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The potential of quantitatively reconstructing climate from modern pollen assemblages from high mountain environments has been widely debated but seldom tested. We analysed the pollen deposition in 53 surface samples (mosses) in relation to July temperature in two elevational transects in the European Alps. Each surface-sample site was assigned climate data derived from the local-scale climate. We compared our results with a larger calibration set extracted from the European Modern Pollen Database (EMPD) and centred on the European Alps. This also was assigned local climate data. The main calibration set (234 pollen samples) had Alnus harmonized at genus level; in contrast, a second set was selected (174) that retained the taxonomic resolution of Alnus viridis, which is one of the main climate indicators in the timberline ecotone. The overall and individual pollen responses to July temperature were inferred by canonical correspondence analysis (CCA), generalized linear regression (eHOF) and weighted averaging (WA). Quantitative climate reconstructions for each sample site of the two elevational transects were obtained using transfer functions, that is, WA and WA partial least squares (WA-PLS) regressions. In each calibration set, around 30% of the pollen taxa show a relationship with July temperature through monotonic or unimodal functions. The best transfer function obtained has a good statistical performance, with a determination coefficient (r(2)) of 0.74. We propose new calibration procedures formulated to include the full climate space of the modelled taxa, as well as to account for uphill pollen transport in the high mountains and for human activity.