4.7 Article

Understanding Water Level Changes in the Great Lakes by an ICA-Based Merging of Multi-Mission Altimetry Measurements

期刊

REMOTE SENSING
卷 14, 期 20, 页码 -

出版社

MDPI
DOI: 10.3390/rs14205194

关键词

lake level changes; satellite altimetry; water level stations; CICA; the Great Lakes

资金

  1. National Natural Science Foundation of China [41874095, 41704013, 42061134010]
  2. Strategic Priority Research Program of the Chinese Academy of Sciences [XDA20100300, XDA15017700]
  3. Max-Planck-Society
  4. Chinese Academy of Sciences [QOP18098]
  5. Natural Science Fund for Distinguished Young Scholars of Hubei Province, China [2019CFA09]
  6. Danmarks Frie Forskningsfond [10.46540/2035-00247B]
  7. Cooperative Institute for Great Lakes Research [SUBK00011366]

向作者/读者索取更多资源

Accurately monitoring spatio-temporal changes in lake water levels is important for studying the impacts of climate change on freshwater resources, and for predicting natural hazards. In this study, multi-mission radar satellite altimetry data was used to reconstruct lake-wide spatio-temporal changes in water level. The results indicate a significant correlation between lake level changes and ENSO episodes.
Accurately monitoring spatio-temporal changes in lake water levels is important for studying the impacts of climate change on freshwater resources, and for predicting natural hazards. In this study, we applied multi-mission radar satellite altimetry data from the Laurentian Great Lakes, North America to optimally reconstruct multi-decadal lake-wide spatio-temporal changes of water level. We used the results to study physical processes such as teleconnections of El Nino and southern oscillation (ENSO) episodes over approximately the past three-and-a-half decades (1985-2018). First, we assessed three reconstruction methods, namely the standard empirical orthogonal function (EOF), complex EOF (CEOF), and complex independent component analysis (CICA), to model the lake-wide changes of water level. The performance of these techniques was evaluated using in-situ gauge data, after correcting the Glacial Isostatic Adjustment (GIA) process using a contemporary GIA forward model. While altimeter-measured water level was much less affected by GIA, the averaged gauge-measured water level was found to have increased up to 14 cm over the three decades. Our results indicate that the CICA-reconstructed 35-year lake level was more accurate than the other two techniques. The correlation coefficients between the CICA reconstruction and the in situ water-level data were 0.96, 0.99, 0.97, 0.97, and 0.95, for Lake Superior, Lake Michigan, Lake Huron, Lake Erie, and Lake Ontario, respectively; similar to 7% higher than the original altimetry data. The root mean squares of errors (RMSE) were 6.07 cm, 4.89 cm, 9.27 cm, 7.71 cm, and 9.88 cm, respectively, for each of the lakes, and similar to 44% less than differencing with the original altimetry data. Furthermore, the CICA results indicated that the water-level changes in the Great Lakes were significantly correlated with ENSO, with correlation coefficients of 0.5-0.8. The lake levels were similar to 25 cm higher (similar to 30 cm lower) than normal during EI Nino (La Nina) events.

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