Parameter Sensitivity of the Noah-MP Land Surface Model with Dynamic Vegetation

Author:

Arsenault Kristi R.1,Nearing Grey S.2,Wang Shugong1,Yatheendradas Soni3,Peters-Lidard Christa D.4

Affiliation:

1. Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, and Science Applications International Corporation, McLean, Virginia

2. Department of Geological Sciences, University of Alabama, Tuscaloosa, Alabama

3. Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, and Earth Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland

4. Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, Maryland

Abstract

Abstract The Noah land surface model with multiple parameterization options (Noah-MP) includes a routine for the dynamic simulation of vegetation carbon assimilation and soil carbon decomposition processes. To use remote sensing observations of vegetation to constrain simulations from this model, it is necessary first to understand the sensitivity of the model to its parameters. This is required for efficient parameter estimation, which is both a valuable way to use observations and also a first or concurrent step in many state-updating data assimilation procedures. We use variance decomposition to assess the sensitivity of estimates of sensible heat, latent heat, soil moisture, and net ecosystem exchange made by certain standard Noah-MP configurations that include the dynamic simulation of vegetation and carbon to 43 primary user-specified parameters. This is done using 32 years’ worth of data from 10 international FluxNet sites. Findings indicate that there are five soil parameters and six (or more) vegetation parameters (depending on the model configuration) that act as primary controls on these states and fluxes.

Funder

National Oceanic and Atmospheric Administration

NASA’s Water Resources Applied Sciences Program

NASA’s Advanced Information Systems Technology (AIST) Program

Publisher

American Meteorological Society

Subject

Atmospheric Science

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