Ground-penetrating radar (GPR) reflection profiles were interpreted and combined with sedimentological data to highlight the morpho-evolutionary history of the southwestern sector of the Bohai Sea. The internal structures in GPR images obtained near the Holocene maximum transgression boundary revealed concave-upward and onlap types of transgressive paleotopography. The relationship between historical courses of the Yellow River and the distribution of shell ridges at three periods (6 ka, 2 ka, and recent times) showed that the concave-upward types derived from the marine sediments overlap the fluvial sediments, and the onlap types from the marine sediments cover the coastal lagoon sediments. Based on the above paleogeographical setting, previous sea-level markers were corrected, taking into account uncertainties of their relationship to former water levels. The rates of vertical tectonic displacement, evaluated through comparison of the relative sea level (RSL) data from the GPR images and the Holocene predicted sea-level elevation, markedly affected RSL changes. The fitted RSL curves from the corrected sea-level indicators showed that the accuracy of former sea-level determinations can be improved by comparing with the maximum transgressive position of GPR detection. A topographic digital elevation model (DEM) for 6 ka is reconstructed based on the corrected data.
Abstract. Arctic sea ice drift motion affects the global material balance, energy exchange and climate change and seriously affects the navigational safety of ships along certain channels. Due to the Arctic's special geographical location and harsh natural conditions, observations and broad understanding of the Arctic sea ice motion are very limited. In this study, sea ice motion data released by the National Snow and Ice Data Center (NSIDC) were used to analyze the climatological, spatial and temporal characteristics of the Arctic sea ice drift from 1979 to 2018 and to understand the multiscale variation characteristics of the three major Arctic sea ice drift patterns. The empirical orthogonal function (EOF) analysis method was used to extract the three main sea ice drift patterns, which are the anticyclonic sea ice drift circulation pattern on the scale of the Arctic basin, the average sea ice transport pattern from the Arctic Ocean to the Fram Strait, and the transport pattern moving ice between the Kara Sea (KS) and the northern coast of Alaska. By using the ensemble empirical mode decomposition (EEMD) method, each temporal coefficient series extracted by the EOF method was decomposed into multiple timescale sequences. We found that the three major drift patterns have four significant interannual variation periods of approximately 1, 2, 4 and 8 years. Furthermore, the second pattern has a significant interdecadal variation characteristic with a period of approximately 19 years, while the other two patterns have no significant interdecadal variation characteristics. Combined with the atmospheric and oceanic geophysical variables, the results of the correlation analysis show that the first EOF sea ice drift pattern is mainly related to atmospheric environmental factors, the second pattern is related to the joint action of atmospheric and oceanic factors, and the third pattern is mainly related to oceanic factors. Our study suggests that the ocean environment also has a strong correlation with sea ice movement. Especially for some sea ice transport patterns, the correlation even exceeds atmospheric forcing.
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