The Evolution of Models

Model evolution

The Darwinian thinking, in its embryonic state, was not a concept that abiotic entities evolve, no, it was a line of thinking based on the evolution of biotic entities.

For example, those of that ilk in that time long ago never contemplated how genes evolve, no, because they did not know that genes even existed, much less that they evolved.

Then, upon the discovery of genes and DNA, the focus changed to genetics and why genes evolve.

Of, course the "obvious" answer to that was "because they are selfish."

Our evolutionary thought processes have evolved too (The Uncertain Gene, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11).

Now, the real question is not what evolves, rather, the real question is why they evolve.

Even the hypotheses and theories about why "things and non-things" evolve also evolve.

Take natural selection, which was originally a concept far less evolved than it is now.

Now, it is trending towards randomness, now having evolved far away from "survival of the fittest" in the biological science realms (but see The Fittest Stars, Planets, & Species).

Where there is randomness in thinking there is variation in thinking:

"The hypothesis put forth to explain the origins of the Universe, our solar system, and our planet is called the Big Bang Theory. The Big Bang Theory IS NOT EVOLUTION! (The theory of evolution deals with living organisms, once they have come into existance" [sic] - Origins of Life).

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"What exactly happened after the Universe was born? Why did stars, planets and huge galaxies form? These are the questions that concern Viatcheslav Mukhanov, and he tries to find the answers with the help of mathematical physics. Mukhanov, Professor of Physics at LMU, is an acknowledged expert in the field of Theoretical Cosmology - and he has used the notion of so-called quantum fluctuations to construct a theory that provides a precise picture of the crucial initial phase of the evolution of our Universe: For without the minimal variations in energy density that result from the tiny but unavoidable quantum fluctuations, one cannot account for the formation of stars, planets and galaxies that characterize the Universe we observe today." - Cosmology Is Evolution

(emphasis added, cf. On the Origin of the Genes of Viruses - 12). Sometimes scientists get a bit possessive about "their science and their universe."

Anyway, models of sea level rise also evolve.

With the same problems.

There are as many models as there are modellers and model problems, so, let's consider some:

"EdGCM provides a research-grade Global Climate Model (GCM) with a user-friendly interface that can be run on a desktop computer. For the first time, students can explore the subject of climate change in the same way that actual research scientists do. In the process of using EdGCM, students will become knowledgeable about a topic that will surely affect their lives, and we will better prepare the next generation of scientists who will grapple with a myriad of complex climate issues.

Our goal is to improve the quality of teaching and learning of climate-change science through broader access to GCMs, and to provide appropriate technology and materials to help educators use these models effectively. With research-quality resources in place, linking classrooms to actual research projects is not only possible, but can also be beneficial to the education and research communities alike." - (Columbia University, American).

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"Climate scientists build large, complex simulations with little or no software engineering training, and do not readily adopt the latest software engineering tools and techniques. In this paper, we describe an ethnographic study of the culture and practices of climate scientists at the Met Office Hadley Centre. The study examined how the scientists think about software correctness, how they prioritize requirements, and how they develop a shared understanding of their models. The findings show that climate scientists have developed customized techniques for verification and validation that are tightly integrated into their approach to scientific research. Their software practices share many features of both agile and open source projects, in that they rely on self organisation of the teams, extensive use of informal communication channels, and developers who are also users and domain experts. These comparisons offer insights into why such practices work." - (Toronto University, Canadian)

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"This educational software is originally deviced for use in high schools as part of the french curriculum in Life and Earth Sciences. It realises climate simulations given user-chosen parameters. Through a friendly interface, the user chooses the length of the simulation (from 100 years to a few billions years) and the initial conditions, and tests the influence of various parameters involved in climate: astronomic forcing, atmospheric composition, carbone cycle, climatic feedbacks (ice albedo, vegetation, ocean, water vapor). Simulation results (such as temperature, sea level and ice cover), calculated on the flys by a physical climate model, appear on the interface, through curves and images." - (SimClimat, French)

The development of a software solution that is prospective, i.e., it is going to be used to anticipate events going forward, brings up problems that remind me of sayings on the Quotes Page:

"Scientists have discovered that 'the present' has always existed, but they are not sure about 'the past' and 'the future'." -Dredd

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"One thing is for sure on the subject of global warming induced climate change: if there was ever a time to err on the safe side, it was long ago." - Dredd

Now, back to my codeine coding.

The next post in this series is here.

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TEDx Talk excerpt from transcript of video below:

"[Unfortunately, talking about climate forecasts is often a great way to end a friendly conversation!] Climate models tell us that by the end of this century, if we carry on burning fossil fuels at the rate we have been doing, and we carry on cutting down forests at the rate we have been doing, the planet will warm by somewhere between 5 to 6 degrees centigrade. That might not seem much, but, to put it into context, in the entire history of human civilization, the average temperature of the planet has not varied by more than 1 degree. So that forecast tells us something major is coming, and we probably ought to pay attention to it.

But on the other hand, we know that weather forecasts don’t work so well the longer into the future we peer. Tomorrow’s forecast is usually pretty accurate. Three day and five day forecasts are reasonably good. But next week? They always change their minds before next week comes. So how can we peer 100 years into the future and look at what is coming with respect to the climate? Should we trust those forecasts? Should we trust the climate models that provide them to us?"

(Should we trust climate models?).

The next post in this series is here.

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