Spring and summer monthly MODIS LST is inherently biased compared to air temperature in snow covered sub-Arctic mountains

Scott N. Williamson, David S. Hik, John A. Gamon, Alexander H. Jarosch, Faron S. Anslow, Garry K.C. Clarke, T. Scott Rupp

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Satellite-derived land surface temperature (skin temperature) provides invaluable information for data-sparse high elevation and Arctic regions. However, the relationship between satellite-derived clear-sky skin temperature and various downscaled air temperature products for snow covered sub-Arctic alpine regions remain poorly understood, such that trend analysis or air temperature product integration is difficult. We compared monthly average air temperatures from two independent downscaled temperature products to MODIS Land Surface Temperature (LST) and air temperature at nine meteorological stations situated above tree-line in the southwest Yukon, Canada, between May and August 2008 for a full range of snow cover fractions. We found that both downscaled products generally agreed with LST for the low elevation, snow-free, vegetation classes. However, a systematic cold bias in Average LST emerged for snow fractions greater than approximately 40%, and this bias increased in magnitude as snow cover increased. In these situations the downscaled air temperatures were 5–7 °C warmer than Average LST for snow fractions of > 90%, and this pattern was largely independent of the number of measurements of LST within a month. Maximum LST was similar to average air temperatures for high snow fractions, but Minimum LST was colder by 10 °C or more for all snow fractions. Consequently, the average of Maximum and Minimum LST produces the cold bias, compared to air temperature, for high snow cover fractions. Air temperature measured at nine meteorological monitoring stations located between elevations of 1408–2690 m, on land cover classes Barren, Sparsely Vegetated or Permanent Snow and Ice, confirmed the cold bias results when incorporating Minimum LST in monthly averages. For snow fractions of < 40% the RMSE for all of the temperature products was < 2.5 °C when compared to station air temperature and all biases were positive and < 2.0 °C. For snow fractions of > 40%, the average LST bias became strongly negative at − 4.5 °C, and the RMSE increased to 6.1 °C, whereas the downscaled products bias and RMSE were similar to those from snow fractions of < 40%. A weak warm bias for all the temperature products occurred for small snow fractions over non-forested land cover classes. Downscaled air temperature fields show physically real differences from Average LST in spring and summer, caused by snow cover and the interplay of Maximum and Minimum LST. These findings indicate that the integration of MODIS LST with downscaled air temperature products or local air temperature requires the incorporation of snow cover.

Original languageEnglish (US)
Pages (from-to)14-24
Number of pages11
JournalRemote Sensing of Environment
Volume189
DOIs
StatePublished - Feb 1 2017
Externally publishedYes

Keywords

  • Cloud cover
  • Cryosphere
  • Downscaled NARR
  • MODIS LST
  • SNAP
  • Snow cover

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences

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