Collaborative Research: A pan-Arctic, storm-by-storm isotopic investigation of the influence of Arctic sea ice on precipitation - a crucial link in the coupled climate system

该项目将量化北冰洋及其周边海域的无冰区与北极地区的蒸发和降水之间的关系。该方法使用了每一场风暴降水样本的同位素组成、泛北极气象数据和数值模拟。降水样本将由9个北极观测站和格陵兰岛的3所高中收集。样品将分析D/H和18O/16O比率。给定风暴的轨迹将使用再分析数据和拉格朗日轨迹算法重建。然后对湿气源进行局部定位，并且18 o,, # 948;利用海表温度、相对湿度和风速计算源蒸气的D和D -excess。利用高分辨率卫星产品获得每次风暴所横切的海冰面积。利用拉格朗日反轨迹确定的时间和区域的气象变量再分析值，并假设一定范围的海冰浓度，将使用大气湿度循环的二维（2D）模型来计算每个站点每次风暴降水的同位素组成。然后将最符合我们同位素测量值的海冰浓度与卫星海冰数据进行比较。因此，同位素数据将通过二维模型得出北极蒸发和降水对冰区的敏感性。该项目将对海冰、水汽来源和北极降水数量之间的联系产生定量的了解，这些联系构成了大范围时间尺度上气候动力学的重要组成部分。其结果将与冰芯数据的解释、冰期动力学、突然气候变化和全球变暖有关。该项目还打算将研究与教育和推广结合起来，这将直接使参与的北极社区受益。该项目旨在通过为北极学生提供新的知识和技能，并鼓励他们继续深造，提高社区对气候变化研究如何进行的理解。与此同时，PI将从参与研究的社区学习观察、分类和预测天气和气候的传统方法中受益。

This project will quantify the relationship between the ice-free area of the Arctic Ocean and surrounding seas, and evaporation and precipitation in the Arctic region. The methodology uses isotopic compositions of storm-by-storm precipitation samples, pan-Arctic meteorological data, and numerical modeling. Precipitation samples will be collected at nine Arctic observatories, and by three high schools in Greenland. Samples will be analyzed for D/H and 18O/16O ratios. The track of a given storm will be reconstructed using reanalysis data and a Lagrangian trajectory algorithm. The moisture sources are then localized, and the δ18O, δD and d-excess of the source vapor are calculated using the sea surface temperature, relative humidity and wind speed. The sea ice area transected by each storm will be obtained using high-resolution satellite products. A two-dimensional (2D) model of the atmospheric moisture cycle will be used to compute the isotopic composition of precipitation for each storm at each site using reanalysis values of meteorological variables at the times and regions identified by the Lagrangian back trajectory, and assuming a range of sea ice concentrations. The sea ice concentration that best fits our isotopic measurements is then compared with the satellite sea ice data. The isotope data will thus yield, via the 2D model, the sensitivity of Arctic evaporation and precipitation to ice area. The project will yield a quantitative understanding of the links among sea ice, and moisture sources and amounts of Arctic precipitation, which comprise an important part of climate dynamics on a wide range of time scales. The results will be pertinent to the interpretation of ice core data, ice age dynamics, sudden climate change, and global warming. This project also intends to integrate research with education and outreach, which will directly benefit participating Arctic communities. The project aims to improve community understanding of how climate change research is done, by providing Arctic students with new knowledge and skills, and by inspiring them to pursue advanced studies. At the same time, the PI's will benefit from learning traditional methods of observing, categorizing, and forecasting weather and climate from the communities participating in the study.