Volume 39 Issue 9
Sep.  2020
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Na Li, Bingrui Li, Ruibo Lei, Qun Li. Comparison of summer Arctic sea ice surface temperatures from in situ and MODIS measurements[J]. Acta Oceanologica Sinica, 2020, 39(9): 18-24. doi: 10.1007/s13131-020-1644-7
Citation: Na Li, Bingrui Li, Ruibo Lei, Qun Li. Comparison of summer Arctic sea ice surface temperatures from in situ and MODIS measurements[J]. Acta Oceanologica Sinica, 2020, 39(9): 18-24. doi: 10.1007/s13131-020-1644-7

Comparison of summer Arctic sea ice surface temperatures from in situ and MODIS measurements

doi: 10.1007/s13131-020-1644-7
Funds:  The National Natural Science Foundation of China under contract No. 41606222; the National Key Research and Development Project under contract No. 2016YFC1400303.
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  • Corresponding author: E-mail: lina@pric.org.cn
  • Received Date: 2019-10-26
  • Accepted Date: 2019-11-18
  • Available Online: 2020-12-28
  • Publish Date: 2020-09-25
  • Ship-borne infrared radiometric measurements conducted during the Chinese National Arctic Research Expedition (CHINARE) in 2008, 2010, 2012, 2014, 2016 and 2017 were used for in situ validation studies of the Moderate Resolution Imaging Spectroradiometer (MODIS) sea ice surface temperature (IST) product. Observations of sea ice were made using a KT19.85 radiometer mounted on the Chinese icebreaker Xuelong between July and September over six years. The MODIS-derived ISTs from the satellites, Terra and Aqua, both show close correspondence with ISTs derived from radiometer spot measurements averaged over areas of 4 km×4 km, spanning the temperature range of 262–280 K with a ±1.7 K (Aqua) and ±1.6 K (Terra) variation. The consistency of the results over each year indicates that MODIS provides a suitable platform for remotely deriving surface temperature data when the sky is clear. Investigation into factors that cause the MODIS IST bias (defined as the difference between MODIS and KT19.85 ISTs) shows that large positive bias is caused by increased coverage of leads and melt ponds, while large negative bias mostly arises from undetected clouds. Thin vapor fog forming over Arctic sea ice may explain the cold bias when cloud cover is below 20%.
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