Theoretical and Applied Climatology

, Volume 94, Issue 3, pp 187–213

Evaluation of Community Climate System Model soil temperatures using observations from Russia

Authors

  • D. PaiMazumder
    • Geophysical Institute and College of Natural Science and MathematicsUniversity of Alaska Fairbanks
  • J. Miller
    • Arctic Region Supercomputing CenterUniversity of Alaska Fairbanks
  • Z. Li
    • Geophysical Institute and College of Natural Science and MathematicsUniversity of Alaska Fairbanks
  • J. E. Walsh
    • International Arctic Research CenterUniversity of Alaska Fairbanks
  • A. Etringer
    • National Snow and Ice Data Center, Cooperative Institute for Research in Environmental SciencesUniversity of Colorado
  • J. McCreight
    • National Snow and Ice Data Center, Cooperative Institute for Research in Environmental SciencesUniversity of Colorado
  • T. Zhang
    • National Snow and Ice Data Center, Cooperative Institute for Research in Environmental SciencesUniversity of Colorado
    • Geophysical Institute and College of Natural Science and MathematicsUniversity of Alaska Fairbanks
Article

DOI: 10.1007/s00704-007-0350-0

Cite this article as:
PaiMazumder, D., Miller, J., Li, Z. et al. Theor Appl Climatol (2008) 94: 187. doi:10.1007/s00704-007-0350-0

Summary

Soil temperatures simulated by the fully coupled Community Climate System Model (CCSM) version 3.0 are evaluated using three gridded climatologies (1951–1980, 1961–1990, 1971–2000) based on data from more than 400 Russian sites. CCSM captures the annual phase of the soil temperature cycle well, but not the amplitude. It provides slightly too high (low) soil temperatures in winter (summer). Root mean square errors, on average, are less than 5 K.

Simulated near-surface air temperatures agree well, on average, with near-surface air temperatures from reanalysis data. Errors in simulated atmospheric-temperature forcing correlate statistically significantly (95% or higher confidence level) with soil temperature errors, i.e. contribute to discrepancy in soil temperature simulation. Comparison to International Satellite Cloud Climatology project data shows that errors in simulated cloud fraction explain some soil and near-surface air temperature and precipitation discrepancies. Evaluation by means of Global Precipitation Climatology Centre data identifies inaccurately-simulated precipitation as a contributor to underestimating summer soil temperatures. Comparison to snow-depth observations shows that overestimating snow depth yields winter soil-temperature overestimation.

Sensitivity studies show that uncertainty in mineral-soil composition notably, and differences between the vegetation in CCSM and nature marginally contribute to discrepancies between simulated and observed soil-temperature climatology.

Copyright information

© Springer-Verlag 2007