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T. H. Chen
,
A. Henderson-Sellers
,
P. C. D. Milly
,
A. J. Pitman
,
A. C. M. Beljaars
,
J. Polcher
,
F. Abramopoulos
,
A. Boone
,
S. Chang
,
F. Chen
,
Y. Dai
,
C. E. Desborough
,
R. E. Dickinson
,
L. Dümenil
,
M. Ek
,
J. R. Garratt
,
N. Gedney
,
Y. M. Gusev
,
J. Kim
,
R. Koster
,
E. A. Kowalczyk
,
K. Laval
,
J. Lean
,
D. Lettenmaier
,
X. Liang
,
J.-F. Mahfouf
,
H.-T. Mengelkamp
,
K. Mitchell
,
O. N. Nasonova
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J. Noilhan
,
A. Robock
,
C. Rosenzweig
,
J. Schaake
,
C. A. Schlosser
,
J.-P. Schulz
,
Y. Shao
,
A. B. Shmakin
,
D. L. Verseghy
,
P. Wetzel
,
E. F. Wood
,
Y. Xue
,
Z.-L. Yang
, and
Q. Zeng

Abstract

In the Project for Intercomparison of Land-Surface Parameterization Schemes phase 2a experiment, meteorological data for the year 1987 from Cabauw, the Netherlands, were used as inputs to 23 land-surface flux schemes designed for use in climate and weather models. Schemes were evaluated by comparing their outputs with long-term measurements of surface sensible heat fluxes into the atmosphere and the ground, and of upward longwave radiation and total net radiative fluxes, and also comparing them with latent heat fluxes derived from a surface energy balance. Tuning of schemes by use of the observed flux data was not permitted. On an annual basis, the predicted surface radiative temperature exhibits a range of 2 K across schemes, consistent with the range of about 10 W m−2 in predicted surface net radiation. Most modeled values of monthly net radiation differ from the observations by less than the estimated maximum monthly observational error (±10 W m−2). However, modeled radiative surface temperature appears to have a systematic positive bias in most schemes; this might be explained by an error in assumed emissivity and by models’ neglect of canopy thermal heterogeneity. Annual means of sensible and latent heat fluxes, into which net radiation is partitioned, have ranges across schemes of30 W m−2 and 25 W m−2, respectively. Annual totals of evapotranspiration and runoff, into which the precipitation is partitioned, both have ranges of 315 mm. These ranges in annual heat and water fluxes were approximately halved upon exclusion of the three schemes that have no stomatal resistance under non-water-stressed conditions. Many schemes tend to underestimate latent heat flux and overestimate sensible heat flux in summer, with a reverse tendency in winter. For six schemes, root-mean-square deviations of predictions from monthly observations are less than the estimated upper bounds on observation errors (5 W m−2 for sensible heat flux and 10 W m−2 for latent heat flux). Actual runoff at the site is believed to be dominated by vertical drainage to groundwater, but several schemes produced significant amounts of runoff as overland flow or interflow. There is a range across schemes of 184 mm (40% of total pore volume) in the simulated annual mean root-zone soil moisture. Unfortunately, no measurements of soil moisture were available for model evaluation. A theoretical analysis suggested that differences in boundary conditions used in various schemes are not sufficient to explain the large variance in soil moisture. However, many of the extreme values of soil moisture could be explained in terms of the particulars of experimental setup or excessive evapotranspiration.

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A. G. Slater
,
C. A. Schlosser
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C. E. Desborough
,
A. J. Pitman
,
A. Henderson-Sellers
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A. Robock
,
K. Ya Vinnikov
,
J. Entin
,
K. Mitchell
,
F. Chen
,
A. Boone
,
P. Etchevers
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F. Habets
,
J. Noilhan
,
H. Braden
,
P. M. Cox
,
P. de Rosnay
,
R. E. Dickinson
,
Z-L. Yang
,
Y-J. Dai
,
Q. Zeng
,
Q. Duan
,
V. Koren
,
S. Schaake
,
N. Gedney
,
Ye M. Gusev
,
O. N. Nasonova
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J. Kim
,
E. A. Kowalczyk
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A. B. Shmakin
,
T. G. Smirnova
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D. Verseghy
,
P. Wetzel
, and
Y. Xue

Abstract

Twenty-one land surface schemes (LSSs) performed simulations forced by 18 yr of observed meteorological data from a grassland catchment at Valdai, Russia, as part of the Project for the Intercomparison of Land-Surface Parameterization Schemes (PILPS) Phase 2(d). In this paper the authors examine the simulation of snow. In comparison with observations, the models are able to capture the broad features of the snow regime on both an intra- and interannual basis. However, weaknesses in the simulations exist, and early season ablation events are a significant source of model scatter. Over the 18-yr simulation, systematic differences between the models’ snow simulations are evident and reveal specific aspects of snow model parameterization and design as being responsible. Vapor exchange at the snow surface varies widely among the models, ranging from a large net loss to a small net source for the snow season. Snow albedo, fractional snow cover, and their interplay have a large effect on energy available for ablation, with differences among models most evident at low snow depths. The incorporation of the snowpack within an LSS structure affects the method by which snow accesses, as well as utilizes, available energy for ablation. The sensitivity of some models to longwave radiation, the dominant winter radiative flux, is partly due to a stability-induced feedback and the differing abilities of models to exchange turbulent energy with the atmosphere. Results presented in this paper suggest where weaknesses in macroscale snow modeling lie and where both theoretical and observational work should be focused to address these weaknesses.

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A. J. Dolman
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J. Noilhan
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P. Durand
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C. Sarrat
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A. Brut
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B. Piguet
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A. Butet
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N. Jarosz
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Y. Brunet
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D. Loustau
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E. Lamaud
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L. Tolk
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R. Ronda
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F. Miglietta
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B. Gioli
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V. Magliulo
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M. Esposito
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C. Gerbig
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S. Körner
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P. Glademard
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M. Ramonet
,
P. Ciais
,
B. Neininger
,
R. W. A. Hutjes
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J. A. Elbers
,
R. Macatangay
,
O. Schrems
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G. Pérez-Landa
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M. J. Sanz
,
Y. Scholz
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G. Facon
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E. Ceschia
, and
P. Beziat

The Second Global Soil Wetness Project (GSWP-2) is an initiative to compare and evaluate 10-year simulations by a broad range of land surface models under controlled conditions. A major product of GSWP-2 is the first global gridded multimodel analysis of land surface state variables and fluxes for use by meteorologists, hydrologists, engineers, biogeochemists, agronomists, botanists, ecologists, geographers, climatologists, and educators. Simulations by 13 land models from five nations have gone into production of the analysis. The models are driven by forcing data derived from a combination of gridded atmospheric reanalyses and observations. The resulting analysis consists of multimodel means and standard deviations on the monthly time scale, including profiles of soil moisture and temperature at six levels, as well as daily and climatological (mean annual cycle) fields for over 50 land surface variables. The monthly standard deviations provide a measure of model agreement that may be used as a quality metric. An overview of key characteristics of the analysis is presented here, along with information on obtaining the data.

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Lifeng Luo
,
Alan Robock
,
Konstantin Y. Vinnikov
,
C. Adam Schlosser
,
Andrew G. Slater
,
Aaron Boone
,
Pierre Etchevers
,
Florence Habets
,
Joel Noilhan
,
Harald Braden
,
Peter Cox
,
Patricia de Rosnay
,
Robert E. Dickinson
,
Yongjiu Dai
,
Qing-Cun Zeng
,
Qingyun Duan
,
John Schaake
,
Ann Henderson-Sellers
,
Nicola Gedney
,
Yevgeniy M. Gusev
,
Olga N. Nasonova
,
Jinwon Kim
,
Eva Kowalczyk
,
Kenneth Mitchell
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Andrew J. Pitman
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Andrey B. Shmakin
,
Tatiana G. Smirnova
,
Peter Wetzel
,
Yongkang Xue
, and
Zong-Liang Yang

Abstract

The Project for Intercomparison of Land-Surface Parameterization Schemes phase 2(d) experiment at Valdai, Russia, offers a unique opportunity to evaluate land surface schemes, especially snow and frozen soil parameterizations. Here, the ability of the 21 schemes that participated in the experiment to correctly simulate the thermal and hydrological properties of the soil on several different timescales was examined. Using observed vertical profiles of soil temperature and soil moisture, the impact of frozen soil schemes in the land surface models on the soil temperature and soil moisture simulations was evaluated.

It was found that when soil-water freezing is explicitly included in a model, it improves the simulation of soil temperature and its variability at seasonal and interannual scales. Although change of thermal conductivity of the soil also affects soil temperature simulation, this effect is rather weak. The impact of frozen soil on soil moisture is inconclusive in this experiment due to the particular climate at Valdai, where the top 1 m of soil is very close to saturation during winter and the range for soil moisture changes at the time of snowmelt is very limited. The results also imply that inclusion of explicit snow processes in the models would contribute to substantially improved simulations. More sophisticated snow models based on snow physics tend to produce better snow simulations, especially of snow ablation. Hysteresis of snow-cover fraction as a function of snow depth is observed at the catchment but not in any of the models.

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