MRI Track 1: Acquisition of High Performance Computing to Model Coastal Responses to a Changing Environment

缅因州海湾正在经历前所未有的变化，由于气候和人为因素的综合影响。按照某些标准，缅因州湾是世界上海洋变暖最快的地区之一。在过去的世纪里，这种变暖趋势与极端事件（定义为前1%的风暴）增加了73%同时发生。这些变化的潜在影响对一个与海洋资源和基础设施密切相关的经济体来说是重大的。从2005年到2013年，缅因州的水产养殖业（主要包括鲑鱼和贝类）的产值翻了一番，现在仅次于该州的龙虾业。2014年，缅因州的商业渔业价值达到创纪录的5.85亿美元。沿海地区自然资源和基础设施的有效管理需要建模工具，这些工具不仅可以帮助我们了解环境驱动因素中自然和人为变化的生态和物理后果，还可以帮助我们预测这些变化并权衡适应或缓解的成本和收益。准确、及时地预报强风暴和沿海洪水对确保海上活动安全、保护沿海沿着的生命财产安全至关重要。为了进一步开发这些建模工具，为缅因州的沿海经济，缅因州大学将显着增加其高性能计算，以满足沿海地区所面临的严峻问题。具体而言，增加缅因州大学的计算能力将使沿海建模人员能够提高模型的空间分辨率，以告知在当地尺度上做出的决策（例如，水产养殖租赁），并显著增加本科生和研究生获得高性能计算的机会。因此，可以培训新一代熟悉先进计算的科学家，以开发不断变化的沿海生态系统所需的环境决策支持基础设施。缅因州大学是海洋科学研究和教育的国际和国家领导者，因此，依赖沿海资源和基础设施的社区希望大学告知他们即将发生的变化。缅因州在地理和经济上都处于受气候变化影响的独特地位。该州坐落在世界上纬度梯度最大的地区之一，拥有全国最长的海岸线。沿着渔业和水产养殖系统的未来很难预测。然而，预测未来潜在变化的多种情景的能力将使管理人员和决策者能够适应。投资提高高性能计算有四个原因：（1）空间分辨率的提高将允许目前正在开发的模型解析更精细尺度的特征，并为在小于100米的尺度上做出的许多决策提供信息，（2）当前的高性能计算集群以接近满负荷的方式运行，减少了研究生和本科生的教育机会，（3）使用动态降尺度而不是更简单的方法将气候变化预测与区域尺度联系起来需要更大的处理能力，（4）运行未来变化的多种情景的能力将更充分地表征不确定性。该集群系统将有28个节点，每个节点配备两个12核Intel Xeon 2.6 GHz CPU（最新的Haswell v3芯片）。这将包括672个核心，并将产生约28个峰值TFlops。这几乎使缅因州大学的高性能计算能力增加了两倍。

The Gulf of Maine is undergoing unprecedented change due to a combination of influences from climatic and anthropogenic sources. By some measures, the Gulf of Maine is among the fastest warming regions of the world's oceans. This warming trend has been concurrent with a 73% increase in extreme events, defined as the top 1% of storms, over the past century. The potential impact of these changes are significant for an economy tightly linked to marine resources and infrastructure. Maine's aquaculture industry (comprising mostly salmon and shellfish) has doubled in value from 2005 to 2013 and is now second only to the lobster industry in the state. Maine's commercial fisheries were valued at a record $585 million dollars in 2014. The effective management of natural resources and infrastructure in the coastal zone requires modeling tools that not only help us understand the ecological and physical consequences of natural and human-induced changes in environmental drivers, but also help us predict those changes and weigh the costs and benefits of adaptation or mitigation. The accurate and timely forecasts of severe storms and coastal inundation are critical to ensure safe maritime activities, protect life and property along the coast. To further the development of these modeling tools for the coastal economy of Maine, the University of Maine will significantly increase its high performance computing to meet the rigors of problems faced by the coastal zone. Specifically, increasing the computing capacity at the University of Maine will allow coastal modelers to increase the spatial resolution of models to inform decisions made on local scales (e.g., aquaculture leases) and significantly increase access to high performance computing for undergraduate and graduate students. Consequently, a new generation of scientists familiar with advanced computing can be trained to develop the environmental decision support infrastructure needed in changing coastal ecosystems. The University of Maine is an established international and national leader in marine science research and education and as such, the community that relies on coastal resources and infrastructure looks to the University to inform them of impending changes. Maine is uniquely positioned physically and economically to be affected by climate change. The state sits on one of the sharpest latitudinal gradients in temperature in the world and has one of the longest coastlines in the country. What the future holds for fisheries and aquaculture systems along the coast is difficult to predict. However, the capacity to forecast multiple scenarios of potential future change will allow managers and decision makers the ability to adapt. There are four reasons for an investment in increased high performance computing: (1) an increase in spatial resolution will allow models currently under development to resolve finer scale features and inform many decisions made on the scale of less than 100 m, (2) the current high performance computing cluster runs at near full capacity, reducing educational opportunities for graduate and undergraduate students, (3) linking climate change projections to the regional scale using dynamic downscaling as opposed to simpler methods requires more processing capacity, and (4) the ability to run multiple scenarios of future change will more adequately characterize uncertainty. The cluster system will have 28 nodes, each with two 12 core Intel Xeon 2.6 GHz CPU's, the latest Haswell v3 chips. This will comprise 672 cores and will yield about 28 peak TFlops. This nearly triples the high performance computing power at the University of Maine.