According to NASA, there is a consensus on climate change and that humans are causing it through their sustained actions. However, while many people know that climate change is happening, few realize the kind of energy that the scientific community has put into ensuring the science on the topic is right. It's interesting to note that many people who deny that climate change is happening accuse scientists of being "harbingers of doom" with their predictions. However, a paper published in Global Environmental Change accuses scientists of erring on the side of least drama. What's really going on with the science behind climate change, and are we done looking into it?

The Shortfalls of Our Scientific Models

It's easy to frame the idea of climate change as something scientists tell us to make us more afraid of the changing world. However, even scientists aren't sure about what the situation will be five, ten, or fifty years into the future. There are a lot of predictions about extreme weather conditions. Still, even so, science was unable to predict truly devastating disasters like the flooding in New York City and Germany's Eifel region. If our scientists are so convinced of climate change, how could they not tell us these events would happen? The answer lies with how scientists interpret the models that they have.

The modeling methodology of current climate science is based on observed data compared with the carbon dioxide levels of a pre-industrial human civilization. The difference in carbon dioxide in the atmosphere, it's assumed, will give us a clue as to what sort of extreme weather phenomenon we're likely to see. However, this approach is fundamentally flawed. Our simulations fall short almost always because they are based on terrible base data. In the IT community, the term "Garbage in, garbage out (GIGO) refers to when rubbish data is used to draw a conclusion. In the case of predicting extreme weather events, this acronym seems like an apt comparison. So why is our data such rubbish? It lies with the level of processing that current cloud models can manage.

What Do Clouds Have to Do With Anything?

Worldwide, kids learn about the water cycle when they're still early on in their academic life. The water cycle is such a fundamental part of understanding how weather and climate work that we teach our kids when they're still young enough to conceptualize new ideas quickly. When we go up the complexity ladder, physicists can accurately model many things, from supernovas that we've never actually observed to what goes on around the edges of a black hole's event horizon. They can also model clouds, the critical element of our climate simulation system, but they have a significant problem. The resolution of the climate grid and the processing power afforded to them don’t give them the granularity they need to develop sufficiently accurate cloud models.

The simplified representations of clouds see them thrown together into amorphous clumps resolving at around 100km per grid square. That's large enough for a wide-scale model, but it's too big a scale for any actual data to be derived regarding extreme weather events. Thanks to this, weather models consistently mispredict the Inter-Tropical Convergence Zones (ITCZ) locations that bring rainfall to tropical regions and anticyclones that bring dry weather to temperate climates. Rain and lack of rain are two essential ingredients in the most recent spate of extreme weather events. Since our scientists consistently get these things wrong, it's no surprise that they can't pinpoint the weather events that may affect large swathes of the world accurately.

Building More Reliable Models is Crucial

How do scientists address something of this nature? Developing more granular simulations is one way, but it doesn't truly solve the problem. For now, our models run simulations twice to get an idea of where extreme events may occur. However, we have no frame of reference for how often these extreme events are happening based on what has already happened. In addition to a more granular system for weather simulation (which would allow more accurate cloud models to be built), there needs to be a track of what extreme weather events have occurred. To do this will require a lot of human resources and dedication to the cause, but it raises another problem. Are we, as a species, allocating our scientific resources towards the best possible method of solving the climate change crisis?

Some scientists estimate that they may have spent hundreds or thousands of hours working on climate change models and proposals over the last year. Fundamental issues like climate mitigation, geoengineering, and adaptation to change (among other things) are crucial to our species' continued survival on this planet. Maybe we need a dedicated forum to assign scientists to work on our climate change problem full-time. Provided with exascale computers and the resources they need, they may develop more accurate prediction models that allow us to perform just-in-time solutions that use a minimum of economic and financial resources. Even owners of oceanfront condos can appreciate the need for this kind of work. Solving climate change won't happen overnight. It will be a concerted effort that will take years of scientific advances to roll back or even stop. For now, we must use what we have to increase the chances that we have a planet we can live on for the next couple of generations.