Sentences with phrase «models agree with observations»

The IPCC's detection and attribution method is meaningful to the extent that the models agree with observations against which they were not tuned and to the extent that the models agree with each other in terms of attribution mechanisms.

«There are models that predict that [nickel - 48] has such a short lifetime that we should not have been able to see it, and other models agree with our observations because they predict that it lives at least a few microseconds.»

Current models agree with observations only if certain parameters take particular values — if the forces holding matter together were stronger or weaker, for instance, the universe would not look the way it does.

Current multiverse models agree with observations only if certain parameters are given specific values — if the forces holding matter together were slightly stronger or weaker, for instance, it would be impossible for us to be here to observe the universe.

As for the models agreeing with observations — that's only because they tweaked the previous models that didn't agree so well, which gives no weight to the idea that the models are any good.

Not exact matches

Under the assumptions of their model, the team quantified the dynamics all over the exposed ocular surface, and the results agreed well with in vivo observations of the tear film gained from fluorescence imaging.

In fact, the calculation has been done very carefully by Hansen and co-workers, taking all factors into consideration, and when compared with observations of ocean heat storage over a period long enough for the observed changes to be reliably assessed, models and observations agree extremely well (see this article and this article.).

What this is saying I think is that no one had managed at that point to build a physics - based model which produces a very high sensitivity while agreeing well with observations such as the effect of the Pinatubo eruption.

The satellite observations also agree with model results that expect a growing energy imbalance as CO2 levels increase.

In models run with the GISS forcing data, the «natural + anthropogenic» temperature evolution matches observations very well for a climate sensitivity of 0.75 °C / W / m ², which agrees with the value derived from palaeoclimate data.

Models actually predict that the interior of the ice sheets should gain mass because of the increased snowfall that goes along with warmer temperatures, and recent observations actually agree with those predictions.

So, I agree with Gavin's optimism: if new models / or even old models with the new data would reproduce observations better — I would be more willing to trust them.

As it happens, AGW is a very highly politicised issue, deals with uncertain predictions based on computer models (rather than observations) and there is a substantial minority of experts, including some IPCC contributors who don't agree with this position.

Because the new precise observations agree with existing assessments of water vapor's impact, researchers are more confident than ever in model predictions that Earth's leading greenhouse gas will contribute to a temperature rise of a few degrees by the end of the century.

I think that you are going a roundabout way to agree with my observation that the models are incomplete.

The proposition to be proved (# 7) is assumed in premise # 3 by virtue of kludging of the model parameters and the aerosol forcing to agree with the 20th century observations of surface temperature.

with respect to «It is seen from the figure with both natural and human forcing that climate models simulations agree with observations very well during the period 1970 - 2000.»

Even in the warmest scenario, fewer than 5 % of model simulations of the long - term, 80 - year trend agree with observations by 2020 and fewer than 2.5 % agree by 2030.

I agree an observation / model mix is required (e.g. such as with the reanalyses), but the absence of observational validation is what is a fundamental flaw in the use of Type 4 downscaling for multi-decadal impact assessments, as I have explained in detail in my posts.

The satellite observations also agree with model results that expect a growing energy imbalance as CO2 levels increase.

If you agree with me about the method of analysis, you should also agree that the observations fall within the range of model estimates (eg Pat Michaels et al analysis, on which I am a co-author).

You'd think they'd be built into the climate models, yet the models aren't agreeing with the empirical observations.

Although I'm convinced some of the details have been mishandled, their findings are not surprising given that tropical tropospheric trends went down in the observations and up in the models for 1979 - 2009 relative to 1979 - 1999 (plus more d.o.f.) I agree with you that the MMH (and Santer H2) analysis is misplaced.

The paleo record does not agree with the instrumental record, satellite observations do not completely agree with the surface record, surface records do not completely agree with each other, and none of the records agree with the model projections.

Overlap with water vapor is important for radiation from clear skies, but shouldn't all models should get relative humidity correct and agree with observations from space?

[Page 16] This summary paragraph claims that the spatial patterns of warming from models forced with GHG's and other anthropogenic forcings agrees well with observations.

Observations agree with climate models that a 1.2 degC rise in surface temperature produces a 2.5 W / m2 increase in OLR, not the 3.7 W / m2 increase expected for a blackbody.

The Russians (one of their academys of science) have devised a climate model that agrees with observations.

I think Eli's point is that you don't just have observations in the absence of a credible physical model, and it's one I agree with.

let's take this to an extreme... suppose that internal variability is zero... then the «within group» s.d. is zero... suppose that models agree pretty well with each other and observations fall within the tight band of model projections... then by steve's method you create the average of models and call it a model... with an s.d. of zero... show that the model falls outside the observational s.d.... proclaim that the model fails... claim that this is a test of modelling... hence extrapolate that all models fail... even though observations fall slap bang in the model range... this result is nonsensical... per tco it isn't how models are used... where's structural uncertainty?

Playing with the starting value only determines whether the models and observations will appear to agree best in the early, middle or late portion of the graph.

2) The hindcast and forecast warmings simulated by climate models do not agree with empiric observations.

In fact, despite a certain warming trend is reproduced in the model, which appears to agree with the observations, the model simulation clearly fail in reproducing the cyclical dynamics of the climate that presents an evident quasi 60 - year cycle with peaks around 1880, 1940 and 2000.

I don't know about Antarctica, and CMIP5 is definitely an improvement over CMIP3, but almost two thirds of the ensemble models do not agree «reasonably well» with observations.

Despite substantial differences in performance between individual models, the CMIP3 1 and CMIP5 multi-model mean annual cycles of sea ice extent in both hemispheres agree reasonably well with observations.

The model's response agrees with observations, including the long record of geopotential height variations (a function of temperature throughout the lower atmosphere), implying that these observed 10 - 12 year oscillations are likely driven, at least partially, by solar variability.

The net result is that the models agree within reasonable bounds with the observations.

[Reply: This has nothing to do with models (who agree quite well with the observations actually).

This model's forced response agrees very well with the observed surface temperatures averaged over the North Atlantic, so in this model one doesn't need to invoke internal multidecadal variability to match these observations.