CaSPAr (products downloaded trough)

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

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

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

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.

Copernicus Climate Change Service (C3S) (2019): ERA5-Land reanalysis. Copernicus Climate Change Service Climate Data Store (CDS), 2019-2020. https://cds.climate.copernicus.eu/cdsapp#!/home

Muñoz Sabater, J. (2019). First ERA5-Land dataset to be released this spring. ECMWF Newsletter, 159, 8-9. https://www.ecmwf.int/node/19001

Luojus, Kari; Pulliainen, Jouni; Takala, Matias; Lemmetyinen, Juha; Moisander, Mikko (2020): GlobSnow v3.0 snow water equivalent (SWE). PANGAEA, https://doi.org/10.1594/PANGAEA.911944

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

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