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

Abstract

Abstract. Precipitation measurements exhibit large coldseason biases due to under-catch in windy conditions. These uncertainties affect water balance calculations, snowpack monitoring and calibration 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, a comprehensive test site for precipitation measurements was established on a mountain plateau in southern Norway. Automatic precipitation gauge data are compared with data from a precipitation gauge in a Double Fence Intercomparison Reference (DFIR) wind shield construction which serves as the reference. A large number of other sensors are provided supporting data for relevant meteorological parameters.In this paper, data from three winters are used to study and determine the wind-induced under-catch of solid precipitation. Qualitative analyses and Bayesian statistics are used to evaluate and objectively choose the model that best describes the data. A continuous adjustment function and its uncertainty are derived for measurements of all types of winter precipitation (from rain to dry snow). A regression analysis does not reveal any significant misspecifications for the adjustment function, but shows that the chosen model does not describe the regression noise optimally. The adjustment function is operationally usable because it is based only on data available at standard automatic weather stations.The results show a non-linear relationship between undercatch and wind speed during winter precipitation events and there is a clear temperature dependency, mainly reflecting the precipitation type. The results allow, for the first time, derivation of an adjustment function based on measurements above 7 m s −1 . This extended validity of the adjustment function shows a stabilization of the wind-induced precipitation loss for higher wind speeds.

Sensitivity of historical orographically enhanced extreme precipitation events to idealized temperature perturbations

“…For a mountainous site in south western Norway the undercatch for snowfall was found to be up to 80% in wind speeds above 7-8 m/s (Wolff et al 2015). In the validation below, no correction for undercatch has been performed to lack of wind and temperature observations at the precipitation locations, but it should be kept in mind that the observations are probably biased low for snowfall (high elevations).…”

Impact of relict rock glaciers on spring and stream flow of alpine watersheds: Examples of the Niedere Tauern Range, Eastern Alps (Austria)

“…The undercatch of precipitation measurements under windy conditions and solid precipitation leads to underestimation of precipitation (e.g. Sevruk et al, 2009;Wolff et al, 2015). However, visual snow cover data is available from an automatic remote digital camera (S-RDC) installed in 2011 at the opposite mountain ridge of the SRG, some 500 meters to the northeast at an elevation of 1960 m a.s.l.…”

Bias corrections of precipitation measurements across experimental sites in different ecoclimatic regions of western Canada

“…Recent data from DFIR with a Geonor gauge (Geonor-DFIR) are available from Brats Lake, and they are useful to improve the catch-wind relationship for various automatic precipitation gauges. For example, the correction function for the Geonor-DFIR vs. the Geonor-SA has been derived, using the intercomparison data from Norway (Wolff et al, 2015). Its applicability to different regions and climatic conditions may need testing and validation.…”