Title: Biophysics and vegetation cover change: a process-based evaluation framework for confronting land surface models with satellite observations
Authors: DUVEILLER BOGDAN GRÉGORY HENRY EFORZIERI GIOVANNIROBERTSON EDDYLI WEIGEORGIEVSKI GORANLAWRENCE PETERWILTSHIRE ANDYCIAIS PHILIPPEPONGRATZ JULIASITCH STEPHENARNETH ALMUTCESCATTI ALESSANDRO
Citation: EARTH SYSTEM SCIENCE DATA vol. 10 no. 3 p. 1265-1279
Publisher: COPERNICUS GESELLSCHAFT MBH
Publication Year: 2018
JRC N°: JRC111706
ISSN: 1866-3508
URI: https://www.earth-syst-sci-data.net/10/1265/2018/essd-10-1265-2018-discussion.html
http://publications.jrc.ec.europa.eu/repository/handle/JRC111706
DOI: 10.5194/essd-2018-24
Type: Articles in periodicals and books
Abstract: Land use and land cover change (LULCC) alter the biophysical properties of the Earth's surface. The associated changes in vegetation cover can perturb the local surface energy balance, which in turn can affect the local climate. The sign and magnitude of this change in climate depends on the specific vegetation transition, its timing and location, as well as on the background climate. Land surface models (LSMs) can be used to simulate such land-climate interactions and study their impact in past and future climates, but their capacity to model biophysical effects accurately across the globe remain unclear due to the complexity of the phenomena. Here we present a framework to evaluate the performance of such models with respect to a dedicated dataset derived from satellite remote sensing observations. Idealized simulations from four LSMs (JULES, ORCHIDEE, JSBACH and CLM) are combined with satellite observations to analyse the changes in radiative and turbulent fluxes caused by 15 specific vegetation cover transitions across geographic, seasonal and climatic gradients. The seasonal variation in net radiation associated with land cover change is the process that models capture best, whereas LSMs perform poorly when simulating spatial and climatic gradients of variation in latent, sensible and ground heat fluxes induced by land cover transitions. We expect that this analysis will help identify model limitations and prioritize efforts in model development as well as to inform where consensus between model and observations is already met, ultimately helping to improve the robustness and consistency of model simulations to better inform land-based mitigation and adaptation policies. The dataset is available at: https://doi.org/10.5281/zenodo.1182145.
JRC Directorate:Sustainable Resources

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