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Sensitivity a la carte

10 Jun 2020 | Science Notes

We've talked about the problem of estimating Equilibrium Climate Sensitivity (ECS) before. We even made a video we invite you to check out, because ECS is shorthand for a vital factor in climate change: how much warming would occur if we doubled the amount of CO2 in the air, once all the knock-on effects had worked themselves out. For decades, scientists have been trying to determine what ECS actually is, including using complex climate models to run “experiments”. Unfortunately they have so many knobs to fiddle they can always make the models fit the past, even starting from very different ECS values. So a few years ago a group of modelers decided that since the knob called “cloud formation” had a big effect on overall warming they should try to get it right to improve the accuracy of ECS modeling. And then there was more trouble.

Clouds are tough to model. Everything that goes on that matters for weather and climate happens at such a microscopic scale it can never be properly observed, let alone programmed into a computer model, because they operate on a macro scale. So the modelers instead use rules of thumb known as guesses to determine how much water vapour becomes rain and how much stays as vapour.

There are a few different rules. One says it's a fixed fraction of the water vapour. Another says there's a threshold value, and once the water droplets exceed it, they all fall as rain. And we really need to know because what the authors found was that cloud formation has such a large effect on climate that what CO2 does to water vapour essentially determines the overall ECS value your model will generate. Change the cloud-making knob and you change the entire model, including whether it warms a lot or a little in response to greenhouse gases.

No problem, you might think, just pick the cloud model that best fits the natural world. But yes problem because the authors found that there was no way to choose—they could both be made to fit the data equally well even though they can’t both be right and they imply completely different things about the future. Which means there’s no way to tell what the real world ECS is based on experiments with models. Instead you get to pick whichever ECS you want simply by picking the cloud formation rule.

On the plus side, you can therefore forecast any future level of warming you want. Or, as the authors put it with something between tact and verbosity, “Given current uncertainties in representing convective precipitation microphysics and the current inability to find a clear observational constraint that favors one version of the authors’ model over the others, the implications of this ability to engineer climate sensitivity need to be considered when estimating the uncertainty in climate projections.”

Which translates as: The predictions aren't right or wrong, you just choose which one you want. Which is useful to keep in mind the next time you are told that climate models predict some disaster or other down the road if we don't do as we're told and stop driving or having jobs.

One comment on “Sensitivity a la carte”

  1. I WROTE THE CO-EFFICIENCY OF EVAPORATION FOR SWIMMING POOLS TO EXPLAIN HOW THROUGH MOLECULAR ADHESION, RELATIVE HUMIDITY, SURFACE AREA, WIND SPEED, COULD EXTRACT FISH EGGS INTO THE CLOUDS. AND OR MINNOWS. BASED ON TWO VISUAL EXPERIENCES I HAD JUST AFTER A LARGE STORM WITH HAIL I WITNESSED MINNOWS FALLING FROM THE SKY. THEN CREATED RAIN INSIDE A SWIMMING POOL COMPLETE WITH CLOUDS. IN THE 70'S JUST FOR FUN. IT WAS MORE THAN CONDENSATION OR DRIPPING OFF THE PHYSICAL. THE PROBLEM WITH DESIGNING ACCURATE WEATHER MODELS IS THE SCIENCE ITSELF, WEATHER IS NOT PREDICTABLE. THE FUNDAMENTAL WEATHER PREDICTION FORMULA IS BASED ON 10 MAJOR SETS, WITH SOME SUBSETS NUMBERING IN THE HUNDREDS OF VARIABLES TO ACHIEVE THE SET NUMBER. ALL CONSTANTLY CHANGING, BLENDING , INTERMIXING. AND CHANGING OVER TIME AS WELL. RULE ONE IS IF YOU HAVE TO GUESS AT ANYTHING, GO HOME. I COULD BUILD THIS MODEL, BUT I DON'T HAVE THE DESIRE OR TIME LEFT, TO DO IT JUSTICE. THE MODEL CONCEPT I STARTED WAS BEFORE COMPUTERS WERE MACHINES NOT PEOPLE. I USED A SLIDE RULE AND CARDEX TO GENERATE MY PREDICTIONS.

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