AbstractsGeography &GIS

Periodicity and patterns of the global wind and wave climate

by Justin Edward Stopa




Institution: University of Hawaii – Manoa
Department:
Year: 2016
Keywords: Wind-generated waves; reanalysis datasets; climate research
Posted: 02/05/2017
Record ID: 2066704
Full text PDF: http://hdl.handle.net/10125/100753


Abstract

Ph.D. University of Hawaii at Manoa 2013. Wind-generated waves propagate across the oceans transporting energy that shapes the shorelines, influences maritime commerce, and defines coastal land-use around the world. Understanding the role of the ocean wind and wave climate is imperative for ocean engineering practices with both societal impacts and scientific contributions. The focus of this dissertation is the description of the patterns and cycles of the wind and wave climate through the use of reanalysis datasets that cover 1979 to 2009. The dissertation consists of three major parts, which examine the validity of the reanalysis datasets for climate research, verify climate signals in the datasets with published indices, and explore the dominant modes of variability. Over thirty years of high quality data from the recent release of the ECMWF Reanalysis Interim (ERA-I) and NCEP Climate Forecast System Reanalysis (CFSR) allows for studies of the global climate with unprecedented detail. Independent observations from altimeters and buoys to provide assessment of their consistency in time and space. Both have good spatial homogeneity with consistent levels of errors in the Northern and Southern Hemispheres representing a significant improvement over previous reanalyzes. ERA-I is homogenous through time, while CFSR exhibits an abrupt decrease in the level of errors in the Southern Ocean beginning in 1994. Although ERA-I proves to be a more consistent dataset, CFSR's increased resolution, enhanced small scale features, and ability to match the observed variability makes it an attractive option for climate research. The continuous 31 years of global wind and wave data from the CFSR datasets are assessed in terms of well established climate patterns and cycles. Quarterly averages and percentile plots of the wind speed and wave height illustrate the seasonal pattern and distributions of extreme events. Statistical analyses of the annual and inter-annual variability suggest relationships to established climate patterns. The data shows strong correlation with published indices of known atmospheric cycles of the Arctic Oscillation (AO), Antarctic Oscillation (AAO), and El Nino Southern Oscillation (ENSO) in both the wind and wave fields. The results are comparable with published climate studies confirming CFSR's use in the study of complex climate dynamics. A standard empirical orthogonal function method extracts dominant spatial structures from time series of CFSR. The results show strong zonal structures in the winds and saturation of swells across the ocean basins, but these dominant features obscure the periodicity of individual climate cycles. A combined method utilizing the Fourier transform and empirical orthogonal functions helps resolve cyclic features of the climate system. Each of the three major ocean basins is characterized by its dominant modes and periodicity. The analysis reveals that the Atlantic is saturated by signals from the Northern Hemisphere including a broad range of intra-seasonal components…