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1 February 2022 Testing remote sensing estimates of snow water equivalent in the framework of the European Drought Observatory
Carmelo Cammalleri, Paulo M. Barbosa, Jürgen V. Vogt
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Abstract

We evaluated the feasibility for operational snow drought monitoring over Europe based on the near-real-time snow water equivalent (SWE) satellite product from the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF). To do so, the consistency of this dataset with the consolidated dataset of the Canadian Meteorological Centre (CMC), as well as with the ERA5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts, was tested in terms of both spatial snow coverage and detection of anomalies from the long-term climatology. The analysis confirms a general good agreement among the three products as well as substantial differences over mountainous terrains, with the H-SAF product capturing only about 30% of the areas identified by CMC as snow-covered in those areas, while a better match between the ERA5 and the CMC spatial coverage is observed. However, significant inconsistencies in the correlation between all three SWE anomalies are observed over mountain areas. Due to the lack of a reliable reference dataset, the observed inconsistencies and the coarse spatial resolution (0.25 deg) of all three products limit the possibility for snow drought monitoring over key European regions such as the Alps.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Carmelo Cammalleri, Paulo M. Barbosa, and Jürgen V. Vogt "Testing remote sensing estimates of snow water equivalent in the framework of the European Drought Observatory," Journal of Applied Remote Sensing 16(1), 014509 (1 February 2022). https://doi.org/10.1117/1.JRS.16.014509
Received: 3 June 2021; Accepted: 10 January 2022; Published: 1 February 2022
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Cited by 1 scholarly publication.
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KEYWORDS
Remote sensing

Satellites

Data modeling

Analytical research

Climatology

Spatial resolution

Statistical analysis

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