Reconstructing glacier-based climates of LGM Europe and Russia – Part 1: Numerical modelling and validation methods

Abstract

Abstract. The mountain environments of mid-latitude Europe and Arctic Russia contain widespread evidence of Late-Quaternary glaciers that have been prescribed to the Last Glacial Maximum (LGM). This glacial-geological record has yet to be used to quantitatively reconstruct the LGM climate of these regions. Here we describe a simple glacier-climate model that can be used to derive regional temperature and precipitation information from a known glacier distribution. The model was tested against the present day distribution of glaciers in Europe. The model is capable of adequately predicting the spatial distribution, snowline and equilibrium line altitude climate of glaciers in the Alps, Scandinavia, Caucasus and Pyrenees Mountains. This verification demonstrated that the model can be used to investigate former climates such as the LGM. Reconstructions of LGM climates from proxy evidence are an important method of assessing retrospective general circulation model (GCM) simulations. LGM palaeoclimate reconstructions from glacial-geological evidence would be of particular benefit to investigations in Europe and Russia, where to date only fossil pollen data have been used to assess continental-scale GCM simulations.

Reconstructing glacier-based climates of LGM Europe and Russia – Part 3: Comparison with GCM and pollen-based climate reconstructions

“…HadCM3 0k climate predicted a distribution of present day glaciers in Europe that is comparable with the result achieved by Allen et al (2007a) using the CRU2.0 climate dataset (New et al, 2002). Predictions of non-glacierized cells exceed 90% in the four modelled regions, and range from 45% to 85% for glacierized cells (Fig.…”

“…The style of glacierization that results from the HadCM3 0k climate suggests that it reflects a colder European climate than the CRU2.0 dataset (New et al, 2002). In all regions (except the Caucasus Mountains) mean and maximum predicted within-cell glacial coverage is substantially greater than described by the WGI (National Snow and Ice Data Center, 1999) and predicted by the mass balance model using CRU2.0 climate data as input (Allen et al, 2007a) (Table 3). Moreover, predicted ELAs are lower than the mean WGI snowlines; for example, in the Alps HadCM3 0k climate mean ELA predictions range from 31 m to 405 m lower than the WGI mean snowline.…”

“…1) using the principles of equilibrium in the glacier-climate system at zero surface mass balance. Annual LGM climate anomalies were reconstructed from a present day climate baseline described by the CRU2.0 ∼20 km resolution climate dataset (New et al, 2002) which had been verified against the present day cryosphere of Europe (Allen et al, 2007a). The LGM palaeoclimate reconstructions of Europe and Russia by Peyron et al (1998) and Tarasov et al (1999) were derived from fossil pollen records (Fig.…”

“…to drive the glacier-climate model. The predictions of present day glaciers in Europe made by the mass balance model driven by the 0 k climate were assessed against the WGI data using the method of Allen et al (2007a).…”

“…7). The reasons for the more limited prediction of glacierized cells are discussed in detail in Allen et al (2007a). The style of glacierization that results from the HadCM3 0k climate suggests that it reflects a colder European climate than the CRU2.0 dataset (New et al, 2002).…”