Franziska Piontek

Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison

Significance Agriculture is arguably the sector most affected by climate change, but assessments differ and are thus difficult to compare. We provide a globally consistent, protocol-based, multimodel climate change assessment for major crops with explicit characterization of uncertainty. Results with multimodel agreement indicate strong negative effects from climate change, especially at higher levels of warming and at low latitudes where developing countries are concentrated. Simulations that consider explicit nitrogen stress result in much more severe impacts from climate change, with implications for adaptation planning. Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

Multimodel assessment of water scarcity under climate change

Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. Here we use a large ensemble of global hydrological models (GHMs) forced by five global climate models and the latest greenhouse-gas concentration scenarios (Representative Concentration Pathways) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that a global warming of 2 °C above present (approximately 2.7 °C above preindustrial) will confront an additional approximate 15% of the global population with a severe decrease in water resources and will increase the number of people living under absolute water scarcity (<500 m3 per capita per year) by another 40% (according to some models, more than 100%) compared with the effect of population growth alone. For some indicators of moderate impacts, the steepest increase is seen between the present day and 2 °C, whereas indicators of very severe impacts increase unabated beyond 2 °C. At the same time, the study highlights large uncertainties associated with these estimates, with both global climate models and GHMs contributing to the spread. GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development.

The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): project framework.

The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up.

The modelling of feedback processes in cosmological simulations of disc galaxy formation

We conduct a systematic study of the angular momentum problem in numerical simulations of disk galaxy formation. We investigate the role of numerical resolution using a semi-cosmological setup which combines an efficient use of the number of particles in an isolated halo while preserving the hierarchical build-up of the disk through the merging of clumps. We perform the same simulation varying the resolution over 4 orders of magnitude. Independent on the level of resolution, the loss of angular momentum stays the same and can be tied to dynamical friction during the build-up phase. This is confirmed in a cosmological simulation. We also perform simulations including star formation and star formation and supernova feedback. While the former has no influence on the angular momentum problem, the latter reduces the loss to a level potentially in agreement with observations. This is achieved through a suppression of early star formation and therefore the formation of a large, slowly rotating bulge. We conclude that feedback is a critical component to achieve realistic disk galaxies in cosmological simulations. Numerical resolution is important, but by itself not capable of solving the angular momentum problem.

Multisectoral climate impact hotspots in a warming world

The impacts of global climate change on different aspects of humanity’s diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980–2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.

The Angular Momentum Problem in Cosmological Simulations of Disk Galaxy Formation

We conduct a systematic study of the angular momentum problem in numerical simulations of disk galaxy formation. We investigate the role of numerical resolution using a semi-cosmological setup which combines an efficient use of the number of particles in an isolated halo while preserving the hierarchical build-up of the disk through the merging of clumps. We perform the same simulation varying the resolution over 4 orders of magnitude. Independent on the level of resolution, the loss of angular momentum stays the same and can be tied to dynamical friction during the build-up phase. This is confirmed in a cosmological simulation. We also perform simulations including star formation and star formation and supernova feedback. While the former has no influence on the angular momentum problem, the latter reduces the loss to a level potentially in agreement with observations. This is achieved through a suppression of early star formation and therefore the formation of a large, slowly rotating bulge. We conclude that feedback is a critical component to achieve realistic disk galaxies in cosmological simulations. Numerical resolution is important, but by itself not capable of solving the angular momentum problem.

A multi-model analysis of risk of ecosystem shifts under climate change

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 (1GMT) 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 with1GMT, approximately doubling between1GMTD 2 and 3 C, and reaching a median value of 35% of the naturally vegetated land surface for1GMTD 4 C. The regions projected to face the highest risk of severe ecosystem changes above1GMTD 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.

Description of the REMIND Model (Version 1.5)

This document describes the REMIND model in its version 1.5. REMIND is an integrated assessment model of the energy-economy-climate system. REMIND stands for “Regional Model of Investments and Development.”

Counterrotating stars in simulated galaxy discs

Fil: Algorry, David Gabriel. Universidad Nacional de Cordoba. Observatorio Astronomico de Cordoba; Argentina. Consejo Nacional de Investigaciones Cientificas y Tecnicas; Argentina