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Literature based approach to estimate future snow

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DataCite Commons2026-05-16 更新2026-05-03 收录
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https://envidat.ch/#/metadata/literature-based-approach-to-estimate-future-snow
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Base data which were used for the methodology projecting future regional snow depths based on temperature scenarios. This study was supported by Seilbahnen Schweiz, Schweiz Tourismus, Seco and Speed2Zero. The data is split in three folders: - Literature-Fit dataset - Literature-Validation dataset - Projections The Literature-Fit dataset is the data which was used to retrieve the fit parameters a, Delta b and Delta c, for different elevations and temperature scenarios, which can be found in data/literature_fit/fitfactor.csv. Those fit factors were used to project future snow depths from climatological snow depths. Futhermore, this dataset was used to link decreases in mean snow depths for different seasonal periods to the NDJFMA period (November until April, in total six months), those differences in reduction values can be found in data/literature_fit/difference_decrease_4differentperiods.csv. The raw reference and future snow depths of different studies and different elevation and temperature scenarios (dt) can be found in data/literature_fit/literature_data/* where each file is named by data_author_station_dt.csv. The Literature-Validation dataset can be found in data/literature_validation/literature_data.csv contains the reference, RCP scenario, reference period, projected period and corresponding temperature scenarios. Furthermore, it contains region, elevation and relative decreases with corresponding seasonal periods, and the number of days with a certain amount of snow during the reference period and the projected period, if literature reported these values. The folder projections contains mean snow depths, 5th and 95th percentile snow depth for each day of the year for the reference period and a temperature scenario of +2°C for all four stations Engelberg, Maloja, Saanenmöser and Weissfluhjoch.
提供机构:
EnviDat
创建时间:
2025-12-11
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