GSTDTAP
项目编号1805213
Collaborative Research: P2C2--Multi-Time-Scale Climate Dynamics in California (CA): An Integrated Multi-Proxy Stalagmite, Monitoring, and Modeling Approach
Peter Swart
主持机构University of Miami Rosenstiel School of Marine&Atmospheric Sci
项目开始年2018
2018-09-01
项目结束日期2021-08-31
资助机构US-NSF
项目类别Continuing grant
项目经费36913(USD)
国家美国
语种英语
英文摘要Southwest North America (SWNA) is one of the world's most climatically sensitive regions with inherently variable hydroclimate. Much evidence exists for repeated, large regime shifts in this region's hydroclimate at the sub-decadal to millennial-scale during the last glacial cycle and Holocene, but the mechanisms driving this change remain uncertain. In the context of this past variability and the potential magnitude of future climate change, a refined understanding of the hydroclimate response to perturbation and of the underlying driving mechanisms is needed.

The research team aims to generate a set of multiproxy calcite and fluid inclusion records, resolved at the sub-decadal to centennial-scale, for four stalagmites from the central and southern Sierra Nevada, CA that span the last deglaciation through Holocene. By integrating high-precision Uranium-Thorium dating, cave monitoring, multi-stalagmite records, and Earth system modeling (single-forcing water-isotope tracking simulations), the research team will (1) evaluate how North Pacific storm track behavior and the resulting precipitation signal is archived in the stalagmite proxy records, and (2) apply this knowledge to investigating the mechanisms underlying this precipitation response in the context of the changing environmental forcings of the past 21,000 years.

Integration of the new Sierra Nevada records with complementary stalagmite records being developed for coastal and northern CA will permit a regionally expansive investigation of the mechanisms influencing storm track behavior and precipitation patterns in SWNA. Data-model comparisons with the new isotope-enabled Transient Climate Evolution since 21-ka simulations (iTraCE-21ka model) will provide further insight into the global drivers and response time of climate in the western U.S. to different forcings. An integrated cave monitoring-stalagmite proxy-water isotope modeling approach could provide (1) insight into how climate and karst processes imprint stalagmite proxy records, and (2) much needed quantitative constraints on how paleo-precipitation in the western U.S. responded to evolving climate conditions.

The potential Broader Impacts (B.I.) include three outreach activities to integrate under-represented high school and undergraduate students into the Sierran stalagmite project and distribute the findings to the public. (1) A team (n=8) of undergraduate students will be formally integrated into the research through the development of a Vertically Integrated Project (VIP) at UC Davis (C3Climate Change in California). This program, supported by a grant from the Helmsley Charitable Trust to the VIP Consortium (UCD is one of 16 universities that participate), will involve weekly seminars, peer-mentoring, and team-based research in the cave-monitoring component. (2) A climate science-based curriculum will be developed for Vacaville (CA) High School, a Hispanic serving institution. The curriculum will integrate aspects of the stalagmite study and target development of critical-thinking skills. (3) An interactive cave exhibit involving a virtual reality research tour and 3-D stalagmite reconstructions will be built for the Sierra Nevada Recreation Corporation (owner of two of the Sierran caves targeted for study). The project would also include support for graduate education.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
文献类型项目
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/73152
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Peter Swart.Collaborative Research: P2C2--Multi-Time-Scale Climate Dynamics in California (CA): An Integrated Multi-Proxy Stalagmite, Monitoring, and Modeling Approach.2018.
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