Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Abstract

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Intermodel variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily-monthly) timescales and reduces on longer (seasonal-annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models. K E Y W O R D S drought, irrigation, rainfall manipulation experiment, terrestrial biosphere models

Climate Extreme Versus Carbon Extreme: Responses of Terrestrial Carbon Fluxes to Temperature and Precipitation

“…Water stress on ecosystem productivity in the satellite observations was estimated based on the atmospheric water demand (i.e., vapor pressure deficit) but not water supply (i.e., soil water availability; W. Smith et al, ), while the TBMs in this study included more sophisticated mechanisms to represent soil water stresses by considering water supply and demand (e.g., Ito & Inatomi, ; Krinner et al, ; Zeng et al, ). Previous studies have reported that the lack of dynamic root growth, hydrological redistribution, groundwater movement, and reasonable carbon allocation during droughts in models are potential causes responsible for larger estimation of vegetation response to water deficit (Hu et al, ; Li et al, ; Paschalis et al, ). For example, during Amazon droughts, trees can increase water use efficiency and uptake water from aquifer through deep roots to mitigate drought impacts (Goll et al, ; Yang et al, ).…”

Timing outweighs amount of rainfall in shaping population dynamics

“…Changes in rainfall regime are occurring worldwide 4,5 and have substantial consequences for vertebrate population dynamics, the species composition of communities and ecosystem functions and services 6,7 .…”

Marching in step: The importance of matching model complexity to data availability in terrestrial biosphere models

“…Rainfall manipulation experiments are among our best physical approximations of future scenarios and serve as important benchmarks for measuring the performance of terrestrial biosphere models. By synthesizing results from rainfall manipulation experiments across a range of biomes and environments, a new study by Paschalis et al (2020) diagnoses current limitations in model structure, identifies new data needs, and provides lessons for future model development.…”

“…Thus, translating rainfall into ecosystem‐level water, energy, and carbon fluxes is a nontrivial and cross‐scale process, with the effects of rainfall at various spatial scales typically captured within terrestrial biosphere models by coupling a land surface scheme with a hydrological modeling component and a dynamic vegetation module. The main question that drives Paschalis et al (2020) is whether ecosystem responses to rainfall variability—subject to all the scaling challenges above—have been adequately represented within terrestrial biosphere models. This is done by synthesizing results from 10 terrestrial ecosystem models applied to rainfall manipulation experiments at a number of sites spanning a wide range of biomes and environments.…”

“…However, even without computational constraints, simulating ecosystem water and carbon fluxes at increasingly fine spatial and temporal scales is not the best way to improve model performance in the absence of scale‐appropriate data. A model originally designed for, and calibrated against, only annual net primary productivity, for example, should not be expected to perform well for intermediate variables (e.g., leaf area index) or at different timescales (e.g., within‐year seasonal variations; exemplified by figure 4 of Paschalis et al, 2020). Therefore, the use of data serves two complementary purposes during model development.…”