FrevaGPT: A Large Language Model-Driven Scientific Assistant for Climate Research and Data Analysis

The chabot writing poems can do climate analysis? Large Language Models (LLMs) promise a paradigm shift as chat-based geoscientific research transformers (chatGRT) by removing technical barriers and empowering scientists to focus on deeper, more innovative inquiries. We introduce FrevaGPT, an LLM-driven “scientific assistant” integrated into Freva, the Free Evaluation System for climate data analysis on high performance computers. FrevaGPT automatically translates natural language questions into traceable, editable, and reusable scripts; retrieves relevant data and publications; executes the analyses; and visualizes the results - the scientist can focus on what matters most: science. By tapping into a wide repository of climate datasets, FrevaGPT ensures transparent, reproducible workflows and lowers the threshold for advanced data handling. Its co-pilot functionality not only delivers answers, tables, and plots, but also proactively suggests next steps, points to relevant climate modes and events, and presents associated scientific findings. Through integrated approaches to model evaluation and observational data comparisons, FrevaGPT accelerates scientific discovery and fosters interdisciplinary collaboration. Real-world use cases highlight FrevaGPT’s capacity to guide researchers beyond routine analysis, freeing them to explore innovative questions and deepen their understanding of complex climatic phenomena. As a pioneering application of LLMs in climate science, FrevaGPT illustrates how such tools can fundamentally reshape research processes, unleashing new possibilities for efficiency and creative exploration in the geosciences.