Sea surface temperature and salinity product comparison against external in situ data in the Arctic Ocean; Journal of Geophysical Research: Oceans; Vol. 120, iss. 11

Sea surface temperature and salinity product comparison against external in situ data in the Arctic Ocean; Journal of Geophysical Research: Oceans; Vol. 120, iss. 11

Bibliographic Details
Parent link:Journal of Geophysical Research: Oceans.— , 1980-
Vol. 120, iss. 11.— 2015.— [P. 7223-7236]
Corporate Author: Национальный исследовательский Томский политехнический университет Институт природных ресурсов Кафедра геологии и разведки полезных ископаемых Международная научно-образовательная лаборатория изучения углерода арктических морей
Other Authors: Stroh J., Panteleev G. G. Gleb Glebovich, Kirillov S. A. Sergey A., Makhotin M. S. Mikhail S., Shakhova N. E. Nataljya Evgenjevna
Summary:Title screen
Sea-surface temperature and salinity (SST/S) in the Arctic Ocean (AO) are largely governed by sea-ice and continental runoff rather than evaporation and precipitation as in lower latitude oceans, and global satellite analyses and models which incorporate remotely observed SST/S may be inaccurate in the AO due to lack of direct measurements for calibrating satellite data. For this reason, we are motivated to validate several satellite sea-surface temperature (SST) data products and SST/S models by comparing gridded data in the AO with oceanographic records from 2006 to 2013. Statistical analysis of product-minus-observation differences reveals that the satellite SST products considered have a temperature bias magnitude of less than 0.5 inline imageC compared to ship-based CTD measurements, and most of these biases are negative in sign. SST/S models also show an overall negative temperature bias, but no common sign or magnitude of salinity bias against CTD data. Ice tethered profiler (ITP) near-surface data span the seasons of several years, and these measurements reflect a sea-ice dominated region where the ocean surface cannot be remotely observed. Against this data, many of the considered models and products show large errors with detectable seasonal differences in SST bias. Possible sources of these errors are discussed, and two adjustments of product SST on the basis of sea-ice concentration are suggested for reducing bias to within less than 0.01 inline imageC of ITP near-surface temperatures.
Language:English
Published: 2015
Subjects:
электронный ресурс
труды учёных ТПУ
Online Access:http://dx.doi.org/10.1002/2015JC011005
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=649647

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