Collaborative Research: Decoding and Predicting Greenland's Surface Melt History and Future with Observations, Regional Atmospheric Modeling, and GCMs

研究人员计划进行为期三年的努力，以提高对格陵兰冰盖表面融化的理解和预测。卫星遥感、区域气候建模和非线性分析技术将用于：评估观测到的表面融化发生的变化;基准模型融化代理与观测到的融化;诊断天气尺度气象/海冰对融化的控制;以及评估基于CMIP 5（耦合模型相互比较项目第5阶段）大气环流模型驱动的区域模型的融化代理的未来变化。了解极地冰盖的表面融化是很重要的，因为表面融化会影响南极洲，可以产生有用的古气候记录，通过径流有助于物质平衡，并且是冰架崩溃的触发器，导致冰流加速和海平面上升。更好地了解融化的天气学-气象学原因以及最新模型准确模拟融化的能力，将有助于评估未来变暖对融化、冰盖流动和海平面上升的影响。研究人员提出了三个主要的研究主题，以帮助解决这些问题：（1）区域大气模式的技能评估和诊断目前的天气控制地面融化;（2）应用模式技能评估的结果，以GCM为基础的气候情景估计未来的变化;和（3）通过使用无源微波和光学/光学的新型融合来检索融化量级，扩大基于卫星的表面融化状态表征检索卫星热数据除了解决格陵兰冰盖平衡与海平面变化有关的关键问题外，该项目还包括主要通过一个网站向公众进行宣传，并产生许多教育影响。该项目将支持本科生和研究生，并涉及来自一个主要的本科机构的调查人员与第一代大学生的显着人口，并从西班牙裔服务机构。所有数据和模型结果将通过ACADIS数据中心存档和提供。

The investigators plan a three-year effort to improve understanding and prediction of surface melting on the Greenland ice sheet. Satellite remote-sensing, regional climate modeling and nonlinear analysis techniques will be used to: assess variability of observed surface melt occurrence; benchmark model-based melt proxies versus observed melt; diagnose synoptic-scale meteorological/sea-ice controls on melt; and assess future change in melt proxies based on regional models driven by CMIP5 (Coupled Model Intercomparison Project Phase 5) general circulation models (GCMs). Understanding surface melt on polar ice sheets is important because surface melt affects albedo, can produce useful paleoclimatic records, contributes to mass balance through runoff, and is a trigger for ice-shelf collapse leading to ice-flow acceleration and sea-level rise. Improved understanding of the synoptic-meteorological causes of melting, and of the ability of state-of-the-art models to simulate melting accurately, would help assess the effects of future warming on melting, ice-sheet flow and sea level rise. The investigators propose three main research themes to help address these issues: (1) regional-atmospheric-model skill assessments and diagnosis of present synoptic controls on surface melt; (2) application of results from the model skill assessments to GCM-based climate scenarios for estimates of future change; and (3) expanding satellite-based retrieval of surface melt state characterization through retrieval of melt magnitude using a novel fusion of passive microwave and optical/thermal satellite data. In addition to addressing key questions relating Greenland ice sheet balance to sea-level change, the project includes outreach to the public, primarily through a web site, and numerous educational impacts. The project would support undergraduate and graduate students, and involves investigators from a primarily undergraduate institution with a significant population of first-generation college students, and from a Hispanic-serving institution. All data and model results will be archived and made available through the ACADIS data center.