Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

Abstract. Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6; https://nsidc.org/data/modis/data_summaries ) and VIIRS Collection 1 (C1; https://doi.org/10.5067/VIIRS/VNP10.001 ) represent the state-of-the-art global snow-cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow-cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map. The increased data content allows flexibility in using the datasets for specific regions and end-user applications. Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375 m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16+ year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms. These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

[1]  Julien Radoux,et al.  Assessment of Automated Snow Cover Detection at High Solar Zenith Angles with PROBA-V , 2016, Remote. Sens..

[2]  S. Jain,et al.  Accuracy assessment and trend analysis of MODIS-derived data on snow-covered areas in the Sutlej basin, Western Himalayas , 2015 .

[3]  Dorothy K. Hall,et al.  Detection of earlier snowmelt in the Wind River Range, Wyoming, using Landsat imagery, 1972–2013 , 2015 .

[4]  Olivier Hagolle,et al.  Assessment of daily MODIS snow cover products to monitor snow cover dynamics over the Moroccan Atlas mountain range , 2015 .

[5]  Christopher J. Crawford,et al.  MODIS Terra Collection 6 fractional snow cover validation in mountainous terrain during spring snowmelt using Landsat TM and ETM+ , 2015 .

[6]  Olivier Hagolle,et al.  A snow cover climatology for the Pyrenees from MODIS snow products , 2014 .

[7]  A. Simmons,et al.  The Concept of Essential Climate Variables in Support of Climate Research, Applications, and Policy , 2014 .

[8]  P. Houser,et al.  Evaluation of the MODIS snow cover fraction product , 2014 .

[9]  M. Punia,et al.  Mapping of Snow Spectral Properties and Regional Climatic Variability in Alaknanda Basin, Uttarakhand, India , 2014 .

[10]  Robert E. Wolfe,et al.  Suomi NPP VIIRS prelaunch and on‐orbit geometric calibration and characterization , 2013 .

[11]  C. Justice,et al.  Land and cryosphere products from Suomi NPP VIIRS: Overview and status , 2013, Journal of geophysical research. Atmospheres : JGR.

[12]  Christopher Conrad,et al.  Snow-cover variability in central Asia between 2000 and 2011 derived from improved MODIS daily snow-cover products , 2013 .

[13]  Quazi K. Hassan,et al.  Reconstruction of Snow Water Equivalent and Snow Depth Using Remote Sensing Data , 2012 .

[14]  Claudia Kuenzer,et al.  European Snow Cover Characteristics between 2000 and 2011 Derived from Improved MODIS Daily Snow Cover Products , 2012, Remote. Sens..

[15]  G. Blöschl,et al.  MODIS-Based Snow Cover Products, Validation, and Hydrologic Applications , 2012 .

[16]  Yun Li,et al.  Comparison of Snow Indexes in Estimating Snow Cover Fraction in a Mountainous Area in Northwestern China , 2012, IEEE Geoscience and Remote Sensing Letters.

[17]  Michael D. Grossberg,et al.  Increasing the Accuracy of MODIS/Aqua Snow Product Using Quantitative Image Restoration Technique , 2012, IEEE Geoscience and Remote Sensing Letters.

[18]  Dorothy K. Hall,et al.  Snow cover, snowmelt timing and stream power in the Wind River Range, Wyoming , 2012 .

[19]  A. Klein,et al.  Fractional snow cover mapping through artificial neural network analysis of MODIS surface reflectance , 2011 .

[20]  Thomas H. Painter,et al.  Assessment of methods for mapping snow cover from MODIS , 2011 .

[21]  Jiahua Zhang,et al.  Spectral reflectance characteristics of different snow and snow-covered land surface objects and mixed spectrum fitting. , 2011 .

[22]  Jiahua Zhang,et al.  Spectra reflectance characteristics of different snow and snow-covered land surface objects and mixed spectrum fitting , 2011, 2011 19th International Conference on Geoinformatics.

[23]  Xiaodong Huang,et al.  Validation of MODIS snow cover products using Landsat and ground measurements during the 2001–2005 snow seasons over northern Xinjiang, China , 2011 .

[24]  Sjur Kolberg,et al.  Interannual stability of grid cell snow depletion curves as estimated from MODIS images , 2010 .

[25]  Hongjie Xie,et al.  Integrated assessment on multi-temporal and multi-sensor combinations for reducing cloud obscuration of MODIS snow cover products of the Pacific Northwest USA , 2010 .

[26]  Hongjie Xie,et al.  Toward advanced daily cloud-free snow cover and snow water equivalent products from Terra-Aqua MODIS and Aqua AMSR-E measurements , 2010 .

[27]  Dorothy K. Hall,et al.  Normalized-Difference Snow Index (NDSI) , 2010 .

[28]  Anil V. Kulkarni,et al.  Hyperspectral analysis of snow reflectance to understand the effects of contamination and grain size , 2010, Annals of Glaciology.

[29]  Charles S. Zender,et al.  MODIS snow albedo bias at high solar zenith angles relative to theory and to in situ observations in Greenland , 2009 .

[30]  Ramesh P. Singh,et al.  Retrieval of sub-pixel snow cover information in the Himalayan region using medium and coarse resolution remote sensing data , 2009 .

[31]  Peter L. Jackson,et al.  Interrelationships between MODIS/Terra remotely sensed snow cover and the hydrometeorology of the Quesnel River Basin, British Columbia, Canada , 2009 .

[32]  Ajanta Goswami,et al.  Accuracy assessment of MODIS, NOAA and IRS data in snow cover mapping under Himalayan conditions , 2008 .

[33]  D. Hall,et al.  Accuracy assessment of the MODIS snow products , 2007 .

[34]  B. Ramsay,et al.  Published online in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/hyp.6720 Enhancements to, and forthcoming developments in the Interactive Multisensor Snow and Ice Mapping System (IMS) † , 2022 .

[35]  Z. Pu,et al.  MODIS/Terra observed seasonal variations of snow cover over the Tibetan Plateau , 2007 .

[36]  Mark A. Templin,et al.  Validation of the MODIS snow product and cloud mask using student and NWS cooperative station observations in the Lower Great Lakes Region , 2006 .

[37]  G. Blöschl,et al.  Validation of MODIS snow cover images over Austria , 2006 .

[38]  Dorothy K. Hall,et al.  An approach to using snow areal depletion curves inferred from MODIS and its application to land surface modelling in Alaska , 2005 .

[39]  Matthew Rodell,et al.  Updating a Land Surface Model with MODIS-Derived Snow Cover , 2004 .

[40]  Melvin B. Satterwhite,et al.  Field spectral signatures of snow, ice, and water , 2003, SPIE Defense + Commercial Sensing.

[41]  Andrew G. Klein,et al.  Validation of daily MODIS snow cover maps of the Upper Rio Grande River Basin for the 2000–2001 snow year , 2003 .

[42]  N. DiGirolamo,et al.  MODIS snow-cover products , 2002 .

[43]  David A. Robinson,et al.  Northern Hemisphere snow extent: regional variability 1972–1994 , 1999 .

[44]  A. Klein,et al.  Improving snow cover mapping in forests through the use of a canopy reflectance model , 1998 .

[45]  B. Ramsay,et al.  The interactive multisensor snow and ice mapping system , 1998 .

[46]  Jeff Dozier,et al.  Automated Mapping of Montane Snow Cover at Subpixel Resolution from the Landsat Thematic Mapper , 1996 .

[47]  D. Hall,et al.  Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data , 1995 .

[48]  J. Dozier.  Spectral Signature of Alpine Snow Cover from the Landsat Thematic Mapper , 1989 .

[49]  Jeff Dozier,et al.  Snow Mapping and Classification from Landsat Thematic Mapper Data , 1987, Annals of Glaciology.

[50]  D. E. Bowker,et al.  Spectral reflectances of natural targets for use in remote sensing studies , 1985 .

[51]  R. G. Crane,et al.  Satellite discrimination of snow/cloud surfaces , 1984 .

[52]  R. D'Entremont,et al.  Improved Cloud Detection Utilizing Defense Meteorological Satellite Program near Infrared Measurements , 1982 .

[53]  Francis R Valovcin,et al.  Spectral Radiance of Snow and Clouds in the Near Infrared Spectral Region , 1978 .

[54]  W. Barnes,et al.  A cloud physics radiometer , 1978 .

[55]  Francis R. Valovcin.  Snow/Cloud Discrimination. , 1976 .