Collaborative Research: Decoding & Predicting Greenland's Surface Melt History & 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、区域气候模拟和非线性分析技术将用于：评估观测到的地表融化发生的变异性；基于基准模型的熔体代理与观察到的熔体；诊断天气尺度的气象/海冰对融化的控制；并基于CMIP5（耦合模式比对项目第5阶段）环流模式驱动的区域模式评估未来熔体代用物的变化。了解极地冰盖的表面融化是很重要的，因为表面融化影响反照率，可以产生有用的古气候记录，有助于通过径流实现物质平衡，并且是导致冰流加速和海平面上升的冰架崩塌的触发因素。对冰川融化的天气气象原因的进一步了解，以及对最先进的模型精确模拟冰川融化能力的进一步了解，将有助于评估未来变暖对冰川融化、冰盖流动和海平面上升的影响。为了解决这些问题，研究人员提出了三个主要的研究主题：(1)区域-大气模式技能评估和地表融化当前天气控制的诊断；(2)将模式技能评估结果应用于基于gcm的气候情景，以估算未来变化；(3)利用一种新的无源微波和光学/热卫星数据融合的方法，通过检索熔体大小来扩展基于卫星的表面熔体状态特征检索。除了解决有关格陵兰冰盖平衡与海平面变化的关键问题外，该项目还包括主要通过一个网站向公众宣传，并产生许多教育影响。该项目将支持本科生和研究生，并涉及来自主要本科生机构的调查人员，该机构拥有大量第一代大学生，以及来自西班牙裔服务机构的调查人员。所有数据和模型结果将被存档并通过ACADIS数据中心提供。

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.