91麻豆天美 climate, math experts calculate statistically sound data on declining snow cover
Contact: Sarah Nicholas
STARKVILLE, Miss.鈥91麻豆天美 University faculty members聽and a national group of researchers have created new statistical methods needed to study declining snow cover and quantify changing climate patterns in the Northern Hemisphere.
The College of Arts and Sciences鈥 Jamie Dyer, a professor of meteorology and climatology, and Jonathan Woody, an associate professor of mathematics and statistics, collaborated on the analyzing snow cover data gathered from satellite flyovers between 1967 and 2021.
The data was divided into grid sections for analysis by NOAA鈥攖he National Oceanic and Atmospheric Administration. In addition to the 91麻豆天美 researchers, the National Science Foundation-supported study included others from the universities of California-Santa Cruz, North Carolina at Chapel Hill, and North Florida.
Of the grid sections researchers determined to be reliable, they found that snow cover is declining in nearly twice as many grids as it is advancing.
鈥淭his was the first statistically sound analysis of Northern Hemispheric snow cover presence,鈥 said Woody, an 91麻豆天美 faculty member since 2011.
鈥淧revious studies failed to accurately assess uncertainty regarding trend estimates. Our team derived novel statistical methods which allow us to not only assess trends, but also to statistically test if the trends were significant,鈥 said the Kernersville, North Carolina, native.
鈥淭he mathematical and statistical foundations necessary to build our models are part of the core statistics and data science curriculum offered at 91麻豆天美,鈥 Woody said.聽
Dyer, interim dean of interdisciplinary studies who joined the 91麻豆天美 faculty in 2005, said while these general patterns of snow cover have been shown in other studies, using the methodology presented in this study allowed for much stronger and statistically robust conclusions.聽
鈥淎s a result, the decreases in snow cover over the Northern Hemisphere can no longer be attributed to biases in the data or methodological approach, as many climate skeptics tend to cite in their arguments,鈥 Dyer said.
鈥淐limate datasets are often difficult to work with due to uneven station distribution, missing data, uneven station length and even sensor issues; therefore, to avoid numerical bias, climate scientists must be quite careful in how they conduct their analysis,鈥 said Dyer, an Atlanta, Georgia, native.
鈥淏y utilizing expertise from statisticians to perform a purely data-driven analysis, then interpreting and validating those results from climate experts, more robust conclusions can be made about patterns in the data.聽 Such a multidisciplinary approach broadens the scope of such work, and is absolutely critical to move climate science forward in a meaningful way,鈥 Dyer said.
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