Monitoring ice variations in Qinghai Lake from 1979 to 2016 using passive microwave remote sensing data
(2017) In Science of the Total Environment 607-608. p.120-131- Abstract
Lake ice is a sensitive indicator of climate change. Based on the disparities between the brightness temperatures of lake ice and water, passive microwave data can be used to monitor the ice variations of a lake. With focus on the analysis of long time series variability of lake ice, this study extracts four characteristic dates related to lake ice (the annual freeze start, freeze completion, ablation start and ablation completion dates) for Qinghai Lake from 1979 to 2016 using Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) passive microwave brightness temperature data. The corresponding freezing duration, ablation duration, complete freezing duration and ice coverage duration are... (More)
Lake ice is a sensitive indicator of climate change. Based on the disparities between the brightness temperatures of lake ice and water, passive microwave data can be used to monitor the ice variations of a lake. With focus on the analysis of long time series variability of lake ice, this study extracts four characteristic dates related to lake ice (the annual freeze start, freeze completion, ablation start and ablation completion dates) for Qinghai Lake from 1979 to 2016 using Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) passive microwave brightness temperature data. The corresponding freezing duration, ablation duration, complete freezing duration and ice coverage duration are calculated. Applying Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow products, the accuracy of the results derived from passive microwave data is validated. The validation analysis shows a strong agreement (R2 ranges from 0.70 to 0.85, mean absolute error (MAE) ranges from 2.25 to 3.94 days) in the freeze start, ablation start, and ablation completion dates derived from the MODIS data and passive microwave data; the ice coverage duration also has a small error (relative error (RE) = 2.95%, MAE = 3.13 days), suggesting that the results obtained from passive microwave data are reliable. The results show that the freezing dates of Qinghai Lake have been delayed and the ablation dates have advanced. Over 38 years, the freeze start date and freeze completion date have been pushed back by 6.16 days and 2.27 days, respectively, while the ablation start date and ablation completion date have advanced by 11.24 days and 14.09 days, respectively. The freezing duration and ablation duration have shortened by 3.89 days and 2.85 days, respectively, and the complete freezing duration and ice coverage duration have shortened by 14.84 days and 21.21 days, respectively. There is a significant negative correlation between the ice coverage duration and the mean air temperature in winter.
(Less)
- author
- Cai, Yu ; Ke, Chang Qing and Duan, Zheng LU
- publishing date
- 2017-12-31
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Climate warming, Freeze-thaw dates, Lake ice, MODIS, Passive microwave remote sensing, Qinghai Lake
- in
- Science of the Total Environment
- volume
- 607-608
- pages
- 12 pages
- publisher
- Elsevier
- external identifiers
-
- scopus:85021767340
- ISSN
- 0048-9697
- DOI
- 10.1016/j.scitotenv.2017.07.027
- language
- English
- LU publication?
- no
- id
- bc46a929-9eaa-4335-90fb-98369b1085f1
- date added to LUP
- 2019-12-22 20:23:14
- date last changed
- 2022-04-10 23:14:50
@article{bc46a929-9eaa-4335-90fb-98369b1085f1,
abstract = {{<p>Lake ice is a sensitive indicator of climate change. Based on the disparities between the brightness temperatures of lake ice and water, passive microwave data can be used to monitor the ice variations of a lake. With focus on the analysis of long time series variability of lake ice, this study extracts four characteristic dates related to lake ice (the annual freeze start, freeze completion, ablation start and ablation completion dates) for Qinghai Lake from 1979 to 2016 using Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) passive microwave brightness temperature data. The corresponding freezing duration, ablation duration, complete freezing duration and ice coverage duration are calculated. Applying Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow products, the accuracy of the results derived from passive microwave data is validated. The validation analysis shows a strong agreement (R<sup>2</sup> ranges from 0.70 to 0.85, mean absolute error (MAE) ranges from 2.25 to 3.94 days) in the freeze start, ablation start, and ablation completion dates derived from the MODIS data and passive microwave data; the ice coverage duration also has a small error (relative error (RE) = 2.95%, MAE = 3.13 days), suggesting that the results obtained from passive microwave data are reliable. The results show that the freezing dates of Qinghai Lake have been delayed and the ablation dates have advanced. Over 38 years, the freeze start date and freeze completion date have been pushed back by 6.16 days and 2.27 days, respectively, while the ablation start date and ablation completion date have advanced by 11.24 days and 14.09 days, respectively. The freezing duration and ablation duration have shortened by 3.89 days and 2.85 days, respectively, and the complete freezing duration and ice coverage duration have shortened by 14.84 days and 21.21 days, respectively. There is a significant negative correlation between the ice coverage duration and the mean air temperature in winter.</p>}},
author = {{Cai, Yu and Ke, Chang Qing and Duan, Zheng}},
issn = {{0048-9697}},
keywords = {{Climate warming; Freeze-thaw dates; Lake ice; MODIS; Passive microwave remote sensing; Qinghai Lake}},
language = {{eng}},
month = {{12}},
pages = {{120--131}},
publisher = {{Elsevier}},
series = {{Science of the Total Environment}},
title = {{Monitoring ice variations in Qinghai Lake from 1979 to 2016 using passive microwave remote sensing data}},
url = {{http://dx.doi.org/10.1016/j.scitotenv.2017.07.027}},
doi = {{10.1016/j.scitotenv.2017.07.027}},
volume = {{607-608}},
year = {{2017}},
}