Data set: Monthly averaged RACMO2.3p2 variables (1979-2022); Antarctica
- 1. Institute for Marine and Atmospheric research Utrecht (IMAU), Utrecht University
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 equivalent mo-1)
smb : (Specific) Surface mass balance defined as SMB = Total precipitation + sublimation - runoff
snowmelt : Surface snowmelt production
refreeze : Refreezing of meltwater
snowfall : Solid precipitation
precip : Total precipitation (snowfall + rainfall); to calculate rainfall use rainfall = precip - snowfall
runoff : Surface meltwater runoff
subl : Snow sublimation (including sublimation of drifting snow). Negative values are sublimation, positive values are snow deposition.
erds : erosion of drifting snow
Atmospheric variables
t2m : 2-m Temperature
q2m : 2-m Specific humidity
rh2m : 2-m Relative humidity (RH)
tskin : Surface/skin temperature. Calculated from closing the surface energy budget.
psurf : Surface pressure
u10m : Zonal wind speed at 10 m
v10m : Meridional wind speed at 10 m
ff10m : Wind speed at 10 m
u0500 : Zonal wind speed at 500 hPa
v0500 : Meridional wind speed at 500 hPa
z0500 : Geopotential height at 500 hPa
Surface Energy Budget (SEB) variables (in J m-2); SEB = LWnet+SWnet+SHF+LHF+GHF
Values are monthly cumulative: to convert to W m-2 divide by amount of seconds in a month: 'nrdaysmonth'*24*3600.
lwsn : Net longwave radiation (LWnet=LWdown-LWup)
swsn : Net shortwave radiation (SWnet=SWdown-SWup)
lwsd : Downwelling longwave radiation at the surface
swsd : Downwelling shortwave radiation at the surface
swsu : Upwelling shortwave radiation at the surface
senf : Upward Sensible Heat Flux (SHF) at the surface
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)
gbot : Soil/Ground Heat Flux (GHF)
Snow variables
totpore : Vertically integrated pore space (m)
totwat : Total liquid water content of the snowpack (kg m-2)
zsnow : Total snowpack thickness (m)
Grid, elevation, coordinates and masks in Height_latlon_ANT27.nc (240 by 262 grid boxes)
mask2d : Full ice mask fraction (grounded ice + floating ice shelves) [0..1]
maskgrounded2d : Grounded ice sheet mask fraction [0..1]
height : Surface elevation (m)
slope : Surface slope (m m-1)
aspect : Direction of surface slope (degrees)
lat : Latitude (polar)
lon : Longitude (polar)
Ice shelf and ice sheet drainage basins mask in TotIS_RACMO_ANT27_IMBIE2.nc
This file contains masks on the RACMO grid for the drainage basins as defined in http://imbie.org/imbie-3/drainage-basins/ (Rignot et al., 2013, IMBIE2, IMBIE3), including masks seperately for the ice shelves they drain into, numbered counterclockwise from 0 to 18.
mask2dF : Full ice mask including ice shelves
IceShelves : Ice shelf masks
GroundedIce : Grounded ice sheet drainage basins
Files
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Additional details
References
- Van Wessem, J. M., van de Berg, W. J., Noël, B. P. Y., van Meijgaard, E., Birnbaum, G., Jakobs, C. L., et al. (2018). Modelling the climate and surface mass balance of polar ice sheets using RACMO2, part 2: Antarctica (1979–2016). The Cryosphere, 2018, 1–35. doi:10.5194/tc-2017-202. issn:1994-0440.
- Van de Berg, W. J., and Medley, B. (2016). Brief Communication: Upper-air relaxation in RACMO2 significantly improves modelled interannual surface mass balance variability in Antarctica. The Cryosphere, 10(1), 459–463. doi:10.5194/tc-10-459-2016. issn:1994-0424.
- Ettema, J., Van den Broeke, M. R., Van Meijgaard, E., Van de Berg, W. J., Box, J. E., and Steffen, K. (2010). Climate of the Greenland ice sheet using a high-resolution climate model – Part 1: Evaluation. The Cryosphere, 4(4), 529–544. doi:10.5194/tc-4-511-2010. issn:1994-0424.
- Van de Berg, W. J., and Medley, B. (2016). Brief Communication: Upper-air relaxation in RACMO2 significantly improves modelled interannual surface mass balance variability in Antarctica. The Cryosphere, 10(1), 459–463. doi:10.5194/tc-10-459-2016. issn:1994-0424.
- Lenaerts, J. T. M., van den Broeke, M. R., Déry, S. J., König-Langlo, G., Ettema, J., Munneke, P. K., and Kuipers Munneke, P. (2010). Modelling snowdrift sublimation on an Antarctic ice shelf. The Cryosphere, 4(2), 179–190. doi:10.5194/tc-4-179-2010. issn:1994-0424.
- Rignot, E., Jacobs, S., Mouginot, J., and Scheuchl, B. (2013). Ice-Shelf Melting Around Antarctica. Science, 341(6143), 266–270. doi:10.1126/science.1235798. issn:0036-8075.