Biogeophysical controls on land-atmosphere fluxes in the Community Earth System Model

Thursday, 18 December 2014
Daniel M Ricciuto, Jiafu Mao and Xiaoying Shi, Oak Ridge National Laboratory, Oak Ridge, TN, United States
Global land surface models and Earth system models are computationally expensive and contain large numbers of uncertain parameters, limiting the feasibility of uncertainty quantification (UQ) studies that require model ensembles on a global scale. Fortunately, even relatively small model ensembles can yield useful information about key model parameter sensitivities. Knowledge about how parameter sensitivities vary across space, time and model outputs are of key importance to not only the modeling community, but also the measurement community as this knowledge can inform observation strategies targeted at reducing prediction uncertainty. Here we apply the Morris method, a basic but efficient way to perform a parameter sensitivity analysis, on 24 biogeophysical parameters in CLM, using 200 global offline 1.9x2.5 degree global simulations. Model output variables of interest are photosynthetic fluxes, energy fluxes, and hydrologic variables. We find that the ranking of parameter importance strongly depends on climate (e.g. mean annual temperature and precipitation). The parameterization of stomatal conductance is particularly important in most locations. We also evaluate the performance of the model ensemble against benchmark datasets for evapotranspiration and gross primary productivity. We then present results from a second ensemble of land-atmosphere coupled simulations, using the Community Earth System Model (CESM), investigating in particular the sensitivity of land-atmosphere feedbacks to 5 key CLM biogeophysical parameters.