Variability and uncertainty in measuring sea surface temperature

Sea Surface Temperature (SST) measurement is one of the most easily obtainable climate variables. However, it is challenging to meet the required absolute accuracy and long term stability whether the data are derived by in situ or satellite measurements. This study explores the quality of SST measur...

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Bibliographic Details
Main Author: Wimmer, Werenfrid
Other Authors: Robinson, Ian
Published: University of Southampton 2012
Subjects:
550
Online Access:https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.581497
Description
Summary:Sea Surface Temperature (SST) measurement is one of the most easily obtainable climate variables. However, it is challenging to meet the required absolute accuracy and long term stability whether the data are derived by in situ or satellite measurements. This study explores the quality of SST measurements, in particular those derived by the Advanced Along Track Scanning Radiometer (AATSR) and in situ measurements recorded by the shipborne Infrared Sea surface temperature Autonomous Radiometer (ISAR), which are used for validating AATSR data. Its broad objective is to improve understanding of measurement uncertainties in order to quantify the quality of satellite derived SST used for climate records. The uncertainties of in situ measurement by ISAR have been analysed and modelled in order to estimate an independent measurement uncertainty for every SST data point in the ISAR records. In a complementary study the separate uncertainties of the SST as observed by AATSR, ISAR and ship-based hull-mounted thermometry (SSTdepth), when observing the same track, have been resolved by means of three way uncertainty analysis. This not only serves to verify the ISAR uncertainty model but also demonstrates the e�ectiveness of using shipborne radiometry in preference to in water thermometry from ships or buoys for validating satellite SST products. A third area of study concerns the errors and uncertainties when comparing satellite and in situ observations, which result from failure to properly match the in situ observations to what the satellite \sees". A new method has been developed for classifying the \match-up quality" of each data pair. Its use is demonstrated to show that the quality of AATSR data may be better than classical validation match