Sentences with phrase «large ensembles of climate models»

Further, a large ensemble of climate model realizations reveals that additional global warming over the next few decades is very likely to create ∼ 100 % probability that any annual - scale dry period is also extremely warm.

A large ensemble of climate model simulations suggests that the frequency of extreme wet - to - dry precipitation events will increase by 25 % to 100 % across California due to anthropogenic forcing.

it says «Large ensembles of climate model simulations have shown that the ability of models to simulate present climate has value in constraining climate sensitivity.».

Not exact matches

To understand the role of human - induced climate change in these new records they compare simulations of the Earth's climate from nine different state - of - the - art climate models and the very large ensemble of climate simulations provided by CPDN volunteers for the weather@home ANZ experiments for the world with and without human - induced climate change.

Murphy, J.M., et al., 2004: Quantification of modelling uncertainties in a large ensemble of climate change simulations.

The analysis of processes contributing to climate feedbacks in models and recent studies based on large ensembles of models suggest that in the future it may be possible to use observations to narrow the current spread in model projections of climate change.

A large ensemble of Earth system model simulations, constrained by geological and historical observations of past climate change, demonstrates our self ‐ adjusting mitigation approach for a range of climate stabilization targets ranging from 1.5 to 4.5 °C, and generates AMP scenarios up to year 2300 for surface warming, carbon emissions, atmospheric CO2, global mean sea level, and surface ocean acidification.

M2009 use a simplified carbon cycle and climate model to make a large ensemble of simulations in which principal uncertainties in the carbon cycle, radiative forcings, and climate response are allowed to vary, thus yielding a probability distribution for global warming as a function of time throughout the 21st century.

Also, even though we focus on the ensemble - mean response, the range of model responses is also interesting and important to understand; and the climate model response of large - scale environmental conditions needs to be more explicitly connected to the response of tropical storms.

Massey, N., R. Jones, F. E. L. Otto, T. Aina, S. Wilson, D. Hassell and M. R. Allen: weather@home: very large ensemble regional climate modelling, submitted to the Quarterly Journal of the Royal Meteorological Society.

Koutsoyiannis (2011) showed that an ensemble of climate model projections is fully contained WITHIN the uncertainty envelope of traditional stochastic methods using historical data, including the Hurst phenomena... the Hurst phenomena (1951) describes the large and long excursions of natural events above and below their mean, as opposed to random processes which do not exhibit such behavior.

Sylvain, one of the main challenges of verifying climate models on a time scale of 1 - 2 decades is that natural forcing (solar and volcanic) is unknown plus the decadal ocean cycles are not deterministic and will not be simulated in a way that matches observations unless a very large ensemble is used.

Using an ensemble of 22 computer climate models and a comprehensive index of drought conditions, as well as analyses of previously published studies, the paper finds most of the Western Hemisphere (along with large parts of Eurasia, Africa, and Australia) may be at threat of extreme drought this century.

M2009 use a simplified carbon cycle and climate model to make a large ensemble of simulations in which principal uncertainties in the carbon cycle, radiative forcings, and climate response are allowed to vary, thus yielding a probability distribution for global warming as a function of time throughout the 21st century.

Alternatively, an automated procedure based on a cluster initialization algorithm is proposed and applied to changes in 27 climate extremes indices between 1986 — 2005 and 2081 — 2100 from a large ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations.

The very high significance levels of model — observation discrepancies in LT and MT trends that were obtained in some studies (e.g., Douglass et al., 2008; McKitrick et al., 2010) thus arose to a substantial degree from using the standard error of the model ensemble mean as a measure of uncertainty, instead of the ensemble standard deviation or some other appropriate measure for uncertainty arising from internal climate variability... Nevertheless, almost all model ensemble members show a warming trend in both LT and MT larger than observational estimates (McKitrick et al., 2010; Po - Chedley and Fu, 2012; Santer et al., 2013).

We assess this possibility using an ensemble of 30 realizations of a single global climate model [the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM1) Large Ensemble experiment («LENS»)-RSB-(29)(Materials and Mensemble of 30 realizations of a single global climate model [the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM1) Large Ensemble experiment («LENS»)-RSB-(29)(Materials and Methmodel [the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM1) Large Ensemble experiment («LENS»)-RSB-(29)(Materials and MethModel (CESM1) Large Ensemble experiment («LENS»)-RSB-(29)(Materials and MEnsemble experiment («LENS»)-RSB-(29)(Materials and Methods).

These fingerprints will be based on a large, multi-model ensemble of state - of - the - art climate model simulations.

The MaRIUS project will make use of the large ensemble of regional climate model runs available from our weather@home experiments.

The black line is a simulated mean sea ice concentration from the CanESM2 large ensemble, a group of models developed at the Canadian Center for Climate Modelling and Analysis.

We are using the citizen science regional climate modelling project weather@home to perform large ensembles of the different experiments described below.

In this study, we primarily investigate the reliability of the climatology (long - term mean of model simulation) of large - scale features of climate model ensembles, but we also consider the trend for surface air temperature where transient simulations are available (that is, for the coupled ocean — atmosphere models).

To answer this question, large ensemble simulations of regional climate models will be carried out for an East Asian domain for two worlds: (1) Real world condition for which the observed sea surface temperatures will be prescribed and (2) Counter-factual world condition for which we will use adjusted sea surface temperatures obtained by removing human - induced ocean warming patterns.

Influence of blocking on Northern European and Western Russian heatwaves in large climate model ensembles (open access)

For independent realisations, the natural variability noise is reduced by the ensemble averaging (averaging to zero for a large enough ensemble) so that -LCB- T -RCB- is an improved estimate of the model s forced climate change Tf.

So I will be interested to hear your take on whether this sort of thing is now justified in light of «Broad range of 2050 warming from an observationally constrained large climate model ensemble» Rowlands et al 2012 Or whether you think there are major problems with that paper (whether along the lines expressed here or different problems).

The community earth system model (CESM) large ensemble project: A community resource for studying climate change in the presence of internal climate variability

In a new study published in the Journal of Climate, the Community Earth System Model Large Ensemble (CESM - LENS) of simulations is used to explore how various characteristics of the mid-latitude atmospheric circulation (zonal flow, synoptic blockings, jet stream meanders) evolve along the course of the 21st century under the RCP8.5 scenario of anthropogenic emissions.

Especially for the climate variables such as SAT, SLP, SW and LW clear - sky radiation as shown in Fig 6 (1), (3), (6), and (9), the average of errors in MMEs and SMEs are similar, but the distances between model ensembles in MMEs are larger than SMEs.