Overview
This dataset, generated by the Global Snow Laboratory at Rutgers State University, provides a binary representation of snow-covered area across the Northern Hemisphere at weekly intervals, inferred from a range of remotely sensed imagery. The archive, which was initiated in 1966, offers the longest continuous remotely sensed record of any environmental phenomenon.

Provider contact information
Principal investigator:
Dr. David Robinson
Distinguished Professor, Department of Geography, Rutgers State University
Piscataway, New Jersey, USA

david.robinson@rutgers.edu 848-445-4741
https://climatechange.rutgers.edu/people/affiliates/robinson-david

Licensing
Use agreement provided at
https://www.ncei.noaa.gov/pub/data/sds/cdr/CDRs/Snow_Cover_Extent_Northern_Hemisphere/UseAgreement_01B-12.pdf

Variable name and units
Presence of snow: binary flag, based on 50% threshold on last visible day nearest to end of granule-week

Spatial coverage and resolution
Published as a regular grid (88 x 88) in the Northern Polar Stereographic Projection. Note that this projection implies variation of cell area from ~10.7 × 10² km2 at the lowest latitudes to ~41.8 × 10³ km² near the geographic North Pole.

The dataset is also available having been regridded to EASE grid (720 x 720 grid)
https://nsidc.org/data/nsidc-0046/versions/4/documentation

Temporal coverage and resolution
The archive includes representations of snow-covered area from October 1966 to the present. There are gaps of several weeks during nine months between 1968 and 1971.
Granules are generated at weekly (Tuesday to Monday) intervals.

Information about related datasets
The US National Snow and Ice Data Center (NSIDC) also publish datasets of daily Northern Hemisphere snow cover derived using the same algorithm (the Interactive Multisensor Snow and Ice Mapping System, or IMS) at spatial resolutions of 1 km, 4 km and 24 km. Details are available at
https://nsidc.org/data/G02156/versions/1

Limitations and strengths for application
The principal strength of the dataset is its long period of record and comprehensive spatial coverage.

The dataset’s main limitation is that it provides only a simple binary classification of snow cover: ‘snow-free’ may be 0 – 49%, ‘snow-covered’ may be 50 – 100%. This may exaggerate estimates of trends at certain times of the year, and is compounded by the increase in cell area at higher latitudes (Allchin and Déry, 2018).

In 1999, the workflow used to generate weekly granules was upgraded from a largely manual process to a more automated system, based on higher-resolution imagery. Several authors (eg Hori et al, 2017, Mudryk et al, 2017) have raised the possibility that these new methods may have resulted in an appreciable improvement in the system’s ability to detect snow cover, consequently introducing bias in trend estimations. However, those involved in generating the dataset maintain that this is not the case, based on detailed comparisons of outputs pre- / post-upgrade. It is also possible that apparently anomalous trend magnitudes, detected particularly in autumn and spring, may have been driven by assumptions adopted in inferring snow-covered area from the dataset’s binary classification (Allchin and Déry, 2018).

A number of individual cells (33), mainly covering mountainous areas have also been identified as providing potentially unreliable records (Déry and Brown, 2007).

References
Dataset:
Robinson, D.A., T.W. Estilow, and NOAA CDR Program, 2012: NOAA Climate Data Record (CDR) of Northern Hemisphere (NH) Snow Cover Extent (SCE), Version 1. [indicate subset used]. NOAA National Centers for Environmental Information. doi: 10.7289/V5N014G9

Descriptive references:
Estilow T.W., A.H. Young and D.A. Robinson, 2015: A long-term Northern Hemisphere snow cover extent data record for climate studies and monitoring. Earth System Science Data, 7, 137-142, doi:10.5194/essd-7-137-2015
https://essd.copernicus.org/articles/7/137/2015/essd-7-137-2015.pdf

Robinson, D.A., and A. Frei, 2000: Seasonal variability of northern hemisphere snow extent using visible satellite data. Professional Geographer, 51, 307-314, doi:10.1111/0033-0124.00226.

Robinson, D.A., K. F. Dewey and R. Heim, Jr., 1993: Global snow cover monitoring: an update. Bulletin of the American Meteorological Society, 74, 1689-1696.

NOAA landing page (includes link to algorithm description)
https://www.ncei.noaa.gov/products/climate-data-records/snow-cover-extent

General information from Rutgers University Global Snow Laboratory
http://climate.rutgers.edu/snowcover/index.php

Link to download data (and format)
NOAA CDR landing page (HTTP download available in NetCDF)
https://www.ncei.noaa.gov/products/climate-data-records/snow-cover-extent

Regridded to EASE grid
https://nsidc.org/data/nsidc-0046/versions/4/documentation

Dataset also available in legacy text format on request from Rutgers Global Snow Lab
http://climate.rutgers.edu/snowcover/index.php