Large-scale Validation of AMIP II Land-surface Simulations: Preliminary Results for Ten Models

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This report summarizes initial findings of a large-scale validation of the land-surface simulations of ten atmospheric general circulation models that are entries in phase II of the Atmospheric Model Intercomparison Project (AMIP II). This validation is conducted by AMIP Diagnostic Subproject 12 on Land-surface Processes and Parameterizations, which is focusing on putative relationships between the continental climate simulations and the associated models' land-surface schemes. The selected models typify the diversity of representations of land-surface climate that are currently implemented by the global modeling community. The current dearth of global-scale terrestrial observations makes exacting validation of AMIP II continental simulations impractical. ... continued below

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PDF-file: 28 pages; size: 0.3 Mbytes

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Phillips, T J; Henderson-Sellers, A; Irannejad, P; McGuffie, K & Zhang, H December 1, 2005.

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This report summarizes initial findings of a large-scale validation of the land-surface simulations of ten atmospheric general circulation models that are entries in phase II of the Atmospheric Model Intercomparison Project (AMIP II). This validation is conducted by AMIP Diagnostic Subproject 12 on Land-surface Processes and Parameterizations, which is focusing on putative relationships between the continental climate simulations and the associated models' land-surface schemes. The selected models typify the diversity of representations of land-surface climate that are currently implemented by the global modeling community. The current dearth of global-scale terrestrial observations makes exacting validation of AMIP II continental simulations impractical. Thus, selected land-surface processes of the models are compared with several alternative validation data sets, which include merged in-situ/satellite products, climate reanalyses, and off-line simulations of land-surface schemes that are driven by observed forcings. The aggregated spatio-temporal differences between each simulated process and a chosen reference data set then are quantified by means of root-mean-square error statistics; the differences among alternative validation data sets are similarly quantified as an estimate of the current observational uncertainty in the selected land-surface process. Examples of these metrics are displayed for land-surface air temperature, precipitation, and the latent and sensible heat fluxes. It is found that the simulations of surface air temperature, when aggregated over all land and seasons, agree most closely with the chosen reference data, while the simulations of precipitation agree least. In the latter case, there also is considerable inter-model scatter in the error statistics, with the reanalyses estimates of precipitation resembling the AMIP II simulations more than to the chosen reference data. In aggregate, the simulations of land-surface latent and sensible heat fluxes appear to occupy intermediate positions between these extremes, but the existing large observational uncertainties in these processes make this a provisional assessment. In all selected processes as well, the error statistics are found to be sensitive to season and latitude sector, confirming the need for finer-scale analyses which also are in progress.

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PDF-file: 28 pages; size: 0.3 Mbytes

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  • Report No.: UCRL-TR-217474
  • Grant Number: W-7405-ENG-48
  • DOI: 10.2172/928178 | External Link
  • Office of Scientific & Technical Information Report Number: 928178
  • Archival Resource Key: ark:/67531/metadc902832

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  • December 1, 2005

Added to The UNT Digital Library

  • Sept. 27, 2016, 1:39 a.m.

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  • Dec. 9, 2016, 8:13 p.m.

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Phillips, T J; Henderson-Sellers, A; Irannejad, P; McGuffie, K & Zhang, H. Large-scale Validation of AMIP II Land-surface Simulations: Preliminary Results for Ten Models, report, December 1, 2005; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc902832/: accessed August 16, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.