Evaluation of annual maximum snow depth data estimation from the European-wide reanalysis C3S MTMSI (Copernicus Climate Change Service – Mountain Tourism Meteorological and Snow Indicators) against in-situ observations

dc.contributor.authorKamir, Elisa
dc.contributor.authorMorin, Samuel
dc.contributor.authorEvin, Guillaume
dc.contributor.authorGehring, Penelope
dc.contributor.authorWichura, Bodo
dc.contributor.authorArslan, Ali Nadir
dc.contributor.departmentfi=Digital Economy|en=Digital Economy|
dc.date.accessioned2026-03-24T11:40:00Z
dc.date.issued2026
dc.description.abstractLarge snow load events are a major hazard for both human societies, in particular buildings and transport safety, and natural ecosystems. National and European frameworks provide guidelines and standards in order to take into account extreme snow load hazard in infrastructure design. However, there is a lack of reference data for their implementation. This is even more challenging in the context of climate change, which modifies the frequency and intensity of major snow load events. In the context of the Framework Partnership Agreement on Copernicus User Uptake, we have developed a pan-European extreme value analysis of annual snow load maxima based on the Mountain Tourism Meteorological and Snow Indicators (MTMSI) dataset available from the Copernicus Climate Change Service. This dataset includes reanalysis data for the period 1962–2015, based on the UERRA (Uncertainties in Ensembles of Regional Reanalyses) reanalysis and snow cover simulations, and past and future climate projections based on regional climate simulations for the period 1951–2100. Here, we describe the evaluation of the MTMSI reanalysis component in terms of annual snow depth maxima against multiple in-situ observation datasets. Results are provided at the NUTS-3 (Nomenclature des unités territoriales statistiques) scale used in MTMSI, for multiple elevations over a large area stretching from the European Alps to the Scandinavian countries. For 75 % of the comparisons between observed and simulated snow depth maxima, we report absolute bias scores between −0.23 and 0.15 m, correlations above 0.59, and a Kling–Gupta Efficiency metric above 0.29. We identify some areas where MTMSI does not adequately portray in-situ observations of snow depth maxima, located in the Alps and coastal areas of the Netherlands, Norway, Sweden, and Croatia. This study thus provides background information for assessing the relevance of this pan-European dataset in terms of annual snow depth maxima, relevant for annual snow mass and snow load maxima based on complementary information derived from snow cover model output. The MTMSI annual maximum snow depth reanalysis dataset is available through the following link: https://doi.org/10.5281/zenodo.15181401 (Kamir et al., 2025).en
dc.description.notification© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License. https://creativecommons.org/licenses/by/4.0/
dc.description.reviewstatusfi=vertaisarvioitu|en=peerReviewed|
dc.format.pagerange17-32
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/19973
dc.identifier.urnURN:NBN:fi-fe2026032422687
dc.language.isoen
dc.publisherCopernicus publications
dc.relation.doihttps://doi.org/10.5194/essd-18-17-2026
dc.relation.funderEuroopan Unionifi
dc.relation.funderEuropean Unionen
dc.relation.ispartofjournalEarth system science data
dc.relation.issn1866-3516
dc.relation.issn1866-3508
dc.relation.issue1
dc.relation.urlhttps://doi.org/10.5194/essd-18-17-2026
dc.relation.urlhttps://urn.fi/URN:NBN:fi-fe2026032422687
dc.relation.volume18
dc.rightshttps://creativecommons.org/licenses/by/4.0/
dc.source.identifierWOS:001653292300001
dc.source.identifier2-s2.0-105026907402
dc.source.identifier1339381b-0446-468e-afb3-720b7f38f648
dc.source.metadataSoleCRIS
dc.subject.disciplinefi=Tietotekniikka tekn|en=Information Technology tech|
dc.titleEvaluation of annual maximum snow depth data estimation from the European-wide reanalysis C3S MTMSI (Copernicus Climate Change Service – Mountain Tourism Meteorological and Snow Indicators) against in-situ observations
dc.type.okmfi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä (vertaisarvioitu)|en=A1 Journal article (peer-reviewed)|
dc.type.publicationarticle
dc.type.versionpublishedVersion

Tiedostot

Näytetään 1 - 1 / 1
Ladataan...
Name:
nbnfi-fe2026032422687.pdf
Size:
4.13 MB
Format:
Adobe Portable Document Format

Kokoelmat