Lake Ice Thickness Retrieval Method with ICESat-2-Assisted CyroSat-2 Echo Peak Selection

Author:

Ye Hao1,Jin Guowang1,Zhang Hongmin2,Xiong Xin13,Li Jiahao1,Wang Jiajun14

Affiliation:

1. Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China

2. Institute of Data and Target Engineering, Information Engineering University, Zhengzhou 450001, China

3. Key Laboratory of Smart Earth, 88 Tujing East Road, Beijing 100094, China

4. 92556 Troops, Ningbo 315000, China

Abstract

Lake ice thickness (LIT) is one of the key climate variables in the lake ice domain, but there are currently large uncertainties in the retrieval of LIT. We present and validate a new LIT retrieval method that utilizes ICESat-2 data to assist CryoSat-2 echo peak selection, aiming to improve the accuracy of LIT retrieval and enable data acquisition without on-site measurements. The method involves screening out similar ICESat-2 and CryoSat-2 tracks based on time and space constraints. It also involves dynamically adjusting the range constraint window of CryoSat-2 waveforms based on the high-precision lake ice surface ellipsoid height obtained from ICESat-2/ATL06 data. Within this range constraint window, the peak selection strategy is used to determine the scattering interfaces between snow-ice and ice-water. By utilizing the distance between the scattering horizons, the thickness of the lake ice can be determined. We performed the ice thickness retrieval experiment for Baker Lake in winter and verified it against the on-site measurement data. The results showed that the accuracy was about 0.143 m. At the same time, we performed the ice thickness retrieval experiment for Great Bear Lake (GBL), which does not have on-site measurement data, and compared it with the climate change trend of GBL. The results showed that the retrieval results were consistent with the climate change trend of GBL, confirming the validity of the proposed method.

Funder

the National Natural Science Foundation of China

Publisher

MDPI AG

Reference33 articles.

1. Quantifying Northern Hemisphere Freshwater Ice: Qualifying Freshwater Ice;Brooks;Geophys. Res. Lett.,2013

2. Belward, A., Bourassa, M., Dowell, M., Briggs, S., Dolman, H.A.J., Holmlund, K., Husband, R., Quegan, S., Simmons, A., and Sloyan, B. (2016). The Global Observing System for Climate: Implementation Needs, World Meteorological Organization.

3. River Ice Phenology and Thickness from Satellite Altimetry: Potential for Ice Bridge Road Operation and Climate Studies;Zakharova;Cryosphere,2021

4. Derouin, S. (2020). River Ice Is Disappearing. Eos, 101.

5. 50 Years of Lake Ice Research from Active Microwave Remote Sensing: Progress and Prospects;Murfitt;Remote Sens. Environ.,2021

Cited by 1 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