kClimate

Learning across the climate system—from atmospheric foundation models to integrated climate intelligence.

2026 · Nature Climate Change 16, 505–507 (Comment)

Artificial intelligence to support cross-disciplinary climate change research

Y Ou, C Rodriguez-Pardo, AA Khourdajie, J Rogelj, P Zhou, SK Mukkavilli, et al.

A proposed general-purpose AI framework connecting climate knowledge across disciplines. Figure 1 · Y Ou et al., 2026

Read publication · Google Scholar

2026 · EarthArXiv · Preprint

A Blueprint for Integrated Climate Intelligence

C Rodriguez-Pardo, G Ascenso, CGA Pedraza, ML Bachelery, et al.

Read publication · Google Scholar

2023 · arXiv preprint arXiv: 2309.10808 · Preprint

AI Foundation Models for Weather and Climate: Applications, Design, and Implementation

S Karthik Mukkavilli, D Salles Civitarese, J Schmude, J Jakubik, A Jones, et al.

Spatiotemporal scales of weather and climate foundation-model applications. Figure 1 · S Karthik Mukkavilli et al., 2023

Read publication · Google Scholar

2024 · AGU24 · Conference abstract / presentation

Efficient Fine-tuning of Atmospheric Foundation Models for Wildfire Modeling

AA Rahman, L Mackey, SK Mukkavilli, S Kahou

Read publication · Google Scholar

2022 · ACM computing surveys (CSUR) 55 (2), 1-96

Tackling climate change with machine learning

D Rolnick, PL Donti, LH Kaack, K Kochanski, A Lacoste, K Sankaran, et al.

Machine-learning opportunities across electricity generation, networks and demand. Figure 1 · D Rolnick et al., 2022

Read publication · Google Scholar

2019 · International Conference on Learning Representations (ICLR), AI for Social …

Visualizing the consequences of climate change using cycle-consistent adversarial networks

V Schmidt, A Luccioni, SK Mukkavilli, N Balasooriya, K Sankaran, et al.

Illustrative flood transformations generated by a CycleGAN; these are not site-specific flood predictions. Figure 1 · V Schmidt et al., 2019

Read publication · Google Scholar

2017 · Penguin; edited by Paul Hawken

Drawdown: The most comprehensive plan ever proposed to reverse global warming

Research contribution by S. Karthik Mukkavilli

Read publication · Google Scholar

In the news

NASA and IBM Research Apply AI to Weather and Climate

KAIST climate research coverage — DongA Science