Model Spread in the Fast Response of Global Precipitation
The spread due to CO2 forcing is linked to the land surface heat flux response, which is strongly influenced by vegetation processes.
We analyzed an ensemble of CMIP5 simulations to diagnose the source of model spread in the fast response of global precipitation to increased atmospheric CO2. The rapid change in land sensible and latent heat flux in response to increased CO2 explains a substantial amount of the spread in the global precipitation response. Comparison of simulations and a literature review reveal that vegetation processes, particularly stomatal closure, are an important source of model disagreement in the land heat flux response.
Our study traces an uncertain aspect of climate change, the fast response of the global hydrologic cycle, to the representation of a specific process in climate models: the physiological response of vegetation to increased CO2. Our findings suggest that an evaluation of simulated vegetation processes, including parameterizations of stomatal conductance, may help constrain model disagreement in the fast response of global-mean precipitation.
In response to an increase in CO2, globally-averaged precipitation initially decreases due to a rapid adjustment of the climate system to suppressed emission of longwave radiation. Different climate models show different magnitudes in the change of global precipitation, which contributes a non-negligible amount of scatter in Earth’s predicted hydrologic cycle intensification in a future climate. We analyzed CMIP5 model experiments to better understand the sources of this scatter. A substantial amount of the scatter can be traced to how the land surface partitions a change in sensible versus latent heat flux in response to a CO2-induced radiative perturbation. In models with a large sensible heat flux increase over land, global precipitation decreases by more, largely because the extra added heat from land stabilizes the atmosphere and suppresses ascent more in important oceanic convective regions. Furthermore, these models tend to have a large decrease in evaporation over land, drying the atmosphere and further suppressing precipitation over the ocean. An analysis of multiple CMIP5 experiments (e.g., sstClim4xCO2, amip4xCO2, and aquaplanet) and a literature review suggest that the vegetation response to increased CO2 generates considerable model variability in the land surface heat flux response. For instance, when the vegetation stomata response to CO2 concentration is disabled, variability in the land surface response reduces substantially. Our analysis suggests that evaluation of model vegetation schemes is an important step toward constraining the fast response of Earth’s hydrologic cycle to CO2 forcing.
University of California Los Angeles
- Regional & Global Climate Modeling
- Identifying Robust Cloud Feedbacks in Observations and Models