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Adjusting for Desert-Dust-Related Biases in a Climate Data Record of Sea Surface Temperature.
- Source :
- Remote Sensing; Aug2020, Vol. 12 Issue 16, p2554-2554, 1p
- Publication Year :
- 2020
-
Abstract
- Atmospheric desert-dust aerosol, primarily from north Africa, causes negative biases in remotely sensed climate data records of sea surface temperature (SST). Here, large-scale bias adjustments are deduced and applied to the v2 climate data record of SST from the European Space Agency Climate Change Initiative (CCI). Unlike SST from infrared sensors, SST measured in situ is not prone to desert-dust bias. An in-situ-based SST analysis is combined with column dust mass from the Modern-Era Retrospective analysis for Research and Applications, Version 2 to deduce a monthly, large-scale adjustment to CCI analysis SSTs. Having reduced the dust-related biases, a further correction for some periods of anomalous satellite calibration is also derived. The corrections will increase the usability of the v2 CCI SST record for oceanographic and climate applications, such as understanding the role of Arabian Sea SSTs in the Indian monsoon. The corrections will also pave the way for a v3 climate data record with improved error characteristics with respect to atmospheric dust aerosol. [ABSTRACT FROM AUTHOR]
- Subjects :
- OCEAN temperature
MINERAL dusts
DUST
ATMOSPHERIC aerosols
CLIMATOLOGY
CLIMATE change
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 12
- Issue :
- 16
- Database :
- Complementary Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 145244005
- Full Text :
- https://doi.org/10.3390/rs12162554