WIFIRE - Data Assimilation (enKF)

This catalog entry optimizes FARSITE model outputs through a data assimilation methodology, informed by actual fire observations. The process uses an ensemble Kalman filter to generate ensembles based on quantified uncertainties in proximate weather station data.

Data and Resources

Additional Info

Field Value
Last Updated March 3, 2026, 21:03 (UTC)
Created March 3, 2026, 21:03 (UTC)
creationMethod <p>This code was created to implement the components of a data assimilation workflow using an ensemble Kalman Filter. It is built on top of the <a href="https://fireforge.wildfirecommons.org/dataset/farsite" rel="noopener noreferrer" target="_blank">FARSITE</a> catalog item. The enKF notebook fetches fire perimeter observations, weather station data, generates .lcp, generates an ensemble based on the quantified uncertainties of the weather station, optimizes the FARSITE prediction, and compares all three outputs by overlaying the predicted, observed, and optimized perimeters.</p>
creatorEmail tcaglar@ucsd.edu
creatorName Tolga Caglar
dataAuthType private
dataType IPYNB
issueDate 2026-03-03
lastUpdateDate 2026-03-03
ndp_creator_md5 0e38ca7a9fbee5939224f7823bedc52d
pocEmail tcaglar@ucsd.edu
pocName Tolga Caglar
publisherEmail
publisherName
purpose <p><br></p>
status submitted
theme []
uploadType code