Comparison of albedos computed by land surface models and evaluation against remotely sensed data

Xue Wei, Andrea N. Hahmann, Robert E. Dickinson, Zong Liang Yang, Xubin Zeng, Kimberly J. Schaudt, Crystal B. Schaaf, Nicholas Strugnell

Research output: Contribution to journalReview articlepeer-review

35 Scopus citations


The albedos of two land surface models, the Biosphere-Atmosphere Transfer Scheme (BATS) and the NCAR Land Surface Model (LSM), are compared with remotely sensed data and each other. The model albedos differ primarily because of their assumptions about and model differences in soil moisture content, soil color, snow albedo, shading of snow by canopy, and prescribed parameters for each land cover type. Global albedo maps for February and July 1995, developed from the advanced very high resolution radiometer (AVHRR) data, are used to evaluate model albedos. The models display a high bias as compared to the remotely sensed values in desert and semidesert regions. Over North Africa, LSM, whose albedos were previously tuned to data from the Earth Radiation Budget Experiment (ERBE), has the highest albedos. Elsewhere, and overall, BATS has the highest bias for desert and semidesert regions. Both models demonstrate a high bias over regions of winter snow, where the AVHRR data are expected to have a negative bias. LSM has especially high winter albedos, apparently because of intercepted snow increasing its canopy albedo.

Original languageEnglish (US)
Article number2001JD900218
Pages (from-to)20687-20702
Number of pages16
JournalJournal of Geophysical Research Atmospheres
Issue numberD18
StatePublished - Sep 27 2001

ASJC Scopus subject areas

  • Geophysics
  • Forestry
  • Oceanography
  • Aquatic Science
  • Ecology
  • Water Science and Technology
  • Soil Science
  • Geochemistry and Petrology
  • Earth-Surface Processes
  • Atmospheric Science
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science
  • Palaeontology


Dive into the research topics of 'Comparison of albedos computed by land surface models and evaluation against remotely sensed data'. Together they form a unique fingerprint.

Cite this