The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe. In large-scale complex dynamical systems such as the Earth system, real experiments are rarely feasible. However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the commonly adopted correlation techniques. Here, we give an overview of causal inference frameworks and identify promising generic application cases common in Earth system sciences and beyond. We discuss challenges and initiate the benchmark platform
causeme.net
to close the gap between method users and developers.
Abstract. Afforestation and reforestation have become popular instruments of climate mitigation policy, as forests are known to store large quantities of carbon. However, they also modify the fluxes of energy, water and momentum at the land surface. Previous studies have shown that these biogeophysical effects can counteract the carbon drawdown and, in boreal latitudes, even overcompensate it due to large albedo differences between forest canopy and snow. This study investigates the role forest cover plays for global climate by conducting deforestation and afforestation experiments with the earth system model of the Max Planck Institute for Meteorology (MPI-ESM). Complete deforestation of the tropics (18.75 • S-15 • N) exerts a global warming of 0.4 • C due to an increase in CO 2 concentration by initially 60 ppm and a decrease in evapotranspiration in the deforested areas. In the northern latitudes (45 • N-90 • N), complete deforestation exerts a global cooling of 0.25 • C after 100 years, while afforestation leads to an equally large warming, despite the counteracting changes in CO 2 concentration. Earlier model studies are qualitatively confirmed by these findings. As the response of temperature as well as terrestrial carbon pools is not of equal sign at every land cell, considering forests as cooling in the tropics and warming in high latitudes seems to be true only for the spatial mean, but not on a local scale.
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