EAR-PF: Reconstructing late Holocene hydroclimatic variability in western Central America using multi-proxy analyses of lacustrine sediments

Derek Gibson博士被授予NSF EAR博士后奖学金，在Jonathan Obrist-Farmer博士的指导下，他将在密苏里州科技大学开展研究和教育计划。过去十年，极端的水文气候，特别是干旱，导致来自中美洲的气候难民史无前例地增加，造成人道主义、经济和国家安全危机。目前的气候模型预测，到本世纪末，中美洲的降水量将进一步减少。然而，用于预测这种变化的模型依赖于过去气候变化的记录，目前反映中美洲过去降水变化的区域数据很少。该项目将使用从危地马拉和墨西哥南部收集的沉积物岩心来提供中美洲过去2000年降水变化的证据。反过来，这些新的记录将改进目前对中美洲降水的预测模型，这对于在中美洲建立一个适应气候变化的未来并在未来几十年减少气候驱动的人类迁徙的程度至关重要。除了产生新的气候数据外，K-12伙伴关系还将通过教育下一代科学家了解气候变化的机制和影响来扩大这项研究的影响。教育活动和国际合作将涉及从小学到研究生的学生，并为历史上服务不足的学生提供机会，为解决21世纪的主要气候科学问题之一作出贡献。可预测的降水模式对中美洲的粮食安全和经济稳定至关重要。然而，当前气候模型之间的模型间异质性，部分是由于缺乏跨越全新世晚期的高分辨率和局部尺度的古气候记录，使得对未来降水的可靠预测变得困难。拟议的研究将利用危地马拉和尤卡坦半岛六个流域的沉积物岩心，在中世纪气候异常、小冰期和当前暖期期间发生的天气尺度气候变化的背景下，对当地尺度的水文气候变异性进行多指标重建。拟议的现场选址使从这些选址收集的沉积物岩芯可用于调查热带辐合带、加勒比低空急流、厄尔尼诺南方涛动和地形的相对影响随时间的变化情况。具体地说，保存在沉积物岩芯中的叶蜡长链(n-C27，n-C29，n-C31)正构烷烃中δ2H的地层变异性将被用来代替区域水文气候变异性，而短链(n-C21，n C23)正构烷烃的δ2H将被用来重建局部(水柱到流域)尺度上的降水/蒸发平衡。这些数据将是中美洲气候复原力和适应计划中使用的预测模型的关键组成部分，这些模型必须在气候驱动的人类迁移导致进一步痛苦之前实施。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Dr. Derek Gibson has been awarded an NSF EAR Postdoctoral Fellowship to carry out research and education plans at Missouri University of Science and Technology under the mentorship of Dr. Jonathan Obrist-Farmer. Hydroclimate extremes, particularly droughts, have resulted in an unprecedented increase in climate refugees from Central America over the past decade, creating a humanitarian, economic, and national security crisis. Current climate models predict that Central American precipitation will further decrease by the end of the century. However, the models used to predict such changes rely on records of past climate change and, at present, regional data that reflect how Central American precipitation changed in the past are sparse. This project will use sediment cores collected from Guatemala and southern Mexico to produce evidence of past changes in Central American precipitation that spans the past 2,000 years. In turn, these new records will improve current predictive models of Central American precipitation, which is critical to building a climate-resilient future in Central America and reducing the extent of climate-driven human migration over the upcoming decades. In addition to producing new climate data, K-12 partnerships will extend the impact of this research by educating the next generation of scientists on the mechanisms and impacts of climate change. Educational activities and international collaborations will involve students from elementary to graduate school and provide opportunities for historically underserved students to contribute to solving one of the major climate science questions of the 21st century.Predictable precipitation patterns are critical to the food security and economic stability of Central America. However, inter-model heterogeneity among current climate models, due in part to a paucity of high-resolution and local-scale paleoclimate records that span the late Holocene, make reliable projections of future precipitation difficult. The proposed research will utilize sediment cores from six watersheds located across Guatemala and the Yucatán Peninsula in order to produce multi-proxy reconstructions of local-scale hydroclimatic variability within the context of the synoptic-scale climate changes that occurred during the Medieval Climate Anomaly, Little Ice Age, and Current Warm Period. The proposed field sites are situated such that sediment cores collected from these sites can be used to investigate variability through time in the relative influences of the Inter-tropical Convergence Zone, Caribbean Low-Level Jet, El Niño Southern Oscillation, and topography. Specifically, stratigraphic variability of δ2H in leaf-wax long chain (n-C27, n-C29, n-C31) n-alkanes preserved in the sediment cores will be used as a proxy for regional hydroclimatic variability, while the δ2H of short chain (n-C21, n C23) n-alkanes will be used to reconstruct precipitation/evaporation balance at the local (water column to watershed) scale. These data will be a critical component of predictive models used in the Central American climate resilience and adaptation plans that must be implemented before climate-driven human migration leads to further suffering.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.