The accuracy of SST retrievals from AATSR: An initial assessment through geophysical validation against in situ radiometers, buoys and other SST data sets

Corlett, Gary K.; Barton, I. J.; Donlon, Craig; Edwards, Martin; Good, Simon; Horrocks, L. A.; Llewellyn‐Jones, David; Merchant, Christopher J.; Minnett, Peter J.; Nightingale, T.; Noyes, Elizabeth; O’Carroll, Anne; Remedios, J. J.; Robinson, I. S.; Saunders, Roger; Watts, J.

doi:10.1016/j.asr.2005.09.037

Cited by 56 publications

(22 citation statements)

References 9 publications

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“…The AATSR is a dual-view instrument, i.e., it provides two SST products: nadir view and dual view. The AATSR level-1 brightness temperature was processed to level-2 SST products with BEAM software http://www.brockmann-consult.de/cms/web/beam/) using dualview and single-view SST retrievals for two channels [7], [10].…”

Section: B Remote Sensing Datamentioning

confidence: 99%

“…Manuscript Composite maps enable SST distributions to be determined for a certain period, e.g., Siegel et al [6] studied interannual variations using monthly mean SST images in the Baltic Sea. The differences between in situ temperature and Advanced Along-Track Scanning Radiometer (AATSR) SST can vary significantly in different conditions, regions, and periods [5], [7]- [10], particularly in regions higher than 50 • N [11]. Brown and Minnett [12] and Reinart and Reinhold [13] showed that the accuracy of SST from MODerate Resolution Imaging Spectroradiometer (MODIS) sensors is ±0.5 • C. MODIS/Aqua has a bias of 0.01 • C, with a standard deviation (STD) of 0.5 • C, for daytime SST retrievals, while MODIS/Terra has a mean bias of −0.20 • C, with the STD of 0.5 • C [4].…”

Section: Introductionmentioning

confidence: 99%

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Upwelling Parameters From Bias-Corrected Composite Satellite SST Maps in the Gulf of Finland (Baltic Sea)

Uiboupin

Laanemets

2015

IEEE Geosci. Remote Sensing Lett.

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This letter proposes a method for using the operational ship of opportunity temperature data at a fixed depth for bias correction of satellite sea surface temperature (SST) images. The bias-corrected SST imagery from MODerate Resolution Imaging Spectroradiometer (MODIS) and Advanced Along-Track Scanning Radiometer (AATSR) sensors were used to calculate mean upwelling characteristics in the Gulf of Finland (GoF, Baltic Sea). First, we determined that the operational flow through temperature data at a 4-m depth can be used for validation and bias correction of satellite SST images in cases of wind speed over 5 m · s −1 . The composite sea temperature maps were calculated from bias-corrected images collected during upwelling events in the GoF, in 2000-2009. Mean upwelling characteristics were estimated from composite maps for both the northern and southern coasts of the gulf.

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Section: B Remote Sensing Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Upwelling Parameters From Bias-Corrected Composite Satellite SST Maps in the Gulf of Finland (Baltic Sea)

Uiboupin

Laanemets

2015

IEEE Geosci. Remote Sensing Lett.

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“…The CASOTS-II blackbody forms an essential element of the end-to-end validation activities performed by the ISAR program and the follow-on reporting of satellite SST uncertainties. ISAR data are approved for satellite validation analyses (e.g., Corlett et al 2006;Wimmer et al 2012) only if CASOTS-II pre-and postdeployment laboratory calibrations quantitatively demonstrate the same instrument accuracy of 60.1 K. For a complete end-to-end validation of the at-sea measurement, a wide variety of sky radiance conditions, surface roughness conditions, ship movement, and their impact on estimates of seawater emissivity are required, which is beyond the scope of the laboratory work described here.…”

Section: A Using the Casots-ii To Quantify Absolute Uncertainty In Imentioning

confidence: 99%

A Second-Generation Blackbody System for the Calibration and Verification of Seagoing Infrared Radiometers

Donlon

Wimmer

Robinson

et al. 2014

Journal of Atmospheric and Oceanic Technology

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Quasi-operational shipborne radiometers provide a fiducial reference measurement (FRM) for satellite validation of satellite sea surface skin temperature (SST skin ) retrievals. External reference blackbodies are required to verify the performance and to quantify the accuracy of the radiometer calibration system. They provide a link in an unbroken chain of comparisons between the shipborne radiometer and a traceable reference standard. A second-generation water bath blackbody reference radiance source has been developed for this purpose. The second generation Concerted Action for the Study of the Ocean Thermal Skin (CASOTS-II) blackbody has a 110-mm-diameter aperture cylinder-cone geometry coated with NEXTEL suede 3103 paint. Interchangeable aperture stops reduce the cavity aperture diameter and minimize stray radiation. Monte Carlo modeling techniques show the effective emissivity of the cavity to be .0.9999 (aperture , 30 mm). The cavity is immersed in a water bath that is vigorously stirred using a pump that slowly heats the water bath at a mean rate of ;0.6 K h 21. The temperature of the water bath is measured using a thermometer traceable to the International System of Units (SI) standards. The worst-case radiance temperature of the CASOTS-II blackbody system is traceable to the SI with an uncertainty of 58 mK (millikelvin). When operating under typical laboratory conditions using an aperture of 40 mm, the uncertainty is 16 mK. An intercomparison with the U.K. National Physical Laboratory Absolute Measurements of Blackbody Emitted Radiance (AMBER) reference radiometer found no significant differences within 75 mK (110-mm aperture) or 50 mK (40-mm aperture), which is the combined uncertainty of the comparison and the reference standard for SI traceability of ISAR radiometer SST skin records used for satellite SST validation. Applications of the CASOTS-II blackbody to monitor the calibration of shipborne radiometers are described and measurement protocols are proposed.

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“…In situ data are a reliable independent source of measurements widely used to validate these products (see [4]), and the Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Brest, France, operationally produces an MDB (http://www.medspiration.org/tools/mdb/) that provides colocated satellite and in situ measurements. The system relies on the Coriolis system (for the worldwide collection and archiving of in situ sea data; http://www.coriolis.eu.org) for in situ measurements and on the Medspiration archive for satellite data, both hosted at IFREMER.…”

Section: Datamentioning

confidence: 99%

A Multivariate Regression Approach to Adjust AATSR Sea Surface Temperature to In Situ Measurements

Autret

Piollé

Tournadre

et al. 2009

IEEE Geosci. Remote Sensing Lett.

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Abstract-The Advanced Along-Track Scanning Radiometer (AATSR) onboard Envisat is designed to provide very accurate measurements of sea surface temperature (SST). Using colocated in situ drifting buoys, a dynamical matchup database (MDB) is used to assess the AATSR-derived SST products more precisely. SST biases are then computed. Currently, Medspiration AATSR SST biases are discrete values and can introduce artificial discontinuities in AATSR level-2 SST fields. The new AATSR SST biases presented in this letter are continuous. They are computed, for nighttime and best proximity confidence data, by linear regression with different MDB covariables (wind speed, latitude, aerosol optical depth, etc.). As found, the difference between dual-view and nadir-only SST products explains most of the variability (26%).

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The accuracy of SST retrievals from AATSR: An initial assessment through geophysical validation against in situ radiometers, buoys and other SST data sets

Cited by 56 publications

References 9 publications

Upwelling Parameters From Bias-Corrected Composite Satellite SST Maps in the Gulf of Finland (Baltic Sea)

Upwelling Parameters From Bias-Corrected Composite Satellite SST Maps in the Gulf of Finland (Baltic Sea)

A Second-Generation Blackbody System for the Calibration and Verification of Seagoing Infrared Radiometers

A Multivariate Regression Approach to Adjust AATSR Sea Surface Temperature to In Situ Measurements

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