The sensitivity of snowpack sublimation estimates to instrument and measurement uncertainty perturbed in a Monte Carlo framework

Abstract

The bulk aerodynamic flux equation is often used to estimate snowpack sublimation since it requires meteorological measurements at only one height above the snow surface. However, to date the uncertainty of these estimates and the individual input variables and input parameters uncertainty have not been quantified. We modeled sublimation for three (average snowpack in 2005, deep snowpack in 2011, and shallow snowpack in 2012) different water years (October 1 to September 30) at West Glacier Lake watershed within the Glacier Lakes Ecosystem Experiments Site in Wyoming.We performed a Monte Carlo analysis to evaluate the sensitivity of modeled sublimation to uncertainties of the input variables and parameters from the bulk aerodynamic flux equation. Input variable time series were uniformly adjusted by a normally distributed random variable with a standard deviation given as follows: 1) the manufacturer’s stated instrument accuracy of 0.3°C for temperature (T), 0.3 m/s for wind speed (Uz), 2% for relative humidity (RH), and 1 mb for pressure (P); 2) 0.0093 m for the aerodynamic roughness length (z0) based on z0 profiles calculations from multiple heights; and 3) 0.08 m for measurement height (z). Often z is held constant; here we used a constant z compared to the ground surface, and subsequently altered z to account for the change in snow depth (ds). The most important source of uncertainty was z0, then RH. Accounting for measurement height as it changed due to snowpack accumulation/ablation was also relevant for deeper snow. Snow surface sublimation uncertainties, from this study, are in the range of 1% to 29% for individual input parameter perturbations. The mean cumulative uncertainty was 41% for the three water years with 55%, 37%, and 32% occurring for the wet, average, and low water years. The top three variables (z varying with ds, z0, and RH) accounted for 74% to 84% of the cumulative sublimation uncertainty.