Research & Projects

(Xiao et al., 2023, highlight in ESD)

Drought events are projected to become more severe and frequent across many regions in the future, but their impacts will likely differ among ecosystems depending on their ability to maintain functioning during droughts, i.e., ecosystem resistance. Plant species have diverse strategies to cope with drought. As a result, divergent responses of different vegetation types for similar levels of drought severity have been observed. It remains unclear whether such divergence can be explained by different drought durations; co-occurring compounding effects, e.g., heat stress or memory effects; management practices; etc.

Objectives

We provide a global synthesis of vegetation resistance to drought and heat using different proxies for vegetation conditions from satellite observations, including the newly developed vegetation optical depth (L-VOD) data from the ESA Soil Moisture and Ocean Salinity (SMOS) passive L-band microwave mission. 

Results

We find that regions with higher forest fraction show stronger ecosystem resistance to extreme droughts than cropland for all three vegetation proxies. L-VOD indicates that primary forests tend to be more resistant to drought events than secondary forests when controlling for the differences in background climate. Our results suggest that ecosystem resistance can be better monitored using L-VOD in dense forests and highlight the role of forest cover, forest management, and irrigation in determining ecosystem resistance to droughts.

Land use and land cover changes can alter terrestrial ecosystem carbon storage through their impacts on ecosystem sensitivity to drought and temperature fluctuations. Dynamic global vegetation models are commonly used to simulate the ecosystem carbon storage and we try to apply them to simulate the land use change effects on carbon storage sensitivity.

Objectives

We estimate drought and temperature sensitivities of ecosystems using vegetation greenness from satellite observations and vegetation biomass from dynamic global vegetation model (DGVM) simulations. Using a space-for-time substitution with satellite data, we first illustrate the effects of vegetation cover changes on drought and temperature sensitivity and compare them with the effects estimated from DGVMs. We also compare simulations forced by scenarios with and without land cover changes to estimate the historical land cover change effects.

Forestation is a land-based strategy to mitigate greenhouse gas emissions adopted in many scenarios to achieve the Paris Agreement goals. Observational evidence suggests that forests dampen the diurnal temperature cycle and recent studies have shown that the land surface model CLM captures this feature when accounting for biomass heat storage (BHS). Yet, the biogeophysical effects of BHS have not been assessed in simulations coupled to the atmosphere, which might strengthen or weaken the effects by changing the structure of the boundary layer or cloud formation, and cause a remote effect.

Objectives

This study uses the regional land-atmosphere coupled model COSMO-CLM2 and

the global land-atmosphere coupled model CESM to investigate the biogeophysical effects of BHS.

Results

Results indicate that BHS not only warms or cools the surface through land surface processes but also triggers changes in atmospheric water vapor and cloud cover. BHS increases evaporation and changes the pattern of moisture transport. BHS also leads to cloud cover change and incoming shortwave radiation change. The land-atmosphere coupled model with BHS reproduces the observed nighttime surface warming from forestation at high latitudes over Europe and attributes a part of it to increased incoming longwave radiation. BHS should

thus be included in land-atmosphere coupled models to assess the climate impacts of land-use changes such as deforestation or afforestation.