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This study aims to analyze the stable isotope composition of the snow cover of the Elbrus Mountain – the highest mountain in Europe. Snow sampled in the middle accumulation period in January 2017, February 2016, January 2001 and during snowmelt in July 1998 and August 2009. Snow sampled at the south slope of Mt. Elbrus at different elevations, and the total altitude range is approximately 1700 m. A significant altitude effect in fresh snow precipitation was determined in February 2001 with gradient –1.3‰ δ18O/100 m (–11.1‰ δ2 H /100 m) at 3100-3900 m a.s.l. and inverse altitude effect in February 2016 with gradient +1.04‰ δ18O /100 m (+8.7‰ δ2 H /100 m) at 3064-3836 m a.s.l. There is no obvious altitude effect of the δ2 H and δ18O values in snow at the Elbrus slope in 2017, except for the height range 2256-3716 m a.s.l., where altitudinal effect of δ18O values was roughly -0.32‰/100m. The δ18O values in the winter snowpack in some cases decrease with increasing altitude, but sometimes are not indicating a temperaturealtitude effect. Post-depositional processes cause isotopic changes, which can result from drifting, evaporation, sublimation, and ablation. The study of altitude effect in snow is important for understanding the processes of snow-ice and snow-meltwater transformation and the snow/ice potential to provide paleo-environmental data.
This study compares three popular approaches to quantify the urban heat island (UHI) effect in Moscow megacity in a summer season (June-August 2015). The first approach uses the measurements of the near-surface air temperature obtained from weather stations, the second is based on remote sensing from thermal imagery of MODIS satellites, and the third is based on the numerical simulations with the mesoscale atmospheric model COSMO-CLM coupled with the urban canopy scheme TERRA_URB. The first approach allows studying the canopy-layer UHI (CLUHI, or anomaly of a near- surface air temperature), while the second allows studying the surface UHI (SUHI, or anomaly of a land surface temperature), and both types of the UHI could be simulated by the atmospheric model. These approaches were compared in the daytime, evening and nighttime conditions. The results of the study highlight a substantial difference between the SUHI and CLUHI in terms of the diurnal variation and spatial structure. The strongest differences are found at the daytime, at which the SUHI reaches the maximal intensity (up to 10°С) whereas the CLUHI reaches the minimum intensity (1.5°С). However, there is a stronger consistency between CLUHU and SUHI at night, when their intensities converge to 5–6°С. In addition, the nighttime CLUHI and SUHI have similar monocentric spatial structure with a temperature maximum in the city center. The presented findings should be taken into account when interpreting and comparing the results of UHI studies, based on the different approaches. The mesoscale model reproduces the CLUHI-SUHI relationships and provides good agreement with in situ observations on the CLUHI spatiotemporal variations (with near-zero biases for daytime and nighttime CLUHI intensity and correlation coefficients more than 0.8 for CLUHI spatial patterns). However, the agreement of the simulated SUHI with the remote sensing data is lower than agreement of the simulated CLUHI with in situ measurements. Specifically, the model tends to overestimate the daytime SUHI intensity. These results indicate a need for further in-depth investigation of the model behavior and SUHI–CLUHI relationships in general.
This study aimed to reconstruct the climatic moisture conditions of the Mid- Russian Upland through the Holocene. Surface moisture conditions in the study region were inferred from published pollen records from the Klukva peatland, in the north- west of the Mid-Russian Upland. Three climatic indices were derived from previously- published reconstructions of mean annual temperature and precipitation: the Climate Moisture Index, the Aridity Index and the Budyko Dryness Index. A simple modeling approach to reconstruct annual potential evapotranspiration and net radiation was developed and used to estimate the indices for different periods of the Holocene. The moisture indices were compared with independent proxies of climate moisture such as peatland surface wetness, reconstructed from testate amoebae and regional fire activity, reconstructed from charcoal. Results show that the surface moisture conditions in the study region were characterized by large variability. Periods of mild temperature and moderately wet conditions were followed by dry periods, which resulted in significant changes in palaeoenvironments. The method developed for calculation of potential evapotranspiration and indices of surface moisture conditions could be a useful tool for climate reconstructions. Our results demonstrate the detailed and nuanced palaeoclimate data which can be derived from pollen data.

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ISSN 2071-9388 (Print)
ISSN 2542-1565 (Online)