Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data

Based on the model evaluation results, there are three recommendations with which the quality of the seNorge model results (and thus of the snow maps for Norway) could be increased

To investigate the influence of snow depth, sea ice density, and area on sea ice thick- ness and volume estimates we use freeboard retrievals from ICESat, together with dif-

The present study investigates the possibil- ity of a relationship between the coastal topography with steep slopes and sea-salt snow chemistry, using high reso- lution data from

An extensive drill-hole measurement campaign was carried out in November and De- cember 2011 collecting information on freeboard, snow depth and snow density, sea ice thickness

Hydrologic response data include hourly stream discharge from the catchment outlet weir, continuous snow depths from one location, intermittent snow depths from 5 locations, and

The function I (z) ˜ is found by measuring light reflectance from snow walls and can be used to retrieve the optical and microphysical properties of the snow layers at any depth..

Given the discontinuous nature of precipitation and snow accumulation (where wind plays a key role), these data suggest that at some point in the season, a snow accu- mulation

Root mean square errors in snow depth estimation from differenc- ing snow-covered and non-snow-covered DSMs were 8.8 cm for a short prairie grain stubble surface, 13.7 cm for a