Large-domain species distribution models (SDMs) fail to identify microrefugia, as they are based on climate estimates that are either too coarse or that ignore relevant topographic climate-forcing factors. Climate station data are considered inadequate to produce such estimates, a viewpoint we challenge here. Using climate stations and topographic data, we developed three sets of large-domain (450 000 km(2)), fine-grain (50m) temperature grids accounting for different levels of topographic complexity. Using these fine-grain grids and the Worldclim data, we fitted SDMs for 78 alpine species over Sweden, and assessed over-versus underestimations of local extinction and area of microrefugia by comparing modelled distributions at species' rear edges. Accounting for well-known topographic climate-forcing factors improved our ability to model fine-scale climate, despite using only climate station data. This approach captured the effect of cool air pooling, distance to sea, and relative humidity on local-scale temperature, but the effect of solar radiation could not be accurately accounted for. Predicted extinction rate decreased with increasing spatial resolution of the climate models and with increasing number of topographic climate-forcing factors accounted for. About half of the microrefugia detected in the most topographically complete models were not detected in the coarser SDMs and in the models calibrated from climate variables extracted from elevation only. Although major limitations remain, climate station data can potentially be used to produce fine-grain topoclimate grids, opening up the opportunity to model local-scale ecological processes over large domains. Accounting for the topographic complexity encountered within landscapes permits the detection of microrefugia that would otherwise remain undetected. Topographic heterogeneity is likely to have a massive impact on species persistence, and should be included in studies on the effects of climate change.