, Volume 171, Issue 1-2, pp 59-85

Roundhouse (RND) Mountain Top Research Site: Measurements and Uncertainties for Winter Alpine Weather Conditions

Purchase on Springer.com

$39.95 / €34.95 / £29.95*

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access

Abstract

The objective of this work is to better understand and summarize the mountain meteorological observations collected during the Science of Nowcasting Winter Weather for the Vancouver 2010 Olympics and Paralympics (SNOW-V10) project that was supported by the Fog Remote Sensing and Modeling (FRAM) project. The Roundhouse (RND) meteorological station was located 1,856 m above sea level that is subject to the winter extreme weather conditions. Below this site, there were three additional observation sites at 1,640, 1,320, and 774 m. These four stations provided some or all the following measurements at 1 min resolution: precipitation rate (PR) and amount, cloud/fog microphysics, 3D wind speed (horizontal wind speed, U h; vertical air velocity, w a), visibility (Vis), infrared (IR) and shortwave (SW) radiative fluxes, temperature (T) and relative humidity with respect to water (RHw), and aerosol observations. In this work, comparisons are made to assess the uncertainties and variability for the measurements of Vis, RHw, T, PR, and wind for various winter weather conditions. The ground-based cloud imaging probe (GCIP) measurements of snow particles using a profiling microwave radiometer (PMWR) data have also been shown to assess the icing conditions. Overall, the conclusions suggest that uncertainties in the measurements of Vis, PR, T, and RH can be as large as 50, >60, 50, and >20 %, respectively, and these numbers may increase depending on U h, T, Vis, and PR magnitude. Variability of observations along the Whistler Mountain slope (~500 m) suggested that to verify the models, model space resolution should be better than 100 m and time scales better than 1 min. It is also concluded that differences between observed and model based parameters are strongly related to a model’s capability of accurate prediction of liquid water content (LWC), PR, and RHw over complex topography.