Archives par mot-clé : Model(s)

Circular reasoning with climate models

by Dr. Wojick, March 1, 2018 in CFact


Climate models play a central role in the attribution of global warming or climate change to human causes. The standard argument takes the following form: “We can get the model to do X, using human causes, but not without them, so human causes must be the cause of X.” A little digging reveals that this is actually a circular argument, because the models are set up in such a way that human causes are the only way to get change.

The finding is that humans are the cause of global warming and climate change is actually the assumption going in. This is circular reasoning personified, namely conclude what you first assume.

This circularity can be clearly seen in what many consider the most authoritative scientific report on climate change going, although it is actually just the most popular alarmist report. We are talking about the Summary for Policymakers (SPM), of the latest assessment report (AR5), of the heavily politicized UN Intergovernmental Panel on Climate Change (IPCC). Their 29 page AR5 SPM is available here.

40387018 – the raging whirlpool

Global-scale multidecadal variability missing in state-of-the-art climate models

by S. Kravstov et al. 2018, in Nature


Reliability of future global warming projections depends on how well climate models reproduce the observed climate change over the twentieth century. In this regard, deviations of the model-simulated climate change from observations, such as a recent “pause” in global warming, have received considerable attention. Such decadal mismatches between model-simulated and observed climate trends are common throughout the twentieth century, and their causes are still poorly understood. Here we show that the discrepancies between the observed and simulated climate variability on decadal and longer timescale have a coherent structure suggestive of a pronounced Global Multidecadal Oscillation. Surface temperature anomalies associated with this variability originate in the North Atlantic and spread out to the Pacific and Southern oceans and Antarctica, with Arctic following suit in about 25–35 years. While climate models exhibit various levels of decadal climate variability and some regional similarities to observations, none of the model simulations considered match the observed signal in terms of its magnitude, spatial patterns and their sequential time development. These results highlight a substantial degree of uncertainty in our interpretation of the observed climate change using current generation of climate models.

Reassessing the RCPs

by Kevin Murphy in Judith Curry, January 28, 2019 in ClimateEtc.


A response to: “Is RCP8.5 an impossible scenario?”. This post demonstrates that RCP8.5 is so highly improbable that it should be dismissed from consideration, and thereby draws into question the validity of RCP8.5-based assertions such as those made in the Fourth National Climate Assessment from the U.S. Global Change Research Program.

Analyses of future climate change since the IPCC’s 5th Assessment Report (AR5) have been based on representative concentration pathways (RCPs) that detail how a range of future climate forcings might evolve.

Several years ago, a set of RCPs were requested by the climate modeling research community to span the range of net forcing from 2.6 W/m2 to 8.5 W/m2 (in year 2100 relative to 1750) so that physics within the models could be fully exercised. Four of them were developed and designated as RCP2.6, RCP4.5, RCP6.0 and RCP8.5. They have been used in ongoing research and as the basis for impact analyses and future climate projections.

Figure 2. History and forecasts of CO2 concentration. RCP8.5 is defined by 936 ppm in 2100.

Simplest climate model yet – a bathtub

by Charles the moderator, January 18, 2019 in WUWT


Climate change: How could artificial photosynthesis contribute to limiting global warming?

Scientists calculate areas needed for forestation and artificial photosynthesis.

After several years during which global emissions at least stagnated, they rose again somewhat in 2017 and 2018. Germany has also clearly missed its climate targets. In order to keep global warming below 2 degrees Celsius, only about 1100 gigatonnes of CO2 may be released into the atmosphere by 2050[1]. And In order to limit global warming to 1.5 degrees, only just under 400 gigatonnes of CO2 may be emitted worldwide. By 2050, emissions will have to fall to zero even. Currently, however, 42 gigatonnes of CO2 are added every year.

Almost all the various scenarios require “negative emissions”

Regional Models: 3-10°C Warming In The Next 80 Years. Observations: No Warming In The Last 40-100 Years.

by K. Richard, January 14, 2019 in NoTricksZone


There are large regions of the globe where observations indicate there has been no warming (even cooling) during the last decades to century. Climate models rooted in the assumption that fossil fuel emissions drive dangerous warming dismiss these modeling failures and project temperature increases of 3° – 10°C by 2100 for these same regions anyway.

Image Source: Partridge et al., 2018

Evolutions récentes du CO2 atmosphérique (3/4)

by J.C. Maurin, 12 novembre 2018 in ScienceClimatEnergie


L’IPCC (GIEC en français) fut créé en 1988 par l’UNEP (United Nations Environment Programme) et le WMO (World Meteorological Organization). Dans les principes régissant les travaux du GIEC (1) on lit : Le GIEC a pour mission d’évaluer … les risques liés au changement climatique d’origine humaine.  Le GIEC respecte son propre principe fondateur : il attribue l’intégralité de la hausse du taux de CO2 depuis 1958 à une cause anthropique. Nous examinerons ici le modèle anthropique du GIEC et nous le confronterons aux mesures contemporaines, puis à un modèle mixte. Cet article fait suite aux deux précédents publiés sur le site SCE au cours des mois de septembre (1/4) et octobre 2018 (2/4).

C.   Modèle anthropique GIEC

C.1   Les contraintes des modèles (Fig. 1)

Le paragraphe A (article 1/4) a montré qu’en 1980 le taux de CO2 atmosphérique était de 338 ppm et le  δ13C de -7.6 ‰. En  2010 le taux de CO2  atmosphérique était de 388 ppm et le δ13C de -8.3 ‰. Il existe une modulation annuelle de ce taux, très marquée dans l’hémisphère Nord.

 

Interview exclusive: Henri Masson, Université d’Anvers, déclare les modèles du GIEC « aberration statistique »

by Henri Masson, 10 mars 2012, in Contrepoints


Des modèles, cela fait 40 ans que j’en fais », précise d’emblée Henri Masson. Ingénieur chimiste de formation (Université Libre de Bruxelles), docteur en sciences appliquées, professeur émérite à l’Université d’Anvers, expert globe-trotter (notamment pour la Banque Mondiale et l’ONU), l’homme est, de surcroît, doté d’un sérieux sens de la vulgarisation. Lorsque Contrepoints lui propose d’analyser les modèles prédictifs du GIEC, le Belge est catégorique : « Si mes étudiants me présentaient de tels modèles, je n’hésiterais pas à les recaler ! »

Contrepoints : Quelle confiance peut-on accorder aux modèles du GIEC, qui prévoient, parmi d’autres choses, un réchauffement planétaire dû aux émissions humaines de CO2 ?

Evolutions récentes du CO2 atmosphérique (3/4)

by J.C. Maurin, 12 novembre 2018 in  ScienceClimatEnergie


L’IPCC (GIEC en français) fut créé en 1988 par l’UNEP (United Nations Environment Programme) et le WMO (World Meteorological Organization). Dans les principes régissant les travaux du GIEC (1) on lit : Le GIEC a pour mission d’évaluer … les risques liés au changement climatique d’origine humaine.  Le GIEC respecte son propre principe fondateur : il attribue l’intégralité de la hausse du taux de CO2 depuis 1958 à une cause anthropique. Nous examinerons ici le modèle anthropique du GIEC et nous le confronterons aux mesures contemporaines, puis à un modèle mixte. Cet article fait suite aux deux précédents publiés sur le site SCE au cours des mois de septembre (1/4) et octobre 2018 (2/4).

C.4.  Conclusions

  • Un modèle qui décrit un monde fixe, en équilibre, un modèle où l’homme est central, un modèle qui parvient à reproduire certaines observations mais pas toutes, un modèle unanimement soutenu par les autorités politiques ou morales, enfin un modèle qui pose a priori un principe intangible… est le type même de modèle qui fut développé  par Ptolémée (6) pour le système solaire. Ce modèle fut jadis l’objet d’un consensus  à  > 97%.

  • L’atmosphère actuelle comporte environ 20 ppm de CO2 anthropique correspondant à 20/400 soit 5% du CO2 atmosphérique. En un siècle les hommes ont donc modifié la composition de l’atmosphère de 20 ppm soit 0,002% : sur ce sujet également, il semble que nous ne soyons pas au centre du monde.

  • Les évolutions récentes du CO2 atmosphérique ne peuvent pas avoir une cause uniquement anthropique: les observations du δ13C l’interdisent. Les causes sont anthropiques et naturelles. Le modèle purement anthropique du GIEC est donc à rejeter.

At IPCC talks Trump Administration emphasizes scientific “uncertainty” and “value of fossil fuels”… MAGA!

by David Middleton, October 4, 2018 in WUWT


95% of the model runs predicted more warming than the RSS data since 1988… And this is the Mears-ized RSS data, the one in which the measurements were influenced to obtain key information (erase the pause and more closely match the surface data).

Their “small discrepancy” would be abject failure in the oil & gas industry.

The observed warming has been less than that expected in a strong mitigation scenario (RCP4.5).

Output of 38 RCP4.5 models vs observations.   The graph is originally from Carbon Brief.  I updated it with HadCRUT4, shifted to 1970-2000 baseline, to demonstrate the post-El Niño divergence.

The ‘Trick’ of Anomalous Temperature Anomalies

by Kip Hansen, September 25, 2018 in WUWT


It seems that every time  we turn around, we are presented with a new Science Fact that such-and-so metric — Sea Level Rise, Global Average Surface Temperature, Ocean Heat Content, Polar Bear populations, Puffin populations — has changed dramatically — “It’s unprecedented!” — and these statements are often backed by a graph illustrating the sharp rise (or, in other cases, sharp fall) as the anomaly of the metric from some baseline.  In most cases, the anomaly is actually very small and the change is magnified by cranking up the y-axis to make this very small change appear to be a steep rise (or fall).

A Test of the Tropical 200- to 300-hPaWarming Rate in Climate Models

by R. McKitrick and J. Christy, July 6, 2018 in AGU100


Abstract
Overall climate sensitivity to CO2
doubling in a general circulation model results from a complex
system of parameterizations in combination with the underlying model structure. We refer to this as the modelsmajor hypothesis, and we assume it to be testable. We explain four criteria that a valid test should meet: measurability, specificity, independence, and uniqueness. We argue that temperature change in the
tropical 200- to 300-hPa layer meets these criteria. Comparing modeled to observed trends over the past
60 years using a persistence-robust variance estimator shows that all models warm more rapidly than
observations and in the majority of individual cases the discrepancy is statistically significant. We argue that
this provides informative evidence against the major hypothesis in most current climate models.

Weather and Climate in the Real World

by Tim Ball, August 18, 2018 in WUWT


All the trillions of dollars spent on AGW have not improved forecasting one bit. Instead, it diverted money that could have helped those large, primary sectors of society and economy that need better and more appropriate information. It is time to close all government weather offices or at least reduce their function to data collection determined by the end users.

Why does climate sensitivity increase over time in models? A look at two possibilities

by A. Zaragoza Comendador, August 16, 2018 in WUWT


Note: if the terms used in this article seem confusing, check out the previous one.

Introduction

It’s well known that climate models show increasing sensitivity over time: for a given forcing, the true long-term temperature increase (ECS) is higher than what you’d estimate if you simply extrapolated from the past (ECS_hist). In other words, the ECS-to-ECS_hist ratio is above 1. This article tries to work out why climate models behave like that; that is to say, the variable I’m trying to explain is the ECS-to-ECS_hist ratio.

Now, there’s probably too many hyphens and underscores in the text. So it will be more readable if I clarify that, every time I talk simply about ‘correlation’, I mean the correlation of thing X with the ECS-to-ECS_hist ratio. If other kind of correlation is mentioned, I’ll say so explicitly.

The Major Change in the Global Warming Groupthink Between 1990 and 1995

byTim Ball, August 12, 2018 in WUWT


Somebody said economists try to predict the tide by measuring one wave. This puts them in the same league as climate scientists trying to predict the climate by measuring one variable, CO2. It is no surprise that an amalgam of the two, climate and economics, produces even worse results, but that is what happened early in the anthropogenic global warming (AGW) deception.

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