A decade of glaciological and meteorological observations in the Arcti (Werenskioldbreen, Svalbard)

The warming of the Arctic climate is well documented, but the mechanisms of Arctic amplification are still not fully understood. Thus, monitoring of glaciological and meteorological variables and the environmental response to accelerated climate warming must be continued and developed in Svalbard. L...

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Bibliographic Details
Published in:Earth System Science Data
Main Authors: Ignatiuk, Dariusz, Błaszczyk, Małgorzata, Budzik, Tomasz, Grabiec, Mariusz, Jania, Jacek Adam, Kondracka, Marta, Laska, Michał, Małarzewski, Łukasz, Stachnik, Łukasz
Format: Article in Journal/Newspaper
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/20.500.12128/23525
https://doi.org/10.5194/essd-14-2487-2022
Description
Summary:The warming of the Arctic climate is well documented, but the mechanisms of Arctic amplification are still not fully understood. Thus, monitoring of glaciological and meteorological variables and the environmental response to accelerated climate warming must be continued and developed in Svalbard. Long-term meteorological observations carried out in situ on glaciers in conjunction with glaciological monitoring are rare in the Arctic and significantly expand our knowledge about processes in the polar environment. This study presents glaciological and meteorological data collected for 2009–2020 in southern Spitsbergen (Werenskioldbreen). The meteorological data are composed of air temperature, relative humidity, wind speed, short-wave and long-wave upwelling and downwelling radiation on 10 min, hourly and daily resolution (2009–2020). The snow dataset includes 49 data records from 2009 to 2019 with the snow depth, snow bulk density and snow water equivalent data. The glaciological data consist of seasonal and annual surface mass balance measurements (point and glacier-wide) for 2009–2020. The paper also includes modelling of the daily glacier surface ablation (2009–2020) based on the presented data. The datasets are expected to serve as local forcing data in hydrological and glaciological models as well as validation of calibration of remote sensing products.