2021
DOI: 10.3389/feart.2021.664648
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Continuous Spatio-Temporal High-Resolution Estimates of SWE Across the Swiss Alps – A Statistical Two-Step Approach for High-Mountain Topography

Abstract: Snow and precipitation estimates in high-mountain regions typically suffer from low temporal and spatial resolution and large uncertainties. Here, we present a two-step statistically based model to derive spatio-temporal highly resolved estimates of snow water equivalent (SWE) across the Swiss Alps. A multiple linear regression model (Step-1 MLR) was first used to combine the CombiPrecip radar-gauge product with the precipitation and wind speed (10 m from the ground) of the numerical weather prediction model C… Show more

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Cited by 10 publications
(10 citation statements)
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“…The final snow distribution at a high spatial resolution of 25 m agreed well with in situ measurements on a selected glacier (Guidicelli et al, 2021).…”
Section: Modelling Snow Accumulationsupporting
confidence: 70%
See 1 more Smart Citation
“…The final snow distribution at a high spatial resolution of 25 m agreed well with in situ measurements on a selected glacier (Guidicelli et al, 2021).…”
Section: Modelling Snow Accumulationsupporting
confidence: 70%
“…Statistical approaches to derive snow accumulation distributions might become an alternative to modelling wind fields. Guidicelli et al (2021) recently presented a statistical…”
Section: Modelling Snow Accumulationmentioning
confidence: 99%
“…51 The reliability of the products based on the interpolation of in situ measurements (e.g., CMC), finally, is strongly linked to the availability of observations, which is generally completely lacking in high-mountain regions or only available once a year at the end of the accumulation period. 52 Additionally, it has been shown that, in the case of high-resolution products, even interpolated data from snow pillows may not perform as well as energy-balance-based estimates over some regions. 53 The coarse spatial resolution of all three products may be another limiting factor over mountain terrains as it may not be suitable to capturing the complex spatial dynamic observed in such areas.…”
Section: Analysis Of the Consistency Among Swe Anomaliesmentioning
confidence: 99%
“…Since melting is often negligible during this time period, SWE on glaciers represents a reliable measure of local winter precipitation and was thus used for a comparison with precipitation products in different studies (e.g. Gugerli et al, 2020;Guidicelli et al, 2021). However, other processes such as deposition of hoar, freezing rain or snow drift caused by winds and avalanching can also influence the accumulation (Dadic et al, 2010;Gascoin et al, 2013).…”
Section: Introductionmentioning
confidence: 99%