AI 4 Good

Second Climate Forecast Revolution

As the first one revolved around Numerical Weather prediction forecasts (solving physics equations to predict weather eg. IFS).

Weatherbench 1

First attempt at a ML data oriented approach to weather forecasting. First winter of AI for climate, as not enough data was available. Data-based approaches were not precise enough to reach NWP levels of accuracy.

Weatherbench 2

• Data: in Zarr format + IFS baselines
• Evaluation Code: usind datacloud or other remote computing services (colab, aws, etc)
• Evaluation platform: interactive graphs, for user visualization

Are AI models just blurring?

How do we understand this factor? First we can check if the model is able to predict extremes (or is just averaging the data).

Blurring exists, but is limited to small scales and does not influence the prediction of extremes. Many ML models have been used for Hurrican Season prediction. Graphcast is better than NWP.