TY - JOUR
T1 - Scale-dependency of surface fluxes in an atmospheric mesoscale model
T2 - Effect of spatial heterogeneity in atmospheric conditions
AU - Hong, Jinkyu
AU - Kim, Joon
N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2008/11/3
Y1 - 2008/11/3
N2 - We examined the nonlinear effect of spatial heterogeneity in atmospheric conditions on the simulation of surface fluxes in the mesoscale model, MM5 by testing their scale-invariance from a tower footprint to regional scales. The test domain was a homogeneous shortgrass prairie in the central part of the Tibetan Plateau with an eddy-covariance flux tower at the center. We found that the spatial variability resulting from changing distribution of clouds and precipitation in the model domain affected radiative forcing at the ground surface, thereby altering the partitioning of surface fluxes. Consequently, due to increasing spatial variability in atmospheric conditions, the results of MM5 did not produce convergent estimates of surface fluxes with increasing grid sizes. Our finding demonstrates that an atmospheric model can underestimate surface fluxes in regional scale not necessarily due to intrinsic model inaccuracy (e.g., inaccurate parameterization) but due to scale-dependent nonlinear effect of spatial variability in atmospheric conditions.
AB - We examined the nonlinear effect of spatial heterogeneity in atmospheric conditions on the simulation of surface fluxes in the mesoscale model, MM5 by testing their scale-invariance from a tower footprint to regional scales. The test domain was a homogeneous shortgrass prairie in the central part of the Tibetan Plateau with an eddy-covariance flux tower at the center. We found that the spatial variability resulting from changing distribution of clouds and precipitation in the model domain affected radiative forcing at the ground surface, thereby altering the partitioning of surface fluxes. Consequently, due to increasing spatial variability in atmospheric conditions, the results of MM5 did not produce convergent estimates of surface fluxes with increasing grid sizes. Our finding demonstrates that an atmospheric model can underestimate surface fluxes in regional scale not necessarily due to intrinsic model inaccuracy (e.g., inaccurate parameterization) but due to scale-dependent nonlinear effect of spatial variability in atmospheric conditions.
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U2 - 10.5194/npg-15-965-2008
DO - 10.5194/npg-15-965-2008
M3 - Article
AN - SCOPUS:57349179894
VL - 15
SP - 965
EP - 975
JO - Nonlinear Processes in Geophysics
JF - Nonlinear Processes in Geophysics
SN - 1023-5809
IS - 6
ER -