Climate Modelling

Climate change increasingly disrupts farming through drought, heat stress and shifting rainfall, but regional climate models are often too coarse or uncertain to guide long-term agricultural planning or crop choices.

Quantum-enhanced simulation and quantum-machine-learning methods could support more detailed climate and weather modelling by exploring large parameter spaces and improving predictive skill for regional climate impacts that matter to farming.

Better (local) climate predictions help farmers and planners choose resilient crops, adapt irrigation, and reduce climate-related losses, supporting sustainable agriculture and food security.