Title: The Plumbing of Land Surface Models: Is Poor Performance a Result of Methodology or Data Quality?

Abstract

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. In conclusion, we present evidence suggesting thatmore » 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.« less

Authors:

Haughton, Ned ^[1]; Abramowitz, Gab ^[1]; Pitman, Andy J. ^[1]; Or, Dani ^[2]; Best, Martin J. ^[3]; Johnson, Helen R. ^[3]; Balsamo, Gianpaolo ^[4]; Boone, Aaron ^[5]; Cuntz, Matthias ^[6]; Decharme, Bertrand ^[5]; Dirmeyer, Paul A. ^[7]; Dong, Jairui ^[8]; Ek, Michael ^[8]; Guo, Zichang ^[7]; Haverd, Vanessa ^[9]; van den Hurk, Bart J. J. ^[10]; Nearing, Grey S. ^[11]; Pak, Bernard ^[12]; Santanello, Jr., Joe A. ^[11]; Stevens, Lauren E. ^[12] more »; Vuichard, Nicolas ^[13] « less

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+ Show Author Affiliations

1. ARC Centre of Excellence for Climate Systems Science, Sydney, NSW (Australia)
2. ETH Zurich, Zurich (Switzerland)
3. Met Office, Exeter (United Kingdom)
4. ECMWF, Reading (United Kingdom)
5. CNRM-GAME, Toulouse (France)
6. Helmholtz Centre for Environmental Research (UFZ), Leipzig (Germany)
7. George Mason Univ., Fairfax, VA (United States)
8. NOAA/NCEP/EMC, College Park, MD (United States)
9. CSIRO, Canberra, ACT (Australia)
10. Royal Netherlands Meteorological Institute (KNMI), De Bilt (Netherlands)
11. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
12. CSIRO, Aspendale, VIC (Australia)
13. Lab. des Sciences du Climat et de l’Environnement, Gif-sur-Yvette (France)

Publication Date:

Wed May 25 00:00:00 EDT 2016

Research Org.:

Oregon State Univ., Corvallis, OR (United States)

Sponsoring Org.:

USDOE Office of Science (SC), Biological and Environmental Research (BER); Terrestrial Carbon Program

OSTI Identifier:

1467090

Grant/Contract Number:  

FG02-04ER63917; FG02-04ER63911

Resource Type:

Accepted Manuscript

Journal Name:

Journal of Hydrometeorology

Additional Journal Information:

Journal Volume: 17; Journal Issue: 6; Journal ID: ISSN 1525-755X

Publisher:

American Meteorological Society

Country of Publication:

United States

Language:

English

Subject:

54 ENVIRONMENTAL SCIENCES