Satellite Sensed Skin Sea Surface Temperature

Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often u...

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Main Author: Donlon, Craig
Format: Other/Unknown Material
Language:unknown
Published: 1997
Subjects:
Online Access:http://hdl.handle.net/2060/19970018037
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spelling ftnasantrs:oai:casi.ntrs.nasa.gov:19970018037 2023-05-15T18:26:00+02:00 Satellite Sensed Skin Sea Surface Temperature Donlon, Craig Unclassified, Unlimited, Publicly available May 22, 1997 application/pdf http://hdl.handle.net/2060/19970018037 unknown Document ID: 19970018037 Accession ID: 97N20118 http://hdl.handle.net/2060/19970018037 No Copyright CASI Earth Resources and Remote Sensing NASA-CR-204438 NAS 1.26:204438 1997 ftnasantrs 2019-08-31T23:03:49Z Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to be confidently detected. Some of these activities are focussed to develop and deploy instrumentation suitable for the collection of precise in situ measurements of the SSST which can be used to improve the accuracy of satellite measurements, while others develop techniques to generate improved global analyses of sea surface temperature using historical data. Other/Unknown Material Southern Ocean NASA Technical Reports Server (NTRS) Southern Ocean
institution Open Polar
collection NASA Technical Reports Server (NTRS)
op_collection_id ftnasantrs
language unknown
topic Earth Resources and Remote Sensing
spellingShingle Earth Resources and Remote Sensing
Donlon, Craig
Satellite Sensed Skin Sea Surface Temperature
topic_facet Earth Resources and Remote Sensing
description Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to be confidently detected. Some of these activities are focussed to develop and deploy instrumentation suitable for the collection of precise in situ measurements of the SSST which can be used to improve the accuracy of satellite measurements, while others develop techniques to generate improved global analyses of sea surface temperature using historical data.
format Other/Unknown Material
author Donlon, Craig
author_facet Donlon, Craig
author_sort Donlon, Craig
title Satellite Sensed Skin Sea Surface Temperature
title_short Satellite Sensed Skin Sea Surface Temperature
title_full Satellite Sensed Skin Sea Surface Temperature
title_fullStr Satellite Sensed Skin Sea Surface Temperature
title_full_unstemmed Satellite Sensed Skin Sea Surface Temperature
title_sort satellite sensed skin sea surface temperature
publishDate 1997
url http://hdl.handle.net/2060/19970018037
op_coverage Unclassified, Unlimited, Publicly available
geographic Southern Ocean
geographic_facet Southern Ocean
genre Southern Ocean
genre_facet Southern Ocean
op_source CASI
op_relation Document ID: 19970018037
Accession ID: 97N20118
http://hdl.handle.net/2060/19970018037
op_rights No Copyright
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