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The plumbing of land surface models: is poor performance a result of methodology or data quality?
Journal article

The plumbing of land surface models: is poor performance a result of methodology or data quality?

  • Haughton N ARC Centre of Excellence for Climate Systems Science, Australia.
  • Abramowitz G ARC Centre of Excellence for Climate Systems Science, Australia.
  • Pitman AJ ARC Centre of Excellence for Climate Systems Science, Australia.
  • Or D Department of Environmental Systems Science, Swiss Federal Institute of Technology - ETH Zurich, Switzerland.
  • Best MJ UK Met Office, Fitzroy Road, Exeter, UK.
  • Johnson HR UK Met Office, Fitzroy Road, Exeter, UK.
  • Balsamo G ECMWF, Reading, UK.
  • Boone A CNRM-GAME, Mto-France, Toulouse.
  • Cuntz M UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany.
  • Decharme B CNRM-GAME, Mto-France, Toulouse.
  • Dirmeyer PA Center for Ocean-Land-Atmosphere Studies, George Mason University, 4400 University Drive, MS6C5, Fairfax Virginia, 22030 USA.
  • Dong J NOAA/NCEP/EMC, College Park, Maryland, 20740.
  • Ek M NOAA/NCEP/EMC, College Park, Maryland, 20740.
  • Guo Z Center for Ocean-Land-Atmosphere Studies, George Mason University, 4400 University Drive, MS6C5, Fairfax Virginia, 22030 USA.
  • Haverd V CSIRO Ocean and Atmosphere, Canberra ACT 2601, Australia.
  • van den Hurk BJJ KNMI, De Bilt, The Netherlands.
  • Nearing GS NASA/GSFC, Hydrological Sciences Laboratory, Code 617, Greenbelt, Maryland, USA.
  • Pak B CSIRO Ocean and Atmosphere, Aspendale VIC 3195, Australia.
  • Santanello JA NASA/GSFC, Hydrological Sciences Laboratory, Code 617, Greenbelt, Maryland, USA.
  • Stevens LE CSIRO Ocean and Atmosphere, Aspendale VIC 3195, Australia.
  • Vuichard N Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212, IPSL-LSCE, CEA-CNRS-UVSQ, 91191, Gif-sur-Yvette, France.
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  • 2018-04-10
Published in:
  • Journal of hydrometeorology. - 2016
Atmospheric Science
English The PALS Land sUrface Model Benchmarking Evaluation pRoject (PLUMBER) illustrated the value of prescribing a priori performance targets in model intercomparisons. It showed that the performance of turbulent energy flux predictions from different land surface models, at a broad range of flux tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all land surface models were outperformed by a linear regression against downward shortwave radiation. For latent heat flux, all land surface models were outperformed by a regression against downward shortwave, surface air temperature and relative humidity. These results are explored here in greater detail and possible causes are investigated. We examine whether particular metrics or sites unduly influence the collated results, whether results change according to time-scale aggregation and whether a lack of energy conservation in flux tower data gives the empirical models an unfair advantage in the intercomparison. We demonstrate that energy conservation in the observational data is not responsible for these results. We also show that the partitioning between sensible and latent heat fluxes in LSMs, rather than the calculation of available energy, is the cause of the original findings. Finally, we present evidence suggesting that the nature of this partitioning problem is likely shared among all contributing LSMs. While we do not find a single candidate explanation for why land surface models perform poorly relative to empirical benchmarks in PLUMBER, we do exclude multiple possible explanations and provide guidance on where future research should focus.
Language
  • English
Open access status
hybrid
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Persistent URL
https://sonar.ch/global/documents/185734
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