Estimating surface water availability in high mountain rock slopes using a numerical energy balance model

Model output, forcing data and physical parameters used to estimate water and energy balance. The model was calibrated with field measurements from a study site in the Mont-Blanc massif, at 3842 m a.s.l, at a slope of 55 deegrees and aspect azimut of 150 degrees (south-east). The different ModelOutp...

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Bibliographic Details
Main Author: Matan Ben-Asher
Format: Dataset
Language:English
Published: 2022
Subjects:
Ice
Online Access:https://zenodo.org/record/7224692
https://doi.org/10.5281/zenodo.7224692
id ftzenodo:oai:zenodo.org:7224692
record_format openpolar
spelling ftzenodo:oai:zenodo.org:7224692 2023-05-15T16:37:51+02:00 Estimating surface water availability in high mountain rock slopes using a numerical energy balance model Matan Ben-Asher 2022-10-19 https://zenodo.org/record/7224692 https://doi.org/10.5281/zenodo.7224692 eng eng info:eu-repo/grantAgreement/ANR//ANR-19-CE01-0018/ doi:10.5281/zenodo.7224691 https://zenodo.org/record/7224692 https://doi.org/10.5281/zenodo.7224692 oai:zenodo.org:7224692 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode mountain permafrost steep rock walls snowmelt mont blanc info:eu-repo/semantics/other dataset 2022 ftzenodo https://doi.org/10.5281/zenodo.722469210.5281/zenodo.7224691 2023-03-10T19:10:28Z Model output, forcing data and physical parameters used to estimate water and energy balance. The model was calibrated with field measurements from a study site in the Mont-Blanc massif, at 3842 m a.s.l, at a slope of 55 deegrees and aspect azimut of 150 degrees (south-east). The different ModelOutput files are from simulations at different elevastions (from 4800 m to 2700 m at steps of 300 m). We used the CryoGrid community model (version 1.0) toolbox (Westermann et al., 2022) to simulate the 1D ground thermal regime and ice/water balance, and estimate the availability of surface water and its potential for infiltration in rock fractures. The S2M-SAFRAN dataset combines output from a numerical weather prediction model and in situ observations, and was originally developed for operational needs to estimate avalanche hazard in mountainous areas (Durand et al., 1993). The S2M-SAFRAN dataset that we used is available for various mountain areas, at elevation steps of 300 m, and with an hourly resolution between the years 1958 to 2021 (Vernay et al., 2022). It includes most parameters that are required for modeling with CryoGrid: Relative humidity, air T, incoming long wavelength radiation, incoming short wavelength solar radiation, and wind speed. To complete the forcing data we used top of the atmosphere incident solar radiation from ERA5 global reanalysis dataset (Hersbach et al., 2020). Dataset Ice permafrost Zenodo Mont Blanc ENVELOPE(69.468,69.468,-49.461,-49.461) Azimut ENVELOPE(-58.300,-58.300,-63.750,-63.750)
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language English
topic mountain permafrost
steep rock walls
snowmelt
mont blanc
spellingShingle mountain permafrost
steep rock walls
snowmelt
mont blanc
Matan Ben-Asher
Estimating surface water availability in high mountain rock slopes using a numerical energy balance model
topic_facet mountain permafrost
steep rock walls
snowmelt
mont blanc
description Model output, forcing data and physical parameters used to estimate water and energy balance. The model was calibrated with field measurements from a study site in the Mont-Blanc massif, at 3842 m a.s.l, at a slope of 55 deegrees and aspect azimut of 150 degrees (south-east). The different ModelOutput files are from simulations at different elevastions (from 4800 m to 2700 m at steps of 300 m). We used the CryoGrid community model (version 1.0) toolbox (Westermann et al., 2022) to simulate the 1D ground thermal regime and ice/water balance, and estimate the availability of surface water and its potential for infiltration in rock fractures. The S2M-SAFRAN dataset combines output from a numerical weather prediction model and in situ observations, and was originally developed for operational needs to estimate avalanche hazard in mountainous areas (Durand et al., 1993). The S2M-SAFRAN dataset that we used is available for various mountain areas, at elevation steps of 300 m, and with an hourly resolution between the years 1958 to 2021 (Vernay et al., 2022). It includes most parameters that are required for modeling with CryoGrid: Relative humidity, air T, incoming long wavelength radiation, incoming short wavelength solar radiation, and wind speed. To complete the forcing data we used top of the atmosphere incident solar radiation from ERA5 global reanalysis dataset (Hersbach et al., 2020).
format Dataset
author Matan Ben-Asher
author_facet Matan Ben-Asher
author_sort Matan Ben-Asher
title Estimating surface water availability in high mountain rock slopes using a numerical energy balance model
title_short Estimating surface water availability in high mountain rock slopes using a numerical energy balance model
title_full Estimating surface water availability in high mountain rock slopes using a numerical energy balance model
title_fullStr Estimating surface water availability in high mountain rock slopes using a numerical energy balance model
title_full_unstemmed Estimating surface water availability in high mountain rock slopes using a numerical energy balance model
title_sort estimating surface water availability in high mountain rock slopes using a numerical energy balance model
publishDate 2022
url https://zenodo.org/record/7224692
https://doi.org/10.5281/zenodo.7224692
long_lat ENVELOPE(69.468,69.468,-49.461,-49.461)
ENVELOPE(-58.300,-58.300,-63.750,-63.750)
geographic Mont Blanc
Azimut
geographic_facet Mont Blanc
Azimut
genre Ice
permafrost
genre_facet Ice
permafrost
op_relation info:eu-repo/grantAgreement/ANR//ANR-19-CE01-0018/
doi:10.5281/zenodo.7224691
https://zenodo.org/record/7224692
https://doi.org/10.5281/zenodo.7224692
oai:zenodo.org:7224692
op_rights info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.722469210.5281/zenodo.7224691
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