Archives par mot-clé : Model(s)

Ross McKitrick: All those warming-climate predictions suddenly have a big, new problem

by Ross McKitrick, June 20, 2018 in FinancialPost


One of the most important numbers in the world goes by the catchy title of Equilibrium Climate Sensitivity, or ECS. It is a measure of how much the climate responds to greenhouse gases. More formally, it is defined as the increase, in degrees Celsius, of average temperatures around the world, after doubling the amount of carbon dioxide in the atmosphere and allowing the atmosphere and the oceans to adjust fully to the change. The reason it’s important is that it is the ultimate justification for governmental policies to fight climate change.

The United Nations Intergovernmental Panel on Climate Change (IPCC) says ECS is likely between 1.5 and 4.5 degrees Celsius, but it can’t be more precise than that. Which is too bad, because an enormous amount of public policy depends on its value. People who study the impacts of global warming have found that if ECS is low — say, less than two — then the impacts of global warming on the economy will be mostly small and, in many places, mildly beneficial.

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100% Of Climate Models Prove that 97% of Climate Scientists Were Wrong!

by Eric Holthaus, May 2018 , in Climatism


SEPTEMBER 2017

Dr. Christy was 100% correct …

A landmark paper by warmist scientists in Nature Geoscience now concedes the world has indeed not warmed as predicted, thanks to a slowdown in the first 15 years of this century. One of its authors, Michael Grubb, professor of international energy and climate change at University College London, admits his past predictions of runaway warming were too alarmist.

When the facts change, I change my mind. We are in a better place than I thought.”

ANOTHER author, Myles Allen, professor of geosystem science at Oxford, confessed that too many of the mathematical models used by climate scientists to predict future warming “were on the hot side” — meaning they exaggerated.

We haven’t seen that rapid acceleration in warming after 2000 that we see in the models.” 

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How Not To Model The Historical Temperature

by Willis Eschenbach, March 24, 2018 in WUWT


Much has been made of the argument that natural forcings alone are not sufficient to explain the 20th Century temperature variations. Here’s the IPCC on the subject:

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I’m sure you can see the problems with this. The computer model has been optimized to hindcast the past temperature changes using both natural and anthropogenic forcings … so of course, when you pull a random group of forcings out of the inputs, it will perform more poorly.

The Modern Warm Period Delimited

by David Archibald, March 10, 2018 on WUWT


This recent post discussed the end of the Modern Warm Period and the year that global cooling began. That post was inspired by a comment to a post on WUWT six to eight years ago to the effect that climate is controlled by the Sun’s magnetic flux – no need to worry about much else. The comment seemed to come from a warmer scientist – they are well funded, have plenty of time on their hands, some are smart and idle curiosity would get a few looking into what controls climate. The results would not be published of course. To paraphrase Mussolini, everything within the narrative, nothing outside the narrative, nothing against the narrative. If the Sun’s magnetic flux controls climate, you don’t have to worry about what goes on under the hood – the effect of EUV on the NAO, the GCR flux, the F10.7 flux, any other flux apart from the magnetic flux (…)

A 1D Model of Global Temperature Changes, 1880-2017: Low Climate Sensitivity (and More)

by Dr Roy Spencer, February 22, 2018 in GlobalWarming


UPDATE(2/23/18): The previous version of this post had improper latitude bounds for the HadCRUT4 Tsfc data. I’ve rerun the results… the conclusions remain the same. I have also added proof that ENSO is accompanied by its own radiative forcing, a controversial claim, which allows it to cause multi-decadal climate change. In simple terms, this is clear evidence the climate system can cause its own, natural, internally-generated climate changes. This is partly what has caused recent warming, and the climate modelling community has assumed it was all human-caused.

IT’S-THE-SUN Climate Science Steamrolls Into 2018

by K. Richard, February 22, 2018 in NoTricksZone


According to the United Nations Intergovernmental Panel on Climate Change (UN-IPCC) and computer modeling, the Sun’s role in modern-era climate change checks in at somewhere slightly above nothing.

And yet it is increasingly evident that more and more scientists across the globe do not take the position that the Sun’s influence on climate change is negligible.

In 2016 and 2017, for example, over 250 papers (see here and here) linking the Sun to climate changes were published in scientific journals.

Worse than we thought’ – climate models underestimate future polar warming

by  FLORIDA MUSEUM OF NATURAL HISTORY,  January 23, 2018, in WUWT, A. Watts


The researchers published their findings this week in the Proceedings of the National Academy of Sciences.

Scientists frequently look to the Eocene to understand how the Earth responds to higher levels of carbon dioxide. During the Eocene, the concentration of carbon dioxide in the atmosphere was more than 560 parts per million, at least twice preindustrial levels, and the epoch kicked off with a global average temperature more than 8 degrees Celsius – about 14 degrees Fahrenheit – warmer than today, gradually cooling over the next 22 million years. These characteristics make the Eocene a good period on which to test our understanding of the climate system, said Laura Cotton, study co-author and curator of micropaleontology at the Florida Museum of Natural History.

Emergent constraint on equilibrium climate sensitivity from global temperature variability

by P.M. Cox et al., January 18, 2018 in Nature


Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO2) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO2.

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This metric of variability can also be calculated from observational records of global warming3, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

Study: Climate models underestimate cooling effect of daily cloud cycle

by Princeton University, January 10, 2018 in WUWT


Princeton University researchers have found that the climate models scientists use to project future conditions on our planet underestimate the cooling effect that clouds have on a daily — and even hourly — basis, particularly over land.

The researchers report in the journal Nature Communications Dec. 22 that models tend to factor in too much of the sun’s daily heat, which results in warmer, drier conditions than might actually occur. The researchers found that inaccuracies in accounting for the diurnal, or daily, cloud cycle did not seem to invalidate climate projections, but they did increase the margin of error for a crucial tool scientists use to understand how climate change will affect us.

Study: Climate models underestimate cooling effect of daily cloud cycle

by Princeton University, January 10, 2018 in A. Watts WUWT


Princeton University researchers have found that the climate models scientists use to project future conditions on our planet underestimate the cooling effect that clouds have on a daily — and even hourly — basis, particularly over land.

The researchers report in the journal Nature Communications Dec. 22 that models tend to factor in too much of the sun’s daily heat, which results in warmer, drier conditions than might actually occur. The researchers found that inaccuracies in accounting for the diurnal, or daily, cloud cycle did not seem to invalidate climate projections, but they did increase the margin of error for a crucial tool scientists use to understand how climate change will affect us.

La modélisation du climat, science ou scientisme ?

by Uzbek, 21 novembre 2017, in Climato-Réalistes


Les prévisions climatiques à très long terme (2100) sont établies à l’aide de modèles qui ne sont rien d’autre des logiciels très complexes, dont le but est de reproduire le comportement du climat terrestre.

Comme on ne peut pas décrire ce qui se passe en tous les points de la terre, celle-ci est découpée en mailles de quelques centaines de kilomètres de côté. Les modèles utilisés par le GIEC pour son cinquième rapport d’évaluation (2013) avaient des résolutions relativement grossières (supérieures à 100 km). La situation évolue toutefois rapidement et les modèles climatiques les plus récents auraient une résolution plus fine (de l’ordre de 20 km).

Egalement ici et ici

Causal feedbacks in climate change

by E.H. van Nes et al., March 30, 2015 in Nature Climate Change


The statistical association between temperature and greenhouse gases over glacial cycles is well documented, but causality behind this correlation remains difficult to extract directly from the data.

We show that such variable time lags are typical for complex nonlinear systems such as the climate, prohibiting straightforward use of correlation lags to infer causation.

Core of climate science is in the real-world data

by Eric Worrall, November 22, 2017 in WUWT


Figure 1 shows one example of data derived from such proxy sources. The top panel of the figure shows a declining temperature trend over the 8,000-year period from the Holocene Climate Optimum to the modern warm period (left-hand scale). It also shows that this location experienced numerous cycles of warming and cooling that involved temperature changes of the order of two degrees Celsius.