Does dynamically modeled leaf area improve predictions of land surface water and carbon fluxes? Insights into dynamic vegetation modules

Abstract. Land surface models represent exchange processes between soil and the atmosphere via the land surface by coupling water, energy and carbon fluxes. As a strong mediator between these cycles, vegetation is an important component of land surface models. Some land surface models include modules for vegetation dynamics, which allow for the adjustment of vegetation biomass, especially leaf area index, to environmental conditions. Here, we conducted a model–data comparison to investigate whether and how vegetation dynamics in the models improve the representation of vegetation processes and related surface fluxes in two specific models, ECLand and Noah-MP, in contrast to using prescribed values from lookup tables or satellite-based products. We compared model results with observations across a range of climate and vegetation types from the FLUXNET2015 dataset and the MODIS leaf area product and used on-site-measured leaf area from an additional site. Yet, switching on the dynamic vegetation did not enhance representativeness of leaf area index and net ecosystem exchange in ECLand, while it improved performance in Noah-MP only for some sites. The representation of energy fluxes and soil moisture was almost unaffected for both models. Interestingly, the performance regarding variables of the carbon and water cycles was unrelated for both models such that the weak performance of, e.g., leaf area index did not deteriorate the performance of, e.g., latent heat flux. We show that one potential reason for this could be that the implemented ecosystem processes diverge from the observations in their seasonal patterns and variability. Noah-MP includes a seasonal hysteresis in the relationship between leaf area index and gross primary production that is not found in observations. The same relationship is represented by a strong linear response in ECLand, which substantially underestimates the observed variability. For both water and carbon fluxes, the currently implemented dynamic vegetation modules in these two models did not result in better model performance compared to runs with static vegetation and prescribed leaf area climatology.