This package contains software used by Schneider et al. to analyze ice sheet climate. Within its core utilities are Python codes that use external libraries (e.g., numpy, netCDF4, cartopy, pyproj, GDAL) to draw elevation contours onto a Lambert azimuthal equal-area map projection using Greenland and Antarctic ice sheet digital elevation model data from Howat et al. (2014) and Bamber et al. (2009), respectively. Also included are analysis scripts to inter-compare reanalysis precipitation over Greenland and Antarctica to net accumulation rates compiled in the the Surface Mass Balance and Snow on Sea Ice Working Group (SUMup) dataset (Koenig & Montgomery, 2019).
bash$ git clone https://github.com/amschne/lnd_srf_for.git; cd lnd_srf_for
lnd_srf_for/$ conda env create -n [ENVNAME] --file environment.yml # this usually takes a few minutes
lnd_srf_for/$ conda activate [ENVNAME]
lnd_srf_for/$ pip install .
lnd_srf_for/$ pytest tests/
lnd_srf_for/$ python schneida_tools/verify_precip_era5.py
lnd_srf_for/$ python schneida_tools/analysis_era5.py
lnd_srf_for/$ python schneida_tools/taylor.py
These scripts write the figure files "p_cruncep_wfde5_sumup_gris_ais_precip.png," sumup_accum_locs.png" and "taylor_e5_we_g3_cn_m2_sumup.pdf" to the "results" directory and "pyplot_figure.png."
All input data needed to run the analyses have been processed and made available within this repository. However, raw data should be obtained from the original sources. If using these data as part of new analyses using this repository, please attribute proper credit to the original authors by citing the references as indicated below.
Regional climate model data used for estimating the net surface vapor fluxes are available at ftp://ftp.climato.be/fettweis/MARv3.5/Greenland/ (Fettweis et al., 2017), for Greenland, and at https://doi.org/10.5281/zenodo.4459259 (Kittel et al., 2021), for Antarctica. ERA5 and WFDE5 data are available at the Climate Data Store via the Copernicus program (DOI:10.24381/cds.f17050d7; DOI:10.24381/cds.20d54e34) (Hersbach et al., 2020; Cucchi et al., 2020). CRUNCEP data are available via the National Center for Atmospheric Research Research Data Archive (DOI: 10.5065/PZ8FF017) under the Creative Commons Attribution 4.0 International License (Viovy, 2018). The GSWP3 dataset (DOI: 10.20783/DIAS.501) is available from the Data Integration and Analysis System Program via the Japan Ministry of Education, Culture, Sports, Science and Technology (Kim, 2017). MERRA-2 monthly precipitation data are available via the U.S. National Aeronautics and Space Administration Global Modeling and Assimilation Office (DOI: 10.5067/0JRLVL8YV2Y4) (Global Modeling And Assimilation Office, 2015).
Please also note that this repository contains data published by Bamber et al. (2009), Howat et al. (2014), and Koenig & Montgomery (2019), the latter which includes numerous datasets from ice core measurement therein. Please refer to Koenig & Montgomery (2019) or Schneider et al. (2023) for more details.
Bamber, J., Gomez-Dans, J. & Griggs, J. (2009). Antarctic 1 km Digital Elevation Model (DEM) from Combined ERS-1 Radar and ICESat Laser Satellite Altimetry, Version 1. NASA National Snow and Ice Data Center DAAC. Retrieved 2020-11-17, from http://nsidc.org/data/NSIDC-0422/versions/1 (type: dataset) doi: 10.5067/H0FQ1KL9NEKM
Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S., Mu¨ller Schmied, H., . . . Buontempo, C. (2020). WFDE5: bias-adjusted ERA5 reanalysis data for impact studies. Earth System Science Data, 12(3), 2097–2120. Retrieved from https://essd.copernicus.org/articles/12/2097/2020/ doi:10.5194/essd-12-2097-2020
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., . . . Gall´ee, H. (2017, April). Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model. The Cryosphere, 11(2), 1015–1033. Retrieved 2020-05-01, from https://www.the-cryosphere.net/11/1015/2017/ doi: 10.5194/tc-11-1015-2017
Global Modeling And Assimilation Office. (2015). MERRA-2 tavgM 2d flx nx:2d,Monthly mean,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics V5.12.4. NASA Goddard Earth Sciences Data and Information Services Center. Retrieved 2023-03-30, from https://disc.gsfc.nasa.gov/datacollection/M2TMNXFLX 5.12.4.html (Type: dataset) doi: 10.5067/0JRLVL8YV2Y4
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Hor´anyi, A., Mun˜oz-Sabater, J., . . . Th´epaut, J.-N. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146 (730), 1999–2049. Retrieved from https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/qj.3803 (eprint: https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.3803) doi: https://doi.org/10.1002/qj.3803
Howat, I. M., Negrete, Al., & Smith, B. E. (2014, August). The Greenland Ice Mapping Project (GIMP) land classification and surface elevation data sets. The Cryosphere, 8(4), 1509-1518. Retrieved 2020-09-23, from https://tc.copernicus.org/articles/8/1509/2014/ doi: 105194/tc-8-1509-2014
Kim, H. (2017). Global Soil Wetness Project Phase 3 Atmospheric Boundary Conditions (Experiment 1). Retrieved from https://doi.org/10.20783/DIAS.501 (Type: dataset) doi: 10.20783/DIAS.501
Kittel, C., Amory, C., Agosta, C., Jourdain, N. C., Hofer, S., Delhasse, A., . . . Fettweis, X. (2021). Diverging future surface mass balance between the Antarctic ice shelves and grounded ice sheet. The Cryosphere, 15(3), 1215–1236. Retrieved from https://tc.copernicus.org/articles/15/1215/2021/ doi: 10.5194/tc-15-1215-2021
Lora Koenig, & Lynn Montgomery. (2019). Surface Mass Balance and Snow Depth on Sea Ice Working Group (SUMup) accumulation on land ice subdataset, Greenland and Antarctica, 1987-2018. Arctic Data Center. urn:uuid:ab62eb85-0417-48e6-89d2-9fee20d1d1a0.
Viovy, N. (2018). _CRUNCEP Version 7 - Atmospheric Forcing Data for the Community Land Model. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. Retrieved from http://rda.ucar.edu/datasets/ds314.3/