The large landmass of northern Russia has the potential to influence global climate through amplification of climate change. Reconstructing the climate in this region over millennial timescales is crucial for understanding the processes that affect the climate system. Chironomids, preserved in lake sediments, have the potential to produce high resolution, low error, quantitative summer air temperature reconstructions. Canonical correspondence analysis (CCA) of modern surface sediments from 100 high-latitude lakes, located in northern European Russia to central Siberia, showed chironomid distribution was primarily driven by July air temperatures. The strong relationship enabled the development of chironomid-inference model based on 81 lake and 89 taxa to reconstruct July air temperature. Analysis of a range of chironomid-inferred temperature model suggest the best to be a two component weighted averaging and partial least squares (WA-PLS model) with r2jack = 0.92 and RMSEP = 0.89°C. Comparison of species responses to July temperature with the Norwegian training set showed the temperature optima of individual species was 1-3°C in the Russian data regardless of modelling technique. This suggests that chironomid-based inference models should only be applied to sediment cores collected within the geographic source area of the training set. The differing responses between the Norwegian and Russian faunas led to the development of a 149 lake, 120 taxa chironomid-continentality inference model. The 2-component WA-PLS model was the minimal adequate model with r2jack = 0.73 and RMSEP = 9.9. Recent warming in the Arctic has been spatial and seasonal heterogeneous; in many areas warming is more pronounced in the spring and autumn leading to a lengthening of the summer, while summer temperatures have remained relatively stable. A continentality model has the potential to detect these seasonal changes in climate. The Russian inference model also improves the representation of a number of taxa, such as Corynocera oliveri-type, Constempellina and Paracladius, which frequently occur in subfossil assemblages from arctic Russian lakes, but are poorly represented in European training sets. These are cold-adapted taxa and their absence from the training sets could lead to overestimations of July temperatures in fossil samples where these taxa form a major component (for example see Andreev et al. 2005). Comparison of reconstructed July air temperatures and continentality indices from a tundra lake in north-east European Russia showed close agreement with local instrumental records over the past 70 years and suggests the models may produce reliable estimates of past climate.