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Exploring parameter sensitivities of the land surface using a locally coupled land‐atmosphere model
Author(s) -
Liu Yuqiong,
Gupta Hoshin V.,
Sorooshian Soroosh,
Bastidas Luis A.,
Shuttleworth William J.
Publication year - 2004
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2004jd004730
Subject(s) - sensitivity (control systems) , atmosphere (unit) , environmental science , atmospheric model , meteorology , data assimilation , atmospheric research , latent heat , climate sensitivity , sensible heat , climate model , climatology , climate change , geology , geography , oceanography , electronic engineering , engineering
This paper presents a multicriteria analysis that explores the sensitivity of the land surface to changes in both land and atmospheric parameters, in terms of reproducing surface heat fluxes and ground temperature; for the land parameters, offline sensitivity analyses were also conducted for comparison to infer the influence of land‐atmosphere interactions. A simple “one‐at‐a‐time” sensitivity analysis was conducted first to filter out some insensitive parameters, followed by a multicriteria sensitivity analysis using the multiobjective generalized sensitivity analysis algorithm. The models used were the locally coupled National Center for Atmospheric Research (NCAR) single‐column community climate model and the offline NCAR land surface model, driven and evaluated by a summer intensive operational periods (IOP) data set from the southern Great Plains. As expected, the results show that land‐atmosphere interactions (with or without land‐atmosphere parameter interactions) can have significant influences on the sensitivity of the land surface to changes in the land parameters, and the single‐criterion sensitivities can be significantly different from the multicriteria sensitivity. These findings are mostly model and data independent and can be generally useful, regardless of the model/data dependence of the sensitivities of individual parameters. The exceptionally high sensitivities of the selected atmospheric parameters in a multicriteria sense (and in particular for latent heat) appeal for adequate attention to the specification of effective values of these parameters in an atmospheric model. Overall, this study proposes an effective framework of multicriteria sensitivity analysis beneficial to future studies in the development and parameter estimation of other complex (offline or coupled) land surface models.

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