Articles | Volume 14, issue 7
https://doi.org/10.5194/essd-14-3329-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-3329-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
19 Jul 2022
Data description paper |
| 19 Jul 2022
| 19 Jul 2022
A 41-year (1979–2019) passive-microwave-derived lake ice phenology data record of the Northern Hemisphere
Yu Cai
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, Key Laboratory for Land Satellite Remote Sensing
Applications of Ministry of Natural Resources, School of Geography and Ocean
Science, Nanjing University, Nanjing, China
Claude R. Duguay
Department of Geography and Environmental Management, University of
Waterloo, Ontario, Canada
H2O Geomatics Inc., Waterloo, Ontario, Canada
Chang-Qing Ke
CORRESPONDING AUTHOR
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, Key Laboratory for Land Satellite Remote Sensing
Applications of Ministry of Natural Resources, School of Geography and Ocean
Science, Nanjing University, Nanjing, China
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Cited articles
Arp, C. D., Jones, B. M., and Grosse, G.: Recent lake ice-out phenology
within and among lake districts of Alaska, U.S.A., Limnol. Oceanogr., 58,
2013–2028, https://doi.org/10.4319/lo.2013.58.6.2013, 2013.
Bellerby, T., Taberner, M., Wilmshurst, A., Beaumont, M., Barrett, E.,
Scott, J., and Durbin, C.: Retrieval of land and sea brightness temperatures
from mixed coastal pixels in passive microwave data, IEEE T. Geosci.
Remote, 36, 1844–1851, https://doi.org/10.1109/36.729355, 1998.
Belward, A., Bourassa, M., Dowell, M., Briggs, S., Dolman, H., Holmlund, K.,
and Verstraete, M.: The Global Observing System for Climate: Implementation
Needs, Ref. Number GCOS-200 315, https://library.wmo.int/opac/doc_num.php?explnum_id=3417 (last access: 1 December 2021), 2016.
Bennartz, R.: On the use of SSM/I measurements in coastal regions, J. Atmos.
Ocean. Tech., 16, 417–431, https://doi.org/10.1175/1520-0426(1999)016<0417:OTUOSI>2.0.CO;2, 1999.
Benson, B., Magnuson, J., and Sharma, S.: Global Lake and River Ice Phenology
Database, Version 1, NSIDC Natl. Snow Ice Data Center [data set], Boulder, https://doi.org/10.7265/N5W66HP8, 2000
(updated 2020).
Benson, B. J., Magnuson, J. J., Jensen, O. P., Card, V. M., Hodgkins, G.,
Korhonen, J., Livingstone, D. M., Stewart, K. M., Weyhenmeyer, G. A., and
Granin, N. G.: Extreme events, trends, and variability in Northern
Hemisphere lake-ice phenology (1855–2005), Climate Change, 112, 299–323,
https://doi.org/10.1007/s10584-011-0212-8, 2012.
Brodzik, M. J., Long, D. G., Hardman, M. A., Paget, A., and Armstrong, R.:
MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid
2.0 Brightness Temperature ESDR, Version 1, NASA National Snow and Ice Data
Center Distributed Active Archive Center [data set], 0–24, https://doi.org/10.5067/MEASURES/CRYOSPHERE/NSIDC-0630.001, 2020.
Brown, L. C. and Duguay, C. R.: The response and role of ice cover in
lake-climate interactions, Prog. Phys. Geogr., 34, 671–704,
https://doi.org/10.1177/0309133310375653, 2010.
Cai, Y., Ke, C.-Q., and Duan, Z.: Monitoring ice variations in Qinghai Lake
from 1979 to 2016 using passive microwave remote sensing data, Sci. Total
Environ., 607–608, 120–131, https://doi.org/10.1016/j.scitotenv.2017.07.027, 2017.
Cai, Y., Ke, C.-Q., Li, X., Zhang, G., Duan, Z., and Lee, H.: Variations of
Lake Ice Phenology on the Tibetan Plateau From 2001 to 2017 Based on MODIS
Data, J. Geophys. Res.-Atmos., 124, 825–843, https://doi.org/10.1029/2018JD028993, 2019.
Cai, Y., Duguay, C. R., and Ke, C.-Q.: Lake ice phenology in the Northern
Hemisphere extracted from SMMR, SSM/I and SSMIS data from 1979 to 2020,
PANGAEA [data set], https://doi.pangaea.de/10.1594/PANGAEA.937904, 2021.
Chaouch, N., Temimi, M., Romanov, P., Cabrera, R., Mckillop, G., and
Khanbilvardi, R.: An automated algorithm for river ice monitoring over the
Susquehanna River using the MODIS data, Hydrol. Process., 28, 62–73,
https://doi.org/10.1002/hyp.9548, 2014.
Crétaux, J. -F., Merchant, C. J., Duguay, C., Simis, S., Calmettes, B., Bergé-Nguyen, M., Wu, Y., Zhang, D., Carrea, L., Liu, X., Selmes, N., and Warren, M.: ESA Lakes Climate Change Initiative (Lakes_cci): Lake products, Version 1.0. Centre for Environmental Data Analysis [data set], https://doi.org/10.5285/3c324bb4ee394d0d876fe2e1db217378, 2020.
Dörnhöfer, K. and Oppelt, N.: Remote sensing for lake research and
monitoring – Recent advances, Ecol. Indic., 64, 105–122,
https://doi.org/10.1016/j.ecolind.2015.12.009, 2016.
Du, J. and Kimball, J. S.: Daily Lake Ice Phenology Time Series Derived from AMSR-E and AMSR2, Version 1. NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/HT4NQO7ZJF7M, 2018.
Du, J., Kimball, J. S., Duguay, C., Kim, Y., and Watts, J. D.: Satellite microwave assessment of Northern Hemisphere lake ice phenology from 2002 to 2015, The Cryosphere, 11, 47–63, https://doi.org/10.5194/tc-11-47-2017, 2017.
Duguay, C. R. and Lafleur, P. M.: Determining depth and ice thickness of
shallow sub-Arctic lakes using space-borne optical and SAR data, Int. J.
Remote Sens., 24, 475–489, https://doi.org/10.1080/01431160304992, 2003.
Duguay, C. R., Pultz, T. J., Lafleur, P. M., and Drai, D.: RADARSAT
backscatter characteristics of ice growing on shallow sub-Arctic lakes,
Churchill, Manitoba, Canada, Hydrol. Process., 16, 1631–1644,
https://doi.org/10.1002/hyp.1026, 2002.
Duguay, C. R., Prowse, T. D., Bonsal, B. R., Brown, R. D., Lacroix, M. P.,
and Ménard, P.: Recent trends in Canadian lake ice cover, Hydrol.
Process., 20, 781–801, https://doi.org/10.1002/hyp.6131, 2006.
Duguay, C. R., Bernier, M., Gauthier, Y., and Kouraev, A.: Remote sensing of
lake and river ice, in: Remote Sensing of the Cryosphere, edited by: Tedesco
M., Wiley-Blackwell, Oxford, UK, 273–306,
https://doi.org/10.1002/9781118368909.ch12, 2015.
Engram, M., Arp, C. D., Jones, B. M., Ajadi, O. A., and Meyer, F. J.:
Analyzing floating and bedfast lake ice regimes across Arctic Alaska using
25 years of space-borne SAR imagery, Remote Sens. Environ., 209,
660–676, https://doi.org/10.1016/j.rse.2018.02.022, 2018.
Geldsetzer, T., Van Der Sanden, J., and Brisco, B.: Monitoring lake ice
during spring melt using RADARSAT-2 SAR, Can. J. Remote Sens., 36,
S391–S400, https://doi.org/10.5589/m11-001, 2010.
Hall, D. K., Riggs, G. A., Foster, J. L., and Kumar, S. V.: Development and
evaluation of a cloud-gap-filled MODIS daily snow-cover product, Remote
Sens. Environ., 114, 496–503, https://doi.org/10.1016/j.rse.2009.10.007, 2010.
Helfrich, S. R., McNamara, D., Ramsay, B. H., Baldwin, T., and Kasheta, T.:
Enhancements to, and forthcoming developments in the Interactive Multisensor
Snow and Ice Mapping System (IMS), Hydrol. Process., 21, 1576–1586,
https://doi.org/10.1002/hyp.6720, 2007.
Jeffries, M. O., Morris, K., Weeks, W. F., and Wakabayashi, H.: Structural
and stratigraphic features and ERS 1 synthetic aperture radar backscatter
characteristics of ice growing on shallow lakes in NW Alaska, winter
1991–1992, J. Geophys. Res., 99, 22459–22471, 1994.
Jiang, J. M. and You, X. T.: Where and when did an abrupt climatic change
occur in China during the last 43 years?, Theor. Appl. Climatol., 55,
33–39, https://doi.org/10.1007/BF00864701, 1996.
Kang, K.-K., Duguay, C. R., and Howell, S. E. L.: Estimating ice phenology on large northern lakes from AMSR-E: algorithm development and application to Great Bear Lake and Great Slave Lake, Canada, The Cryosphere, 6, 235–254, https://doi.org/10.5194/tc-6-235-2012, 2012.
Ke, C.-Q., Tao, A.-Q., and Jin, X.: Variability in the ice phenology of Nam
Co Lake in central Tibet from scanning multichannel microwave radiometer and
special sensor microwave/imager: 1978 to 2013, J. Appl. Remote Sens., 7,
073477, https://doi.org/10.1117/1.jrs.7.073477, 2013.
Knoll, L. B., Sharma, S., Denfeld, B. A., Flaim, G., Hori, Y., Magnuson, J.
J., Straile, D., and Weyhenmeyer, G. A.: Consequences of lake and river ice
loss on cultural ecosystem services, Limnol. Oceanogr., 4, 119–131,
https://doi.org/10.1002/lol2.10116, 2019.
Kropáček, J., Maussion, F., Chen, F., Hoerz, S., and Hochschild, V.: Analysis of ice phenology of lakes on the Tibetan Plateau from MODIS data, The Cryosphere, 7, 287–301, https://doi.org/10.5194/tc-7-287-2013, 2013.
Latifovic, R. and Pouliot, D.: Analysis of climate change impacts on lake
ice phenology in Canada using the historical satellite data record, Remote
Sens. Environ., 106, 492–507, https://doi.org/10.1016/j.rse.2006.09.015, 2007.
Livingstone, D. M.: Break-up dates of Alpine lakes as proxy data for local
and regional mean surface air temperatures, Climatic Change, 37, 407–439,
https://doi.org/10.1023/A:1005371925924, 1997.
Long, D. G. and Brodzik, M. J.: Optimum Image Formation for Spaceborne
Microwave Radiometer Products, IEEE T. Geosci. Remote, 54, 2763–2779,
https://doi.org/10.1109/TGRS.2015.2505677, 2016.
Magnuson, J. J. and Lathrop, R. C.: Lake ice: winter beauty, value, changes
and a threatened future, LakeLine, 43, 18–27,
https://lter.limnology.wisc.edu (last access: 15 April 2021), 2014.
Magnuson, J. J., Robertson, D. M., Benson, B. J., Wynne, R. H., Livingstone,
D. M., Arai, T., Assel, R. A., Barry, R. G., Card, V., Kuusisto, E., Granin,
N. G., Prowse, T. D., Stewart, K. M., and Vuglinski, V. S.: Historical trends
in lake and river ice cover in the Northern Hemisphere, Science, 289,
1743–1746, https://doi.org/10.1126/science.289.5485.1743, 2000.
Maslanik, J. A. and Barry, R. G.: Lake ice formation and breakup as an indicator of climate change: Potential for monitoring using remote sensing techniques, The Influence of Climate Change and Climatic Variability on the Hydrologic Regime and Water Resources, International Association of Hydrological Sciences Press, IAHS Publ. No. 168, 153–161, 1987.
Messager, M. L., Lehner, B., Grill, G., Nedeva, I., and Schmitt, O.: Estimating the volume and age of water stored in global lakes using a geo-statistical approach, Nat. Commun., 7, 13603, https://doi.org/10.1038/ncomms13603, 2016 (data available at: https://www.hydrosheds.org/page/hydrolakes, last access: 3 December 2019).
Mishra, V., Cherkauer, K. A., Bowling, L. C., and Huber, M.: Lake Ice
phenology of small lakes: Impacts of climate variability in the Great Lakes
region, Global Planet. Change, 76, 166–185,
https://doi.org/10.1016/j.gloplacha.2011.01.004, 2011.
Morris, K., Jeffries, M. O., and Weeks, W. F.: Ice processes and growth
history on Arctic and sub-Arctic lakes using ERS-1 SAR data, Polar Rec. (Gr.
Brit)., 31, 115–128, https://doi.org/10.1017/S0032247400013619, 1995.
Murfitt, J. and Duguay, C. R.: 50 years of lake ice research from active
microwave remote sensing: Progress and prospects, Remote Sens. Environ.,
264, 112616, https://doi.org/10.1016/j.rse.2021.112616, 2021.
NOAA Great Lakes Environmental Research Laboratory: Historical Great Lakes Ice Cover [data set], Digital media, https://www.glerl.noaa.gov/data/ice/#historical (last access: 23 November 2021), 2021.
Nonaka, T., Matsunaga, T., and Hoyano, A.: Estimating ice breakup dates on
Eurasian lakes using water temperature trends and threshold surface
temperatures derived from MODIS data, Int. J. Remote Sens., 28,
2163–2179, https://doi.org/10.1080/01431160500391957, 2007.
Pour, H. K., Duguay, C. R., Martynov, A., and Brown, L. C.: Simulation of
surface temperature and ice cover of large northern lakes with 1-D models: A
comparison with MODIS satellite data and in situ measurements, Tellus A, 64, 17614, https://doi.org/10.3402/tellusa.v64i0.17614, 2012.
Prowse, T., Alfredsen, K., Beltaos, S., Bonsal, B. R., Bowden, W. B.,
Duguay, C. R., Korhola, A., McNamara, J., Vincent, W. F., Vuglinsky, V.,
Walter Anthony, K. M., and Weyhenmeyer, G. A.: Effects of changes in arctic
lake and river ice, Ambio, 40, 63–74,
https://doi.org/10.1007/s13280-011-0217-6, 2011.
Sharma, S., Magnuson, J. J., Batt, R. D., Winslow, L. A., Korhonen, J., and
Aono, Y.: Direct observations of ice seasonality reveal changes in climate
over the past 320–570 years, Sci. Rep.-UK, 6, 1–11,
https://doi.org/10.1038/srep25061, 2016.
Sharma, S., Blagrave, K., Magnuson, J. J., O'Reilly, C. M., Oliver, S.,
Batt, R. D., Magee, M. R., Straile, D., Weyhenmeyer, G. A., Winslow, L., and
Woolway, R. I.: Widespread loss of lake ice around the Northern Hemisphere
in a warming world, Nat. Clim. Change, 9, 227–231,
https://doi.org/10.1038/s41558-018-0393-5, 2019.
Šmejkalová, T., Edwards, M. E., and Dash, J.: Arctic lakes show
strong decadal trend in earlier spring ice-out, Sci. Rep.-UK, 6, 1–8,
https://doi.org/10.1038/srep38449, 2016.
Su, L., Che, T., and Dai, L.: Variation in ice phenology of large lakes over
the northern hemisphere based on passive microwave remote sensing data,
Remote Sens., 13, 1389, https://doi.org/10.3390/rs13071389, 2021.
Surdu, C. M., Duguay, C. R., and Fernández Prieto, D.: Evidence of recent changes in the ice regime of lakes in the Canadian High Arctic from spaceborne satellite observations, The Cryosphere, 10, 941–960, https://doi.org/10.5194/tc-10-941-2016, 2016.
Weber, H., Riffler, M., Nõges, T., and Wunderle, S.: Lake ice phenology
from AVHRR data for European lakes: An automated two-step extraction method,
Remote Sens. Environ., 174, 329–340, https://doi.org/10.1016/j.rse.2015.12.014, 2016.
Weyhenmeyer, G. A., Livingstone, D. M., Meili, M., Jensen, O., Benson, B.,
and Magnuson, J. J.: Large geographical differences in the sensitivity of
ice-covered lakes and rivers in the Northern Hemisphere to temperature
changes, Glob. Change Biol., 17, 268–275,
https://doi.org/10.1111/j.1365-2486.2010.02249.x, 2011.
Woolway, R. I. and Merchant, C. J.: Worldwide alteration of lake mixing
regimes in response to climate change, Nat. Geosci., 12, 271–276,
https://doi.org/10.1038/s41561-019-0322-x, 2019.
Wu, Y., Duguay, C. R., and Xu, L.: Assessment of machine learning classifiers
for global lake ice cover mapping from MODIS TOA reflectance data, Remote
Sens. Environ., 253, 112206, https://doi.org/10.1016/j.rse.2020.112206, 2021.
Xiao, D. and Li, J.: Spatial and temporal characteristics of the decadal
abrupt changes of global atmosphere-ocean system in the 1970s, J. Geophys.
Res.-Atmos., 112, 1–18, https://doi.org/10.1029/2007JD008956, 2007.
Short summary
Seasonal ice cover is one of the important attributes of lakes in middle- and high-latitude regions. This study used passive microwave brightness temperature measurements to extract the ice phenology for 56 lakes across the Northern Hemisphere from 1979 to 2019. A threshold algorithm was applied according to the differences in brightness temperature between lake ice and open water. The dataset will provide valuable information about the changing ice cover of lakes over the last 4 decades.
Seasonal ice cover is one of the important attributes of lakes in middle- and high-latitude...
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