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Data · dataset · 2026

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

Listed in National Center for Atmospheric Research

Land surface models incorporate a large number of process descriptions, containing a multitude of parameters.

Description

These parameters are typically read from tabulated input files. Some of these parameters might be fixed numbers in the computer code though, which hinder model agility during calibration.

Here we identified 139 hard-coded parameters in the model code of the Noah land surface model with multiple process options (Noah-MP). We performed a Sobol' global sensitivity analysis of Noah-MP for a specific set of process options, which includes 42 out of the 71 standard parameters and 75 out of the 139 hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated at 12 catchments within the United States with very different hydrometeorological regimes.

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Noah-MP's hydrologic output fluxes are sensitive to two thirds of its applicable standard parameters (i.e., Sobol' indexes above 1%). The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for direct evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs.

These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities because of their tight coupling via the water balance.

A calibration of Noah-MP against either of these fluxes should therefore give comparable results. Moreover, these fluxes are sensitive to both plant and soil parameters. Calibrating, for example, only soil parameters hence limit the ability to derive realistic model parameters.

It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

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Hydrology 70%
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National Center for Atmospheric Researchf03a7594-90e2-4fc6-aca0-3b792d553db711 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].anzsrc:group:3707enrichment · data ucar edutaxonomy-embedding@1.1.0title+keywords+description (70%)
concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0