A 41-year (1979–2019) passive-microwave-derived lake ice phenology data record of the Northern Hemisphere

Author:

Cai Yu,Duguay Claude R.ORCID,Ke Chang-Qing

Abstract

Abstract. Seasonal ice cover is one of the important attributes of lakes in middle- and high-latitude regions. The annual freeze-up and breakup dates as well as the duration of ice cover (i.e., lake ice phenology) are sensitive to the weather and climate; hence, they can be used as an indicator of climate variability and change. In addition to optical, active microwave, and raw passive microwave data that can provide daily observations, the Calibrated Enhanced-Resolution Brightness Temperature (CETB) dataset available from the National Snow and Ice Data Center (NSIDC) provides an alternate source of passive microwave brightness temperature (TB) measurements for the determination of lake ice phenology on a 3.125 km grid. This study used Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave/Imager (SSM/I), and Special Sensor Microwave Imager/Sounder (SSMIS) data from the CETB dataset to extract the ice phenology for 56 lakes across the Northern Hemisphere from 1979 to 2019. According to the differences in TB between lake ice and open water, a threshold algorithm based on the moving t test method was applied to determine the lake ice status for grids located at least 6.25 km away from the lake shore, and the ice phenology dates for each lake were then extracted. When ice phenology could be extracted from more than one satellite over overlapping periods, results from the satellite offering the largest number of observations were prioritized. The lake ice phenology results showed strong agreement with an existing product derived from Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and Advanced Microwave Scanning Radiometer 2 (AMSR2) data (2002 to 2015), with mean absolute errors of ice dates ranging from 2 to 4 d. Compared with near-shore in situ observations, the lake ice results, while different in terms of spatial coverage, still showed overall consistency. The produced lake ice record also displayed significant consistency when compared to a historical record of annual maximum ice cover of the Laurentian Great Lakes of North America. From 1979 to 2019, the average complete freezing duration and ice cover duration for lakes forming a complete ice cover on an annual basis were 153 and 161 d, respectively. The lake ice phenology dataset – a new climate data record (CDR) – will provide valuable information to the user community about the changing ice cover of lakes over the last 4 decades. The dataset is available at https://doi.org/10.1594/PANGAEA.937904 (Cai et al., 2021).

Funder

National Natural Science Foundation of China

China Scholarship Council

Natural Sciences and Engineering Research Council of Canada

Publisher

Copernicus GmbH

Subject

General Earth and Planetary Sciences

Reference55 articles.

1. 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.

2. 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.

3. 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.

4. 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.

5. 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).

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3