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Climate change

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


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Journal ArticleDOI
TL;DR: EC-Earth, a new Earth system model based on the operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (ECMWF), is presented in this paper.
Abstract: EC-Earth, a new Earth system model based on the operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (ECMWF), is presented. The performance of version 2.2 (V2.2) of the model is compared to observations, reanalysis data and other coupled atmosphere–ocean-sea ice models. The large-scale physical characteristics of the atmosphere, ocean and sea ice are well simulated. When compared to other coupled models with similar complexity, the model performs well in simulating tropospheric fields and dynamic variables, and performs less in simulating surface temperature and fluxes. The surface temperatures are too cold, with the exception of the Southern Ocean region and parts of the Northern Hemisphere extratropics. The main patterns of interannual climate variability are well represented. Experiments with enhanced CO2 concentrations show well-known responses of Arctic amplification, land-sea contrasts, tropospheric warming and stratospheric cooling. The global climate sensitivity of the current version of EC-Earth is slightly less than 1 K/(W m−2). An intensification of the hydrological cycle is found and strong regional changes in precipitation, affecting monsoon characteristics. The results show that a coupled model based on an operational seasonal prediction system can be used for climate studies, supporting emerging seamless prediction strategies.

586 citations

Journal ArticleDOI
10 Oct 2013-Nature
TL;DR: A new index of the year when the projected mean climate of a given location moves to a state continuously outside the bounds of historical variability under alternative greenhouse gas emissions scenarios is presented.
Abstract: Ecological and societal disruptions by modern climate change are critically determined by the time frame over which climates shift beyond historical analogues. Here we present a new index of the year when the projected mean climate of a given location moves to a state continuously outside the bounds of historical variability under alternative greenhouse gas emissions scenarios. Using 1860 to 2005 as the historical period, this index has a global mean of 2069 (±18 years s.d.) for near-surface air temperature under an emissions stabilization scenario and 2047 (±14 years s.d.) under a 'business-as-usual' scenario. Unprecedented climates will occur earliest in the tropics and among low-income countries, highlighting the vulnerability of global biodiversity and the limited governmental capacity to respond to the impacts of climate change. Our findings shed light on the urgency of mitigating greenhouse gas emissions if climates potentially harmful to biodiversity and society are to be prevented.

586 citations

Journal ArticleDOI
TL;DR: The North American Regional Climate Change Assessment Program (NARCCAP) as mentioned in this paper explores separate and combined uncertainties in regional projections of future climate change resulting from the use of multiple atmosphere- ocean general circulation models (AOGCMs) to drive multiple regional climate models (RCMs).
Abstract: There are two main uncertainties in determining future climate: the trajectories of future emissions of greenhouse gases and aerosols, and the response of the global climate system to any given set of future emissions [Meehl et al., 2007]. These uncertainties normally are elucidated via application of global climate models, which provide information at relatively coarse spatial resolutions. Greater interest in, and concern about, the details of climate change at regional scales has provided the motivation for the application of regional climate models, which introduces additional uncertainty [Christensen et al., 2007a]. These uncertainties in fi ne- scale regional climate responses, in contrast to uncertainties of coarser spatial resolution global models in which regional models are nested, now have been documented in numerous contexts [Christensen et al., 2007a] and have been found to extend to uncertainties in climate impacts [Wood et al., 2004; Oleson et al., 2007]. While European research in future climate projections has moved forward systematically to examine combined uncertainties from global and regional models [Christensen et al., 2007b], North American climate programs have lagged behind. To fi ll this research gap, scientists developed the North American Regional Climate Change Assessment Program (-NARCCAP). The fundamental scientifi c motivation of thismore » international program is to explore separate and combined uncertainties in regional projections of future climate change resulting from the use of multiple atmosphere- ocean general circulation models (AOGCMs) to drive multiple regional climate models (RCMs). An equally important, and related, motivation for this program is to provide the climate impacts and adaptation community with high- resolution regional climate change scenarios that can be used for studies of the societal impacts of climate change and possible adaptation strategies.« less

586 citations

Journal ArticleDOI
TL;DR: In this paper, the authors quantify the uncertainty in the projections of these impacts arising from four sources of uncertainty: initial datasets (Data), statistical methods (SDM), general circulation models (GCM), and gas emission scenarios (GES), and extract the variance explained by each source from this whole ensemble of projections.
Abstract: Species distribution modelling has been widely applied in order to assess the potential impacts of climate change on biodiversity. Many methodological decisions, taken during the modelling process and forecasts, may, however, lead to a large variability in the assessment of future impacts. Using measures of species range change and turnover, the potential impacts of climate change on French stream fish species and assemblages were evaluated. Our main focus was to quantify the uncertainty in the projections of these impacts arising from four sources of uncertainty: initial datasets (Data), statistical methods [species distribution models (SDM)], general circulation models (GCM), and gas emission scenarios (GES). Several modalities of the aforementioned uncertainty sources were combined in an ensemble forecasting framework resulting in 8400 different projections. The variance explained by each source was then extracted from this whole ensemble of projections. Overall, SDM contributed to the largest variation in projections, followed by GCM, whose contribution increased over time equalling almost the proportion of variance explained by SDM in 2080. Data and GES had little influence on the variability in projections. Future projections of range change were more consistent for species with a large geographical extent (i.e., distribution along latitudinal or stream gradients) or with restricted environmental requirements (i.e., small thermal or elevation ranges). Variability in projections of turnover was spatially structured at the scale of France, indicating that certain particular geographical areas should be considered with care when projecting the potential impacts of climate change. The results of this study, therefore, emphasized that particular attention should be paid to the use of predictions ensembles resulting from the application of several statistical methods and climate models. Moreover, forecasted impacts of climate change should always be provided with an assessment of their uncertainty, so that management and conservation decisions can be taken in the full knowledge of their reliability.

585 citations

Journal ArticleDOI
26 Jun 2015-Science
TL;DR: An updated global surface temperature analysis reveals that global trends are higher than those reported by the Intergovernmental Panel on Climate Change, especially in recent decades, and that the central estimate for the rate of warming during the first 15 years of the 21st century is at least as great as the last half of the 20th century.
Abstract: Much study has been devoted to the possible causes of an apparent decrease in the upward trend of global surface temperatures since 1998, a phenomenon that has been dubbed the global warming “hiatus.” Here, we present an updated global surface temperature analysis that reveals that global trends are higher than those reported by the Intergovernmental Panel on Climate Change, especially in recent decades, and that the central estimate for the rate of warming during the first 15 years of the 21st century is at least as great as the last half of the 20th century. These results do not support the notion of a “slowdown” in the increase of global surface temperature.

584 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20253
20247
202312,805
202223,277
20217,120
20206,646