Climate History from the Paleosalinity of Lakes in the Northern Great Plains

预测未来气候需要可靠的 循环模型。 最不可靠的参数估计 目前的GCM是净水分，降水少蒸发。 该提案要求支持解决这一问题， 开发新的方法来重建过去的水分（P-E）， 将结果与GCM的水分计算值进行比较 模拟 PI将开发一种定量方法， 利用硅藻重建过去的有效水分（P-E） 6-8个湖泊的介形虫组合和地球化学变化 横跨大平原的湿度梯度 详细 盐度波动将被校准到当地 该地区的气象记录，以获得一个独特的转移 功能 然后利用传递函数进行重构 大平原的盐度历史 冰川作用 这项研究很重要，因为它将提供 更准确地估计过去的降水和蒸发， 这个气候敏感的地区，它将提供最好的 基线数据与GCM对过去气候的模拟进行比较。

Predictions of future climate require reliable General Circulation Models. And the least reliable parameter estimated by current GCMs is net moisture, precipitation less evaporation. This proposal requests support to address this problem by developing new methods to reconstruct past moisture (P-E) and to compare the results to calculated values of moisture from GCM simulations. The PIs will develop a quantitative method for reconstructing past effective moisture (P-E) using diatom assemblages and ostracod geochemistry variations in 6-8 lakes which span the moisture gradients of the Great Plains. Detailed salinity fluctuations will be calibrated to the local meteorological records for the region to derive a unique transfer function. Then the transfer function will be used to reconstruct the history of salinity in the Great Plains since the last glaciation. This research is important because it will provide more accurate estimates of past precipitation and evaporation in this climatically sensitive region, and it will provide the best baseline data to compare to GCM simulations of past climate.