Metocean data management and modeling to support U.S. offshore wind power development in the Mid-Atlantic

Efforts to encourage more conservative electricity consumption, through public awareness campaigns and government-mandated energy efficiency standards, have consistently been overshadowed by population increase and increased standards of living, leading to higher electricity demand, year after year. Sufficient resources and technology exist to support the development of a robust offshore wind industry to help meet this rising demand, but a number of barriers unique to the U.S. have hindered progress. Addressing many of these obstacles involves resolving uncertainty issues related to development. Not only is there a general lack of data to provide stakeholders, developers, and governing authorities with sufficient information for informed decision-making for offshore wind projects, but the data that do exist are often fragmented or isolated within a particular project or application. There is an immediate need to improve the reliability of metocean data as it pertains to characterizing the offshore wind resource, and to share that and other related information in a standard format that promotes and encourages interoperability across multiple platforms associated with offshore wind development. The methodology for addressing some of these data challenges began with the evaluation of a proposed improvement to a particular atmospheric modeling system being utilized to provide wind resource data within the “Virginia Offshore Wind Advanced Technology Demonstration Site Development” project. By considering the current limitations associated with SST data acquisition and initial analyses, it was determined that the integration of higher resolution SST data would be valuable only if latency issues in the data were resolved, which would require the development of an SST forecasting mode to be coupled with the operational model. This did not prove justifiable due to the lack of significant improvements in wind speed forecasting capability. Data accessibility issues were then addressed in the development of a web mapping portal designed to dynamically display geo-referenced project results and integrate publicly-available metocean data. By utilizing best practices for data sharing and information dissemination, optimum interoperability was established through smart design and the use of standard web service protocols

Maximal Independent Sets In Graphs With At Most r Cycles

We find the maximum number of maximal independent sets in two families of graphs: all graphs with $n$ vertices and at most $r$ cycles, and all such graphs that are also connected. In addition, we characterize the extremal graphs.Comment: 31 pages, 11 figures, Latex, see related papers at http://www.math.msu.edu/~sagan, split paper into two part

A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix

This paper describes a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction. It also establishes consistency of the estimated covariance matrix under fairly general conditions.

An investigation of the utilization of four study areas in Yaquina Bay, Oregon, by hatchery and wild juvenile salmonids

Results of a study of spatial and temporal utilization of a tidal river estuary by hatchery and wild juvenile salmonids (Oncorhynchus spp. and Salmo spp,), of overlap in food habits of hatchery and wild juvenile salmonids, and of size and relative abundance of associated fish species are reported in this thesis. The investigation was conducted in Yaquina Bay, Oregon in 1977 and 1978 to provide information for evaluation of concerns over the biological impact of large releases of hatchery salmon on wild fish in the estuary. A 100- X 3-m beach seine was used to sample four beach study areas from July 1977 through December 1978, and a 222-m lampara net was used to sample two channel study areas from March 1978 through October 1978. Approximately 2. 2 million hatchery salmon were released into Yaquina Bay in 1977, and 9.6 million were released in 1978. Tags, fin clips, dye marks, scales, species, release date, external parasites, visceral fat, size, and fin erosion were used to determine hatchery or wild origin of individual salmonids in the catch. Chinook (Oncorhynchus tshawytscha), chum (0. keta), and coho (0. kisutch) salmon, in decreasing order, were the most abundant wild salmonid species, and coho salmon were the most abundant hatchery species. In 1978 wild populations of chum and coho salmon were present in the estuary for 2-3 mo (March-June), and wild Chinook were present during 9 mo (January, April-November). Increase in mean length of wild chum and Chinook, and decrease in mean length of wild coho, indicated that wild chum and Chinook utilized the estuary as a rearing area, and wild coho did not. Lack of overlap in peak migration periods of wild chum (early April), coho (mid May), and chinook (late July-early August) suggests the need to minimize overlap in utilization of the estuary by hatchery and wild juvenile salmonids. The length of residence of hatchery coho in Yaquina Bay was described by the equation: N=N 0 e-kt. The "residency half-life" (E®2) ranged from 1. 7 to 9. 0 days for different No release groups of hatchery coho in 1977 and 1978. Juvenile hatchery coho that remained for an extended period (1-3 mo) in Yaquina Bay during 1977 increased in mean length from 11.5 cm FL in mid July to 21. 0 cm FL in October. Some individuals within summer release groups of hatchery chinook also remained in the estuary for extended periods (> 2 mo)a Groups of juvenile hatchery coho and chinook released into Yaquina Bay earlier in the year (June-August) remained in the estuary for longer periods than groups released later in the year (September-October), Overlap in food habits of hatchery and wild juvenile salmonids in the estuary was C ften high, although overlap was found to vary with species, time, habitat, space, length of estuarine residence, and prey abundance. In terms of biomass, larval and juvenile fish (Clupeidae, Engraulidae, and Osmeridae) were the most important prey organisms of hatchery and wild coho and chinook salmon in Yaquina Bay. Approximately 58 fish species were captured at the study areas in 1977 and 1978, and 17 were identified in the stomach contents of hatchery and wild salmonids. Overlap in spatial and temporal utilization and in food habits of hatchery and wild juvenile salmon in the estuary indicates that the potential for competition between these groups does exist, should space or food resources become a limiting factor. To reduce overlap in spatial and temporal utilization, consideration should be given to not releasing hatchery salmon during peak migration periods of wild chum, coho, and chinook salmon. To reduce length of residence of hatchery coho and chinook released after May, mid to late summer releases should be considered

Automatic Lag Selection in Covariance Matrix Estimation

We propose a nonparametric method for automatically selecting the number of autocovariances to use in computing a heteroskedasticity and autocorrelation consistent covariance matrix. For a given kernel for weighting the autocovariances, we prove that our procedure is asymptotically equivalent to one that is optimal under a mean squared error loss function. Monte Carlo simulations suggest that our procedure performs tolerably well, although it does result in size distortions.