Coal combustion aerosol particles contribute to the concentrations of ice-nucleating particles (INPs) in the atmosphere. Especially, immersion freezing can be considered as one of the most important mechanisms for INP formation in supercooled tropospheric clouds that exist at temperatures between 0°C and -38°C. The U.S. contains more than 550 operating coal-burning plants consuming 7.2 x 10^8 metric tons of coal (in 2016) to generate a total annual electricity of >2 billion MW-h, resulting in the emission of at least 4.9 x 10^5 metric tons of PM10 (particulate matter smaller than 10 µm in diameter). In Texas alone, 19 combustion plants generate 0.15 billion MW-h electricity and >2.4 x 10^4 metric tons of PM10. Here we present the immersion freezing behavior of combustion fly ash and bottom ash particles collected in the Texas Panhandle region. Two types of particulate samples, namely <45 µm sieved bottom ash (B_Ash_TX_PH) and <45 µm sieved fly ash (F_Ash_TX_PH), were prepared. Afterwards, their immersion freezing abilities were measured using the Cryogenic Refrigerator Applied to Freezing Test (CRAFT) system covering the heterogeneous freezing temperature down to -30 °C. The results were generated and are reported through two metrics, frozen fraction, ffrozen(T), and ice nucleation active site density per unit mass, nm(T) as a function of temperature. Our preliminary results show that an onset increase in ffrozen(T) for B_Ash_TX_PH (ffrozen) occurred as high as at -15°C, whereas the onset for F_Ash_TX_PH is at -18°C. Secondly, B_Ash_TX_PH exhibited a higher nm(-20 °C) of 10^5 g^-1 than that of F_Ash_TX_PH ( 5 x 10^3 g^-1). On the other hand, previous studies on different combustion ash samples have reported that the opposite trend (i.e., ice nucleation efficiency of fly ash is greater than that of bottom ash; Grawe et al., 2016, ACP; Umo et al., 2015, ACP). We will discuss possible reasons for the observed differences. In addition, the results of complementary physico-chemical analyses via X-ray diffraction technique, Raman microscopy and scanning electron microscopy on both ash types will also be presented to relate the crystallographic and chemical properties to their ice nucleation abilities.

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.

In 2015, Integrated Ocean Discovery Program Expedition 356 drilled along the margin off Western Australian to investigate the history of the Indonesian Throughflow (ITF) and its integral role in the development of global thermohaline circulation and climate. Throughout the expedition, a suite of foraminiferal analyses were employed wherein planktic specimens provided biostratigraphy and an incredibly diverse benthic fauna (~ 260 species) was used to reveal palaeo- water depth, palaeobathymetric setting and variable conditions at the sediment-water interface. Benthic foraminiferal biofacies are particularly sensitive to changes in environmental conditions, have a rapid turnover and are ideal proxies for monitoring physical and chemical changes in marine environments. When this information is combined with lithostratigraphic and other microfossil data, a robust understanding of past environments and past geological events can be reconstructed. Shipboard data were used to isolate horizons of interest for more intense sampling at IODP Site U1461, situated on the North-West Shelf, at 127 m of water depth. The shipboard data revealed a large (~150 m-thick) turbidite horizon hosting benthic foraminifera from a substantially shallower water depth than the horizon immediately preceding the horizon. We present preliminary foraminiferal results combined with shipboard sedimentary descriptions to better constrain the deposit’s occurrence in the biostratigraphic record, use benthic foraminifera to elucidate the deposit’s sedimentary origins and link this event with others in the region to investigate potential catalysts for its deposition.

The natural sound generated by an unmanned aerial vehicle is used in conjunction with tomography to remotely sense atmospheric temperature and wind profiles simultaneously. Sound fields recorded onboard the aircraft and by an array of microphones on the ground are compared and converted to sound speed estimates for the ray paths intersecting the intervening medium. Tomographic inversion is then used to transform these sound speed values into vertical cross-sections and 3D volumes of virtual temperature and wind vectors, which enables the atmosphere to be visualised and monitored over time up to altitudes of 1,200m and over baselines of up to 600m. This paper reports on results from two short campaigns during which 2D and 3D profiles of wind and temperature obtained in this way were compared to: measurements taken by co-located mid-range Doppler SODAR and LIDAR; and temperature measurements made by instruments carried by unmanned aircraft flying through the intervening atmosphere. Large eddy simulation of daytime atmospheric boundary layers were also used to examine the anticipated performance of the instruments and the nature of any errors. The observations obtained using all systems are shown to correspond closely.

Spectral entropy (Hs) is an index which can be used to measure the structural complexity of time series data. When a time series is made up of one periodic function, the Hs value becomes smaller, while Hs becomes larger when a time series is composed of several periodic functions. We hypothesized that this characteristic of the Hs could be used to quantify the water stress history of vegetation. For the ideal condition for which sufficient water is supplied to an agricultural crop or natural vegetation, there should be a single distinct phenological cycle represented in a vegetation index time series (e.g., NDVI and EVI). However, time series data for a vegetation area that repeatedly experiences water stress may include several fluctuations that can be observed in addition to the predominant phenological cycle. This is because the process of experiencing water stress and recovering from it generates small fluctuations in phenological characteristics. Consequently, the value of Hs increases when vegetation experiences several water shortages. Therefore, the Hs could be used as an indicator for water stress history. To test this hypothesis, we analyzed Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data for a natural area in comparison to a nearby sugarcane area in seasonally-dry western Costa Rica. In this presentation, we will illustrate the use of spectral entropy to evaluate the vegetative responses of natural vegetation (dry tropical forest) and sugarcane under three different irrigation techniques (center pivot irrigation, drip irrigation and flood irrigation). Through this comparative analysis, the utility of Hs as an indicator will be tested. Furthermore, crop response to the different irrigation methods will be discussed in terms of Hs, NDVI and yield.

Nonmigrating tidal diagnostics of SABER temperature observations in the ionospheric dynamo region reveal a large amount of variability on time-scales of a few days to weeks. In this paper, we discuss the physical reasons for the observed short-term tidal variability using a novel approach based on Information theory and Bayesian statistics. We diagnose short-term tidal variability as a function of season, QBO, ENSO, and solar cycle and other drivers using time dependent probability density functions, Shannon entropy and Kullback-Leibler divergence. The statistical significance of the approach and its predictive capability is exemplified using SABER tidal diagnostics with emphasis on the responses to the QBO and solar cycle. Implications for F-region plasma density will be discussed.

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.

Structural imaging using body-wave energy present in ambient seismic data remains a challenging task, largely because these wave modes are commonly much weaker than surface wave energy. In a number of situations body-wave energy has been extracted successfully; however, (nearly) all successful body-wave extraction and imaging approaches have focused on cross-correlation processing. While this is useful for interferometric purposes, it can also lead to the inclusion of unwanted noise events that dominate the resulting stack, leaving body-wave energy overpowered by the coherent noise. Conversely, wave-equation imaging can be applied directly on non-correlated ambient data that has been preprocessed to mitigate unwanted energy (i.e., surface waves, burst-like and electromechanical noise) to enhance body-wave arrivals. Following this approach, though, requires a significant preprocessing effort on often Terabytes of ambient seismic data, which is expensive and requires automation to be a feasible approach. In this work we outline an automated processing workflow designed to optimize body wave energy from an ambient seismic data set acquired on a large-N array at a mine site near Lalor Lake, Manitoba, Canada. We show that processing ambient seismic data in the recording domain, rather than the cross-correlation domain, allows us to mitigate energy that is inappropriate for body-wave imaging. We first develop a method for window selection that automatically identifies and removes data contaminated by coherent high-energy bursts. We then apply time- and frequency-domain debursting techniques to mitigate the effects of remaining strong amplitude and/or monochromatic energy without severely degrading the overall waveforms. After each processing step we implement a QC check to investigate improvements in the convergence rates - and the emergence of reflection events - in the cross-correlation plus stack waveforms over hour-long windows. Overall, the QC analyses suggest that automated preprocessing of ambient seismic recordings in the recording domain successfully mitigates unwanted coherent noise events in both the time and frequency domain. Accordingly, we assert that this method is beneficial for direct wave-equation imaging with ambient seismic recordings.

We perform physics-based simulations of earthquake rupture propagation on geometrically complex strike-slip faults. We consider many different realization of the fault roughness and obtain heterogeneous stress fields by performing dynamic rupture simulation of large earthquakes. We calculate the Coulomb failure function (CFF) for all these realizations so that we can quantify zones of stress increase/shadows surrounding the main fault and compare our results to seismic catalogs. To do this comparison, we use relocated earthquake catalogs from Northern and Southern California. We specify the range of fault roughness parameters based on past observational studies. The Hurst exponent (H) varies in range from 0.5 to 1 and RMS height to wavelength ratio ( RMS deviation of a fault profile from planarity) has values between 10-2 to 10-3. For any realization of fault roughness, the Probability density function (PDF) values relative to the mean CFF change show a wider spread near the fault and this spread squeezes into a narrow band as we move away from fault. For lower value of RMS ratio ( 10-3), we see bigger zones of stress change near the hypocenter and for higher value of RMS ratio ( 10-2), we see alternate zones of stress increase/decrease surrounding the fault to have comparable lengths. We also couple short-term dynamic rupture simulation with long-term tectonic modelling. We do this by giving the stress output from one of the dynamic rupture simulation (of a single realization of fault roughness) to long term tectonic model (LTM) as initial condition and then run LTM over duration of seismic cycle. This short term and long term coupling enables us to understand how heterogeneous stresses due to fault geometry influence the dynamics of strain accumulation in the post-seismic and inter-seismic phase of seismic cycle.

Reliable automatic water samplers allow repetitive sampling of various water sources over long periods of time without requiring a researcher on site, reducing human error as well as the monetary and time costs of traveling to the field, particularly when the scale of the sample period is hours or days. The high fixed cost of buying a commercial sampler with little customizability can be a barrier to research requiring repetitive samples, such as the analysis of septic water pre- and post-treatment. DIY automatic samplers proposed in the past sacrifice maximum volume, customizability, or scope of applications, among other features, in exchange for a lower net cost. The purpose of this project was to develop a low-cost, highly customizable, robust water sampler that is capable of sampling many sources of water for various analytes. A lightweight aluminum-extrusion frame was designed and assembled, chosen for its mounting system, strength, and low cost. Water is drawn from two peristaltic pumps through silicone tubing and directed into 24 foil-lined 250mL bags using solenoid valves. A programmable Arduino Uno microcontroller connected to a circuit board communicates with a battery operated real-time clock, initiating sampling stages. Period and volume settings are programmable in-field by the user via serial commands. The OPEnSampler is an open design, allowing the user to decide what components to use and the modular theme of the frame allows fast mounting of new manufactured or 3D printed components. The 24-bag system weighs less than 10kg and the material cost is under $450. Up to 6L of sample water can be drawn at a rate of 100mL/minute in either direction. Faster flowrates are achieved by using more powerful peristaltic pumps. Future design changes could allow a greater maximum volume by filling the unused space with more containers and adding GSM communications to send real time status information.

Better understanding of the hydrological cycle of the Lower Mekong River Basin (LMRB) and addressing the value-added information of using remote sensing data on the spatial variability of soil moisture over the Mekong Basin is the objective of this work. In this work, we present the development and assessment of the LMRB (drainage area of 495,000 km2) Soil and Water Assessment Tool (SWAT). The coupled model framework presented is part of SERVIR, a joint capacity building venture between NASA and the U.S. Agency for International Development, providing state-of-the-art, satellite-based earth monitoring, imaging and mapping data, geospatial information, predictive models, and science applications to improve environmental decision-making among multiple developing nations. The developed LMRB SWAT model enables the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil texture, and land cover and land use data to drive SWAT model simulations over the Lower Mekong River Basin. The LMRB SWAT model driven by remote sensing climate data was calibrated and verified with observed runoff data at the watershed outlet as well as at multiple sites along the main river course. Another LMRB SWAT model set driven by in-situ climate observations was also calibrated and verified to streamflow data. Simulated soil moisture estimates from the two models were then examined and compared to a downscaled Soil Moisture Active Passive Sensor (SMAP) 36 km radiometer products. Results from this work present a framework for improving SWAT performance by utilizing a downscaled SMAP soil moisture products used for model calibration and validation.

Non-proteinaceous and proteinaceous biological aerosols are abundant within the atmosphere and have the potential to impact the climate through cloud and precipitation formation. In this study, we present the differences in the laboratory-measured freezing capabilities of the non-proteinaceous and proteinaceous biological materials to determine which has more potential to impact the ice nucleation in the clouds. As non-proteinaceous surrogates, we examined multiple cellulose materials (e.g., microcrystalline and nanocrystalline cellulose) whose sizes range from ~100 nm to >100 μm (according to manufacturer report). For proteinaceous proxies, we looked at different gram-negative bacteria, such as Pseudamonas aeruginosa, Escherichia coli, Serratia marcescens, Citrobacter freundii, and Snomax, (which contains P. syringae) that can be found around the proximity of the Texas Panhandle. By using the Cryogenic Refrigeration Applied Freezing Test (CRAFT) system, we estimated immersion freezing efficiency (i.e., ice nucleation activity scaled to a unit of mass) of each sample at the temperatures greater than -30°C. We have observed that not all gram-negative bacteria has high immersion freezing activity, but the few do have a warmer temperature onset (>-20 °C) than the cellulose used. For those that did not exhibit substantial freezing efficiencies, they had similar freezing properties as the broth, in which the bacteria were incubated, as well as the cellulose materials examined. These observations suggest the presence and potential importance of bacterial cellulose in the atmospheric ice nucleation. From here, we need to conduct more in-depth investigation in the effects of a wider variety of atmospherically relevant biological aerosols to get a better understanding of the effects of said aerosols on overall aerosol-cloud interactions. Acknowledgments: K. Cory would like to acknowledge NSF-EAPSI and JSPS Summer Program for the travel fellowship support. N. Hiranuma acknowledges financial aids by the Higher Education Assistance Fund (HEAF), WTAMU Office of Graduate School and Killgore Research Center.

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.

The planetary boundary layer (PBL) is a layer in the lowest part of the atmosphere where Earth’s surface strongly influences temperature, moisture, and wind through the turbulent transfer of air mass. It is a key component of air pollution transport studies. An urban heat island (UHI) is a metropolitan area which is significantly warmer than its surrounding rural areas. The El Paso - Juarez Metropolitan area, with a combined population of ~ 1.972 million (in 2010) and growing urban infrastructure, can be studied as an UHI surrounded by rural areas. In this study, we have analyzed the temperature fields for the lower levels of the troposphere for the El Paso - Juarez metropolitan area and neighboring rural areas during the day and night hours both for the summer and winter seasons. The Vaisala Boundary Layer View Software (BLView) was used to obtain the aerosol mixing layer height (ML), a proxy for the PBL height, using data from a Vaisala ceilometer, model CL31. The ceilometer is situated at the University of Texas at El Paso (UTEP) campus. The BLView analyzes the ceilometer backscatter profile data and provided the ML structure. In addition, the Weather Research Forecast Model (WRF) was used to simulate PBL heights for the El Paso - Juarez Airshed and its surrounding rural areas. The overall objective of the project is to contribute to a better understanding of the PBL structure and the effect the UHI has for the El Paso - Juarez Airshed.

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.

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.

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.