What strategies can you employ to enhance the accuracy of climate change models?

As we lack the computational power our climate models are increasingly unable to predict the increases in extreme events driven by the dynamic parts of the Earth system which increasingly show larger system swings. This said the only way to be able to predict the increases we are facing is by extrapolate the recent increases in a non-linear fashion. Of further importance it is to include jump wise increases caused by the temperature jumps of the system which increase in size and likely a higher frequency. My advice take the increases of 2020 to 2023 and compare this trend with the one evolving just now and extrapolate it. Best shot you've got...

FOCUS ON YHE ONE DATA POINT THAT SEEMS TO MATER THE MOST TO US. THIS IN MY OPINION IS THE WATER TEMP OF THE ATLATIC OF THE COAST OF WEST AFRICA.( INFLUENCING TEMPS IN THE GULF AND HURRICANE CREATIONS, AS WELL AS DROUGHT IN AFRICA) . FOCUS ON WHAT CAUSES THESE HIGHER TEMPS. DEVELOP A CAUSE AND EFFECT RELATIONSHIP IN ONE AREA. IS INCREASED CO2, LESS CLOUD COVER, ECT CAUSING THESE HISTORIC TEMPERATURES TO BE INCREASING?

If you use models use “k-scale” climate modeling operating at small scales of 1-2km grid boxes and assume a back ground state of our climate system that warms faster than current predictions. Likely we will reach 2°C of warming around 2030 as too many feedback are now acting mutually reinforcing like non-linear expansion of marine heatwaves, heat release of subsurface oceans, and even a reduced heat uptake of the oceans is now being increasingly being discussed. Add to that a cloud feedback over drying out continents and warmer oceans and further exceptional sea ice losses till 2030 combined with an exceptional EL Nino possible around 2030. Better to be prepared than sorry...

Use data-driven hydrological modelling, such as Machine Learning (ML), Artificial Intelligence (AI), and Deep Learning (DL) methods. Problem thou is that it will be increasingly be difficult to project which way the changes will develop in a given region as teleconnection patterns can change fast in our Earth system now driven by changing SST patterns which intensify. Just now many regions change from too wet to too dry or the opposite. While other regions that continue to dry out are exposed to exceptional flooding events. I would say even known teleconnections from ENSO are now changing as outgoing teleconnections from too many other regions are now strengthening as their variability increases (e.g. temps., moisture, speed, pressure)...

Like I said use a worst case scenario of 2°C of warming reached by 2030 (from a pure mechanistic point of view eve more possible now with the latest study results showing).

In my opinion a global map is needed down to the process level of all the neuralgic processes needed to run the global value chains. The vulnerability of the economic fabric is now increasing fast as ever more important processes are becoming increasingly concentrated. Huge problem in the face of non-linear increasing extremes that start now to persist for years...