Search Results
State-of-the-art global models underestimate impacts from climate extremes
2019, Schewe, Jacob, Gosling, Simon N., Reyer, Christopher, Zhao, Fang, Ciais, Philippe, Elliott, Joshua, Francois, Louis, Huber, Veronika, Lotze, Heike K., Seneviratne, Sonia I., van Vliet, Michelle T. H., Vautard, Robert, Wada, Yoshihide, Breuer, Lutz, Büchner, Matthias, Carozza, David A., Chang, Jinfeng, Coll, Marta, Deryng, Delphine, de Wit, Allard, Eddy, Tyler D., Folberth, Christian, Frieler, Katja, Friend, Andrew D., Gerten, Dieter, Gudmundsson, Lukas, Hanasaki, Naota, Ito, Akihiko, Khabarov, Nikolay, Kim, Hyungjun, Lawrence, Peter, Morfopoulos, Catherine, Müller, Christoph, Müller Schmied, Hannes, Orth, René, Ostberg, Sebastian, Pokhrel, Yadu, Pugh, Thomas A. M., Sakurai, Gen, Satoh, Yusuke, Schmid, Erwin, Stacke, Tobias, Steenbeek, Jeroen, Steinkamp, Jörg, Tang, Qiuhong, Tian, Hanqin, Tittensor, Derek P., Volkholz, Jan, Wang, Xuhui, Warszawski, Lila
Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
Three centuries of dual pressure from land use and climate change on the biosphere
2015, Ostberg, Sebastian, Schaphoff, Sibyll, Lucht, Wolfgang, Gerten, Dieter
Human land use and anthropogenic climate change (CC) are placing mounting pressure on natural ecosystems worldwide, with impacts on biodiversity, water resources, nutrient and carbon cycles. Here, we present a quantitative macro-scale comparative analysis of the separate and joint dual impacts of land use and land cover change (LULCC) and CC on the terrestrial biosphere during the last ca. 300 years, based on simulations with a dynamic global vegetation model and an aggregated metric of simultaneous biogeochemical, hydrological and vegetation-structural shifts. We find that by the beginning of the 21st century LULCC and CC have jointly caused major shifts on more than 90% of all areas now cultivated, corresponding to 26% of the land area. CC has exposed another 26% of natural ecosystems to moderate or major shifts. Within three centuries, the impact of LULCC on landscapes has increased 13-fold. Within just one century, CC effects have caught up with LULCC effects.
A multi-model analysis of risk of ecosystem shifts under climate change
2013, Warszawski, Lila, Friend, Andrew, Ostberg, Sebastian, Frieler, Katja, Lucht, Wolfgang, Schaphoff, Sibyll, Beerling, David, Cadule, Patricia, Ciais, Philippe, Clark, Douglas B., Kahana, Ron, Ito, Akihiko, Keribin, Rozenn, Kleidon, Axel, Lomas, Mark, Nishina, Kazuya, Pavlick, Ryan, Rademacher, Tim Tito, Buechner, Matthias, Piontek, Franziska, Schewe, Jacob, Serdeczny, Olivia, Schellnhuber, Hans Joachim
Climate change may pose a high risk of change to Earth's ecosystems: shifting climatic boundaries may induce changes in the biogeochemical functioning and structures of ecosystems that render it difficult for endemic plant and animal species to survive in their current habitats. Here we aggregate changes in the biogeochemical ecosystem state as a proxy for the risk of these shifts at different levels of global warming. Estimates are based on simulations from seven global vegetation models (GVMs) driven by future climate scenarios, allowing for a quantification of the related uncertainties. 5–19% of the naturally vegetated land surface is projected to be at risk of severe ecosystem change at 2 ° C of global warming (ΔGMT) above 1980–2010 levels. However, there is limited agreement across the models about which geographical regions face the highest risk of change. The extent of regions at risk of severe ecosystem change is projected to rise with ΔGMT, approximately doubling between ΔGMT = 2 and 3 ° C, and reaching a median value of 35% of the naturally vegetated land surface for ΔGMT = 4 °C. The regions projected to face the highest risk of severe ecosystem changes above ΔGMT = 4 °C or earlier include the tundra and shrublands of the Tibetan Plateau, grasslands of eastern India, the boreal forests of northern Canada and Russia, the savanna region in the Horn of Africa, and the Amazon rainforest.
Benchmarking carbon fluxes of the ISIMIP2a biome models
2017, Chang, Jinfeng, Ciais, Philippe, Wang, Xuhui, Piao, Shilong, Asrar, Ghassem, Betts, Richard, Chevallier, Frédéric, Dury, Marie, François, Louis, Frieler, Katja, Ros, Anselmo GarcÃa Cantú, Henrot, Alexandra-Jane, Hickler, Thomas, Ito, Akihiko, Morfopoulos, Catherine, Munhoven, Guy, Nishina, Kazuya, Ostberg, Sebastian, Pan, Shufen, Peng, Shushi, Rafique, Rashid, Reyer, Christopher, Rödenbeck, Christian, Schaphoff, Sibyll, Steinkamp, Jörg, Tian, Hanqin, Viovy, Nicolas, Yang, Jia, Zeng, Ning, Zhao, Fang
The purpose of this study is to evaluate the eight ISIMIP2a biome models against independent estimates of long-term net carbon fluxes (i.e. Net Biome Productivity, NBP) over terrestrial ecosystems for the recent four decades (1971–2010). We evaluate modeled global NBP against 1) the updated global residual land sink (RLS) plus land use emissions (E LUC) from the Global Carbon Project (GCP), presented as R + L in this study by Le Quéré et al (2015), and 2) the land CO2 fluxes from two atmospheric inversion systems: Jena CarboScope s81_v3.8 and CAMS v15r2, referred to as F Jena and F CAMS respectively. The model ensemble-mean NBP (that includes seven models with land-use change) is higher than but within the uncertainty of R + L, while the simulated positive NBP trend over the last 30 yr is lower than that from R + L and from the two inversion systems. ISIMIP2a biome models well capture the interannual variation of global net terrestrial ecosystem carbon fluxes. Tropical NBP represents 31 ± 17% of global total NBP during the past decades, and the year-to-year variation of tropical NBP contributes most of the interannual variation of global NBP. According to the models, increasing Net Primary Productivity (NPP) was the main cause for the generally increasing NBP. Significant global NBP anomalies from the long-term mean between the two phases of El Niño Southern Oscillation (ENSO) events are simulated by all models (p < 0.05), which is consistent with the R + L estimate (p = 0.06), also mainly attributed to NPP anomalies, rather than to changes in heterotrophic respiration (Rh). The global NPP and NBP anomalies during ENSO events are dominated by their anomalies in tropical regions impacted by tropical climate variability. Multiple regressions between R + L, F Jena and F CAMS interannual variations and tropical climate variations reveal a significant negative response of global net terrestrial ecosystem carbon fluxes to tropical mean annual temperature variation, and a non-significant response to tropical annual precipitation variation. According to the models, tropical precipitation is a more important driver, suggesting that some models do not capture the roles of precipitation and temperature changes adequately.