Meteorological observations at Bayelva Station in 2020 (level 1) ...

• Main Authors: Boike, Julia, Bornemann, Niko, Cable, William L, Grünberg, Inge, Lange, Stephan
• Format: Dataset
• Language: English
• Published: PANGAEA 2021
• Subjects: air temperature; Arctic; Bayelva; Permafrost; precipitation; radiation; relative humidity; snow depth; snow height; Svalbard; wind direction; wind speed; DATE/TIME; Temperature, air; Quality flag, air temperature; Precipitation; Quality flag, precipitation; Humidity, relative; Quality flag, relative humidity; Net radiation; Quality flag, net radiation; Short-wave downward GLOBAL radiation; Quality flag, short-wave downward GLOBAL radiation; Short-wave upward REFLEX radiation; Quality flag, short-wave upward REFLEX radiation; Long-wave downward radiation; Quality flag, long-wave downward radiation; Long-wave upward radiation; Quality flag, long-wave upward radiation; Wind speed; Quality flag, wind speed; Wind direction; Quality flag, wind direction; Wind direction, standard deviation; Quality flag; Snow height; Quality flag, snow height; Permittivity, relative; Quality flag, permittivity; Monitoring station; Permafrost Research AWI_Perma; Ny-Ålesund; Ny Ålesund; permafrost
• Online Access: https://dx.doi.org/10.1594/pangaea.936272; https://doi.pangaea.de/10.1594/PANGAEA.936272

Understanding permafrost processes and changes requires long-term observational datasets. This dataset is a continuation of the dataset available from the Bayelva Site at Ny-Ålesund, Svalbard, where meteorology, energy balance components and subsurface observations have been made for more than the last 20 years. The data provide observations of temporally variable parameters that mitigate energy fluxes between permafrost and atmosphere, such as snow depth, snow dielectric number, snow temperature, liquid precipitation, air temperature, relative humidity, wind speed and direction and radiation fluxes. They are suitable for use in integrating, calibrating and testing permafrost as a component in Earth System Models. The resulting quality-controlled dataset is unique in the Arctic and serves as a baseline for future studies. ... : This dataset of 2020 is a continuation of a data record, which was published in Boike et al. (2018), doi:10.5194/essd-10-355-2018. If you use this dataset, please cite this publication. ...