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围海域的无冰区域与北极地区蒸发和降水之间的关系。该方法使用了逐个风暴的降水样本、泛北极气象数据和数值模拟的同位素组成。九个北极观测站和格陵兰岛的三所高中将采集降水样本。将对样品进行D/H和18O/16O的分析。将使用再分析数据和拉格朗日轨迹算法重建给定风暴的轨迹。然后定位水汽来源，并使用海面温度、相对湿度和风速计算来源水汽的&amp；18O、&d和d-过剩。每一次风暴横切的海冰面积将使用高分辨率卫星产品获得。将使用大气水分循环的二维(2D)模式，利用拉格朗日后向轨迹确定的时间和地区的气象变量的再分析值，并假设海冰浓度范围，计算每个地点每个风暴的降水同位素组成。然后将最符合我们的同位素测量的海冰密度与卫星海冰数据进行比较。因此，同位素数据将通过2D模式得出北极蒸发和降水对冰区的敏感性。该项目将使人们对海冰、水汽来源和北极降水量之间的联系有一个定量的了解，这是广泛时间尺度上气候动态的一个重要组成部分。这些结果将与冰芯数据、冰期动力学、气候突变和全球变暖的解释有关。该项目还打算将研究与教育和外联相结合，这将使参与的北极社区直接受益。该项目旨在通过向北极学生提供新的知识和技能，并通过激励他们继续深造，来提高社区对气候变化研究是如何进行的理解。与此同时，PI将受益于从参与研究的社区学习观察、分类和预报天气和气候的传统方法。

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.