Most Earth system models are missing element of future climate puzzle

Another major geophysical/geochemical system for which we have poor models is the subsurface ocean. Our measurements are simply too sparse to build a realistic model of the dynamics even though we know they have a major impact on climate.

For a long time there was an assumption that oceanic subsurface dynamics were relatively static to a first approximation for climate modeling purposes. But localized measurements in recent decades have provided evidence that it is far more dynamic than models allowed for. Despite knowing this, we still don’t have much data to build models with due to lack of oceanic sensing platforms capable of collecting detailed data across 70% of the planet. It will likely be at least a couple decades before we begin to get a handle on these dynamics.

I think people that have not worked in climate modeling tend to overestimate the fidelity of the climate models. The only things we can predict reliably are extremely coarse, like “it will get warmer on average” and “weather variance will increase”. The short-period systemic effects at any particular locale are far beyond what the models can currently predict with any reliability.

I don't know why not just include it in submission title... Spoiler: consequences of permafrost thawing.

Before these guys get even more funding to add even more stuff to their models they should debug their existing code first. The level of disagreement between the existing set of models has been increasing over time, not decreasing. We're told the science is certain but it's been getting less certain as the models get more complex. They also often suffer numerical instability problems in which model runs end up as hot as venus or Earth as an iceball. Rather than fix the bugs these runs are simply discarded and they try again. Models are often full of hacks too where things that should be program-stopping assertions are just wallpapered over by adding a min/max call to the values.

As an engineer but not a climate scientist, it is really difficult to make sense of these models. They come in at least three levels of complexity, where simpler ones are used to verify the output of the more complex ones.

If you want to try, Hector is a great one to start with: https://github.com/JGCRI/hector

I wrote a little blog post with an overview of some of the open source models: https://possibleplanets.com/2022/05/06/how-to-forecast-the-c...

> Most Earth system models are missing element of future climate puzzle

I think that's what they want to achive with those models. /s

> As these modeling systems are becoming increasingly complex, it is hard—and getting harder—for a graduate student or postdoc to 'come up to speed' quickly enough to really understand the full scope of the model development needs and wrap up a development project on the typical three-year timeline of a proposal," said David Lawrence, who co-leads the Community Terrestrial Systems Model at the National Center for Atmospheric Research. "Unfortunately, that leaves many projects unfinished."

Click bait ad for funding, move along