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Data Announcement: Linking Atmospheric Rivers to Wildfire Patterns in the Southwest

Friday, 3 March 2017

This winter, parts of drought-stricken California have been besieged by heavy flooding, mudslides, and feet of snow. The cause? A meteorological phenomenon known as an atmospheric river, which carries high concentrations of water vapor in narrow bands from the warm tropics up to western North America.

In the western U.S., atmospheric rivers are relatively common and are critical providers of winter rain and snow. However, they can also be a source of extreme flooding and costly damage to transportation networks, public utilities, and other infrastructure. While the economic and social impacts of strong atmospheric rivers are well understood, we know much less about how they can impact ecosystems.

new dataset and publication developed by researchers working with the DOI Southwest Climate Science Center helps identify the ecological impacts of atmospheric rivers in the interior Southwest. Researchers examined how atmospheric rivers affect dryland vegetation productivity and thus fuel loads available for wildfires.

What do atmospheric rivers have to do with wildfire?

Climate and weather are key drivers of fire activity in the Southwest, mainly through their alteration of fuel (i.e. vegetation) accumulation and moisture. In fact, atmospheric conditions in the months and even years preceding a particular fire season can be influential. Atmospheric rivers, which bring increased precipitation to a region, may impact fire patterns in subsequent months or years by influencing vegetation growth.

Researchers examined this relationship in the interior Southwest, the region located east of the Sierra Nevada Mountains. While the impacts of atmospheric rivers are typically less intense to the east of major topographic barriers like the Sierra Nevada, they can be consequential here when more frequent or particularly intense atmospheric rivers hit southern California. 

More about the data

Researchers examined the historical (1989-2011) relationships between atmospheric rivers and changes in winter precipitation, vegetation productivity, and area burned by large wildfires during both the same year as atmospheric river landfalls and during the following year. The resulting dataset includes 32 grids representing the relationships between four sets of variables, across eight different latitudinal ranges. These relationships include:

(1) Annual winter atmospheric river precipitation vs. total annual winter precipitation
(2) Annual winter atmospheric river precipitation vs. annual maximum NDVI (a measure of vegetation productivity)
(3) Spatially-averaged annual winter atmospheric precipitation vs. area burned by wildfire during the same year
(4) Spatially-averaged annual winter atmospheric river precipitation vs. area burned by wildfire during the following year

What does the data show?

First, the results show that atmospheric river precipitation has the strongest influence on area burned by wildfire in the more arid parts of the region, while they have less of an effect in forested areas. Second, atmospheric rivers tend to have more of an influence on area burned during the year following the event, rather than during the same year. This is because atmospheric river events increase soil moisture, promoting the quick growth of these plants – and also inhibiting fire during the same year. However, once the plants dry out, there is more fuel available to feed fires, and therefore a larger fire season.

Understanding the linkages between atmospheric rivers, vegetation productivity, and fuel conditions can provide important insight into future ecosystem and wildfire conditions in the region. This work can provide key information to federal, state, and local resource managers to help prioritize vegetation monitoring and forest fuel reduction efforts following atmospheric river events.

Learn more

  • Download the data and learn more about the project here. To access the data, click on “Project Products”, “Data”.
  • Read more about the methods used to create these datasets and the study’s results here.