote Sensing)
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Abstract

Sea surface temperature is a key component of the climate record, with multiple independent records giving confidence in observed changes. As part of the European Space Agencies (ESA) Climate Change Initiative (CCI) the satellite archives have been reprocessed with the aim of creating a new dataset that is independent of the in situ observations, and stable with no artificial drift (<0.1 K decade−1 globally) or step changes. We present a method to assess the satellite sea surface temperature (SST) record for step changes using the Penalized Maximal t Test (PMT) applied to aggregate time series. We demonstrated the application of the method using data from version EXP1.8 of the ESA SST CCI dataset averaged on a 7 km grid and in situ observations from moored buoys, drifting buoys and Argo floats. The CCI dataset was shown to be stable after ~1994, with minimal divergence (~0.01 K decade−1) between the CCI data and in situ observations. Two steps were identified due to the failure of a gyroscope on the ERS-2 satellite, and subsequent correction mechanisms applied. These had minimal impact on the stability due to having equal magnitudes but opposite signs. The statistical power and false alarm rate of the method were assessed. View Full-Text
Keywords: Along Track Scanning Radiometer (ATSR); sea surface temperature; stability; homogeneity; drifting buoys; Argo; Global Tropical Moored buoy Array (GTMBA); Penalized Maximal t Test Along Track Scanning Radiometer (ATSR); sea surface temperature; stability; homogeneity; drifting buoys; Argo; Global Tropical Moored buoy Array (GTMBA); Penalized Maximal t Test
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Berry, D.I.; Corlett, G.K.; Embury, O.; Merchant, C.J. Stability Assessment of the (A)ATSR Sea Surface Temperature Climate Dataset from the European Space Agency Climate Change Initiative. Remote Sens. 2018, 10, 126.

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