Understanding drivers of wildfires in California
Measuring correlation between ENSO, precipitation, and wildfires in CA.
DOI:
https://doi.org/10.47611/jsrhs.v13i2.6847Keywords:
wildfires, California, CA, Precipitation, ENSO, El Nino, environmental science, meterologyAbstract
This research study investigates the intricate relationship between El Niño events, precipitation patterns, and wildfires in California over the past two decades. California, known for its susceptibility to wildfires, has experienced significant variations in precipitation influenced by the El Niño-Southern Oscillation (ENSO) phenomenon. The objective of this research is to examine the impact of El Niño events on California's precipitation patterns and subsequently assess their association with wildfire occurrences. Predicting wildfire and precipitation wildfires are important to California’s significant agriculture production and better preparing for possible droughts or wildfires. To achieve this objective, a comprehensive analysis of climate data spanning the last 20 years was conducted. Historical records of El Niño episodes, obtained from reputable sources, were measured by correlation with precipitation data acquired from meteorological databases. Additionally, wildfire occurrence and severity data were collected from relevant agencies and organizations to be measured for correlation. As it turns out, while there was some positive correlation with El Nino and precipitation, there was little direct correlation between El Nino and wildfires. This means that there are many more complex factors to be assessed when figuring out causes of wildfires in addition to El Nino. The findings of this research will contribute to a better understanding of the main causes of wildfires in California. The results can inform policymakers, land managers, and disaster response agencies in developing more effective strategies to mitigate the risks associated with wildfires. Additionally, the study will provide valuable insights into the influence of climate variability on fire-prone ecosystems, aiding in the prediction and management of future wildfire events.
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