Derivation of a new continuous adjustment function for correcting wind-induced loss of solid precipitation: results of a Norwegian field study

Precipitation measurements exhibit large cold-season biases due to under-catch in windy conditions. These uncertainties affect water balance calculations, snowpack monitoring and calibrations of remote sensing algorithms and land surface models. More accurate data would improve the ability to predict future changes in water resources and mountain hazards in snow-dominated regions. In 2010, an extensive test-site for precipitation measurements was established at a mountain plateau in Southern Norway. Precipitation data of automatic gauges were compared with a precipitation gauge in a Double Fence Intercomparison Reference (DFIR) wind shield construction which served as the reference. Additionally, a large number of sensors were monitoring supportive meteorological parameters. In this paper, data from three winters were used to study and determine the wind-induced under-catch of solid precipitation. Qualitative analyses and Bayesian statistics were used to evaluate and objectively choose the model that is describing the data best. A continuous adjustment function and its uncertainty were derived for measurements of all types of winter precipitation (from rain to dry snow). A regression analysis did not reveal any significant misspecifications for the adjustment function, but showed that the chosen model uncertainty is slightly insufficient and can be further optimized. The adjustment function is operationally usable based only on data available at standard automatic weather stations. Our results show a non-linear relationship between under-catch and wind speed during winter precipitation events and there is a clear temperature dependency, mainly reflecting the precipitation type. The results allowed for the first time to derive an adjustment function with a data-tested validity beyond 7 m s−1 and proved a stabilisation of the wind-induced precipitation loss for higher wind speeds.