“Modeling climate change is much easier than Weather – Do you get it?

Guest essay by Eric Worrall

According to the UCL Professor of Earth System Science, the diverse predictions made by 20 major research centers represent “power in numbers.” Mark Maslin.

Three reasons why climate change models are our best hope for understanding the future

Mark Maslin
Professor of Earth System Science, UCL

Its a common argument Among climate deniers: scientific models cannot predict the future, so why should we trust them to tell us how the climate will change?

…

Regular Deniers confuse climate with weather when assuming that models are inherently inaccurate. Weather refers to the short-term conditions in the atmosphere at any given time. Whereas, climate is the weather of an area averaged over several decades.

There are many weather predictions more exactly over the past 40 years, but the turbulent nature of the weather means they become unreliable after a week or so. However, modeling climate change is much easier, since you are dealing with long-term averages. For example, we know the weather will be warmer in summer and colder in winter.

…

This is a useful comparison. It is impossible to predict at what age any particular person will die, but we can say with a high degree of confidence about the average life expectancy of a person in a particular country. And we can say with 100% confidence that they will die. Just as we can say with certainty that the introduction of greenhouse gases into the atmosphere will warm the planet.

…

The power of numbers

Have a lot of climate model, from efforts to understand specific mechanisms such as the behavior of clouds, to general circulation models (GCMs) used to predict our planet’s future climate.

There are more than 20 main international research center where a team of some of the smartest people in the world have built and run these GCMs contain millions of lines of code represent the latest insights into the climate system. These models are continuously examined against historical and palaeontological data (this refers to climate data from before direct measurement, like the last ice age), as well as individual climate events such as major volcanic eruptions to ensure they recreate the gas after all, which they do very well.

No single model can be considered complete as they represent a very complex global climate system. But Having so many different models independently built and calibrated means scientists can be confident when the models agree.

…

Error about error

Since climate is such a complex system, you might reasonably ask how scientists deal with potential sources of error, especially when modeling climate over hundreds of years.

…

Our scientists are well aware that models are simplifications of a complex world. But with so many different models, built by different groups of experts, we can be more certain of the results they produce. All the models showed the same thing: put greenhouse gases in the atmosphere and the world warmed up. We represent potential faults by showing the range of warming generated by all models for each situation.

…

Read more: https://theconversation.com/three-reasons-why-climate-change-models-are-our-best-hope-for-und understanding-the-future-175936

I have some problems with these arguments:

1. In my opinion, comparing a climate model with a life expectancy model is a misnomer.

   Life expectancy models are built from millions of independent observations, medical records versus downtime. In contrast, climate scientists struggle to reconstruct what happened yesterday. There is a significant difference between temperature reconstructions over the past 30 years, let alone climate projections.

   (the source Wood for trees)
   

2. “Millions of lines of code” is not a reliable source. Millions of lines of code are millions of opportunities for addition. As a software developer, I have worked with physicists and mathematicians. They all thought they knew how to code, but with very few exceptions, they wrote scary pieces of code.

   The problem I’ve seen over and over again is that the math and physics training creates an irresistible internal pressure to reduce everything to the simplest possible expression, even if the reduction this means ignoring software best practices designed to reduce the risk of fatal errors. I knew well what to expect before I read it.”Harry read to me“.

3. If climate models are fit for purpose, scientists will need only one unified model. The fact that there are so many diverse models is in itself proof that climate scientists are struggling to get it right. Compare these multitude of climate models to say that the models are used to predict the motions of the satellites. If satellite orbit predictions are as uncertain as climate forecasts, it would be impossible to create a global position system that can tell you where you are on Earth’s surface within a few feet.
4. Climate models can contain large physics errors. Lord Monckton, Willie Soon, David Legates and William Briggs created a peer-reviewed “The climate model is simply unbelievable“, it seems to demonstrate that most mainstream climate scientists use a climate feedback model that is completely faulty.

   … In formal climatology, feedback not only accounts for 90% of total warming, but also accounts for 90% of the uncertainty about how much warming will take place. How is “stable science” solved, when after 40 years and trillions of spending, modelers still can’t limit that vast amount of time? The lower limit of IPCC is Charney sensitivity of 1.5 K; the upper limit of the CMIP5 model is 4.7 K. The usual skeptics do not know how much warming will be.

   My co-authors and I apologize. The response is not great enchilada. Official climatology – as far as we can discover – has completely ignored a central truth. The truth is that any feedback processes present in the climate at any given time must necessarily respond to more than just pre-existing changes in temperature: they must respond to the whole the reference temperature obtained at that time especially including the emission temperature will be present even without any uncondensable greenhouse gas or any feedback. …

   Read more: https://wattsupwiththat.com/2019/06/08/feedback-is-not-the-big-enchilada/

   Lord Monckton’s point was that, since feedback is a function of temperature, feedback processes cannot distinguish the difference between greenhouse warming and the initial launch temperature, all that is the total temperature. You must include the initial starting temperature along with any greenhouse warming when calculating the total response, you cannot just use the temperature change due to the addition of CO2 to the atmosphere. Making this adjustment significantly reduces the estimated climate sensitivity, cuts future projections of global warming, and eliminates the need for confusion about anthropogenic CO2.

5. Cloud error. As Dr. Roy Spencer explains in a 2007 paper supporting Richard Lindzen’s Iris ConjectureClouds are likely to play an important role in future climate change. However, as scientists sometimes admit, Climate models do a terrible job of explaining cloud behavior. If climate models cannot explain the key processes that cause global surface temperatures, they are not ready to be used as a serious guide to future surface temperatures.

Why are climate scientists so eager to have accepted models, why do they seem so willing to cover up shortcomings? The following quote from the Climategate email provides an important hint as to what may have happened;

… K Hutter added that politicians have accused scientists of high signal-to-noise ratios; scientists have to make sure they give out stronger signals. The time frames for science and politics are very different; Politicians need instant information, but scientific results take time…

Source: Climategate Email 0700.txt

In my view, political leaders demand certainty, so certainty is what they get.

Science needs people like Mark Maslin, who are confident and ready to defend their views and models.

I am not suggesting to Mark Maslin in any way to run after money or act in a way that is contrary to his conscience. If there’s one thing that comes out very clearly in the Climategate emails, it’s that the climate scientists who wrote them were completely sincere.

What climate science has broken, in my opinion, is that the other side of this equation has been completely eliminated. What I am suggesting is that climate scientists are not confident in their models, and their predictions have mostly failed, through a politically brutal Darwinian selection process, sort of leave out most of those who are not “sure”.

We can still see this happening today. Climate scientists who favor politically approved stories receive lavish funding, while those like Peter Ridd who questioned the official stories, not so much.

I am not opposed to such climate models, I believe that there is a chance, although unlikely, that we will eventually have a comprehensive model of climate change that can provide predictions. future climate assessment. What I argue is that most current climate models tend to run too hot for the purpose. In my opinion, climate models should be considered a work in progress, not a useful tool for government policy advice.

Correction (EW): Corrected the title in the cited article.