Improving Representation of Deforestation Effects on Evapotranspiration in the E3SM Land Model

Abstract

Evapotranspiration (ET) plays an important role in land‐atmosphere coupling of energy, water, and carbon cycles. Following deforestation, ET is typically observed to decrease substantially as a consequence of decreases in leaf area and roots and increases in runoff. Changes in ET (latent heat flux) revise the surface energy and water budgets, which further affects large‐scale atmospheric dynamics and feeds back positively or negatively to long‐term forest sustainability. In this study, we used observations from a recent synthesis of 29 pairs of adjacent intact and deforested FLUXNET sites to improve model parameterization of stomatal characteristics, photosynthesis, and soil water dynamics in version 1 of the Energy Exascale Earth System Model (E3SM) Land Model (ELMv1). We found that default ELMv1 predicts an increase in ET after deforestation, likely leading to incorrect estimates of the effects of deforestation on land‐atmosphere coupling. The calibrated model accurately represented the FLUXNET observed deforestation effects on ET. Importantly, the search for global optimal parameters converged at values consistent with recent observational syntheses, confirming the reliability of the calibrated physical parameters. Applying this improved model parameterization to the globe scale reduced the bias of annual ET simulation by up to ~600 mm/year. Analysis on the roles of parameters suggested that future model development to improve ET simulation should focus on stomatal resistance and soil water‐related parameterizations. Finally, our predicted differences in seasonal ET changes from deforestation are large enough to substantially affect land‐atmosphere coupling and should be considered in such studies.

A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5

“…However, it is likely that this variation is small relative to other types of PFT variation (e.g., phenology) which we are able to capture using this dataset. Using the equations of Campbell and Norman (1998), which relate leaf width to dleaf by a leaf shape-dependent factor, we produce PFTdependent uncertainty bounds for dleaf (Table S6). These minimum and maximum values are then applied consistently across all PFTs for the minimum and maximum dleaf perturbation simulations, respectively.…”

“…It has also been shown previously that it is difficult to find global optimal parameter values which consistently improve skill in a climate model (Jackson et al, 2008;Williamson et al, 2015;Li et al, 2018), and we find a similar outcome when studying biophysical processes with a land model. Cai et al (2019) calibrated evapotranspiration (ET) across multiple paired FLUXNET sites in the Energy Exascale Earth System Model Land Model and found a reduction in the mean annual bias of ET when the global model was tested with the optimized parameters. This study demonstrates the potential for site-level calibration to improve a global model simulation.…”

“…Hand tuning parameter values can be computationally inefficient, requiring many model simulations and large amounts of computer time, especially when the spatial domain is large or global. Single point simulations provide a lower computational cost and the ability to more easily run large ensembles; however, results from parameter estimation at a single site may not be transferable to other regions due to differences in climate, soil, and vegetation types (Post et al, 2017;Cai et al, 2019;Huang et al, 2016;Lu et al, 2018;Ray et al, 2015). Undirected model calibration can be limited in its ability to objectively assess whether the optimal parameter configuration has been found due to the ambiguous and subjective nature of the hand tuning process (Mendoza et al, 2015;Prihodko et al, 2008).…”

Can Landsat-Derived Variables Related to Energy Balance Improve Understanding of Burn Severity From Current Operational Techniques?

“…Fire has a clear impact on stand water cycle [120] and hydrology at watershed scale [121]. Forest wildfires, importantly, alter the hydrological processes, which may impact on the growth of the forest and climate at regional scale [122,123].…”

Incorporating Spatial Variations in Parameters for Improvements of an Evapotranspiration Model

“…Specifically, a process‐based model of the terrestrial surface, which integrates biogeochemical and biogeophysical land surface processes with physical climate models, is critical to understanding the temporal and spatial patterns of ecosystem processes and their response to climate change (Atkin et al, 2015; Lin et al, 2015). Over the years, ecosystem models have grown in sophistication to include multilayer hydrology, multilayer canopies, and carbon and nitrogen cycling (Cai et al, 2019; Collalti et al, 2014; Pitman, 2003; Zaehle et al, 2014).…”