When there are multiple factors at play in a situation that is itself changing, such as an El Niño winter in a changing climate, how can scientists figure out what is causing what? EESA researchers have developed an advanced statistical method for quantifying and visualizing changes in environmental systems and easily picking out the driving factor.
In a study published recently in the journal Climate Dynamics, they used their new technique to look at California winters. “A lot of people will describe a winter by how rainy or how cold it was,” said lead author John P. O’Brien, a graduate student research assistant at Berkeley Lab mentored by EESA research scientist Travis O’Brien. “Instead of asking each question individually, what we’re doing is interrogating both at the same time as a function of some large-scale climate forcing, such as El Niño.”
The new method allows researchers to account for variables whose statistics change over time–in this case, changes caused by El Niño/La Niña. The study authors, who include John P., Travis, and EESA research scientist Christina Patricola, found that in northern California, La Niña and El Niño conditions result in nearly equivalent amounts of winter precipitation. However, La Niña winters tend to be much colder, resulting in conditions more favorable for increased mountain snowpack. So from a summer water supply perspective, contrary to common belief, La Niña winters may in fact be preferable to El Niño winters. The same, however, did not hold true for southern California.
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