Climate change

About: Climate change is a research topic. Over the lifetime, 99222 publications have been published within this topic receiving 3572006 citations.

Projected distributions of novel and disappearing climates by 2100 AD

Abstract: Key risks associated with projected climate trends for the 21st century include the prospects of future climate states with no current analog and the disappearance of some extant climates. Because climate is a primary control on species distributions and ecosystem processes, novel 21st-century climates may promote formation of novel species associations and other ecological surprises, whereas the disappearance of some extant climates increases risk of extinction for species with narrow geographic or climatic distributions and disruption of existing communities. Here we analyze multimodel ensembles for the A2 and B1 emission scenarios produced for the fourth assessment report of the Intergovernmental Panel on Climate Change, with the goal of identifying regions projected to experience (i) high magnitudes of local climate change, (ii) development of novel 21st-century climates, and/or (iii) the disappearance of extant climates. Novel climates are projected to develop primarily in the tropics and subtropics, whereas disappearing climates are concentrated in tropical montane regions and the poleward portions of continents. Under the high-end A2 scenario, 12-39% and 10-48% of the Earth's terrestrial surface may respectively experience novel and disappearing climates by 2100 AD. Corresponding projections for the low-end B1 scenario are 4-20% and 4-20%. Dispersal limitations increase the risk that species will experience the loss of extant climates or the occurrence of novel climates. There is a close correspondence between regions with globally disappearing climates and previously identified biodiversity hotspots; for these regions, standard conservation solutions (e.g., assisted migration and networked reserves) may be insufficient to preserve biodiversity.

Mapping vulnerability to multiple stressors: climate change and globalization in India

Abstract: There is growing recognition in the human dimensions research community that climate change impact studies must take into account the effects of other ongoing global changes. Yet there has been no systematic methodology to study climate change vulnerability in the context of multiple stressors. Using the example of Indian agriculture, this paper presents a methodology for investigating regional vulnerability to climate change in combination with other global stressors. This method, which relies on both vulnerability mapping and local-level case studies, may be used to assess differential vulnerability for any particular sector within a nation or region, and it can serve as a basis for targeting policy interventions.

Uncertainty in predictions of the climate response to rising levels of greenhouse gases.

Abstract: In the climateprediction.net project, thousands of individuals have volunteered spare computing capacity on their PCs to help quantify uncertainty in the way our climate responds to increasing levels of greenhouse gases. By running a state-of-the-art climate model thousands of times, it is possible to find out how the model responds to slight changes in the approximations of physical processes that cannot be calculated explicitly. The first batch of results has now been analysed, and surface temperature changes in simulations that capture the climate realistically are ranging from below 2 °C to more than 11 °C. These represent the possible long-term change, averaged over the whole planet, as a result of doubling the levels of atmospheric carbon dioxide in the model. This is the first time that complex models have been found with such a wide range of responses. Their existence will help in quantifying the risks associated with climate change on a regional level. The range of possibilities for future climate evolution1,2,3 needs to be taken into account when planning climate change mitigation and adaptation strategies. This requires ensembles of multi-decadal simulations to assess both chaotic climate variability and model response uncertainty4,5,6,7,8,9. Statistical estimates of model response uncertainty, based on observations of recent climate change10,11,12,13, admit climate sensitivities—defined as the equilibrium response of global mean temperature to doubling levels of atmospheric carbon dioxide—substantially greater than 5 K. But such strong responses are not used in ranges for future climate change14 because they have not been seen in general circulation models. Here we present results from the ‘climateprediction.net’ experiment, the first multi-thousand-member grand ensemble of simulations using a general circulation model and thereby explicitly resolving regional details15,16,17,18,19,20,21. We find model versions as realistic as other state-of-the-art climate models but with climate sensitivities ranging from less than 2 K to more than 11 K. Models with such extreme sensitivities are critical for the study of the full range of possible responses of the climate system to rising greenhouse gas levels, and for assessing the risks associated with specific targets for stabilizing these levels.

Results of PMIP2 coupled simulations of the Mid-Holocene and Last Glacial Maximum - Part 1: experiments and large-scale features

Abstract: . A set of coupled ocean-atmosphere simulations using state of the art climate models is now available for the Last Glacial Maximum and the Mid-Holocene through the second phase of the Paleoclimate Modeling Intercomparison Project (PMIP2). This study presents the large-scale features of the simulated climates and compares the new model results to those of the atmospheric models from the first phase of the PMIP, for which sea surface temperature was prescribed or computed using simple slab ocean formulations. We consider the large-scale features of the climate change, pointing out some of the major differences between the different sets of experiments. We show in particular that systematic differences between PMIP1 and PMIP2 simulations are due to the interactive ocean, such as the amplification of the African monsoon at the Mid-Holocene or the change in precipitation in mid-latitudes at the LGM. Also the PMIP2 simulations are in general in better agreement with data than PMIP1 simulations.

A framework for community interactions under climate change

Abstract: Predicting the impacts of climate change on species is one of the biggest challenges that ecologists face Predictions routinely focus on the direct effects of climate change on individual species, yet interactions between species can strongly influence how climate change affects organisms at every scale by altering their individual fitness, geographic ranges and the structure and dynamics of their community Failure to incorporate these interactions limits the ability to predict responses of species to climate change We propose a framework based on ideas from global-change biology, community ecology, and invasion biology that uses community modules to assess how species interactions shape responses to climate change