Sentence examples for accuracy of snow from inspiring English sources

Snow depth observations made at ground stations were used to assess the accuracy of snow mapping.

For the entire dry-snow season, the deviation of the fullyAuto routine is larger than of the semiAuto algorithm indicating that the accuracy of snow surface tracking improved when phase information was included.

Finally we investigated the relation between number of stations and estimation accuracies of snow distributions using a Monte Carlo sensitivity analysis.

There is an undisputed need to increase accuracy of Fractional Snow Cover (FSC) estimation in regions of complex terrain, especially in areas dependent on winter snow accumulation for a substantial portion of their water supply, such as the western United States.

In this study, we applied a four-step methodology that aims to optimize the accuracy of MODIS snow data.

The steps of the data assimilation procedure (evaluation, sensitivity analysis, optimization) and their contribution to significantly increased accuracy of the snow maps are demonstrated with a case from eastern Norway in winter 2013/2014.

To better assess and quantify the accuracy of the snow depth estimate using the dipole antenna system, a long-term experiment is underway during the 2013/2014 winter season and reference data from other snow sensors (geodetic GPS as well as laser and ultrasonic ranging) will be used.

Snow cover area was validated against ETM+ data and the SWE was assessed against in situ measurements; the overall accuracy of the snow cover maps was ∼85%, whereas, the comparison between ground points measured and remotely sensed derived SWE indicates a poor correlation.

Results suggest that including the phase information is crucial to improve accuracy for snow height determination.

With this in mind, we list several model deficiencies that limit the accuracy of retrieving the snow parameters.

This increased variability may have been caused by a degradation in the accuracy of the GPS due to snow cover.