Title: Identifying local and synoptic-scale meteorological and land cover conditions favorable for the occurrence of large fires in California

Presenter(s):  E’lysha Guerrero

Date: 24 October 2024 3:15 pm – 3:45 pm ET

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About Speaker: E’lysha Guerrero,

Abstract: Whilst global warming projections lead to continuous warming trends and California wildfire activity is expected to increase, the state of wildfire predictions will need to be enhanced to keep up with the ever-changing climate conditions. This research project aims to characterize meteorological and land conditions related to large wildfires in California and identify their connection to predictable climate patterns, potentially enhancing future wildfire predictions. We utilize historical wildfire perimeter data (2000 “2022) and apply the K-means Clustering Algorithm on localized meteorological variables to group wildfires based on similar conditions. Larger-scale synoptic meteorology is analyzed to identify potential predictors for future wildfire occurrences. The research questions addressed during the NERTO are: (a) What are the local regional and seasonal characteristics of California’s historically larger wildfires from 2000 – 2022? and (b) What are the typical large-scale circulation patterns associated with each California clustered group?The value of this research lies in its contribution to NOAA’s mission to understand and predict climate and weather changes, specifically through advancing wildfire prediction capabilities. The insights gained can improve both prediction models and wildfire management strategies, supporting NOAA’s broader goal of mitigating the impacts of extreme weather and natural hazards. Additionally, the use of machine learning techniques, like K-means clustering, fosters innovation in predictive skills, aligning with the NOAA Physical Sciences Laboratory’s mission to develop new knowledge and tools for forecasting extreme events such as wildfires. The results are from the NOAA EPP/MSI CSC NERTO graduate internship project that was conducted with NOAA mentor Dr. Andrew Hoell, Dr. Rochelle Worsnop, and Dr. Melissa Breeden of NOAA Physical Sciences Laboratory, Boulder, CO. The NERTO aligns with NOAA CSC CESSRST-II’s goal to understand and predict changes in climate and weather. The NERTO project deepened the intern’s understanding and increased the research skill sets of data acquisition, preprocessing, analyses, and validation techniques required for earth system science research.