Data set: Monthly averaged RACMO2.3p2 variables (1979-2022); Antarctica
This is a data set of monthly averaged variables from January 1979 to December 2022 simulated by the hydrostatic regional atmospheric climate model RACMO2.3p2 over Antarctica. At the lateral and ocean boundaries the model is forced by ERA5 reanalysis data every 3 hours from 1979-2022. The model is r...
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ftzenodo:oai:zenodo.org:7845736 2024-09-15T17:47:47+00:00 Data set: Monthly averaged RACMO2.3p2 variables (1979-2022); Antarctica Jan Melchior van Wessem Willem Jan van de Berg Michiel Roland van den Broeke 2023-03-23 https://doi.org/10.5281/zenodo.7845736 unknown Zenodo https://doi.org/10.5281/zenodo.7760490 https://doi.org/10.5281/zenodo.7845736 oai:zenodo.org:7845736 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode RACMO2.3p2 Antarctica Climate model Regional climate model Climate info:eu-repo/semantics/other 2023 ftzenodo https://doi.org/10.5281/zenodo.784573610.5281/zenodo.7760490 2024-07-25T23:24:12Z This is a data set of monthly averaged variables from January 1979 to December 2022 simulated by the hydrostatic regional atmospheric climate model RACMO2.3p2 over Antarctica. At the lateral and ocean boundaries the model is forced by ERA5 reanalysis data every 3 hours from 1979-2022. The model is run at a horizontal resolution of 27 km and 40 vertical levels for the entire Antarctic ice sheet, which constitutes an update of the simulation forced from 1979-2018 by ERA-Interim reported in van Wessem et al., 2018. Upper air relaxation of wind, humidity and temperature is also active (Van de Berg et al., 2016). This version of the model is specifically applied to the polar regions by interactive coupling to a multilayer snow model that calculates melt, refreezing, percolation and runoff of meltwater (Ettema et al., 2010). In addition, snow albedo is calculated through a prognostic scheme for snow grain size (Kuipers Munneke et al., 2011) while a drifting snow scheme simulates the interaction of the near-surface air with drifting snow (Lenaerts et al., 2010). This dataset is provided on a rotated polar coordinate grid. In such a rotated pole projection the grid is defined over the equator and then rotated to the area of interest. One of the advantages is that the grid distance can be defined in fraction of degrees, which results in near equidistant grid cells as long as the domain is small enough, and provides the most accurate model calculations. However, re-projecting these data on other grids is often troublesome, as after rotation the grid is non-equidistant and most software packages cannot directly handle this. Stef Lhermitte provided a nice solution for reprojecting the RACMO data on his gitlab-page: https://gitlab.tudelft.nl/slhermitte/manuals/blob/master/RACMO_reproject.md. The dataset includes the following surface- and atmospheric variables. Additional variables and higher temporal resolutuon up to 3 hourly are available on request: Surface mass balance (SMB) variables (in kg m -2 mo -1 or mm water ... Other/Unknown Material Antarc* Antarctic Antarctica Ice Sheet Zenodo |
institution |
Open Polar |
collection |
Zenodo |
op_collection_id |
ftzenodo |
language |
unknown |
topic |
RACMO2.3p2 Antarctica Climate model Regional climate model Climate |
spellingShingle |
RACMO2.3p2 Antarctica Climate model Regional climate model Climate Jan Melchior van Wessem Willem Jan van de Berg Michiel Roland van den Broeke Data set: Monthly averaged RACMO2.3p2 variables (1979-2022); Antarctica |
topic_facet |
RACMO2.3p2 Antarctica Climate model Regional climate model Climate |
description |
This is a data set of monthly averaged variables from January 1979 to December 2022 simulated by the hydrostatic regional atmospheric climate model RACMO2.3p2 over Antarctica. At the lateral and ocean boundaries the model is forced by ERA5 reanalysis data every 3 hours from 1979-2022. The model is run at a horizontal resolution of 27 km and 40 vertical levels for the entire Antarctic ice sheet, which constitutes an update of the simulation forced from 1979-2018 by ERA-Interim reported in van Wessem et al., 2018. Upper air relaxation of wind, humidity and temperature is also active (Van de Berg et al., 2016). This version of the model is specifically applied to the polar regions by interactive coupling to a multilayer snow model that calculates melt, refreezing, percolation and runoff of meltwater (Ettema et al., 2010). In addition, snow albedo is calculated through a prognostic scheme for snow grain size (Kuipers Munneke et al., 2011) while a drifting snow scheme simulates the interaction of the near-surface air with drifting snow (Lenaerts et al., 2010). This dataset is provided on a rotated polar coordinate grid. In such a rotated pole projection the grid is defined over the equator and then rotated to the area of interest. One of the advantages is that the grid distance can be defined in fraction of degrees, which results in near equidistant grid cells as long as the domain is small enough, and provides the most accurate model calculations. However, re-projecting these data on other grids is often troublesome, as after rotation the grid is non-equidistant and most software packages cannot directly handle this. Stef Lhermitte provided a nice solution for reprojecting the RACMO data on his gitlab-page: https://gitlab.tudelft.nl/slhermitte/manuals/blob/master/RACMO_reproject.md. The dataset includes the following surface- and atmospheric variables. Additional variables and higher temporal resolutuon up to 3 hourly are available on request: Surface mass balance (SMB) variables (in kg m -2 mo -1 or mm water ... |
format |
Other/Unknown Material |
author |
Jan Melchior van Wessem Willem Jan van de Berg Michiel Roland van den Broeke |
author_facet |
Jan Melchior van Wessem Willem Jan van de Berg Michiel Roland van den Broeke |
author_sort |
Jan Melchior van Wessem |
title |
Data set: Monthly averaged RACMO2.3p2 variables (1979-2022); Antarctica |
title_short |
Data set: Monthly averaged RACMO2.3p2 variables (1979-2022); Antarctica |
title_full |
Data set: Monthly averaged RACMO2.3p2 variables (1979-2022); Antarctica |
title_fullStr |
Data set: Monthly averaged RACMO2.3p2 variables (1979-2022); Antarctica |
title_full_unstemmed |
Data set: Monthly averaged RACMO2.3p2 variables (1979-2022); Antarctica |
title_sort |
data set: monthly averaged racmo2.3p2 variables (1979-2022); antarctica |
publisher |
Zenodo |
publishDate |
2023 |
url |
https://doi.org/10.5281/zenodo.7845736 |
genre |
Antarc* Antarctic Antarctica Ice Sheet |
genre_facet |
Antarc* Antarctic Antarctica Ice Sheet |
op_relation |
https://doi.org/10.5281/zenodo.7760490 https://doi.org/10.5281/zenodo.7845736 oai:zenodo.org:7845736 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.784573610.5281/zenodo.7760490 |
_version_ |
1810497349984714752 |