Training Modules

Understand how CE's data-derived combined models are structured, trained, and evaluated — including the role of component weights, fusion strategies, and provenance maintenance when multiple source models disagree.

Master how climate-economy pressures and opportunities translate into the six CE-covered industries through operating, financing, and supply-chain channels. Learn which signals matter most for each sector and how to weight them correctly.

Build a working understanding of how leading climate models are selected, interpreted, stress-tested, and translated into decision-ready signals for CE.

Understand how leading macroeconomic and climate-economy models differ, what they are actually good at, and how CE converts them into transparent economic signals.

Learn how CE converts climate and economic model families into a transparent integrated forecast through scenario envelopes, industry transmission, fusion logic, and provenance.

Learn how to design defensible CE scenarios, build stress families, and interpret how scenario assumptions propagate into economic, climate, and integrated outputs.

Learn why reviewing the accuracy of past forecasts is not an optional compliance exercise but a core analytical discipline. Build a working understanding of how CE surfaces historical forecast performance and how to use that evidence to calibrate confidence in future outputs.

A complete end-to-end walkthrough of the CE Workbench: selecting and comparing models, running the integration desk, saving and retrieving runs, comparing archive outputs, and using training and documentation resources.