You know what actually needs an investment? Climate models which are completely shit right now. It's actually preposterous that there are trillions of dollars worth of decisions in ESG and climate credits and government incentives while the science behind this is supported by old fortran code that has terrible quality and can't give reasonable predictions. We have trillions of dollars chasing predictions of code bare…
Say more about this! Let's say you had $100B to build better climate models over the next 5 years. Where would you spend it? My general sense is the models are good enough to tell us that a) things are headed in the wrong direction and b) we're really far off from a solution. Generally in agreement with you but I haven't researched deeply about what's needed on more modeling and how to prioritize.
It needs to be open source, and it needs to be way more organized, no physical constants which aren't constant or which have bad precision or which have different values in different parts of the code.
Actual error modeling built in or at least a way to measure and quantify the accuracy.
Some models only use CO2 input for radiation and not for many other parameters that depend on CO2. Because the code is a mess and constants that shouldn't be constants are all over the place. And getting "constants" right is even more important than having high resolution to the simulation.
Getting real physical data to replace all the ad hoc constants is extremely important. And validating the correctness of the cloud modeling with real world data is also important.
And you can't write huge spaghetti code, it needs to be readable and comprehensible to someone other than original programmer so that people can validate the assumptions.