The effect of including Δρ in the bulk density model (ρ_sim) is illustrated in Figure 10(b). Due to the exceptionally large snow accumulation in January/February 1999 ρ_sim (without Δρ = diamond) overestimates the observed ρ. In contrast, when HN is included to model ρ_sim (stars) the bias decreases on 29 January and 6 February. Note that ρ_sim is not improved on days without new snow accumulation as the offset Δρ = 0. Still on 2 February 1999 (Figure 10(b)), the bias between ρ and ρ_sim is particularly large as a result of the above average HS during that period (see also Figure 6(a)). The extended bulk density model is used to compute ρ_sim and SWE_sim of the stations where long-term records of HN are available (Table 4). The available time series of SWE at the seven stations are reduced to times where daily HN measurements are available. At the different locations, 31–43% of the available SWE data (n) was recorded during or shortly after snowfall (Table 4). In this table, nHN denotes the number of new snow events occurring in combination with manual SWE measurements. Whether HN or ΔHS is used to calculate Δρ, almost no differences in the results for ρ_sim and SWE_sim are detected. At the stations Jochberg, Ginzling and Felbertauern, the application of HN leads to slightly better results but at Hinteriss, Boden and Obernberg the application of ΔHS results in slightly lower model errors. In Figure 11, the MAE_rel of the seven stations are evaluated applying the different modelling approaches. Starting with the approach used by Jonas et al. (2009) (Figure 11(a)), an adapted version of the Tyrol model with daily resolution (Figure 11(c)) is introduced using a quasi-monthly resolution (k and d of the 15th of a month (Figure 11(b)). Furthermore, the Tyrolean model with daily resolution is applied using an additional regional offset (Figure 11(d)) and the regional offset plus Δρ (Figure 11(e)).