Abstract

AbstractThe continental terrestrial record preserves an archive of how ancient sedimentary systems respond to and record changes in global climate. A database-driven quantitative assessment reveals differences in the preserved sedimentary architectures of siliciclastic eolian systems with broad geographic and stratigraphic distribution that developed under icehouse versus greenhouse climatic conditions. Over 5600 geological entities, including architectural elements, facies, sediment textures, and bounding surfaces, have been analyzed from 34 eolian systems of Paleoproterozoic to Cenozoic ages. Statistical analyses have been performed on the abundance, composition, preserved thickness, and arrangement of different eolian lithofacies, architectural elements, and bounding surfaces. Results demonstrate that preserved sedimentary architectures of icehouse and greenhouse systems differ markedly. Eolian dune, sand sheet, and interdune architectural elements that accumulated under icehouse conditions are significantly thinner relative to their greenhouse counterparts; this is observed across all basin settings, supercontinents, geological ages, and dune field physiographic settings. However, this difference between icehouse and greenhouse eolian systems is exclusively observed for paleolatitudes <30°, which suggests that climate-induced changes in the strength and circulation patterns of trade winds may have partly controlled eolian sand accumulation. These changes acted in combination with variations in water table levels, sand supply, and sand transport, ultimately influencing the nature of long-term sediment preservation. During icehouse episodes, Milankovitch cyclicity resulted in deposits typified by glacial accumulation and interglacial deflation. Greenhouse conditions promoted the accumulation of eolian elements into the geological record due to elevated water tables and biogenic- and chemical-stabilizing agents, which could protect deposits from wind-driven deflation. In the context of a rapidly changing climate, the results presented here can help predict the impact of climate change on Earth surface processes.

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