The Normalized Difference Snow Index (NDSI) is an effective index for snow-cover mapping at large scales, but in forested regions the identification accuracy for snow using the NDSI is low because of forest cover effects. In this study, typical evergreen coniferous forest zones on Qilian Mountain in the Upper Heihe River Basin (UHRB) were chosen as example regions. By analyzing the spectral sig...

Freshly fallen snow is a popular natural phenomenon able to evoke great beauty in all kinds of scenes. However, there still does not exist an all-purpose algorithm for automated snow distribution in virtual worlds. Previous works modelled snow either relying on costly particle simulations or oversimplified surface displacements. In this paper we develop a novel geometric snow model. In a first ...

[1] The design of sensor networks for measuring the mean and spatial distribution of snow depth at the scale of 1–16 km was evaluated by deploying an embedded‐sensor network consisting of ultrasonic snow depth sensors to capture the variable physiographic features around an operational snow course in Yosemite National Park in the Sierra Nevada of California. Manual snow surveys were also carrie...

Improved representations of snow processes in vegetation canopies and snow hydrology are implemented in the Met Office Surface Exchange Scheme 2 (MOSES 2) land-surface model. Snow falling on forests is partitioned between interception and throughfall; the intercepted snow is removed by sublimation, melt and unloading. A reduction in sublimation of wind-blown snow through trapping by shrubs is s...

Snow disasters cause immeasurable losses to human society each year, threatening people’s lives and properties and therefore attaching much importance to the measurement of snow cover. Snowfall, however, is one of the most difficult to be measured among meteorological elements, especially on the railways. To solve this problem, the real-time monitoring of snow along the railway can be helpful. ...

An analysis of snow grain size behavior with respect to other snow parameters such as snow depth, density, and temperature was performed. From this analysis, a pattern was derived which can be used to approximate the range of grain size variations. Data used in this research are from NASA Cold Land Processes Field Experiment (CLPX) in Colorado. This intensive field survey was conducted in Febru...

It is important to understand reflective properties of snow, for example for remote sensing applications and for modeling of energy balances in snow packs. We present a method with which we can compare reflectance measurements and calculations for the same snow sample structures. Therefore, we first tomograph snow samples to acquire snow structure images (6 x 2 mm). Second, we calculated the sa...

In this study, daily maps of snow cover distribution and sea ice extent produced by NOAA’s interactive multisensor snow and ice mapping system (IMS) were validated using in situ snow depth data from observing stations obtained from NOAA’s National Climatic Data Center (NCDC) for calendar years 2006 to 2010. IMS provides daily maps of snow and sea ice extent within the Northern Hemisphere using ...

In aerial radiation monitoring (ARM), the air dose rate cannot be appropriately estimated under snowy conditions due to attenuation of gamma rays by the snow layer. A technique to address this issue is required for ARM to obtain enough signals for air dose rates. To develop this technique, we investigated the relationship between snow depth and ARM measurement results using ARM, laser imaging d...

Abstract. In winter storms, enhanced radar reflectivity is often associated with heavy snow. However, some higher reflectivities are the result of mixed precipitation including melting The correlation coefficient (a dual-polarization variable) can identify regions precipitation, but this information usually presented separately from reflectivity. Especially under time pressure, data users mista...