re: Scott Pruitt is absolutely right about Climate Change.

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Except the models in the graph pretty much all agree to within their error bars and they nearly universally predict a climate sensitivity that suggests the majority of warming in recent decades is caused by humans.

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wrong. They all (except for 3) include zero.

do you know what it means if a model's CI contains zero?

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Conservative analyses conclude that humans are responsible for AT LEAST half, probably more.

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apparently not

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Prudence would be calling for further study to get to the bottom of a scientific question,

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It's very easy for vested interests to point out that science has uncertainties (it always does) and demand increasing precision well past the point of absurdity. This was the strategy pursued by the tobacco companies, that we should do nothing until we can assign four significant figures to the relative risk of lung cancer.

An example of this absurdity is including the Lindzen & Choi sub-1°C figure for climate sensitivity when we've already passed that with less than half of a doubling, declining natural forcings, and the system not at equilibrium. That paper was straight trash, it's no wonder Lindzen took emeritus status and ran off to the Cato Institute.

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Well I look at it sort of like this, this is an over simplification but it gets at my feelings on the issue:

We can either do the types of things that are being recommended by GW advocates, changing our entire economy as you put it, or not. There are essentially 4 scenarios that follow:

1. If we change our economy and the data IS correct, then we will avert disaster.

2. If we change our economy and the data ISN'T correct, then we will have displaced a large portion of our workforce unnecessarily and presumably brought on economic hardship that otherwise would not have happened.

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3. We DON'T change our economy, and the data IS correct, presumably most of the dire predictions come true and life on earth is irrevocably changed for the worse or long term maybe is no longer tenable at all.

4. We DON'T change our economy, and the data ISN'T correct, and nothing or relatively little happens and life goes on more or less unabated.



Now of those options, I'd rather go with #1 and risk #2 being the outcome than go with #4 and risk #3.

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I understand your position. However, here is where we differ:

1-2. In these scenarios, (I'm assuming your career, so my apologies if wrong) my career and family's income is at stake. Not just mine, but my extended family and my regional economy are based on an industry that is directly threatened by the current climatology industry's interpretation of it's data (forgive the characterization). I would/could face severe financial ruin if this change were to take place. In that respect, I feel justified in asking for a higher standard of proof than what has been provided by the current computer models, which I have stated in other posts here, have been wholly incorrect before, even after previous consensuses.

3. While this may happen, I think it is reasonable to say that we don't truly know the effects of climate change long term. We simply postulate all the possible negative effects and possible positive ones for global warming are not examined. The earth has been significantly warmer in the past, and life continued to flourish.

So from my perspective, I have a lot more to lose than many people on the climatology side if the data is wrong, which of course, has been true in the past.

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wrong. They all (except for 3) include zero.

do you know what it means if a model's CI contains zero?

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You should have a closer look at the x-axis, champ.

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like those employed by the left

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you trumpanzees are all the same

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wrong. They all (except for 3) include zero.

do you know what it means if a model's CI contains zero?

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Haha, literally NONE of them contain zero. The vertical line shown on the plot is at 2º C, which means that doubling the atmospheric CO2 would lead to an increase of 2º C. No shame in making a mistake, but maybe make sure you know how to read graphs before trying to get smug with your emoticons, lol.

As I said, the results in the figure are quite consistent with one another, and they all support the hypothesis that human activity is the primary cause of the warming seen in recent decades. The author of this article is either foolishly or purposefully basing his entire argument on a claim that is exactly contrary to what the data he shows supports.

This board thinks farmers buy green houses because they look nice. They literally don't believe they do anything.

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again the only debate is among the political right and a few shills for business lobbys

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So 50% of the country is still debating something, therefore it shouldn't be considered?

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Among self-rated papers expressing a position on AGW, 97.2% endorsed the consensus.

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What is the consensus? That 100% or 30% of climate change is created by manmade CO2 production? Do you believe anything you read that has an abstract?

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Oh my, not believing computer models are scientific fact? What is the world coming to?

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"Models are wrong...some are useful." - Box

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Which computer models are you talking about? As far as I know the oldest computer models are Manabe's which date back to the 1960s but they're actually remarkably accurate. You might be talking about Hansen's 1980s models but they projected both CO2 and CFC increases so that's more of a failure to predict the Montreal Protocol than a failure of the model's physical fidelity.

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All models are currently bad at accounting for variations in cloud coverage, there's that water vapor again.

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The simulation of clouds with global climate models (GCMs) involves many nonlinear processes spanning a large range of spatial and temporal scales. While cloud systems such as the subtropical stratocumulus decks can extend over thousands of kilometers, cloud droplet formation and droplet growth occur on the micrometer scale. Similarly, time scales relevant to clouds and cloud microphysics range from weeks to fractions of seconds. All of this makes the simulation of clouds with climate models very difficult (Solomon et al. 2007). Because of the large impact of clouds on the radiation budget and their pivotal role in the hydrological cycle, even small changes in cloud properties could have a significant impact on climate (e.g., Hartmann and Doelling 1991). Clouds and their response to climate change therefore remain a major source of uncertainty for projections of the climate response to anticipated anthropogenic forcing (e.g., Cess et al. 1990; Bony and Dufresne 2005; Stowasser et al. 2006; Solomon et al. 2007; Medeiros et al. 2008; Lauer et al. 2010). Even for simulations of the long-term mean cloud fields under present-day conditions, GCMs generally display rather large deviations from observations, and there are quite large disagreements among GCMs in various aspects of their cloud climatology simulations (Weare 2004; Zhang et al. 2005; Waliser et al. 2007, 2009; Lauer et al. 2010; Chen et al. 2011). Deficiencies in GCM representation of cloud fields will affect the application of such models to simulate chemistry–climate interactions (e.g., by causing biases in photolysis rates) and, specifically, to simulate aerosol indirect climate forcing (e.g., underestimation in cloud frequency could underestimate indirect aerosol effect). Significant biases in the simulation of present-day clouds also raise concerns about the accurate representation of cloud feedback processes in climate change projections.

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Also for other posters in this thread, there is certainly some high level disagreement on what adjustments should be made to models.