Posted on 09/13/2025 8:09:56 AM PDT by Oldeconomybuyer
Global climate models are software behemoths, often containing more than a million lines of code.
Inevitably, such complex models will contain mistakes, or "bugs." But because model outputs are widely used to inform climate policy, it's important that they generate trustworthy results.
Ulrike Proske and Lieke Melsen set out to understand how climate modelers think about, identify, and address bugs. They interviewed 11 scientists and scientific programmers from the Max-Planck-Institut für Meteorologie who work on the ICON climate model for their study published in Earth's Future.
When new code is developed for ICON, it's screened and tested to catch bugs before being integrated into the model itself, the interviewees said. After code is integrated, however, such testing usually stops.
The code is assumed to be bug free until the model behaves weirdly or a programmer serendipitously discovers a bug while examining the code for other reasons. Even when the model crashes, it's not necessarily a sign that a bug needs to be fixed, because researchers are always making trade-offs between the speed and the stability of the model, and sometimes they simply push the model outside the bounds of what it can handle given those constraints.
Tracking down bugs and fixing them can be time-consuming, so even if the team suspects the presence of a bug, they sometimes estimate its impact to be minor enough that it doesn't warrant correction. When the researchers do decide to fix a bug, many view the process as an extension of climate science: They generate hypotheses about how the bug might cause the model to behave, then test those hypotheses to discern the exact nature of the bug and how to address it.
The best way to avoid bugs is to test code thoroughly before it's integrated into the full model, many interviewees said. Tools exist to facilitate testing, such as Buildbot and the GitLab development platform, and the scientists said such tools could be leveraged more fully in ICON's development process. However, they also said there are inherent limits to how thoroughly researchers can test climate models because researchers don't always know what a 100% accurate model output would look like. Thus, they do not have that basis to which they can compare actual model output.
Though the interviewees acknowledged that ICON is imperfect, they also considered it to be "good enough" to forecast weather or to answer research questions such as how increased atmospheric carbon will affect global temperatures. The authors write that although "the principle of 'good enoughness'" is pragmatic and understandable, it could also lead to misunderstandings if users don't appreciate a model's limits.
“All models are wrong; some are useful.”
George E. P. Box
When it isn’t manipulated to demonstrate a desired outcome to fit a cultish agenda. How’s that?
The most accurate “climate model” of all is the solar cycle, but we can’t use that because it doesn’t yield the answer we want.
Uh, never?
So where are all those hurricanes this year?
Anecdotal evidence....the beaches I’ve been to since I was born are the same now as then. From Guam to Hawaii, west coast, east coast, Gulf coast, Mediterranean over 78 years. But nothing below the equator so someone else will need to weigh in there.
> When is a climate model ‘good enough?’ <
The first test: Do the developers of the model encourage free and open debate on the issue?
As we all know, such debate is strictly forbidden when it comes to man-made climate change. That’s not science. It is instead a form of fascism.
🙁
Michael Mann, in a just world would die in prison after being tried for fraud.
Oh, good grief.
Weather systems are dynamic systems.
Forecasting for the hurricane season is just that.
And yet they are certain that the planet only has 8 years left.
Of course they will twist it as no hurricanes are a sign of climate change, and that hurricanes are good.
The difference in albedo between vegetation and bare mineral soil alone is so great that unless an accurate mapping of that distribution is obtained, NO model will EVER be accurate.
They would have to map every green leaf on earth accurately. Ain't gonna happen.
Climate models are nothing more than a rigged game to justify massive gov’t intrusion into everyone’s daily well-being, based on phony results. The dire prediction never pan out.
The world climate is far too complex for these rudimentary tools to yield anything approximating accuracy.
Phys.org has proved to be a liberal sounding board rather than a sound science platform.
When communism has been achieved.
The first question they should be asking is ‘why do all the models run hot?’ - if one looks at graphs of model predictions versus reality, all (except maybe one by some Russians) predict temperatures higher than those actually observed.
Which suggests the major problem is not bugs in the programming, but unsupported assumptions that are accepted by all and never fixed.
When it says the world is going to end unless we give control over all things to the United nations.
this is when the climate model is perfect.
Oh good, they know what github is, so no problem publishing the datasets and the code base. When every bug report is handled by a vibrant and active community, then we can provide some public funding.
However, they also said there are inherent limits to how thoroughly researchers can test climate models because researchers don’t always know what a 100% accurate model output would look like. Thus, they do not have that basis to which they can compare actual model output.
The models “work” by continual adjustment of critical variables to make the model produce the results the modelers think look like they should look.
This does not produce output which can be relied upon for the climate, because we do not have accurate data to compare the model to reality.
We simply do not have 100 or 10 years worth of accurate data to compare the model to.
Regressions rarely reveal the fundamental marxist policy of omitting data that does not agree with the outcome-based proposition. In fact, hockey stick was specifically assembled with that in mind, omitting the fact (among others) that the Medieval Warm Period was warmer on average than the latter half of the Last Century.
Statistical analysis was what led McIntyre and McKitrick to smashing the hockey in 2005 with "Hockey sticks, principal components, and spurious significance" [PDF].
as soon as it says exactly what tree huggers want it to say, it is good enough
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