Experimental forecast predicts above-average fire season this summer

According to an experimental prediction method developed by scientists at the National Center for Atmospheric Research (NCAR), this summer’s western wildfire season will likely be worse than average, but not as devastating as the near-record. from last year.

The new method, detailed in a peer-reviewed study, analyzes precipitation, temperature, drought and other weather conditions in winter and spring to predict the extent of wildfires in the western United States. United over the following summer. The research team developed the method by applying machine learning techniques to observations of every wildfire season since 1984, when current satellite measurements of fires first became available.

Although scientists previously knew that weather conditions in spring and summer influence fire risk, the new study demonstrates that, even months before the peak of the fire season, weather in large parts of the West plays an important role in staging fires. .

“What our research shows is that the climate of the previous winter and spring can explain more than 50% of the year-to-year variability and overall trend in fire activity in summer,” said NCAR scientist Ronnie Abolafia-Rosenzweig, lead author of the study. study. “This gives us the ability to predict fire activity before the summer fire season begins.”

Applying their research method to the next fire season, the scientists predicted that fires this summer will burn 1.9 to 5.3 million acres in the West, with 3.8 million acres being the highest total. more likely. Although well below the record 8.7 million acres burned in 2020, this would represent the 8and the largest area burned since 1984, part of a long-term trend of more widespread fires.

The scientists stressed that their prediction is currently for research purposes only. But they said their method, once tested and improved, could help provide guidance to firefighting agencies in the future. It provides more explicit information than current seasonal forecasts which may call for a relatively mild or destructive wildfire season without predicting how many acres are likely to burn.

“This information can be extremely useful to firefighting agencies as they allocate resources and prepare for the upcoming fire season,” Abolafia-Rosenzweig said.

Abolafia-Rosenzweig and co-authors describe the prediction method in a new study in Environmental Research Letters. The work was supported by the NOAA MAPP program as well as the US National Science Foundation, which is NCAR’s sponsor.

A lingering influence

With wildfires becoming more widespread across much of the West, the NCAR team wanted to see if weather conditions earlier in the year could offer any clues to the extent of the fires in the summer. when fire season peaked.

The scientists turned to Generalized Additive Statistical Model Ensembles, which are widely used machine learning tools that help reveal complex relationships – in this case, the correspondence between climate conditions from November to May and the extent burned areas from June to September. . They analyzed every year since 1984, focusing on western regions that rely on snowpack for water.

The research team found that air dryness (vapour pressure deficit) in the lowest part of the atmosphere during winter and spring has a particularly pronounced effect on summer fires. This dryness influences the amount of snow that falls and, in turn, is affected by the snow on the ground which eventually releases moisture into the overlying air. The extent of the April snowpack is particularly important because it moistens both the ground and the air as it melts during the warmer months.

“We found that the April snowpack has a lingering influence on the land and the atmosphere during the summer,” Abolafia-Rosenzweig said. “If you have a heavy snowpack in April, it will take longer to melt and there is a more persistent transfer of moisture from the earth to the atmosphere from late spring through summer. But in the case less snowpack, you will have both a drier land surface and a drier atmosphere in the summer, which translates to more conducive conditions for fires to spread.”

Scientists also studied a number of additional climate variables, including precipitation, temperature, soil moisture, evapotranspiration and drought indices, examining how each variable in different seasons influences the extent of summer fires.

They concluded that winter and spring weather conditions can be used to predict up to 53% of year-to-year variability in summer burned areas. When summer climatic conditions such as precipitation and air dryness are also taken into account, the explained variability increases to 69%.

The study also looked at the overall impact of climate change on fire activity in the West. While wildfires have gradually increased since 1984, the research team’s modeling showed that climate variables such as rising temperatures and persistent droughts can explain 83% of this increase.

This year’s experimental prediction – which encompasses the entire West, not just snow-dependent regions – indicates that fires will burn 38% more land in the West this summer than the average since 1984. The forecast does not does not include early season fires before June, such as the widespread blazes that devastated New Mexico this spring, nor does it estimate how different regions in the West will fare. In the future, however, scientists may add such details.

“Our plan is to include local climate variables such as winds so that we can learn about specific fire conditions at a state or even county level,” said NCAR scientist Cenlin He, co. – author of the study. “This will make it more valuable to stakeholders and fire managers so they can anticipate fire activity in specific regions of the West.”

This material is based on work supported by the National Center for Atmospheric Research, a major facility sponsored by the National Science Foundation and operated by the University Corporation for Atmospheric Research. The opinions, findings, and conclusions or recommendations expressed herein do not necessarily reflect the views of the National Science Foundation.

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