WildfireGPT: Tailored Large Language Model for Wildfire Analysis

Understanding and adapting to climate change is paramount for professionals such as urban planners, emergency managers, and infrastructure operators, as it directly influences urban development, disaster response, and the maintenance of essential services. Nonetheless, this task presents a complex challenge that necessitates the integration of advanced technology and scientific insights. Recent advances in LLMs present an innovative solution, particularly in democratizing climate science. They possess the unique capability to interpret and explain technical aspects of climate change through conversations, making this crucial information accessible to people from all backgrounds Rillig et al. [2023], Bulian et al. [2023], Chen et al. [2023]. However, given that LLMs are generalized models, their performance can be improved by providing additional domain-specific information. Recent research has been focusing on augmenting LLMs with external tools and data sources to ensure that the information provided is scientifically accurate: for example, leveraging authoritative data sources such as ClimateWatch Kraus et al. [2023] and findings from the IPCC AR6 reports Vaghefi et al. [2023] helps in refining the LLM's outputs, ensuring that the information is grounded in the latest research.