2019JD030262.pdf (11.2 MB)
Toward a Combined Surface Temperature Data Set for the Arctic From the Along-Track Scanning Radiometers
journal contribution
posted on 2019-07-29, 15:19 authored by E. M. A. Dodd, K. L. Veal, D. J. Ghent, M. R . van den Broeke, J. J. RemediosSurface temperature data sets for, or including, the Arctic have been derived from various thermal infrared sensors. However, a combined, all surface temperature data set for the Arctic has not been generated previously. Here we present the first combined land, ocean, and ice surface temperature data set for the Arctic produced from Along-Track Scanning Radiometer - 2 and the Advanced Along-Track Scanning Radiometer satellite sensors: the Along-Track Scanning Radiometer Arctic combined Surface Temperature data set. Separate products, produced independently for each sensor and containing quantified uncertainties, together cover the period August 1995 to April 2012. Product validation, utilizing a more extensive in situ database than previous studies, shows that Along-Track Scanning Radiometer Arctic combined Surface Temperature surface temperatures generally agree with in situ data and are similar to previous validation of input surface temperature retrievals. Biases range from −1.74 to 0.23 K over open ocean, sea ice, snow over land, and the Greenland ice sheet with higher variability over snow/ice. However, there are noticeable outliers in the validation results, particularly over Arctic land in boreal summer for Along-Track Scanning Radiometer - 2, which are likely due to cloud contamination resulting from a climatologically static snow field being used for that sensor. This study suggests that the Along-Track Scanning Radiometer Arctic combined Surface Temperature data set presented here is a useful tool for assessment of models in the Arctic. Further work would have clear benefits including improvements to snow cover and cloud clearing to achieve a fully consistently processed, climate quality combined surface temperature data set for the Arctic region.
Funding
The research presented in this paper was funded by The UK Department for Business, Energy, and Industrial Strategy (formally The UK Department of Energy and Climate Change). Darren Ghent is funded by the European Space Agency and a NERC grant to the National Centre for Earth Observation (NCEO) in the UK. This research used the ALICE High Performance Computing Facility at the University of Leicester and the CEDA JASMIN super‐data‐cluster. The authors would like to thank Gary Corlett for providing access to in situ SST data used in this study.
History
Citation
Journal of Geophysical Research: Atmospheres, 2019, 124(13) pp. 6718-6736Author affiliation
/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Physics and AstronomyVersion
- VoR (Version of Record)
Published in
Journal of Geophysical Research: AtmospheresPublisher
American Geophysical Union (AGU), Wileyissn
2169-897Xeissn
2169-8996Acceptance date
2019-05-23Copyright date
2019Available date
2019-07-29Publisher DOI
Publisher version
https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019JD030262Notes
AAST data are freely available from the CEDA Archive (https://doi.org/10.5285/b8141fa5842b45e8863816da536def5a).Language
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