If this is the first you are hearing about global climate change, I will assume that you, like Rip Van Winkle, have been in a deep sleep for the past 20 years. It is one of the major topics of discussion worldwide (climate change that is, not RVW) – when people are not talking about Covid-19 or all the bogus “cures” or the equally bogus fears about getting vaccinated. I will address Covid-19 in another post – for now it’s all about global climate change and why it is real. 

Scientists and others who believe global climate change is real base their assertion on the results from climate change models. All the major valid climate models predict that the earth is heating up. They may differ slightly in how much or how fast that change is happening but there is no conflict over the direction that global temperatures are moving in. Higher temperatures are coming – that is unless we can do something about it.

Global temperatures are increasing because more energy from the sun is being absorbed by the earth and its atmosphere than is being lost back into space. Normally the earth should be in a state of equilibrium where energy absorbed = energy lost; but something appears to have upset that balance and as a result the earth is getting warmer. 

A warmer earth will likely have severe consequences on the earth’s climate including changing rainfall patterns (where, when and how much rain occurs), the frequency and magnitude of climate events such as hurricanes, drought, and floods – including flooding of coastal areas due to rising sea levels. I will discuss impacts in a future post – for now let’s concentrate on the first issue of contention: climate change models.

What is a climate change model?

Let’s get the concept of models sorted first. No, we are not talking about scale models or about artists models, we are talking about predictive models and we use them all the time. We often don’t know we are using them.

There are two kinds of models, deterministic models and stochastic models (also called probabilistic models). Let’s talk deterministic models first as they are much simpler to understand.

Deterministic Models

In a deterministic model something you do always has the same result – provided everything is working the way it should. So, if we go back to the example I used for the scientific method, any time I put water in my kettle, plug it in, and turn it on the kettle will boil the water. It will not suddenly and unexpectedly get up and sing “Good day Sunshine”. No, it will just boil the water inside the kettle. That’s it. 

So, in my brain, I have constructed a model that says – put water in kettle, plug in to electricity and turn kettle on, water will boil. That’s how I know that if it does not boil the water, there is a problem. We have many of these models that we (unconsciously) use every day – from driving to watching tv to cooking to pretty much every aspect of our daily lives. 

Stochastic Models

In a stochastic model, there is more than one outcome possible, and each outcome has a certain probability of occurring – none of those probabilities is 100% (if it were, that would be a deterministic model). That is, there is uncertainty.

Imagine for a moment if kettles worked on a stochastic system with a 50:50 chance (50% probability or, if you wish, a 50% uncertainty) of boiling water. Any time I turn on my kettle I would not know if it would boil water or if it would just sit there (perhaps silently humming Good day sunshine to itself). You wouldn’t know whether to try and fix the kettle or throw it away and drink your coffee or tea cold.

We humans are not comfortable with stochastic models because they are not particularly useful in daily life. Imagine living in a world where everything is stochastic – driving to work you wouldn’t know if your car would start when you turn the ignition, and you wouldn’t know if it would stop when you use the brakes; on one of those occasions you get to the office alive you wouldn’t know if your computer would turn on when you hit the “on” button or if it was one of those times it was not; and so on. Life would definitely be interesting but we would probably suffer tremendous psychological problems and self-destruct as a species.

What use are stochastic models?

So, if stochastic models are not exact, why use them? Think of stochastic models and deterministic models as a continuum – we start with stochastic models because we don’t yet have the knowledge or tools to create deterministic models. As our knowledge and tools improve we can get to a point where we may be able to create a deterministic system. 

Going back to deterministic models – someone did not suddenly invent a kettle and it worked perfectly from the first attempt. Scientists and inventors spent many hours working on creating and then perfecting systems that work the way you want them to work, reliably and consistently. 

The earliest electric kettles were introduced as an alternative to stovetop kettles in the late 1800’s. In these early kettles the heating element had to be kept apart from the water and were inefficient at heating water. If they came into contact with water they would “short-out” which is a nice way of saying you will be toast (toasted by a kettle?). To put it another way you would be electrocuted. But it also means the kettle would not work. A stochastic electric kettle? Who would buy that?

In 1922, Leslie Large designed a heating element that could be immersed in water and thereby invented the first reliable (deterministic) and efficient electric kettle.

So then, why not wait until we have good deterministic models for predicting the earth’s climate – because then (if we ever get to that point) it will be too late. Climate change is not some esoteric concept that has no impact on humanity – it is an existential threat that we have to address now, with the tools we have (while working on better options), or face significant harm and possible extinction in the not-so-distant future.

Again, what is a climate change model?

Climate change models are stochastic models that generate an output that predicts probable future climatic conditions. These models are very complex mathematical models – where the mathematical part is effectively a black box to anyone who is not an advanced modeler (that is, people like you and I). I think NOAA says it best:

“Climate models are based on well-documented physical processes to simulate the transfer of energy and materials through the climate system.”

NOAA

The models use mathematical equations to characterize how energy and matter interact in different parts of the ocean, atmosphere and land. So if I don’t have a deep understanding of the math that was used to arrive at the prediction(s) why do I trust them? I’ll get to that.

First, lets discuss how the models are developed and verified (checked). There are some things we do know about climate change – we know what happened in the past. Data is better in the near past than it is in the distant past and we don’t really have much reliable data earlier than the 19^th century – but that is still a lot of data. 

For periods earlier than the 19^th century scientists use other sources – proxy data such as lake and ocean sediments, corals, fossil records, or anecdotal descriptions in historical writings, and similar sources to make generalizations about a probable climate. For modeling however, only real data can and are used.

What kind of data are used to model climate?

Over many years and countless iterations of model “runs” scientists have looked at the various factors that can reasonably affect climate, and applied these factors to mathematical models to predict what past climate should have been. Factors include the physical characteristics of matter, chemistry, energy, fluid motion, composition, and so on. These predicted values can then be checked against the actual past data recorded (called hind-testing). Models that successfully predict past climatic conditions have met the first verification check. Keep in mind – the data used to generate the prediction is not the climate data itself – it is those factors known to impact climate. If we used climate data to check climate data that is a nonsensical model that would be laughed out of science.

The second, more telling verification check is, how good is the model at predicting future climate. Obviously we cannot wait until we have catastrophic climate change to verify the models were correct. So the results of model runs are checked against new climate data as it comes in. Each new iteration of data also represents an opportunity to improve the model – so model mathematics and assumptions may be updated over time. 

So why do I trust the current global climate models? Because they have been very good at predicting the changes that have happened so far – when increasing atmospheric CO₂ is taken into account.

The Intergovernmental Panel on Climate Change

The most ambitious and newest effort at predicting future climate is contained in the United Nations Intergovernmental Panel on Climate Change (IPCC) 6^th Assessment Report which was published in August 2021. The 6^th Assessment Report used 40 Coupled Model Intercomparison Projects (CMIP) – essentially 40 different climate models.

Why not pick one model? Its all about uncertainty. Each model gives a slightly different set of predictions – how do we know which one to pick? By using several different models to generate climate predictions the IPCC can arrive at a “happy medium” and in the process avoid criticism that we may have deliberately picked a model that gave the most extreme results.

Even though the IPCC used this conservative approach there are still those with an agenda who will criticize the approach – usually in the form of a question such as “Are Climate Models Overpredicting Global warming.” This approach is commonly used by conspiracy theorists and science skeptics as a way to make the public question the results of scientific study – usually for some personal agenda. Much of this effort to discredit science is also driven by groups with a hidden (or not-so-hidden) agenda – so follow the money before you believe.

The IPCC 6^th Assessment Report is long and comprehensive and I will not go over all aspects of the report in this blog. However, I do recommend you read at least the Summary for Policymakers (SPM) 39 pages which is less technical. You know who this summary is intended for. They don’t do technical.

There is also a technical summary of 150 pages, and the full report of approximately 1300 pages. There are also outreach materials and a slidepack with figures that can also be downloaded by readers.

A frequent argument put forward by climate change deniers/science skeptics is that the change happening now is due to “natural factors” – not due to human activity. Figure SPM.1 (page SPM-7) is worth looking at. The graph on the left shows what global temperatures were probably like since the time of Christ – based on reconstruction of historical records. The shaded area is then expanded on the graph on the right to show global surface temperature from 1850 to 2020 (when we have more reliable data). 

In the right-hand graph, the climate change models considered two scenarios: A. What would happen if only natural factors were occurring (for example from Solar radiation and emissions from volcanoes etc. – green line), and B. What would happen if human activity was also included (brown line). The black line shows actualrecorded global surface temperature.

Note also that while the black line (actual observed global surface temperature) and brown line (global surface temperature simulated using human and natural factors) follow very similar paths, they are not identical. This is because….. all together now ….the model used to simulate the global surface temperature is a stochasticmodel! 

The other interesting feature of the graph on the right is that the “observed” and “simulated human & natural” lines start to show divergence from the “simulated natural only” line around the mid-1900’s when human use of fossil fuels began to accelerate.

The Human Factor

What the data show clearly to anyone but the most obtuse is that human factors (activities) have been a primary cause of global temperature increase. What are those activities? The combustion of hydrocarbons (coal, oil, natural gas), deforestation, large-scale agriculture…you name it, we’ve done it. And, unfortunately we have continued with these behaviors even though we know the probable consequences.

In an earlier post I reviewed how greenhouse gasses work to contain energy on earth. We have exacerbated that situation by also destroying large swaths of vegetation that would otherwise have absorbed (sequestered) some of those GHG’s. It’s a double whammy. At least no one can accuse humans of doing things half-heartedly – including destroying ourselves.

What if Science is wrong?

We all have to ask this question of ourselves: What if we are wrong and human activities – specifically GHG emissions – are not causing global warming and climate change?

Lets ask the question a different way – what if global warming and climate change are true – can we afford to let it happen?

By acting now, as if GHG’s do cause global climate change, at worst we would have developed technology to generate power in ways that give us some independence from external geopolitical forces (I think that’s good). We would have created an industry around clean energy that provides jobs that are much less hazardous than the coal, oil or gas industries (hmmm I think that is good also). We would have stopped contaminating our precious freshwater resources with toxic chemicals from processes such as fracking, discharging contaminated “produced water” onto land or into lakes and seas (wtf … why is it all good?). 

We would re-green the earth (I’ll do another post on this in the future – but I suspect this is good also). And the list goes on. 

It is a win-win situation to respond quickly and respond hard. 

On the bad side – some people may have to learn new skills if the hydrocarbon industry winds down. No one expects this to happen overnight but it is possible. But, when you think of it, events like this have happened to most of us sometime during our lifetimes anyway – there is nothing wrong with learning and applying new skills. I wonder if we had those same concerns when motor vehicles were replacing horse or bullock drawn modes of transport? Was there a “motor vehicles are fake” movement? Did newspapers carry articles titled “Are horse-drawn carriage drivers overestimating the impact of motor vehicles?” I wonder. 

If we lose (or didn’t have in the first place) the ability or agility to adapt to changing circumstances or a changing environment we likely will not survive what is coming our way!

If you have constructive comments on this post please share with me using the comments form below. I will respond to reasonable posts within a few days. More posts are coming on various aspects of the environment but if you feel there is a priority issue, let me know. Finally, if you would like to contribute a post on the environment, travel or food in the context of change please contact us.