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Understand the links between weather and wildfire

Weather data is a crucial input into fire models. However, the factors that converge to cause a particular wildfire to grow rapidly can be difficult to discern, especially when fire growth depends not on large-scale, regional conditions but on small-scale, hyper-local factors. Our knowledge of these factors has been limited by insufficient historical analysis of the associations between large wildfires and atmospheric conditions, as well as by deficiencies in our collection of weather data. Without this information, accurately predicting fire weather can be very difficult. 

The Pyregence Extreme Weather Team is working to fill these gaps. 

Provide groundbreaking insights into the impact of extreme weather on wildfire

To ensure that wildfire models have the right data inputs, our scientists are developing a methodology that identifies blindspots in our network of weather stations, and providing a plan to pinpoint where additional stations are needed. 

In addition, our scientists have tested the benefits of an upper-air profiler—a device that measures winds above ground level—and determined that this technology could provide advance warning of the strong surface winds that can drive fast-spreading fires. 

Pyregence scientists are also running simulations to identify locations that are particularly vulnerable to dangerous fire weather conditions.

Finally, we’re analyzing historical wildfires to identify the weather conditions—including hyper-local factors—associated with large fires over the past two decades. 

We aim to give utility companies and public safety agencies the data they need to make life-saving decisions.

As a result of the work done by the Pyregence Extreme Weather Team, fire forecasting models will become more accurate.

With our recommendations on how to optimize the collection of weather data, we’re helping to ensure that hyper-local conditions are accounted for in models. Additionally, we’re the first to deliver research that shows how upper-air profilers can predict the onset of winds at ground level hours in advance, giving officials time to take critical mitigation measures. And with a firm understanding of weather conditions associated with past wildfires, we will make it easier to forecast the dangerous fires of the future.

Goals of the Extreme Weather Team


We’re helping utility companies identify blindspots in their network of weather observation stations and optimize the location of new stations.


By conducting tests of a sodar system, we determined that measuring winds in the upper atmosphere can help predict the onset of strong winds at ground level.


We analyzed the types of extreme weather associated with major fires in eight distinct regions across California.


We’re using weather modeling to identify locations where combinations of factors produce extreme winds that can drive fast-spreading fires.


Extreme Fire Weather Products

Historical Analysis Map

Map shows locations of California’s eight fire regions and the extreme weather types associated with each

Historical Analysis Research Paper
Research into extreme weather types associated with large fires across California.
Historical Analysis Data
Dataset contains source code as well as inputs and outputs of research into weather associated with major fires in the past
Historical Analysis Report
Report summarizes the findings from the historical weather analysis, including the factors influencing major wind-driven and plume-driven fires in California

Optimize Weather Station Locations

Weather Station Optimization Maps

Maps show where adding new weather stations would improve fire weather awareness

Weather Station Optimization Report

Report will make recommendations for improving the weather station network, and evaluate costs of new installations

Weather Station Optimization Data

Datasets (on weather, fuels, topography, and more)  used for optimization analysis

Weather Station Optimization Code

Code used to identify areas where new weather stations may be needed

Implement Upper-Air Profiler

Upper-Air Profiler Data
An early version of data collected as part of the pilot test is now available
Upper-Air Profiler
Report offers guidance to electric utilities on deploying profiler networks and using the data to improve fire weather forecasts

Conduct Wildfire Simulations

CAWFE Simulations
Wildfire visualizations/animations show simulations of selected California fires