Sentences with phrase «over the historical period»

The best way is to look at an example that compares these options over a historical period.

«[1] Projections of 21st century warming may be derived by using regression - based methods to scale a model's projected warming up or down according to whether it under - or over-predicts the response to anthropogenic forcings over the historical period.

In any event, Marvel use the single forcing runs to appraise how TCR and ECS estimated from observations over the historical period compare with actual, CO2 forced, TCR and ECS.

The point I was making was that even if all forcing agents had an efficacy of one, as for CO2, estimating the ECS of GISS - E2 - R from simulated changes over the historical period would be expected to give too low a value, since its effective sensitivity over such a period is lower than its ECS.

Marvel et al. reached this conclusion from analysing the response of the GISS - E2 - R climate model in simulations over the historical period (1850 — 2005) when driven by six individual forcings, and also by all forcings together, the latter referred to as the «Historical» simulation.

The recent paper by Kate Marvel and others (including me) in Nature Climate Change looks at the different forcings and their climate responses over the historical period in more detail than any previous modeling study.

This approach allows us to examine what the models say about future warming relative to future emissions, without bringing in any potential model bias simulated over the historical period.

When the percentage is compared with similar companies within an industry, investors can assess those with higher income growth rates over a historical period, and gain a better idea of how profitable a company could be over time.

This is largely a result of the low efficacy of ozone and volcanic forcings and the high efficacy of aerosol and [land use] forcing (which have had a cooling effect over the historical period), although further study is needed to explore model differences in simulating efficacies and to enhance confidence in these estimates.

The prediction is initialised with the mean of the observed sea ice extent for September 2009 - 2013 and an ensemble prediction is created simply by adding all of the observed changes in the sea ice extent record from one September to the next over the historical period 1979 - 2013.

This project uses the output of an ensemble of regional climate models, driven by gridded reanalysis data over the historical period and the output of global climate models for projections of the future, to generate and analyze indices of climate extremes, as well as changes to the return periods for extreme climate events, for the Columbia Basin.

It follows that the real effect of masking to HadCRUT4 coverage over the historical period is, in the southern extra-tropics, almost certainly the opposite of that simulated by CMIP5 models.

Together these two modes explain an average of 70 % of the interannual variability seen in model Hadley Cell width indices over the historical period.

Hansen 2005 concluded that, at least for climate forcing agents over the historical period, Fs was a good measure of the effective forcing (the product of a forcing, however defined, and the efficacy taken relative thereto), notwithstanding that some forcings had different spatial distributions from others.

I find Shindell's results difficult to reconcile with the observed evolution of hemispherical and tropical temperatures relative to GMST over the historical period.

A typical experiment is over a historical period where we have observations of how much CO2 humans have put into the atmosphere, how many aerosols, how many pollutants, and you run experiments that include all of those human additions to the atmosphere.

This Nature Climate Change paper concluded, based purely on simulations by the GISS - E2 - R climate model, that estimates of the transient climate response (TCR) and equilibrium climate sensitivity (ECS) based on observations over the historical period (~ 1850 to recent times) were biased low.

Gillett et al. derive the TCR by using a regression - based method to scale the model's projected warming up or down according to whether it under - or over-predicts the response to anthropogenic forcings over the historical period.

They find that though corn yield has increased over the historical period, the sensitivity of the yields to drought stress has also increased and that the largest factor contributing to drought sensitivity are changes in vapour pressure deficit.

They do this by simulations over the historical period (1850 — 2005) driven by individual forcings, and by all forcings together, the latter referred to as the «Historical» simulation.

Gillett et al. use new historical simulations and Representative Concentration Pathway (RCP) scenario simulations using the second generation Canadian Earth System Model (CanESM2) firstly to derive scaling factors on the greenhouse gas and aerosol forcing responses which give the best fit to observations over the historical period, and then to derive observationally - constrained projections of 21st - century temperature change.

They use a regression - based method to scale the model - projected warming up or down according to whether it under - or over-predicts the response to anthropogenic forcings over the historical period.

This new NASA paper builds upon those previous studies by better quantifying the efficiencies of different forcings over the historical period and the effect this has on energy budget approach climate sensitivity estimates.

Although Marvel et al. do not mention the very low efficacy of solar forcing in their simulations, this appears to have more effect on ERF efficacy for the sum of forcings over the historical period than does low volcanic efficacy.

And the conclusion is, over the historical period, that we can not reproduce the actual observed evolution of snowpack over the region unless we introduce the human contribution to the chemistry of the atmosphere.

To help address these challenges, scientists run hurricane models calibrated with observations over the historical period to project future trends and understand the major factors driving these trends.