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The aim of this wiki is to help foster impactful research to tackle the climate crisis, by identifying problems where ML can be useful. This wiki is maintained and moderated by members of CCAI.

The scope of solutions to address the climate crisis goes far beyond the intersection we address here; the problems of climate change require cooperation between diverse stakeholders, and action in many forms. Whether you are a machine learning researcher looking to apply your skills to combat climate change, or a young researcher aiming to have impact in your career, or a practitioner in one of these areas looking to apply ML to your problem, or for any other reason you are interested in the intersection of climate change and ML, we hope these pages can help inform and facilitate your research!

We welcome your contributions and feedback! See editing guidelines here.

Quick start

General Resources page
Tackling Climate Change with Machine Learning review paper

Topics by Application Area

The pages below provide overviews and resources on topics at the intersection of climate change and machine learning. Mitigation refers to reducing emissions in order to lessen the extent of climate change, while adaptation refers to preparing for the effects of climate change. We also provide overviews of various tools for action -- such as policy, economics, education, and finance -- that can help enable mitigation and adaptation strategies.

Mitigation

Adaptation

Climate science

Tools for Action

Topics by Cross-cutting Theme

There are several cross-cutting themes and research problems that recur across the topic areas above.

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+The aim of this wiki is to help foster impactful research to tackle the climate crisis, by identifying problems where ML can be useful. This wiki is maintained and moderated by members of [https://www.climatechange.ai/about CCAI].
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+The scope of solutions to address the climate crisis goes far beyond the intersection we address here; the problems of climate change require cooperation between diverse stakeholders, and action in many forms. Whether you are a machine learning researcher looking to apply your skills to combat climate change, or a young researcher aiming to have impact in your career, or a practitioner in one of these areas looking to apply ML to your problem, or for any other reason you are interested in the intersection of climate change and ML, we hope these pages can help inform and facilitate your research!
+We welcome your contributions and feedback! See editing guidelines [[Guidelines|here]].
+=== Quick start ===
+*[[General Resources]] page
+*[https://arxiv.org/abs/1906.05433 Tackling Climate Change with Machine Learning] review paper
+=== Topics by Application Area===
+The pages below provide overviews and resources on topics at the intersection of climate change and machine learning. ''Mitigation'' refers to reducing emissions in order to lessen the extent of climate change, while ''adaptation'' refers to preparing for the effects of climate change. We also provide overviews of various ''tools for action'' -- such as policy, economics, education, and finance -- that can help enable mitigation and adaptation strategies.
+====Mitigation====
+*[[Electricity Systems|Electricity systems]]
+*[[Transportation]]
+*[[Buildings and Cities|Buildings and cities]]
+*[[Industry]]
+*[[Agriculture]]
+*[[Forestry and Other Land Use|Forestry and other land use]]
+*[[Negative Emissions Technologies|CO<sub>2</sub> removal and negative emissions technologies]]
+====Adaptation====
+*[[Climate Change Adaptation|Climate change adaptation]]
+*[[Biodiversity]]
+*[[Solar Geoengineering|Solar geoengineering]]
+====Climate science====
+*[[Climate_Modeling_and_Analysis|Climate modeling and analysis]]
+*[[Weather prediction|Weather forecasting]]
+====Tools for Action====
+*[[Public Policy and Decision Science|Public policy and decision science]]
+*[[Climate and Environmental Economics|Climate and environmental economics]]
+*[[Education]]
+*[[Climate Finance|Climate finance]]
+*[[Tools for Individuals|Tools for individuals]]
+===Topics by Cross-cutting Theme ===
+There are several cross-cutting themes and research problems that recur across the topic areas above.
+*[[Accelerated Science|Accelerated science]]
+*[[Remote Sensing|Remote sensing]]
+*[[Predictive Maintenance|Predictive maintenance]]
+*[[Efficient sensing]]
+*[[Surrogate modeling]]
+<br />
+<!-- === Topics organized by Machine Learning Area ===
+Here pages are organized by the area or type of machine learning research. If you are an ML researcher in one of these areas, this provides a quick way to see which problems of climate change potentially best align with your expertise.
+* [[Causal inference]]
+* [[Computer vision]]
+* [[Interpretable models]]
+* [[Natural language processing (NLP)]]
+* [[Reinforcement learning (RL), Bandits, and Control]]
+* [[Time-series analysis]]
+* [[Transfer learning and Generalization]]
+* [[Uncertainty quantification and Bayesian methods]]
+* [[Unsupervised and Self-supervised learning]]
+-->
+<br />