Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
5
datasets available to search
ShareScore release 0.9.0
Dataset results
5 results for “RACMO2.3p2”
Data set: Monthly averaged RACMO2.3p2 variables (1979-2022); Antarctica
<p>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).<br> <br> 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). </p> <p>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.</p> <p>The dataset includes the following surface- and atmospheric variables. Additional variables and higher temporal resolutuon up to 3 hourly are available on request:</p> <p><strong>Surface mass balance (SMB) variables (in kg m<sup>-2 </sup>mo<sup>-1</sup> or mm water equivalent mo<sup>-1</sup>)</strong><br> smb : (Specific) Surface mass balance defined as SMB = Total precipitation + sublimation - runoff<br> snowmelt : Surface snowmelt production<br> refreeze : Refreezing of meltwater<br> snowfall : Solid precipitation<br> precip : Total precipitation (snowfall + rainfall); to calculate rainfall use rainfall = precip - snowfall<br> runoff : Surface meltwater runoff<br> subl : Snow sublimation (including sublimation of drifting snow). Negative values are sublimation, positive values are snow deposition.<br> erds : erosion of drifting snow</p> <p><strong>Atmospheric variables </strong><br> t2m : 2-m Temperature<br> q2m : 2-m Specific humidity<br> rh2m : 2-m Relative humidity (RH)<br> tskin : Surface/skin temperature. Calculated from closing the surface energy budget.<br> psurf : Surface pressure<br> u10m : Zonal wind speed at 10 m<br> v10m : Meridional wind speed at 10 m<br> ff10m : Wind speed at 10 m<br> u0500 : Zonal wind speed at 500 hPa<br> v0500 : Meridional wind speed at 500 hPa<br> z0500 : Geopotential height at 500 hPa</p> <p><strong>Surface Energy Budget (SEB) variables (in J m<sup>-2</sup>); SEB = LWnet+SWnet+SHF+LHF+GHF</strong><br> Values are monthly cumulative: to convert to W m<sup>-2</sup> divide by amount of seconds in a month: 'nrdaysmonth'*24*3600.<br> lwsn : Net longwave radiation (LWnet=LWdown-LWup)<br> swsn : Net shortwave radiation (SWnet=SWdown-SWup)<br> lwsd : Downwelling longwave radiation at the surface<br> swsd : Downwelling shortwave radiation at the surface<br> swsu : Upwelling shortwave radiation at the surface<br> senf : Upward Sensible Heat Flux (SHF) at the surface<br> latf : Upward Latent Heat Flux (LHF) at the surface (our simulated LHF doesn't explicitly close the SEB, as it also includes in-air sublimation, but the effect should be rougly neglible)<br> gbot : Soil/Ground Heat Flux (GHF)</p> <p><strong>Snow variables</strong></p> <p>totpore : Vertically integrated pore space (m)<br> totwat : Total liquid water content of the snowpack (kg m<sup>-2</sup>)<br> zsnow : Total snowpack thickness (m)</p> <p><strong>Grid, elevation, coordinates and masks in <em>Height_latlon_ANT27.nc</em> (240 by 262 grid boxes)</strong></p> <p>mask2d : Full ice mask fraction (grounded ice + floating ice shelves) [0..1]<br> maskgrounded2d : Grounded ice sheet mask fraction [0..1]<br> height : Surface elevation (m)<br> slope : Surface slope (m m<sup>-1</sup>)<br> aspect : Direction of surface slope (degrees)<br> lat : Latitude (polar)<br> lon : Longitude (polar)</p> <p><strong>Ice shelf and ice sheet drainage basins mask in <em>TotIS_RACMO_ANT27_IMBIE2.nc</em></strong></p> <p>This file contains masks on the RACMO grid for the drainage basins as defined in <a href="http://imbie.org/imbie-3/drainage-basins/">http://imbie.org/imbie-3/drainage-basins/</a> (Rignot et al., 2013, IMBIE2, IMBIE3), including masks seperately for the ice shelves they drain into, numbered counterclockwise from 0 to 18.</p> <p>mask2dF : Full ice mask including ice shelves<br> IceShelves : Ice shelf masks<br> GroundedIce : Grounded ice sheet drainage basins</p>
IMAU-FDM v1.2G and RACMO2.3p2 data on ice slabs, aquifers and their climatic drivers
<p>Model results used in the following paper:</p> <p>Brils, M., Kuipers Munneke, P., Jullien, N., Tedstone, A.J., Machguth, H., van de Berg, W. J., & van den<br> Broeke, M. R. Climatic drivers of ice slabs and firn aquifers in Greenland</p> <p> </p> <p>Contains:</p> <p>- 10-daily ice slab fraction within the upper 20 m of firn</p> <p>- 10-daily total irreducible liquid water content firn</p> <p>- monthly snow accumulation and melt</p>
RACMO2.3p2 South Greenland data set, 2007
<p>This data set contains RACMO2.3p2 output for South Greenland for 2007 on a 20 km grid. Netcdf files are provided every 3 hours. The most relevant variables are declared in RACMO2.3p2_output_variable_declaration.pdf. This data set is used in the manuscript "A module to convert spectral to narrowband snow albedo for use in climate models: SNOWBAL v1.0".</p>
Mean firn and atmospheric characteristics for different periods, regions and NAO conditions, as simulated by IMAU-FDM v1.2G and RACMO2.3p2
<p>This data set contains IMAU-FDM v1.2G and RACMO2.3p2 output for the Greenland ice sheet from November 1957 to 2020. Netcdf files are provided with mean accumulation, skin temperature, 500 hPa geopotential height and temperature, zonal and meridional velocities and skin temperature for the periods 1995 - 2012 and 2013 - 2020 and for different NAO conditions. Basin averages of firn air content, firn thickness, 10-m firn temperatures, and surface height velocity components are provided as well. This data set is used in the manuscript "Spatial response of Greenland’s firn layer to NAO variability".</p>
Data set: Yearly RACMO2.3p2 variables, threshold temperature and Sentinel-2 melt pond volume
<p>Data set of yearly regional atmospheric climate model RACMO2.3p2 data over Antarctica. At the lateral and ocean boundaries the model is forced by ERA5 reanalysis data every 6 hours from 1979-2021. The model is run at 27 km horizontal resolution 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 is also active.<br> To simulate the recent past (1950-2014) and the future (2015-2100) we use RACMO2.3p2 at 27 km resolution to dynamically downscale one historical and three future projections emission scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Detailed CESM2 description and latest updates are provided in Danabasoglu et., al 2020 and an evaluation over Greenland in Van Kampenhout et al., 2020.</p> <p>These data are then used to fit exponential and power-law relations of annual total liquid water production (melt + rain) and snow accumulation (snowfall - sublimation) to calculate MoA sensitivity as a function of annual average 2 m temperature. A comparison with Sentinel-2 melt pond observations can then be performed.</p> <p><strong>Data set includes: </strong></p> <p><strong>RACMO2.3p2-ERA5-3H</strong> - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 1979-2021 in mm w.e per year, and yearly average 2 m temperature in K, forced by 3 hourly ERA5 reanalysis data.</p> <p><strong>RACMO2.3p2-hist_r567</strong> - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 1950-2014 in mm w.e per year, and yearly average 2 m temperature in K, forced by 6 hourly CESM2 historical data.</p> <p><strong>RACMO2.3p2-SSP''126,245,585''_r567</strong> - Yearly average precipitation, snowfall, snowmelt and sublimation for the period 2015-2100 in mm w.e per year, and yearly average 2 m temperature in K, forced by 6 hourly CESM2 future scenario (SSP1-2.6, SSP2-4.5, SSP5-8.5) data.</p> <p><strong>TT_ALL.nc </strong>- Antarctic threshold temperature <span class="math-tex">\(T_T\)</span> for MoA = 0.7 as described in the Methods section.</p> <p><strong>dT_ALL.nc </strong>- Uncertainty in Antarctic threshold temperature <span class="math-tex">\(T_T\)</span> for MoA = 0.7 as described in the Methods section.</p> <p><strong>TT_IS.nc </strong>- Antarctic threshold temperature <span class="math-tex">\(T_T\)</span> for MoA = 0.7 of 56 selected ice shelves as described in the Methods section.</p> <p><strong>dT_IS.nc </strong>- Uncertainty in Antarctic threshold temperature <span class="math-tex">\(T_T\)</span> for MoA = 0.7 of 56 selected ice shelves as described in the Methods section.</p> <p><strong>S2_meltpondvolume_v3.nc</strong> - Sentinel-2 melt pond volume as described in the Methods section.</p> <p><strong>Height_latlon_ANT27.nc </strong>- Grids of latitude, longitude, surface elevation (height), land/ice mask (mask2d), grounded land/ice mask (maskgrounded2d), aspect ratio, and surface slope.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.