Most Accurate Models Predict Highest Climate Warming

December 18, 2017

Interview here that I missed at the American Geophysical Union last week.
I had scheduled Patrick Brown, author of a new study comparing climate model predictions, for a session Monday, but his plane was delayed, and we never caught up.
Here he is describing his research, above.

Patrick Brown PhD:

The primary goal of our study was to narrow this range of model uncertainty and to assess whether the upper or lower end of the range is more likely. We utilize the idea that the models that are going to be the most skillful in their projections of future warming should also be the most skillful in other contexts like simulating the recent past. Thus, if there is a relationship between how well models simulate the recent past and how much warming models simulate in the future, then we should be able to use this relationship, along with observations of the recent past, to narrow the range of future warming projections (this general technique falls under the “emergent constraint” paradigm, see e.g., Hall and Qu [2006] or Klein and Hall [2015]). The principal theme here is that models and observations together give us a more complete picture of reality than models can give us alone.

So, what variables are most appropriate to use to evaluate climate models in this context? Global warming is fundamentally a result of a global energy imbalance at the top of the atmosphere so we chose to assess models in their ability to simulate various aspects of the Earth’s top-of-atmosphere energy budget. We used three variables in particular: reflected solar radiation, outgoing infrared radiation, and the net energy balance. Also, we used three attributes of these variables: their average (AKA climatological) values, the average magnitude of their seasonal variability and the average magnitude of their month-to-month variability. These three variables and three attributes combine to make nine features of the climate system that we used to evaluate the climate models (see below for more information on our decision to use these nine features).

We found that that there is indeed a relationship between the way that climate models simulate these nine features over the recent past, and how much warming they simulate in the future. Importantly, models that match observations the best over the recent past, tend to simulate more 21st-century warming than the average model. This indicates that we should expect greater warming than previously calculated for any given emissions scenario, or it means that we need to reduce greenhouse gas emissions more than previously thought to achieve any given temperature stabilization target.

Much more at the link, if you want a deeper dive.

Having touched on model performance, it is incumbent to reassert that climate science is by no means dependent on models, any more any other field that uses mathematical analysis. See Below.

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One Response to “Most Accurate Models Predict Highest Climate Warming”

  1. dumboldguy Says:

    Brown: “…if anything, model shortcomings can be used to dismiss the LEAST severe projections ” (of climate change)

    Dressler: “It’s inarguable—-although some people still argue it ” (with a “heh heh-heh”, although I don’t think he’s really amused)

    Dressler hits the real problem—those who want to “argue” the inarguable, like the Trumpies and all the others who want to destroy the planet for profit. We will NEVER make progress against climate change until we deal with them.


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