ESA CCI Snow¶

ESA Snow Climate Change Initiative (Snow_cci) — Snow Water Equivalent (SWE) and Snow Cover Fraction (SCF) climate data records (including the predecessor ESA GlobSnow)

Available

At a glance¶

Note on period: Periods differ by product. SWE v4.0 covers 1979-01-02 to 2023-12-31 (CEDA record; the PUG gives a 6 January 1979 start), every second day until May 1987 and daily from October 1987, with values only in the Northern Hemisphere winter season (roughly November–May). Snow cover fraction: AVHRR v4.0 1979-01-01 to 2023-12-31 (gaps concentrated in 1979–1986, about 99% coverage overall), MODIS v4.0 2000-02-24 to 2023-12-31, ATSR-2 v1.0 1995-08-01 to 2003-06-22. Sentinel-3 SLSTR v1.0 (2020–2022) is listed on the ESA project page, but its CEDA records were still unpublished (preview only) when checked on 2026-10-13. The predecessor GlobSnow SWE v3.0 covers 1979–2018.

Overview¶

A set of research climate data records produced by the snow project (Snow_cci) of ESA's Climate Change Initiative. Snow water equivalent (SWE) is a daily 0.1° Northern Hemisphere record (1979–2023) that combines SMMR, SSM/I and SSMIS passive microwave observations with snow depth from synoptic weather stations through Bayesian assimilation. Snow cover fraction (SCF) is a global daily record from optical MODIS (1 km, 2000–2023) and AVHRR (5 km, 1979–2023) data, with separate layers for snow visible from above, including on the forest canopy (SCFV), and snow on the ground beneath it (SCFG). Both build on the methods of ESA GlobSnow (SWE v3.0, Snow Extent v2.0) and carry per-pixel uncertainty estimates.

What changes with the successor¶

ESA GlobSnow SWE v3.0 → ESA CCI Snow SWE v4.0¶

The Northern Hemisphere snow water equivalent (SWE) record that FMI built in the ESA GlobSnow project continued in ESA CCI Snow. It keeps the GlobSnow approach — Bayesian assimilation of passive microwave radiometer data and ground-based snow depth observations — but the grid, period and algorithm details have changed, so do not splice the two into one time series.

Sources: CEDA — Snow_cci SWE v4.0 (1979–2023) · CEDA — Snow_cci SWE v3.1 (1979–2022) · Luojus et al. (2021) GlobSnow v3.0, Scientific Data · Snow_cci Product User Guide v5.1 (2025-12)

ESA GlobSnow Snow Extent v2.0 → ESA CCI Snow snow cover fraction (SCFG, SCFV)¶

Transition: 2021-05

Building on the method behind GlobSnow's optical Snow Extent (SE; ATSR-2 and AATSR, 1995–2012; Metsämäki et al. 2015), CCI Snow produced global daily snow cover fraction from MODIS (2000 onward), AVHRR (1979 onward) and ATSR-2 (first release v1.0 on 2021-05-10). With v4.0 in 2025, both the MODIS and AVHRR records run to December 2023.

Sources: CEDA — MODIS SCFG v4.0 (list of improvements) · CEDA — MODIS SCFG v1.0 (2000–2019, superseded) · Metsämäki et al. (2015) GlobSnow Snow Extent, Remote Sensing of Environment · GlobSnow website (SE v2.0, SWE v2.0/v3.0)

Available variables¶

Names checked against the CEDA catalogue records and the CCI THREDDS (OPeNDAP) variable listings. The PUG text writes the SWE variables in capitals (SWE, SWE_STD) and in one place calls the uncertainty SWE_VAR, but the actual v4.0 files use lower-case swe and swe_std. Snow cover values outside 0–100 are status codes, so always filter them out before computing.

instantaneous mean accumulated maximum minimum static — instantaneous: value at the time stamp · mean/accumulated/maximum/minimum: over the indicated interval · static: does not change with time

Snow water equivalent (SWE v4.0, Northern Hemisphere 0.1°)¶

Snow cover fraction (SCFG, SCFV — MODIS and AVHRR v4.0, ATSR-2 v1.0)¶

The full variable list is in the official documentation.

How to get the data¶

• CEDA — ESA CCI Snow data (HTTP, FTP, OPeNDAP) — HTTP download / anonymous FTP / OPeNDAP — no account needed
  • Paths under https://data.ceda.ac.uk/neodc/esacci/snow/data/ are split into swe/MERGED/v4.0/ (about 9,580 files, 14 GB), scfg/MODIS/v4.0/, scfv/MODIS/v4.0/ (about 8,640 files, 816 GB), scfv/AVHRR_SINGLE/v4.0/ (about 37,000 files, 533 GB) and so on, with year/month folders below. Anonymous FTP is at ftp://anon-ftp.ceda.ac.uk/neodc/esacci/snow/data/.
• CEDA — MODIS SCFG v4.0 / SCFV v4.0 records — HTTP / FTP / OPeNDAP
  • The SCFV v4.0 record is https://catalogue.ceda.ac.uk/uuid/bc13bb02a958449aac139853c4638f32/ ; AVHRR SCFG and SCFV v4.0 are uuid 80d96e3a14854420b6f742d70877c431 and 3c71c04cf08a410fac2c680cbf88cfd7.
• CCI THREDDS aggregated OPeNDAP (whole period at one address) — OPeNDAP — read only the region and period you need
  • The whole SWE v4.0 period is aggregated at https://data.cci.ceda.ac.uk/thredds/dodsC/esacci.SNOW.day.L3C.SWE.multi-sensor.multi-platform.MERGED.4-0.r1 , and MODIS SCFG v4.0 at esacci.SNOW.day.L3C.SCFG.MODIS.Terra.MODIS_TERRA.4-0.r1. A single MODIS day is 36000 × 18000, so always subset by region.
• ESA CCI Open Data Portal — Web search and download (links to the CEDA data)
• GlobSnow v3.0 (predecessor SWE record) — HTTP download (daily at https://www.globsnow.info/swe/archive_v3.0/ ) / PANGAEA (monthly, doi:10.1594/PANGAEA.911944)
  • The GlobSnow-2 project has ended and its products remain archived on the website. When checked on 2026-10-13, the globsnow.info data folder did not respond.

Example code¶

Opens the aggregated SWE v4.0 address on the CCI THREDDS server via OPeNDAP and reads only the West Siberian Plain (60–80°E, 55–65°N) for winter 2020 (no account needed). Because of the mountain mask, mountainous areas have almost no values, so a lowland region is used. Negative mask codes are set to missing before computing, and the latitude order is checked because it may be descending.

import xarray as xr

url = ("https://data.cci.ceda.ac.uk/thredds/dodsC/"
       "esacci.SNOW.day.L3C.SWE.multi-sensor.multi-platform.MERGED.4-0.r1")
ds = xr.open_dataset(url)

lat_slice = slice(65, 55) if ds.lat[0] > ds.lat[-1] else slice(55, 65)
swe = ds["swe"].sel(time=slice("2020-01-01", "2020-03-31"),
                    lat=lat_slice, lon=slice(60, 80))
swe = swe.where(swe >= 0)          # -1 no retrieval, -10 water, -20 mountain, -30 glacier -> NaN
print(swe.mean(["lat", "lon"]).values)   # mm, daily area mean

# In MODIS snow cover daily files only 0-100 are valid values.
# scf = xr.open_dataset("20200115-ESACCI-L3C_SNOW-SCFG-MODIS_TERRA-fv4.0.nc")["scfg"]
# scf = scf.where(scf <= 100)      # drops 205 cloud, 210 water, 215 permanent snow, etc.

Practical tips¶

• Values such as 205 (cloud), 206 (polar night), 210 (water), 215 (permanent snow and ice) and 254 (no acquisition) in snow cover files are status codes, not percentages. Keep only 0–100, or averages will be grossly inflated.
• Negative SWE values (-1, -10, -20, -30) are mask codes. In particular, -20 (mountain) removes every grid cell with large sub-grid elevation variability, so mountainous regions (including the Korean Peninsula) can be largely missing. Do not use this record for mountain snow.
• SWE is reliable only for dry snow up to about 1 m depth. It can underestimate during spring melt (wet snow) and for very deep snow.
• SWE is available only every second day in 1979–1987 and daily from October 1987. Daily statistics spanning this boundary have different sample counts.
• SCFV (viewable snow) and SCFG (snow on ground) differ only in forests. Use SCFG to compare with ground snow cover in models, and SCFV for satellite reflectance or albedo studies.
• Some MODIS v4.0 files were replaced or removed on 2025-12-12 and 2026-02-12. If you downloaded MODIS files before December 2025, download the affected dates again (see notices).
• The AVHRR record joins many NOAA and MetOp satellites with different overpass times. CEDA files are split by satellite, so the same day can have several files.
• GlobSnow v3.0, CCI v3.1 and CCI v4.0 all use 'the same method' but give different values. State the exact version and DOI in your paper.

Notices and change history¶

References for your paper¶

Dataset citation¶

Snow_cci SWE v4.0 (CEDA) — DOI 10.5285/edf8abd23f4a40aabd4d52e48dec06ea

@misc{luojus2025snowcci_swe_v4,
  author    = {Luojus, Kari and Ven{\"a}l{\"a}inen, Pinja and Moisander, Mikko and Pulliainen, Jouni and Takala, Matias and Lemmetyinen, Juha and Mortimer, Colleen and Mudryk, Lawrence and Schwaizer, Gabriele and Nagler, Thomas},
  title     = {{ESA} Snow Climate Change Initiative ({Snow\_cci}): Snow Water Equivalent ({SWE}) level 3C daily global climate research data package ({CRDP}) (1979 - 2023), version 4.0},
  publisher = {NERC EDS Centre for Environmental Data Analysis},
  year      = {2025},
  doi       = {10.5285/edf8abd23f4a40aabd4d52e48dec06ea}
}

Snow_cci MODIS SCFG v4.0 (CEDA) — DOI 10.5285/375ffdb8f0a445e380b4b9548655f5f9

@misc{schwaizer2025snowcci_scfg_modis_v4,
  author    = {Schwaizer, Gabriele and Nagler, Thomas and Hetzenecker, Markus and Heinrich, Maria and M{\"o}lg, Nico and Nemec, Johanna and Haslinger, Beat and Fasching, Ursula and Scolamiero, Andrea and Malcher, Petra and Mets{\"a}m{\"a}ki, Sari},
  title     = {{ESA} Snow Climate Change Initiative ({Snow\_cci}): Daily global Snow Cover Fraction - snow on ground ({SCFG}) from {MODIS} (2000-2023), version 4.0},
  publisher = {NERC EDS Centre for Environmental Data Analysis},
  year      = {2025},
  doi       = {10.5285/375ffdb8f0a445e380b4b9548655f5f9}
}

Snow_cci MODIS SCFV v4.0 (CEDA) — DOI 10.5285/bc13bb02a958449aac139853c4638f32

@misc{schwaizer2025snowcci_scfv_modis_v4,
  author    = {Schwaizer, Gabriele and Nagler, Thomas and Hetzenecker, Markus and Heinrich, Maria and M{\"o}lg, Nico and Nemec, Johanna and Haslinger, Beat and Fasching, Ursula and Scolamiero, Andrea and Malcher, Petra and Mets{\"a}m{\"a}ki, Sari},
  title     = {{ESA} Snow Climate Change Initiative ({Snow\_cci}): Daily global Snow Cover Fraction - viewable snow ({SCFV}) from {MODIS} (2000 - 2023), version 4.0},
  publisher = {NERC EDS Centre for Environmental Data Analysis},
  year      = {2025},
  doi       = {10.5285/bc13bb02a958449aac139853c4638f32}
}

Snow_cci AVHRR SCFG v4.0 (CEDA) — DOI 10.5285/80d96e3a14854420b6f742d70877c431

@misc{xiao2025snowcci_scfg_avhrr_v4,
  author    = {Xiao, X. and Naegeli, Kathrin and Neuhaus, Christoph and Salberg, Arnt-B{\o}rre and Schwaizer, Gabriele and Wiesmann, Andreas and Wunderle, Stefan and Nagler, Thomas},
  title     = {{ESA} Snow Climate Change Initiative ({Snow\_cci}): Daily global Snow Cover Fraction - snow on ground ({SCFG}) from {AVHRR} (1979 - 2023), version 4.0},
  publisher = {NERC EDS Centre for Environmental Data Analysis},
  year      = {2025},
  doi       = {10.5285/80d96e3a14854420b6f742d70877c431}
}

Snow_cci AVHRR SCFV v4.0 (CEDA) — DOI 10.5285/3c71c04cf08a410fac2c680cbf88cfd7

@misc{xiao2025snowcci_scfv_avhrr_v4,
  author    = {Xiao, X. and Naegeli, Kathrin and Neuhaus, Christoph and Salberg, Arnt-B{\o}rre and Schwaizer, Gabriele and Wiesmann, Andreas and Wunderle, Stefan and Nagler, Thomas},
  title     = {{ESA} Snow Climate Change Initiative ({Snow\_cci}): Daily global Snow Cover Fraction - viewable ({SCFV}) from {AVHRR} (1979 - 2023), version 4.0},
  publisher = {NERC EDS Centre for Environmental Data Analysis},
  year      = {2025},
  doi       = {10.5285/3c71c04cf08a410fac2c680cbf88cfd7}
}

GlobSnow v3.0 SWE monthly data (PANGAEA) — DOI 10.1594/PANGAEA.911944

@misc{luojus2020globsnow_v3,
  author    = {Luojus, Kari and Pulliainen, Jouni and Takala, Matias and Lemmetyinen, Juha and Moisander, Mikko},
  title     = {{GlobSnow} v3.0 snow water equivalent ({SWE})},
  publisher = {PANGAEA},
  year      = {2020},
  doi       = {10.1594/PANGAEA.911944}
}

Reference papers¶

GlobSnow v3.0 SWE data paper — DOI 10.1038/s41597-021-00939-2

@article{luojus2021globsnow,
  author  = {Luojus, Kari and Pulliainen, Jouni and Takala, Matias and Lemmetyinen, Juha and Mortimer, Colleen and Derksen, Chris and Mudryk, Lawrence and Moisander, Mikko and Hiltunen, Mwaba and Smolander, Tuomo and Ikonen, Jaakko and Cohen, Juval and Salminen, Miia and Norberg, Johannes and Veijola, Katriina and Ven{\"a}l{\"a}inen, Pinja},
  title   = {{GlobSnow} v3.0 {Northern Hemisphere} snow water equivalent dataset},
  journal = {Scientific Data},
  volume  = {8},
  pages   = {163},
  year    = {2021},
  doi     = {10.1038/s41597-021-00939-2}
}

SWE retrieval algorithm (GlobSnow assimilation approach) — DOI 10.1016/j.rse.2011.08.014

@article{takala2011swe,
  author  = {Takala, Matias and Luojus, Kari and Pulliainen, Jouni and Derksen, Chris and Lemmetyinen, Juha and K{\"a}rn{\"a}, Juha-Petri and Koskinen, Jarkko and Bojkov, Bojan},
  title   = {Estimating northern hemisphere snow water equivalent for climate research through assimilation of space-borne radiometer data and ground-based measurements},
  journal = {Remote Sensing of Environment},
  volume  = {115},
  number  = {12},
  pages   = {3517--3529},
  year    = {2011},
  doi     = {10.1016/j.rse.2011.08.014}
}

Dynamic snow density (approach used from CCI SWE v3.1) — DOI 10.5194/tc-15-2969-2021

@article{venalainen2021density,
  author  = {Ven{\"a}l{\"a}inen, Pinja and Luojus, Kari and Lemmetyinen, Juha and Pulliainen, Jouni and Moisander, Mikko and Takala, Matias},
  title   = {Impact of dynamic snow density on {GlobSnow} snow water equivalent retrieval accuracy},
  journal = {The Cryosphere},
  volume  = {15},
  number  = {6},
  pages   = {2969--2981},
  year    = {2021},
  doi     = {10.5194/tc-15-2969-2021}
}

Basis of the snow cover fraction method (GlobSnow Snow Extent) — DOI 10.1016/j.rse.2014.09.018

@article{metsamaki2015globsnow,
  author  = {Mets{\"a}m{\"a}ki, Sari and Pulliainen, Jouni and Salminen, Miia and Luojus, Kari and Wiesmann, Andreas and Solberg, Rune and B{\"o}ttcher, Kristin and Hiltunen, Mwaba and Ripper, Elisabeth},
  title   = {Introduction to {GlobSnow} Snow Extent products with considerations for accuracy assessment},
  journal = {Remote Sensing of Environment},
  volume  = {156},
  pages   = {96--108},
  year    = {2015},
  doi     = {10.1016/j.rse.2014.09.018}
}

Acknowledgements¶

Under the CEDA terms of use, publications must acknowledge "the ESA Climate Change Initiative and the Snow CCI project" together with the individual data providers, and cite the dataset DOI of each product used (SWE, MODIS or AVHRR SCFG/SCFV). If you used an earlier version (e.g. SWE v3.1, doi:10.5285/9d9bfc488ec54b1297eca2c9662f9c81), cite that version's DOI.

Information on the datasets used in this study was compiled with the help of the Korean Climate Data Navigator (KCDN) (Sim, 2026; https://doi.org/10.5281/zenodo.23300923).

Links¶

• ESA CCI Snow project page (products and data links)
• Snow_cci Product User Guide v5.1 (2025-12)
• Snow_cci Climate Research Data Package v5.1 (2025-12)
• Snow_cci Product Validation and Intercomparison Report v4.0 (2024-05)
• Gap-filled daily AVHRR snow cover fraction composite 1979–2023 (Zenodo, AVHRR10C1.V4)
• AVHRR snow cover fraction method paper (Remote Sensing of Environment 334, 115235, 2026)
• GlobSnow website
• CEDA terms of use — ESA CCI Snow Terms and Conditions