A new parameterization of snow water equivalent (SWE) based on snow depth (HS) has been developed from observations made in northern Sweden. When applying previous SWE parameterization from the Alps on observations from northern Sweden, the SWE values are systematically 20% lower. The new SWE parameterization is derived from a snow layer density regression model using snow layer hardness and snow particle size. The model was evaluated with a detailed field reference dataset, and then applied to the long-term Abisko Scientific Research Station stratigraphic snowpack dataset. The model enables a regional adjustment of snow layer density values for northern Swedish conditions. The snow layer density model provides an accurate estimation of snow bulk density used to derive the SWE parameterization based solely on HS. Snow depth observations are made on a daily basis; by applying our new parameterization, daily values of SWE can be obtained for northern Scandinavian conditions, which can be used, for example, for hydropower production planning and risk assessments.
In future, one of our new products will support weather services, road operators, operators of winter sport areas and energy producers in the field of environmental monitoring: The SHM31 is able to deliver snow depths of up to 15 meters. It represents an advancement of the SHM30, which came onto the market in mid-2009.New snow height sensor SHM31 compared to its predecessor SHM30In contrast to the SHM30, which has one interface only, the new SHM31 snow depth sensor is equipped with the three communication interface...
This year’s Intersolar Europe, the world’s leading exhibition for the solar industry and its partners, will take place between May 31 and June 2, 2017 at the Neue Messe München – and we will be on-site for you! You can find us on the joint booth of Baden-Württemberg International with the number A3.460. Here we present a selection of our all-in-one weather sensors as well as our snow depth sensor for solar monitoring applications.
Why you should get to know our all-in-one weather...
An extensive collection of in-situ snow measurements is used to characterize snow conditions in the entire elevation range of the alpine area of Tyrol, Austria. Regularly observed snow station data are evaluated with respect to mean snow density–time curves of the period 1952–2010. Dependent on the observed snow depth (HS), the snow bulk density (ρ) is statistically modelled for different elevation zones and snow-climate regions. Model improvements allow daily estimates of ρ, and introducing an additional parameter...
Snow density is an important measure in hydrology used to convert snow depth to the snow water equivalent (SWE). A model developed by Sturm, Tara and Liston predicts the snow density by using snow depth, the snow age and a snow class defined by the location. In this work this model is extended to include location and seasonal weather-specific variables. The model is named Weather Snow Density Model (Weather SDM). A Bayesian framework is chosen, and the model is fitted to and tested for 4,040 Norwegian snow depth...
Central Asian countries depend highly on water resources from snow and glacier melt, which has to be studied thoroughly to estimate water availability. However, the observation network in Central Asia is poor to carry out such studies in detail. Observations from space using remote sensing techniques might fill this observation gap, which needs to be validated. Therefore, this study evaluates the Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover product in Central Asia. For the evaluation, in...
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