• Armstrong, R. L., , and Brodzik M. J. , 2001: Recent northern hemisphere snow extent: A comparison of data derived from visible and microwave satellite sensors. Geophys. Res. Lett., 28, 36733676, doi:10.1029/2000GL012556.

    • Search Google Scholar
    • Export Citation
  • Barry, R. G., 2002: The role of snow and ice in the global climate system: A review. Polar Geogr., 26, 235246, doi:10.1080/789610195.

    • Search Google Scholar
    • Export Citation
  • Barry, R. G., , Armstrong R. , , Callaghan T. , , Cherry J. , , Gearhead S. , , Nolin A. , , Russell D. , , and Zockler C. , 2007: Snow. Global outlook for ice and snow, United Nations Environment Programme Publ., 39–62.

  • Brasnett, B., 1999: A global analysis of snow depth for numerical weather prediction. J. Appl. Meteor., 38, 726740, doi:10.1175/1520-0450(1999)038<0726:AGAOSD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Brown, R., , Derksen C. , , and Wang L. , 2010: A multi-data set analysis of variability and change in Arctic spring snow cover extent, 1967-2008. J. Geophys. Res., 115, D16111, doi:10.1029/2010JD013975.

    • Search Google Scholar
    • Export Citation
  • Chang, A. T. C., , Foster J. L. , , and Hall D. K. , 1987: Nimbus-7 SMMR derived global snow cover parameters. Ann. Glaciol., 9, 3944.

  • Chang, A. T. C., , Foster J. L. , , Hall D. K. , , Goodison B. E. , , Walker A. E. , , and Metcalfe J. R. , 1997: Snow parameters derived from microwave measurements during the BOREAS winter field experiment. J. Geophys. Res., 102, 29 66329 671, doi:10.1029/96JD03327.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., 1994: Snow cover and climate. Weather, 49, 150156, doi:10.1002/j.1477-8696.1994.tb05997.x.

  • Cohen, J., , and Entekhabi D. , 1999: Eurasian snow cover variability and Northern Hemisphere climate predictability. Geophys. Res. Lett., 26, 345348, doi:10.1029/1998GL900321.

    • Search Google Scholar
    • Export Citation
  • Derksen, C., 2008: The contribution of AMSR-E 18.7 and 10.7 GHz measurements to improved boreal forest snow water equivalent retrievals. Remote Sens. Environ., 112, 27012710, doi:10.1016/j.rse.2008.01.001.

    • Search Google Scholar
    • Export Citation
  • Derksen, C., , LeDrew E. , , Walker A. , , and Goodison B. , 2000: Influence of sensor overpass time on passive microwave-derived snow cover parameters. Remote Sens. Environ., 71, 297308, doi:10.1016/S0034-4257(99)00084-X.

    • Search Google Scholar
    • Export Citation
  • Dong, J., , Walker J. P. , , and Houser P. R. , 2005: Factors affecting remotely sensed snow water equivalent uncertainty. Remote Sens. Environ., 97, 6882, doi:10.1016/j.rse.2005.04.010.

    • Search Google Scholar
    • Export Citation
  • Dyer, J., 2008: Snow depth and streamflow relationships in large North American watersheds. J. Geophys. Res., 113, D18113, doi:10.1029/2008JD010031.

    • Search Google Scholar
    • Export Citation
  • Ferraro, R. R., and Coauthors, 2005: NOAA operational hydrological products derived from the AMSU. IEEE Trans. Geosci. Remote Sens., 43, 10361049, doi:10.1109/TGRS.2004.843249.

    • Search Google Scholar
    • Export Citation
  • Foster, J. L., , Hall D. K. , , and Chang A. T. C. , 1984: An overview of passive microwave snow research and results. Rev. Geophys. Space Phys., 22, 195208, doi:10.1029/RG022i002p00195.

    • Search Google Scholar
    • Export Citation
  • Foster, J. L., , Sun C. , , Walker J. P. , , Kelly R. , , Chang A. , , Dong J. , , and Powell H. , 2005: Quantifying the uncertainty in passive microwave snow water equivalent observations. Remote Sens. Environ., 94, 187203, doi:10.1016/j.rse.2004.09.012.

    • Search Google Scholar
    • Export Citation
  • Frei, A., , Tedesco M. , , Lee S. , , Foster J. , , Hall D. K. , , Kelly R. , , and Robinson D. A. , 2012: A review of global satellite-derived snow products. Adv. Space Res., 50, 10071029, doi:10.1016/j.asr.2011.12.021.

    • Search Google Scholar
    • Export Citation
  • Grody, N. C., 1991: Classification of snow cover and precipitation using the Special Sensor Microwave Imager. J. Geophys. Res., 96, 74237435, doi:10.1029/91JD00045.

    • Search Google Scholar
    • Export Citation
  • Grody, N. C., , and Basist A. N. , 1996: Global identification of snowcover using SSM/I measurements. IEEE Trans. Geosci. Remote Sens., 34, 237249, doi:10.1109/36.481908.

    • Search Google Scholar
    • Export Citation
  • Grody, N. C., , Weng F. , , and Ferraro R. , 2000: Application of AMSU for obtaining hydrological parameters. Microwave Radiometry and Remote Sensing of the Earth’s Surface and Atmosphere, P. Pampaloni and S. Paloscia, Eds., VSP, 339 –351.

  • Hall, D. K., , Tait A. B. , , Foster J. L. , , Chang A. T. C. , , and Allen M. , 2000: Intercomparison of satellite-derived snow-cover maps. Ann. Glaciol., 31, 369376, doi:10.3189/172756400781820066.

    • Search Google Scholar
    • Export Citation
  • Hamlet, A. F., , and Lettenmaier D. P. , 1999: Effects of climate change on hydrology and water resources in the Columbia River basin. J. Amer. Water Resour. Assoc., 35, 15971623, doi:10.1111/j.1752-1688.1999.tb04240.x.

    • Search Google Scholar
    • Export Citation
  • Helfrich, S. R., , McNamara D. , , Ramsay B. H. , , Baldwin T. , , and Kasheta T. , 2007: Enhancements to, and forthcoming developments in the Interactive Multisensor Snow and Ice Mapping System (IMS). Hydrol. Processes, 21, 15761586, doi:10.1002/hyp.6720.

    • Search Google Scholar
    • Export Citation
  • Hollinger, J. P., , Peirce J. L. , , and Poe G. A. , 1990: SSM/I instrument evaluation. IEEE Trans. Geosci. Remote Sens., 28, 781790, doi:10.1109/36.58964.

    • Search Google Scholar
    • Export Citation
  • Imaoka, K., , Kachi M. , , Kasahara M. , , Ito N. , , Nakagawa K. , , and Oki T. , 2010: Instrument performance and calibration of AMSR-E and AMSR2. ISPRS Technical Commission VIII Symposium: Networking the World with Remote Sensing, K. Kajiware et al., Eds., Vol. XXXVIII, Part 8, ISPRS, 13–16.

  • IPCC, 2007: Climate Change 2007: The Physical Science Basis. Cambridge University Press, 996 pp.

  • Josberger, E. G., , Gloersen P. , , Chang A. , , and Rango A. , 1996: The effects of snowpack grain size on satellite passive microwave observations from the Upper Colorado River Basin. J. Geophys. Res., 101, 66796688, doi:10.1029/95JC02959.

    • Search Google Scholar
    • Export Citation
  • Kelly, R. E., 2009: The AMSR-E snow depth algorithm description and initial results. J. Remote Sens. Soc. Japan, 29, 307317, doi:10.11440/rssj.29.307.

    • Search Google Scholar
    • Export Citation
  • Kelly, R. E., , Chang A. T. , , Tsang L. , , and Foster J. L. , 2003: A prototype AMSR-E global snow area and snow depth algorithm. IEEE Trans. Geosci. Remote Sens., 41, 230242, doi:10.1109/TGRS.2003.809118.

    • Search Google Scholar
    • Export Citation
  • Kongoli, C., , and Helfrich S. , 2015: A multi-source interactive analysis approach for Northern Hemispheric snow depth estimation. Proc. IGARSS 2015: Remote Sensing; Understanding the Earth for a Safer World, Milan Italy, IGARSS, MOP.PO.10. [Available online at http://www.igarss2015.org/Papers/viewpapers.asp?papernum=8441.]

  • Kongoli, C., , Dean C. A. , , Helfrich S. R. , , and Ferraro R. R. , 2007: Evaluating the potential of a blended passive microwave-interactive multi-sensor product for improved mapping of snow cover and estimations of snow water equivalent. Hydrol. Processes, 21, 15971607, doi:10.1002/hyp.6722.

    • Search Google Scholar
    • Export Citation
  • Kongoli, C., , Romanov P. , , and Ferraro R. , 2012: Snow cover monitoring from remote-sensing satellites. Remote Sensing and Drought: Innovative Monitoring Approaches, B. Wardlow, M. Anderson, and J. Verdin, Eds., CRC Press, 359–386.

  • LCSCG, 2012: User guide for the MODIS Land Cover Type Product (MCD12Q1). Land Cover and Surface Climate Group, Boston University. [Available online at http://www.bu.edu/lcsc/files/2012/08/MCD12Q1_user_guide.pdf.]

  • Liang, T., , Zhang X. , , Xie H. , , Wu C. , , Feng Q. , , Huang X. , , and Chen Q. , 2008: Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements. Remote Sens. Environ., 112, 3750–3761, doi:10.1016/j.rse.2008.05.010.

    • Search Google Scholar
    • Export Citation
  • Markus, T., , Powell D. C. , , and Wang J. R. , 2006: Sensitivity of passive microwave snow depth retrievals to weather effects and snow evolution. IEEE Trans. Geosci. Remote Sens., 44, 6877, doi:10.1109/TGRS.2005.860208.

    • Search Google Scholar
    • Export Citation
  • NOHRSC, 2004: Snow Data Assimilation System (SNODAS) data products at NSIDC. National Snow and Ice Data Center, Boulder, CO, digital media, doi:10.7265/N5TB14TC.

  • Ramsay, B., 1998: The interactive multisensor snow and ice mapping system. Hydrol. Processes, 12, 15371546, doi:10.1002/(SICI)1099-1085(199808/09)12:10/11<1537::AID-HYP679>3.0.CO;2-A.

    • Search Google Scholar
    • Export Citation
  • Savoie, M. H., , Armstrong R. L. , , Brodzik M. J. , , and Wang J. R. , 2009: Atmospheric corrections for improved satellite passive microwave snow cover retrievals over the Tibet Plateau. Remote Sens. Environ., 113, 26612669, doi:10.1016/j.rse.2009.08.006.

    • Search Google Scholar
    • Export Citation
  • Schweiger, A. J., , and Barry R. G. , 1989: Evaluation of algorithms for mapping snow cover parameters in the Federal Republic of Germany using passive microwave data. Erdkunde, 43, 8594, doi:10.3112/erdkunde.1989.02.02.

    • Search Google Scholar
    • Export Citation
  • Sturm, M., , Holmgren J. , , and Liston G. E. , 1995: A seasonal snow cover classification system for local to global applications. J. Climate, 8, 12611283, doi:10.1175/1520-0442(1995)008<1261:ASSCCS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Sun, N., , and Weng F. , 2008: Evaluation of Special Sensor Microwave Imager/Sounder (SSMIS) environmental data records. IEEE Trans. Geosci. Remote Sens., 46, 10061016, doi:10.1109/TGRS.2008.916984.

    • Search Google Scholar
    • Export Citation
  • Tedesco, M., , and Wang J. R. , 2006: Atmospheric correction of AMSR-E brightness temperatures for dry snow cover mapping. IEEE Geosci. Remote Sens. Lett., 3, 320324, doi:10.1109/TGRS.2008.917368.

    • Search Google Scholar
    • Export Citation
  • Tedesco, M., , and Narvekar P. S. , 2010: Assessment of the NASA AMSR-E SWE product. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 3, 141159, doi:10.1109/JSTARS.2010.2040462.

    • Search Google Scholar
    • Export Citation
  • Townshend, J., , Hansen M. , , Carroll M. , , DiMiceli C. , , Sohlberg R. , , and Huang C. , 2011: User guide for the MODIS Vegetation Continuous Fields product: Collection 5 version 1. University of Maryland. [Available online at http://glcf.umd.edu/library/guide/VCF_C5_UserGuide_Dec2011.pdf.]

  • Vuyovich, C. M., , and Jacobs J. M. , 2011: Snowpack and runoff generation using AMSR-E passive microwave observations in the Upper Helmand Watershed, Afghanistan. Remote Sens. Environ., 115, 33133321, doi:10.1016/j.rse.2011.07.014.

    • Search Google Scholar
    • Export Citation
  • Vuyovich, C. M., , Jacobs J. M. , , and Daly S. F. , 2014: Comparison of passive microwave and modeled estimates of total watershed SWE in the continental United States. Water Resour. Res., 50, 9088–9102, doi:10.1002/2013WR014734.

    • Search Google Scholar
    • Export Citation
  • Walsh, J. E., 1984: Snow cover and atmospheric variability: Changes in the snow covering the earth’s surface affect both daily weather and long-term climate. Amer. Sci., 72, 5057.

    • Search Google Scholar
    • Export Citation
  • Wang, J. R., , and Tedesco M. , 2007: Identification of atmospheric influences on the estimation of snow water equivalent from AMSR-E measurements. Remote Sens. Environ., 111, 398408, doi:10.1016/j.rse.2006.10.024.

    • Search Google Scholar
    • Export Citation
  • Yang, D., , Robinson D. , , Zhao Y. , , Estilow T. , , and Ye B. , 2003: Streamflow response to seasonal snow cover extent change in large Siberian watersheds. J. Geophys. Res., 108, 4578, doi:10.1029/2002JD003149.

    • Search Google Scholar
    • Export Citation
  • Zhang, X., , Harvey K. D. , , Hogg W. D. , , and Yuzyk T. R. , 2001: Trends in Canadian streamflow. Water Resour. Res., 37, 987998, doi:10.1029/2000WR900357.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 32 32 15
PDF Downloads 21 21 14

An In-Depth Evaluation of Heritage Algorithms for Snow Cover and Snow Depth Using AMSR-E and AMSR2 Measurements

View More View Less
  • 1 Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin–Madison, Madison, Wisconsin
  • 2 Cooperative Institute for Climate and Satellites, University of Maryland, College Park, College Park, Maryland
  • 3 Center for Satellite Applications and Research, NOAA/NESDIS, Madison, Wisconsin
© Get Permissions
Restricted access

Abstract

The Advanced Microwave Scanning Radiometer 2 (AMSR2) was launched in 2012 on board the Global Change Observation Mission 1st–Water (GCOM-W1) satellite. This study presents a robust evaluation of AMSR2 algorithms for the retrieval of snow-covered area (SCA) and snow depth (SD) that will be used operationally by the National Oceanic and Atmospheric Administration (NOAA). Quantitative assessment of the algorithms was performed for a 10-yr period with AMSR-E and a 2-yr period with AMSR2 data using the NOAA Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover and in situ SD data as references. AMSR-E SCA showed a monthly overall accuracy rate of about 80% except in May. Accuracy improves significantly to over 90% when wet snow cases are excluded, and accuracy differences between ascending and descending portions of orbits also decrease. Microwave-derived SCA over dry snow areas can therefore be obtained with accuracy close to optically derived SCA. An evaluation of the results for AMSR-E SD showed a low overall bias of 1 cm and a root-mean-square error of 20 cm. Results for AMSR2-based SCA and SD are similar to those from AMSR-E. Biases and root-mean-square errors show dependencies on elevation, forest fraction, the magnitude of snow depth, and snow cover class.

Denotes Open Access content.

Publisher’s Note: This article was revised on 12 February 2016 to include the open access designation that was added after initial publication.

Corresponding author address: Yong-Keun Lee, CIMSS, University of Wisconsin, 1225 W. Dayton St., Madison, WI 53706. E-mail: yklee@ssec.wisc.edu

Abstract

The Advanced Microwave Scanning Radiometer 2 (AMSR2) was launched in 2012 on board the Global Change Observation Mission 1st–Water (GCOM-W1) satellite. This study presents a robust evaluation of AMSR2 algorithms for the retrieval of snow-covered area (SCA) and snow depth (SD) that will be used operationally by the National Oceanic and Atmospheric Administration (NOAA). Quantitative assessment of the algorithms was performed for a 10-yr period with AMSR-E and a 2-yr period with AMSR2 data using the NOAA Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover and in situ SD data as references. AMSR-E SCA showed a monthly overall accuracy rate of about 80% except in May. Accuracy improves significantly to over 90% when wet snow cases are excluded, and accuracy differences between ascending and descending portions of orbits also decrease. Microwave-derived SCA over dry snow areas can therefore be obtained with accuracy close to optically derived SCA. An evaluation of the results for AMSR-E SD showed a low overall bias of 1 cm and a root-mean-square error of 20 cm. Results for AMSR2-based SCA and SD are similar to those from AMSR-E. Biases and root-mean-square errors show dependencies on elevation, forest fraction, the magnitude of snow depth, and snow cover class.

Denotes Open Access content.

Publisher’s Note: This article was revised on 12 February 2016 to include the open access designation that was added after initial publication.

Corresponding author address: Yong-Keun Lee, CIMSS, University of Wisconsin, 1225 W. Dayton St., Madison, WI 53706. E-mail: yklee@ssec.wisc.edu
Save