OS Ocean Science OS 1812-0792 Copernicus GmbH Göttingen, Germany 10.5194/os-8-959-2012 Arctic surface temperatures from Metop AVHRR compared to in situ ocean and land data Dybkjær G. 1 Tonboe R. 1 Høyer J. L. 1 Center for Ocean and Ice, Danish Meteorological Institute, Lyngbyvej 100, 2100 København, Denmark 08 11 2012 8 6 959 970 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.ocean-sci.net/8/959/2012/os-8-959-2012.html The full text article is available as a PDF file from http://www.ocean-sci.net/8/959/2012/os-8-959-2012.pdf

The ice surface temperature (IST) is an important boundary condition for both atmospheric and ocean and sea ice models and for coupled systems. An operational ice surface temperature product using satellite Metop AVHRR infra-red data was developed for MyOcean. The IST can be mapped in clear sky regions using a split window algorithm specially tuned for sea ice. Clear sky conditions prevail during spring in the Arctic, while persistent cloud cover limits data coverage during summer. The cloud covered regions are detected using the EUMETSAT cloud mask. The Metop IST compares to 2 m temperature at the Greenland ice cap Summit within STD error of 3.14 °C and to Arctic drifting buoy temperature data within STD error of 3.69 °C. A case study reveals that the in situ radiometer data versus satellite IST STD error can be much lower (0.73 °C) and that the different in situ measurements complicate the validation. Differences and variability between Metop IST and in situ data are analysed and discussed. An inter-comparison of Metop IST, numerical weather prediction temperatures and in situ observation indicates large biases between the different quantities. Because of the scarcity of conventional surface temperature or surface air temperature data in the Arctic, the satellite IST data with its relatively good coverage can potentially add valuable information to model analysis for the Arctic atmosphere.

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