Robust detection of deforestation effects on climate takes decades

Globally, about 22 million square kilometres (Mio km2) of forest have been removed between AD 800 and 2015. This deforestation might double until 2100 under the most pessimistic land-use scenario. To understand how deforestation affects climate, carbon and water fluxes is very important in view of anticipated climate change mitigation and adaptation actions.

In the recent study in Biogeosciences led by Dr Lena Boysen, Prof Victor Brovkin, and Prof Julia Pongratz from Max Planck Institute for Meteorology (MPI-M), an international team of scientists carried out idealized experiments to quantify climate effects of deforestation using nine Earth System Models (ESMs) participating in the Coupled Modeling Intercomparison Project, phase 6 (CMIP6). They found out that biogeophysical temperature changes can only be robustly detected after several decades and that these changes propagate from the centre towards the edges of tropical deforestation and westward in the boreal region.

Changes in forest cover impact climate through alterations of the biogeophysical and biogeochemical surface properties. While the first includes characteristics that impact water and energy fluxes between the land and the atmosphere, the latter include changes in the carbon cycle. The idealized scenario prepared in the Land Use Model Intercomparison Project LUMIP within the CMIP6 framework is very drastic: 20 Mio km2 of the densest pre-industrial forest areas are linearly replaced by grassland within 50 years, thus much faster than observed historically and concentrated on the boreal and tropical regions (see contours in Fig. 1).

One expected outcome was confirmed: Most of the models simulate a globally dominating cooling of on average 0.2°C with a tropical warming over deforested land due to biogeophysical effects alone. The switch in sign from warming to cooling was found to be at 23°N. The changes to the carbon cycle could induce a warming of almost half a degree. A novel contribution of the group was to estimate a “time of emergence” of deforestation, when the detected signal becomes stronger than the noise, and to analyse its spatial pattern (Fig. 1). “It is surprising“, Lena Boysen says, “that we found a radial and zonal propagation of the temperature signal in the tropics and boreal zone, respectively, partly caused by the areal shape of deforestation.” Two important lessons could be learned: First, that the biogeophysical effects of deforestation are indeed not restricted to their original location but propagated by atmospheric processes, confirming recent studies. Second, that it may take decades or a deforestation area as large as one third or half of a model’s grid cell size to detect the temperature signal. Victor Brovkin emphasizes: “It is often assumed that biogeophysical effects of large-scale forest changes are almost immediate. We show that their robust identification takes decades.” This is especially relevant since today’s annual deforestation rates are about 20% of that in the presented study. Although CO2 emissions by deforestation remain the dominant driver of global mean temperatures, biogeophysical effects can regionally dominate. "Our study provides a baseline for how differently — or similarly — nine widely used models react to changes in forest cover", says Julia Pongratz. "This is important to know because reducing deforestation and expanding reforestation are part of the portfolio of mitigating future climate change and all future projections rely on models."

Original publication:

Boysen, L., V. Brovkin, J. Pongratz, D. Lawrence, P. Lawrence, N. Vuichard, P. Peylin, S. Liddicoat, T. Hajima, Y. Zhang, M. Rocher, C. Delire, R. Séférian, V. K. Arora, L. Nieradzik, P. Anthoni, W. Thiery, M. Laguë, D. Lawrence and M-H Lo (2020) Global climate response to idealized deforestation in CMIP6 models. Biogeosciences. https://doi.org/10.5194/bg-17-5615-2020

Contact:

Dr Lena Boysen
Max Planck Institute for Meteorology
Email: lena.boysen@we dont want spammpimet.mpg.de