|Title||A new method to characterize changes in the seasonal cycle of snowpack|
|Publication Type||Journal Article|
|Year of Publication||2019|
|Journal||Journal of Applied Meteorology and Climatology|
|Type of Article||Article|
|Keywords||climate-change; Hydrology; Meteorology & Atmospheric Sciences; precipitation; river-basin; snowpack; Time series; trends; variability; western|
In the western United States, water stored as mountain snowpack is a large percentage of the total water needed to meet the region's demands, and it is likely that, as the planet continues to warm, mountain snowpack will decline. However, detecting such trends in the observational record is challenging because snowpack is highly variable in both space and time. Here, a method for characterizing mountain snowpack is developed that is based on fitting observed annual cycles of snow water equivalent (SWE) to a gamma-distribution probability density function. A new method for spatially interpolating the distribution's fitting parameters to create a gridded climatology of SWE is also presented. Analysis of these data shows robust trends in the shape of the annual cycle of snowpack in the western United States. Over the 1982-2017 water years, the annual cycle of snowpack is becoming narrower and more Gaussian. A narrowing of the annual cycle corresponds to a shrinking of the length of the winter season, primarily because snowpack melting is commencing earlier in the water year. Because the annual cycle of snowpack at high elevations tends to be more skewed than at lower elevations, a more Gaussian shape suggests that snowpack is becoming more characteristic of that at lower elevations. Although no robust downward trends in annual-mean SWE are found, robust trends in the shape of the SWE annual cycle have implications for regional water resources.
|Short Title||J. Appl. Meteorol. Climatol.|