Review of 80 studies finds Morocco's climate AI work is held back by data gaps

Research activity rose markedly after 2022, concentrated in agriculture, water resources and climate-risk applications. Morocco faces desertification, recurrent droughts, rising temperatures and water scarcity, which threaten agriculture, water, energy, urban planning and environmental management.

The review found that data and deployment gaps limited how far the work could be reproduced or put into operation. Most applications supported adaptation, while mitigation remained less developed.

The authors searched four databases and analysed each of the 80 eligible publications by sector, model family, dataset and access type, geographic scale, evaluation metric and stated or implicit research gap. The review covers seven climate-sensitive sectors.

Model choice followed data type: tree-based ensembles dominated for heterogeneous tabular and geospatial data, while neural models were used mainly for imagery and time-series forecasting. Public satellite and reanalysis products gave broad coverage.

Constraints included sparse ground observations, restricted institutional data, resolution mismatch, limited spatial transfer testing and minimal use of explainable AI. These limited reproducibility and operational uptake.

The authors present the Morocco-specific cross-sector synthesis as an evidence-based roadmap for reproducible, locally generalisable and trustworthy climate-AI systems, extending narrower domain reviews.