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  • Author or Editor: C. A. Schlosser x
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Paul A. Dirmeyer
,
C. Adam Schlosser
, and
Kaye L. Brubaker

Abstract

A synthesis of several approaches to quantifying land–atmosphere interactions is presented. These approaches use data from observations or atmospheric reanalyses applied to atmospheric tracer models and stand-alone land surface schemes. None of these approaches relies on the results of general circulation model simulations. A high degree of correlation is found among these independent approaches, and constructed here is a composite assessment of global land–atmosphere feedback strength as a function of season. The composite combines the characteristics of persistence of soil moisture anomalies, strong soil moisture regulation of evaporation rates, and reinforcement of water cycle anomalies through recycling. The regions and seasons that have a strong composite signal predominate in both summer and winter monsoon regions in the period after the rainy season wanes. However, there are exceptions to this pattern, most notably over the Great Plains of North America and the Pampas/Pantanal of South America, where there are signs of land–atmosphere feedback throughout most of the year. Soil moisture memory in many of these regions is long enough to suggest that real-time monitoring and accurate initialization of the land surface in forecast models could lead to improvements in medium-range weather to subseasonal climate forecasts.

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A. G. Slater
,
C. A. Schlosser
,
C. E. Desborough
,
A. J. Pitman
,
A. Henderson-Sellers
,
A. Robock
,
K. Ya Vinnikov
,
J. Entin
,
K. Mitchell
,
F. Chen
,
A. Boone
,
P. Etchevers
,
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
,
J. Kim
,
E. A. Kowalczyk
,
A. B. Shmakin
,
T. G. Smirnova
,
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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