ClimAgent: LLM as Agents for Autonomous Open-ended Climate Science Analysis
ClimAgent is an LLM agent framework that runs end-to-end climate science analyses, introducing ClimaBench and a 40% gain over baseline LLM solutions.
LLMs & agents
Language models and agents for weather and climate science: QA, data analysis, model-running agents, multimodal models that read weather fields.
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All papers (10)
CLIMATEAGENT: Multi-Agent Orchestration for Complex Climate Data Science Workflows
A multi-agent LLM framework completes climate data workflows with 100% task completion on an 85-task benchmark, beating a GPT-5 baseline.
Zephyrus: An Agentic Framework for Weather Science
Zephyrus is an LLM agent with a weather-data environment and ZephyrusBench, outperforming text-only baselines by up to 44 points in correctness.
WeatherQA: Can Multimodal Language Models Reason about Severe Weather?
WeatherQA is a multimodal benchmark of 8,000+ image-text pairs for severe convective weather reasoning; GPT-4o shows a substantial gap to human forecasters.
Allen Institute for AI (Ai2, ACE)University of Washingtoncode
ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change
ClimateGPT is a domain-specific language model for synthesizing climate-change research text; it does not model the atmosphere or climate system directly.
Local climate services for all, courtesy of large language models
Discusses using large language models for local climate services; the abstract is absent, so the classification relies on the title only.
Assessing Large Language Models on Climate Information
Framework and AI-assisted rating protocol show LLM climate answers have a significant gap between surface presentation and epistemological quality.
chatClimate: Grounding Conversational AI in Climate Science
GPT-4 grounded with IPCC AR6 content via retrieval; expert-scored answers show the hybrid chatClimate more accurate than GPT-4 alone.
Enhancing Large Language Models with Climate Resources
LLM agent retrieves emissions data from ClimateWatch and web search to give more precise answers on climate change topics.
ClimateBert: A Pretrained Language Model for Climate-Related Text
ClimateBERT is a language model pretrained on climate-related text; it does not target the atmosphere or climate system itself.
Also relevant (4)
Role of Artificial Intelligence in Disseminating Climate Information Services in Africa
Reviews how AI, including ML and NLP, can improve climate information services and drought early warning in Africa, with sub-Saharan case studies.
Recent Advances in Environmental Weather Monitoring and Prediction System Using IoT and Multi-Model Progressive Dense Self-Attention: A Systematic Review
Systematic review of IoT and deep learning weather monitoring and prediction, covering CNN, LSTM, transformer and hybrid models; no new results are reported.
Scientific strategies associated with mitigating the challenges in predicting track and intensity of cyclones across the world basins
Systematic review of 51 studies on tropical cyclone track and intensity prediction using NWP, machine learning and satellite methods across basins.
RStudio AI Blog: An introduction to weather forecasting with deep learning
Tutorial introducing deep learning for weather time-series forecasting from station data; abstract not available, so classification is low confidence.