GEM and Compute Canada ressources
Compute Canada resources
GEM/CRCM
When using model results from GEM or CRCM4/5/6, cite the following two papers:
- Girard, C. et al. (2014). Staggered Vertical Discretization of the Canadian Environmental Multiscale (GEM) Model Using a Coordinate of the Log-Hydrostatic-Pressure Type. Mon. Wea. Rev., 142, 1183–1196, https://doi.org/10.1175/MWR-D-13-00255.1
- McTaggart‐Cowan, R. et al. (2019). Modernization of Atmospheric Physics Parameterization in Canadian NWP. JAMES, Vol. 11, Issue 11, p. 3593-3635. https://doi.org/10.1029/2019MS001781
Datasets
CaSPAr (products downloaded trough as CaPA-fine)
- Mai, J., Kornelsen, K., Tolson, B., Fortin, V., Gasset, N., & Bouhemhem, D. et al. (2020). The Canadian Surface Prediction Archive (CaSPAr): A Platform to Enhance Environmental Modeling in Canada and Globally. Bulletin Of The American Meteorological Society. doi: 10.1175/bams-d-19-0143.1
CMIP5 (CanESM, MPI-ESM)
- When using data from CMIP5 simulations "you are obligated to acknowledge CMIP5 and the participating modeling groups". Check under the following link for citation: http://cmip5.whoi.edu/?page_id=339
CRU
- Acknowledgement should usually be made by citing one or more of the papers referenced on the appropriate page. Suggestions can be found here: http://www.cru.uea.ac.uk/data
Daymet
- Thornton, P., Running, S., & White, M. (1997). Generating surfaces of daily meteorological variables over large regions of complex terrain. Journal Of Hydrology, 190(3-4), 214-251. https://doi.org/10.1016/S0022-1694(96)03128-9
- Thornton, P.E., M.M. Thornton, B.W. Mayer, Y. Wei, R. Devarakonda, R.S. Vose, and R.B. Cook. 2016. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 3. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1328
- Thornton, P.E., R. Shrestha, M.M. Thornton, S.C. Kao, Y. Wei, and B.E. Wilson. 2020. Gridded daily weather data for North America with comprehensive uncertainty quantification – Daymet version 4. https://daymet.ornl.gov/files/Thornton_Daymet_V4_submitted_2021-01-20.pdf
ERA5
- Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service Climate Data Store (CDS), date of access. https://cds.climate.copernicus.eu/cdsapp#!/home
- Hersbach, H, Bell, W, Berrisford, P, Horányi, A, J., M-S, Nicolas, J, Radu, R, Schepers, D, Simmons, A, Soci, C, Dee, D. (2019) Global reanalysis: goodbye ERA-Interim, hello ERA5; Newsletter Feature Article. ECMWF Newsletter, https://www.ecmwf.int/node/19027, 10.21957/vf291hehd7.
ERA5-Land
Globsnow
MSWEP
- Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M., Weedon, G. P., … Wood, E. F. (2017). Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling. Hydrology and Earth System Sciences, 21(12), 6201–6217. https://doi.org/10.5194/hess-21-6201-2017
- Beck, H., Wood, E., Pan, M., Fisher, C., Miralles, D., & van Dijk, A. et al. (2019). MSWEP V2 Global 3-Hourly 0.1° Precipitation: Methodology and Quantitative Assessment. Bulletin Of The American Meteorological Society, 100(3), 473-500. doi: 10.1175/bams-d-17-0138.1
SNODAS
- Barrett, A. (2003). National Operational Hydrologic Remote Sensing Center Snow Data Assimilation System (SNODAS) Products at NSIDC. NSIDC Special Report 11. Boulder: National Snow and Ice Data Center, p.19 pp.
- National Operational Hydrologic Remote Sensing Center (NOHRSC). 2004. Snow Data Assimilation System (SNODAS) Data Products at NSIDC, Version 1. Unmasked data. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. 2020. https://doi.org/10.7265/N5TB14TC
TRMM