Addressing the ability of a land biosphere model to predict key biophysical vegetation characterisation parameters with Global Sensitivity Analysis

摘要

Sensitivity Analysis (SA) of the SimSphere Soil Vegetation Atmosphere Transfer (SVAT) model has been performed in this study using a cutting edge and robust Global Sensitivity Analysis (GSA) approach, based on the use of the Gaussian Emulation Machine for Sensitivity Analysis (GEM-SA) tool. The sensitivity of the following model outputs was evaluated: the ambient CO_2 concentration, the rate of CO_2 uptake by the plant, the ambient O_3 concentration, the flux of O_3 from the air to the plant/soil boundary and the flux of O_3 taken up by the plant alone. The most sensitive model inputs for the majority of outputs were: The Leaf Area Index (LAI), Fractional Vegetation Cover (Fr), Cuticle Resistance (CR) and Vegetation Height (VH). The influence of the external CO_2 on the leaf and O_3 concentration in the air as input parameters was also significant. Our study provides an important step forward in the global efforts towards SimSphere verification given the increasing interest in its use as an independent modelling or educational tool. Results of this study are also timely given the ongoing global efforts focused on deriving, at an operational level, spatio-temporal estimates of energy fluxes and soil moisture content using SimSphere synergistically with Earth Observation (EO) data.