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

GSTDTAP

项目编号	1532013
	MRI Track 1: Acquisition of High Performance Computing to Model Coastal Responses to a Changing Environment
	Damian Brady
主持机构	University of Maine
项目开始年	2015
	2015-08-15
项目结束日期	2018-07-31
资助机构	US-NSF
项目类别	Standard Grant
项目经费	266309(USD)
国家	美国
语种	英语
英文摘要	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.
来源学科分类	Geosciences - Ocean Sciences
文献类型	项目
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/68465
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	Damian Brady.MRI Track 1: Acquisition of High Performance Computing to Model Coastal Responses to a Changing Environment.2015.