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This article describes the extension of the ESCIMO.spreadspreadsheet-based point energy balance snow model by (i) an advanced approachfor precipitation phase detection, (ii) a method for cold content andliquid water storage consideration and (iii) a canopy sub-model thatallows the quantification of canopy effects on themeteorological conditions inside the forest as well as thesimulation of snow accumulation and ablation inside a foreststand. To provide the data for model application and evaluation,innovative low-cost snow monitoring systems (SnoMoS) have beenutilized that allow the collection of important meteorological andsnow information inside and outside the canopy. The model performancewith respect to both, the modification of meteorological conditionsas well as the subsequent calculation of the snow cover evolution,are evaluated using inside- and outside-canopy observations ofmeteorological variables and snow cover evolution as provided bya pair of SnoMoS for a site in the Black Forest mountain range(southwestern Germany). The validation results for the simulated snow waterequivalent with Nash–Sutcliffe model efficiency values of 0.81 and 0.71 androot mean square errors of 8.26 and 18.07 mm indicate a good overall modelperformance inside and outside the forest canopy, respectively. The newlydeveloped version of the model referred to as ESCIMO.spread (v2) isprovided free of charge together with 1 year of sample dataincluding the meteorological data and snow observations used in thisstudy

ESCIMO.spread (v2): parameterization of a spreadsheet-based energy balance snow model for inside-canopy conditions