Baker et al (2015) developed the Community Earth System Model Ensemble Consistency Test (CESM-ECT) to provide a metric for software quality assurance by determining statistical consistency between an ensemble of CESM outputs and new test runs. The test has proved useful for detecting statistical difference caused by compiler bugs and errors in physical modules. However, detection is only the necessary first step in finding the causes of statistical difference. The CESM is a vastly complex model comprised of millions of lines of code which is developed and maintained by a large community of software engineers and scientists. Any root cause analysis is correspondingly challenging. We propose a new capability for CESM-ECT: identifying the sections of code that cause statistical distinguishability. The first step is to discover CESM variables that cause CESM-ECT to classify new runs as statistically distinct, which we achieve via Randomized Logistic Regression. Next we use a tool developed to identify CESM components that define or compute the variables found in the first step. Finally, we employ the application Kernel GENerator (KGEN) created in Kim et al (2016) to detect fine-grained floating point differences. We demonstrate an example of the procedure and advance a plan to automate this process in our future work.

The partial reflection facility of the Polar Geophysical Institute (the Tumanny observatory, 69.0N, 35.7E) has observed behavior of the high-latitude lower ionosphere during the 20 March 2015 total solar eclipse. There were several effects during the eclipse. At the heights of 60–80 km the ionosphere has shown the effect of a “short night”, but at the higher altitudes local enhanced electron concentration had a wave-like form. Data received by the riometer of the Tumanny observatory have also shown wave-like behavior. The behavior can be explained by influence of acoustic-gravity waves which originated after cooling of the atmosphere during the lunar shadow supersonic movement, and transport processes during the eclipse. During the 21 August 2017 solar eclipse there was a substorm at the high latitudes. But after the end of the substorm in the region of the Tumanny observatory the observed amplitudes of the reflected waves had wave effects which could be connected with the coming waves from the region of the eclipse. The wave features were also shown in the behavior of the total electron content (TEC) of the lower ionosphere. During several solar eclipses it was implemented observations of lower ionosphere behavior by the partial reflection facility of the Tumanny observatory. The consideration of the lower ionosphere TEC had revealed common features in the TEC behavior during the eclipses. The photochemical theory of processes in the lower ionosphere is very complicated and up to now it is not completely developed. Therefore introduction of the effective coefficients determining the total speed of several important reactions has been widely adopted when modeling the D-region of the ionosphere. However, experimental opportunities for obtaining effective recombination coefficients are rather limited. One of the methods to estimate effective recombination coefficients uses the phenomenon of a solar eclipse. During solar eclipses at the partial reflection facility of the Tumanny observatory observations were carried out. It gave possibility to obtain the behavior of the electron concentration in time at the selected heights. Using the obtained experimental profiles, the effective recombination coefficients at the D-region heights of the ionosphere have been evaluated.

Scientific research is increasingly collaborative and globally distributed; research groups now rely on web- based scientific tools and data management systems to simplify their day-to-day collaborative workflows. However, such tools often lack seamless interfaces, requiring researchers to contend with manual data transfers, annotation and sharing. MyGeoHub is a web platform that supports out-of-the-box, seamless workflows involving data ingestion, metadata extraction, analysis, sharing and publication. MyGeoHub is built on the HUBzero cyberinfrastructure platform and adds general-purpose software building blocks (GABBs), for geospatial data management, visualization and analysis. A data management building block iData, processes geospatial files, extracting metadata for keyword and map-based search while enabling quick previews. iData is pervasive, allowing access through a web interface, scientific tools on MyGeoHub or even mobile field devices via a data service API. GABBs includes a Python map library as well as map widgets that in a few lines of code, generate complete geospatial visualization web interfaces for scientific tools. GABBs also includes powerful tools that can be used with no programming effort. The GeoBuilder tool provides an intuitive wizard for importing multi-variable, geo-located time series data (typical of sensor readings, GPS trackers) to build visualizations supporting data filtering and plotting. MyGeoHub has been used in tutorials at scientific conferences and educational activities for K-12 students. MyGeoHub is also constantly evolving; the recent addition of Jupyter and R Shiny notebook environments enable reproducible, richly interactive geospatial analyses and applications ranging from simple pre- processing to published tools. MyGeoHub is not a monolithic geospatial science gateway, instead it supports diverse needs ranging from just a feature-rich data management system, to complex scientific tools and workflows.

Wave breaking transfers momentum between waves to currents. In doing so it dissipates wave energy and affects long-term dispersion and transport of tracers, Wave breaking also affects the transfer of wind stresses to the ocean and is a major player in ocean acoustics, the dynamics of near-surface gas exchanges and the dynamics of phytoplankton and buoyant pollutants. Progressive waves were generated numerically using Gerris [6]. The velocity field was then used to estimate Lagrangian parcel dynamics in the neighborhood of the breaking event. The trans- port generated by the breaking events is shown to be significant, when compared to the wave-generated residual flow, as captured by the Stokes drift. We formulate a parametrization of the break- ing velocity based upon an analysis of the Largrangian dynamics of fluid parcels. Further, we describe how the breaking velocity is incorporated in the vortex force formulation of wave current interactions [1, 2].

A major source of lithospheric stresses is believed to be in variations of surface topography and lithospheric density. The traditional approach to stress estimation is based on direct calculations of the Gravitational Potential Energy (GPE), the depth integrated density moment of the lithosphere column. GPE is highly sensitive to density structure which, however, is often poorly constrained. Density structure of the lithosphere may be refined using methods of gravity modeling. However, the resulted density models suffer from non-uniqueness of the inverse problem. An alternative approach is to directly estimate lithospheric stresses (depth integrated) from satellite gravimetry data. Satellite gravity gradient measurements by the ESA GOCE mission ensures a wealth of data for mapping lithospheric stresses if a link between data and stresses or GPE can be established theoretically. Following (Camelbeeck et al., 2013), we adopt the method that constrains lithospheric stresses by direct utilization of the gravity gradient tensor. For comparison, we use more traditional methods as well: (2) the filtered geoid approach (e.g., Chase et al., 2002; Coblentz et al., 2015), and (3) the direct thin-sheet approximation based on depth integration of density moment (e.g., Medvedev, 2016). Whereas the last two approaches (2)-(3) calculate GPE and utilize a computationally expensive finite element mechanical modeling to calculate stresses, the approach (1) uses a much simpler numerical treatment but requires simplifying assumptions that yet to be tested. We applied all methods to the North Atlantic region where reliable additional constraints are available and tested results against the World Stress Map.

Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions (~ several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.

Accurately estimating the net seasonal snow accumulation (or “winter balance”) on glaciers is central to assessing glacier health and predicting glacier runoff. However, measuring and modeling snow distribution is inherently difficult in mountainous terrain, resulting in high uncertainties in estimates of winter balance. Our work focuses on uncertainty attribution within the process of converting direct measurements of snow depth and density to estimates of winter balance. We collected more than 9000 direct measurements of snow depth across three glaciers in the St. Elias Mountains, Yukon, Canada in May 2016. Linear regression (LR) and simple kriging (SK), combined with cross correlation and Bayesian model averaging, are used to interpolate estimates of snow water equivalent (SWE) from snow depth and density measurements. Snow distribution patterns are found to differ considerably between glaciers, highlighting strong inter- and intra-basin variability. Elevation is found to be the dominant control of the spatial distribution of SWE, but the relationship varies considerably between glaciers. A simple parameterization of wind redistribution is also a small but statistically significant predictor of SWE. The SWE estimated for one study glacier has a short range parameter (90 m) and both LR and SK estimate a winter balance of ~0.6 m w.e. but are poor predictors of SWE at measurement locations. The other two glaciers have longer SWE range parameters (~450 m) and due to differences in extrapolation, SK estimates are more than 0.1 m w.e. (up to 40%) lower than LR estimates. By using a Monte Carlo method to quantify the effects of various sources of uncertainty, we find that the interpolation of estimated values of SWE is a larger source of uncertainty than the assignment of snow density or than the representation of the SWE value within a terrain model grid cell. For our study glaciers, the total winter balance uncertainty ranges from 0.03 (8%) to 0.15 (54%) m w.e. depending primarily on the interpolation method. Despite the challenges associated with accurately and precisely estimating winter balance, our results are consistent with the previously reported regional accumulation gradient.

The Cyclone Global Navigation Satellite System (CYGNSS) is a multi-satellite constellation that utilizes Global Positioning System (GPS) reflectometry to retrieve near-surface wind speeds over the ocean. While CYGNSS is primarily aimed at measuring wind speeds in tropical cyclones, our research has established that the mission may also provide valuable insight into the relationships between wind-driven surface fluxes and general tropical oceanic convection. Currently, we are examining organized tropical convection using a mixture of CYGNSS level 1 through level 3 data, IMERG (Integrated Multi-satellite Retrievals for Global Precipitation Measurement), and other ancillary datasets (including buoys, GPM level 1 and 2 data, as well as ground-based radar). In addition, observing system experiments (OSEs) are being performed using hybrid three-dimensional variational assimilation to ingest CYGNSS observations into a limited-domain, convection-resolving model. Our focus for now is on case studies of convective evolution, but we will also report on progress toward statistical analysis of convection sampled by CYGNSS. Our working hypothesis is that the typical mature phase of organized tropical convection is marked by the development of a sharp gust-front boundary from an originally spatially broader but weaker wind speed change associated with precipitation. This increase in the wind gradient, which we demonstrate is observable by CYGNSS, likely helps to focus enhanced turbulent fluxes of convection-sustaining heat and moisture near the leading edge of the convective system where they are more easily ingested by the updraft. Progress on the testing and refinement of this hypothesis, using a mixture of observations and modeling, will be reported.

Electric field mills are used popularly for atmospheric electric field measurements. Atmospheric Electric Field variation is the primary signature for Lightning Early Warning systems. There is a characteristic change in the atmospheric electric field before lightning during a thundercloud formation. A voltage controlled variable capacitance is being proposed as a method for non-contacting measurement of electric fields. A varactor based mini electric field measurement system is developed, to detect any change in the atmospheric electric field and to issue lightning early warning system. Since this is a low-cost device, this can be used for developing countries which are facing adversities. A network of these devices can help in forming a spatial map of electric field variations over a region, and this can be used for more improved atmospheric electricity studies in developing countries.

Although the Brown mathematical model is the standard model for waveform retracking over open oceans, coastal waveforms usually deviate from open ocean waveform shapes due to inhomogeneous surface reflections within altimeter footprints, and thus cannot be directly interpreted by the Brown model. Generally, the two primary sources of heterogeneous surface reflections are land surfaces and bright targets such as calm surface water. The former reduces echo power, while the latter often produces particularly strong echoes. In previous studies, sub-waveform retrackers, which use waveform samples collected from around leading edges in order to avoid trailing edge noise, have been recommended for coastal waveform retracking. In the present study, the peaky-type noise caused by fixed-point bright targets is explicitly detected and masked using the parabolic signature in the sequential along-track waveforms (or, azimuth-range echograms). Moreover, the power deficit of waveform trailing edges caused by weak land reflections is compensated for by estimating the ratio of sea surface area within each annular footprint in order to produce pseudo-homogeneous reflected waveforms suitable for the Brown model. Using this method, Jason-2 altimeter waveforms are retracked in several coastal areas. Our results show that both the correlation coefficient and root mean square difference between the derived sea surface height anomalies and tide gauge records retain similar values at the open ocean (0.9 and 20 cm) level, even in areas approaching 3 km from coastlines, which is considerably improved from the 10 km correlation coefficient limit of the conventional MLE4 retracker and the 7 km sub-waveform ALES retracker limit. These values, however, depend on the coastal topography of the study areas because the approach distance limit increases (decreases) in areas with complicated (straight) coastlines.

The response of atmospheric variability to the Tibetan Plateau (TP) snow cover (TPSC) at interannual to decadal time-scales has been extensively investigated. However, the response of the atmosphere to the subseasonal variability of the TPSC has been largely ignored. Here, we found that the subseasonal variability of the TPSC revealed by daily data can serve as an indicator of East Asian atmospheric circulation on medium-range time-scales (approximately 3–7 days in advance). The subseasonal variability of the TPSC influences the upper-level regional atmospheric circulations, especially the East Asia upper-level westerly jet stream (EAJS), during wintertime. The variability of the TPSC modulates the land surface thermal conditions over the TP, which acts as an elevated cooling source in the middle troposphere during wintertime. The upper-level geopotential height is affected by the TPSC and then the zonal wind. As a result, the EAJS is influenced.

The natural flow regime within a watershed can be considered as the expected temporal patterns of streamflow variation in the absence of human impacts. While ecosystems have evolved to function under these conditions, the natural flow regime of most rivers has been significantly altered by human activities. Land use change, including the development of agriculture and urbanization, is a primary cause of the loss of natural flow regimes. These changes have altered discharge volume, timing, and variability, and consequently affected the structure and functioning of river ecosystems. The Meramec River watershed is located in east central Missouri and changes in land use have been the primary factor impacting flow regimes across the watershed. In this study, a watershed model, the Soil and Water Assessment Tool (SWAT), was developed to simulate a long-term time series of streamflow (1978-2014) within the watershed. Model performance was evaluated using statistical metrics and graphical technique including R-squared, Nash-Sutcliffe efficiency, cumulative error, and 1:1-ratio comparison between observed and simulated variables. The calibrated and validated SWAT model was then used to quantify the responses of the watershed when it was a forested natural landscape. An Indicator of Hydrologic Alteration (IHA) approach was applied to characterize the flow regime under the current landcover conditions as well as the simulated natural flow regime under the no land use change scenario. Differences in intra- and inter-annual ecologically relevant flow metrics were then compared using SWAT model outputs in conjunction with the IHA approach based on model outputs from current and no land use change conditions. This study provides a watershed-scale understanding of effects of land use change on a river’s flow variability and provides a framework for the development of restoration plans for heavily altered watersheds.

Microbial transformation and decomposition of organic matter in sediments constitutes one of the largest fluxes of carbon in marine environments. Mineralization of sedimentary organic matter by microorganisms results in selective degradation such that bioavailable or accessible compounds are rapidly metabolized while more recalcitrant, complex compounds are preserved and buried in sediment (Mahmoudi et al., 2017). Recent studies have found that the ability to use different carbon sources appears to vary among microorganisms, suggesting that the availability of certain pools of carbon can be specific to the taxa that utilize the pool. This implies that organic matter mineralization in marine environments may depend on the metabolic potential of the microbial populations that are present and active. The goal of our study was to investigate the extent to which organic matter availability and transformation may be species-specific using sediment from Guaymas Basin (Gulf of California). We carried out time-series incubations using bacterial isolates and sterilized sediment in the IsoCaRB system (Beaupre et al., 2016) which allowed us to measure the production rates and natural isotopic signatures (δ13C and Δ14C) of microbially-respired CO2. Separate incubations using two different marine bacterial isolates (Vibrio sp. and Pseudoalteromonas sp.) and sterilized Guaymas Basin sediment under oxic conditions showed that the rate and total quantity of organic matter metabolized by these two species differs. Approximately twice as much CO2 was collected during the Vibrio sp. incubation compared to the Pseudoalteromonas sp. incubation. Moreover, the rate at which organic matter was metabolized by the Vibrio sp. was much higher than the Pseudoalteromonas sp. indicating the intrinsic availability of organic matter in sediments may depend on the species that is present and active. Isotopic analyses of microbially respired CO2 will be used to constrain the type and age of organic matter that is accessible to each species. Moreover, molecular analysis of subsamples collected from each incubation will link carbon utilization with the underlying gene expression. Our study sheds light on the degree to which the metabolic capacities of microorganisms affect carbon transformation in sedimentary environments.

The left-lateral Enriquillo-Plantain Garden Fault (EPGF) is one of two transform systems that define the Northern Caribbean plate boundary zone. Relative motion across its trace (~ 10 mm/yr) evolves from nearly pure strike-slip in western Haiti to transpressional in eastern Haiti, where the fault system may terminate against a south-dipping oblique reverse fault. Lake Azuei is a large (10 km x 25 km) and shallow (< 30 m deep) lake that lies in the direct extension of the EPGF in eastern Haiti. A single core previously collected in the lake suggests high sedimentation rates at its depocenter (~6 mm/yr). The shallow lake stratigraphy is therefore expected to faithfully record any tectonic deformation that occurred within the past few thousand years. In January 2017, we acquired a grid of high-resolution (~10 cm), shallow penetration (~4 to 5 m) subbottom seismic (CHIRP) profiles spaced 1.2 km apart across the entire lake. A new bathymetric map compiled from these CHIRP data and some prior echosounder survey reveals a flat lake floor (<0.01°) surrounded by steep (~5°) shoreline slopes. The CHIRP profiles highlight several gentle folds that protrude from the flat lakebed near the southern shore, an area where transpressional deformation is presumably focused. Thin (< 20 cm) horizontal strata from the lakebed can be traced onto the flanks of these gentle folds and pinch out in an upward curve. They also often pinch upward onto the base of the shoreline slopes, indicating that young sediments on the lakebed bypassed the folds as well as the shoreline slopes. We interpret this feature as diagnostic of sediments deposited by turbidity currents. The fact that young turbidites pinch out in upward curves suggests that the folds are actively growing, and that active contractional structures (folds and/or blind thrust faults) control much of the periphery of the lake. A few sediment cores were strategically located where beds are pinching out in order to maximize stratigraphic records. Two of these cores successfully penetrated strata imaged by the CHIRP profiles. On-going Pb210 dating of sediment samples from the cores should constrain sedimentation rates and thus help quantify the rates of the tectonic deformation.

We investigate 85 129 MODIS satellite active fire events from 2007 to 2015 in the Niger Delta of Nigeria. The region is the oil base for Nigerian economy and the hub of oil exploration where oil facilities (i.e. flowlines, flow stations, trunklines, oil wells and oil fields) are domiciled, and from where crude oil and refined products are transported to different Nigerian locations through a network of pipeline systems. Pipeline and other oil facilities are consistently susceptible to oil leaks due to operational or maintenance error, and by acts of deliberate sabotage of the pipeline equipment which often result in explosions and fire outbreaks. We used ground oil spill reports obtained from the National Oil Spill Detection and Response Agency (NOSDRA) database (see www.oilspillmonitor.ng) to validate MODIS satellite data. NOSDRA database shows an estimate of 10 000 spill events from 2007 - 2015. The spill events were filtered to include largest spills by volume and events occurring only in the Niger Delta (i.e. 386 spills). By projecting both MODIS fire and spill as ‘input vector’ layers with ‘Points’ geometry, and the Nigerian pipeline networks as ‘from vector’ layers with ‘LineString’ geometry in a geographical information system, we extracted the nearest MODIS events (i.e. 2192) closed to the pipelines by 1000m distance in spatial vector analysis. The extraction process that defined the nearest distance to the pipelines is based on the global practices of the Right of Way (ROW) in pipeline management that earmarked 30m strip of land to the pipeline. The KML files of the extracted fires in a Google map validated their source origin to be from oil facilities. Land cover mapping confirmed fire anomalies. The aim of the study is to propose a near-real-time monitoring of spill events along pipeline routes using 250 m spatial resolution of MODIS active fire detection sensor when such spills are accompanied by fire events in the study location.

Seasonal African Dust (AD) transports soluble iron to oligotrophic Caribbean waters, and when bioavailable, it could increase marine primary productivity (PP). Recently, the region has experienced the proliferation of unusually high quantities of Sargassum, an iron-absorbing macroalgae inhabiting the air-sea interface, which possess ecological and economic challenges and whose driving factors are still uncertain. AD events reach Puerto Rico (PR) mostly during boreal summer months. This is also the season when chlorophyll-α (CHL) concentrations are highest, when the algae starts to bloom, and when sediment plumes from the Orinoco River (ORP), also reach nutrient discharge maxima. This study seeks to better understand the temporal relationships between increases in chlorophyll-α (CHL) and the presence of AD events in the region. Aerosol data collected at the Cabezas de San Juan Atmospheric Observatory was used to identify AD events between January 2005 and December 2015. Light scattering coefficients were measured with a integrating Nephelometer, while light absorption coefficients were obtained from either the Particle Soot/Absorption Photometer (PSAP) or the Continuous Light Absorption Photometer (CLAP). Spectral properties suggesting AD events were cross-referenced with surface dust concentration image models and source-attributed air masses corresponding to dusty periods using Hybrid Single-Particle Lagrangian Integrated Trajectories (HYSPLIT). For all years with spectral data, modeled monthly wet dust deposition was correlated (R= 0.64) with mean CHL concentrations from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). Daily dust mass column densities from NASA’s MERRA-2 model were also correlated (R^2= 0.53) to sea surface iron concentrations from NASA’s Ocean Biogeochemical Model. We present the 2010 case study, which coincides with the start of the Sargassum bloom and shows CHL peaks occurring a month before ORPs but during the AD season, suggesting the AD role in enhancing PP. Other possible influencing climatic and oceanographic variables could be associated to these observations. Further efforts include spatially linking the Floating Algae Index in satellite imagery to AD concentrations, to better predict harmful algal blooms and inform management.

Horizontally-extensive lightning flashes occur frequently in association with mature and late phases of multicellular thunderstorms, both in trailing stratiform regions and horizontally-extensive anvils. The spatial relationship between these flashes and the parent cloud volume is of importance for space launch operational decision making, and is of broader scientific interest. Before this question can be accurately addressed, there is a need to understand the degree to which current lightning observation systems can depict the spatial extent of these long flashes. In this ongoing work, we will intercompare the depiction of horizontally-extensive flashes using several ground-based lightning locating systems (LLSs) located at Kennedy Space Center (KSC) with space-based observations observed by the recently-launched Geostationary Lightning Mapper (GLM) onboard the GOES-16 satellite. Ground-based datasets include the KSC Lightning Mapping Array (KSCLMA), the operational narrowband digital interferometer network MERLIN, and the combined cloud-to-ground and cloud lightning dataset produced by the U.S. National Lightning Detection Network (NLDN). The KSCLMA system is a network of VHF time-of-arrival sensors that preferentially report breakdown processes, and MERLIN is a network of VHF interferometers that point to the discharges in the horizontal plane. Observations to date indicate that MERLIN and the KSCSLMA provide similar overall descriptions of the spatial and temporal extent of these flashes, while the NLDN does not provide adequate spatial mapping of these flashes. The KSC LMA system has much better location accuracy, and provides excellent 3-dimensional representation within ~100 km of KSC. It also has sufficient sensitivity to provide 2-dimensional flash mapping within ~250 km of KSC. The MERLIN system provides a more-detailed representation of fast leader propagation (in 2 dimensions) with ~100 km of KSC. Earlier work during the CHUVA campaign in Brazil with similar systems and the (orbital) Lightning Imaging System (LIS) has shown that the interferometric data correlated much better in space and time with the LIS optical observations. We are currently investigating this relationship at KSC, where both the LMA and interferometer perform much better than the systems used during CHUVA.

Shoreline change along the Eastern Atlantic shore of Virginia has been studied for the individual barrier islands but not as an integrated system. This study combines the Atlantic shoreline locations for eleven barrier islands obtained from LANDSAT 5, 7, and 8 images. Approximately 250 shoreline locations over a 24-year period from Jan 1990 to Dec 2014 were extracted from the digitized shoreline data at 338 transects. The resulting 338 by 250 matrix was analyzed by the empirical orthogonal function (EOF) technique. The first four principal components (PC) explained 86 percent of the sample variance. Since the data was not detrended, the first PC was the overall trend of the data with a discontinuity in 2004-2005. The 2004-2005 years included storm events and large shoreline changes. PCs 2 to 4 reflect the effects of El Nino events and tropical and non-tropical storms. Eigenvectors 1 to 4 all show the effects of the nine inlets in the island group. Eigenvector (EV) 1 explains 59 percent of the shoreline spatial variance and shows the largest changes at the northern and southern island ends. EVs 2 to 4 reflect the pattern of EV1 but at sequentially smaller percentages of the spatial variance. As a group, the eleven islands are losing ocean side shoreline. The lone exception is Hog Island. Sea level had the strongest correlation with the shoreline loss trend of PC1. The coefficient of determination was 0.41. The NAO and MEI also correlated with PC1 with correlations of determination of 0.05 and 0.12 respectively. These confidence level for the three factors was better than 99 percent. Sea level also correlated with PC3 and PC4. The PCs as a group show that the year intervals 2004-2005 and 2009-2010 had large effects on the shoreline change pattern for the island group. EVs 1 to 4 had the highest range of shoreline change at the island ends indicating the effect the changes of the inlets have on the adjacent islands. The smaller islands as a group had a higher level of eigenvector variance than the other eight islands. Sea level change is the major factor affecting the ocean shorelines of these islands. Continued sea level increase will facilitate loss of ocean shoreline for the barrier islands as a group.