Climate models like ICON, developed by Max Planck scientists, are massive software systems with over a million lines of code, making small errors almost unavoidable.
Bugs (mistakes in code) can appear even after careful testing, but models are still considered trustworthy if they give reliable results overall.
Scientists at Max Planck say most bugs are caught before new code is added, but testing usually stops once it’s part of the full model.
Even when the model crashes, it doesn't always mean a bug needs fixing, sometimes it's just pushed beyond what it was built to handle.
Fixing bugs can take a lot of time, so scientists often weigh how much the bug actually affects the model before deciding to fix it.
Some scientists see bug fixing as part of climate science, like solving a puzzle to figure out how a bug impacts model behaviour.
To catch bugs early, tools like Buildbot and GitLab can help, but even with testing, scientists often can’t tell exactly what the “perfect” model result should be.
ICON may not be flawless, but scientists believe it's “good enough” to predict weather and study how rising carbon levels impact Earth.
The idea of a model being 'good enough' helps scientists move forward, but users must still understand that no model is perfect.
The study, published in Earth’s Future, reminds us that while climate models guide global policy, their limitations must be clearly understood.
Read more at Phys.org. Research published in Earth's Future.