Forecasting Salinity in the Laguna Madre Using Deep Learning

Salinity is an important metric in the Laguna Madre for establishing the long term health of the local ecological population. By utilizing Deep Learning (DL) techniques, the predicted and forecasted salinity in the Laguna Madre is generated from data provided by the Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua satellite. Currently, only one other DL model has been used to forecast Sea Surface Salinity (SSS), being a Recurrent Neural Network (RNN). However, the RNN model requires the prediction of a full area of salinity to function. As such, several model architectures were tested, with the best one, being a Multi-input MPNN, utilized to evaluate the feasibility of forecasting utilizing simpler DL models. The results show that a one-day forecast is plausible, while three and five-day forecasts would require a data-rich environment, unlike that of the Laguna Madre

Processes influencing formation of low-salinity high-biomass lenses near the edge of the Ross Ice Shelf

© The Author(s), 2016. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Marine Systems 166 (2017): 108-119, doi:10.1016/j.jmarsys.2016.07.002.Both remotely sensed and in situ observations in austral summer of early 2012 in the Ross Sea suggest the presence of cold, low-salinity, and high-biomass eddies along the edge of the Ross Ice Shelf (RIS). Satellite measurements include sea surface temperature and ocean color, and shipboard data sets include hydrographic profiles, towed instrumentation, and underway acoustic Doppler current profilers. Idealized model simulations are utilized to examine the processes responsible for ice shelf eddy formation. 3-D model simulations produce similar cold and fresh eddies, although the simulated vertical lenses are quantitatively thinner than observed. Model sensitivity tests show that both basal melting underneath the ice shelf and irregularity of the ice shelf edge facilitate generation of cold and fresh eddies. 2-D model simulations further suggest that both basal melting and downwelling-favorable winds play crucial roles in forming a thick layer of low-salinity water observed along the edge of the RIS. These properties may have been entrained into the observed eddies, whereas that entrainment process was not captured in the specific eddy formation events studied in our 3-D model—which may explain the discrepancy between the simulated and observed eddies, at least in part. Additional sensitivity experiments imply that uncertainties associated with background stratification and wind stress may also explain why the model underestimates the thickness of the low-salinity lens in the eddy interiors. Our study highlights the importance of incorporating accurate wind forcing, basal melting, and ice shelf irregularity for simulating eddy formation near the RIS edge. The processes responsible for generating the high phytoplankton biomass inside these eddies remain to be elucidated.YL is supported by the Postdoctoral Scholarship Program at Woods Hole Oceanographic Institution, with funding provided by the Dr. George D. Grice Postdoctoral Scholarship.2018-07-0

Phytoplankton and Carbon Dynamics in the Estuarine-Coastal Waters of the Northern Gulf of Mexico from Field Data and Ocean Color Remote Sensing

In this study, phytoplankton community and carbon dynamics were examined in the optically complex estuarine-coastal regions of the northern Gulf of Mexico (nGOM) from field and satellite ocean color observations. As part of this study, bio-optical ocean color algorithms for i) dissolved organic carbon (DOC), ii) phytoplankton pigment composition, iii) adaptive estimation of Chl a and iv) phytoplankton size fractions were developed to facilitate the study of biogeochemical cycling in the nGOM. The phytoplankton based algorithms were applied to Sentinel 3A/B-OLCI oean color data to assess phytoplankton community dynamics to extreme river discharge conditions as well as hurricanes in the nGOM. This study revealed that the effects of hurricanes on phytoplankton community dynamics were dependent on background nutrient conditions, as well as the intensity, track and translational speed of storms: 1) Strong flooding associated with Hurricane Harvey (2017) shifted the dominance of phytoplankton community in Galveston Bay from cyanobacteria and dinoflagellate to diatom and chlorophyte; 2) high levels of organic matter delivered from estuaries to shelf waters after Hurricane Michael (2018) fueled a red tide mixed with coccolithophore bloom in the nGoM; 3) the physical and chemical environment after hurricanes are favorable for the growth and dominance of coccolithophores in shelf waters. Further, microphytoplankton mainly controlled by freshwater inflows showed dominance in estuaries of the nGoM, with highest/lowest values observed in spring/fall. In comparison, phytoplankton size fraction (PSF) dynamics in the midshelf and offshore waters of the nGoM are strongly influenced by Loop Current (LC) expansion, and eddy shedding with highest picophytoplankton fraction observed in the warm waters of LC. DOC dynamics was studied using an empirical algorithm that was developed and applied to multiple satellite sensors (Landsat 5 TM and MODIS-Aqua) to assess multi-decadal (1985-2012) DOC trends in Barataria Basin. The linkages between DOC and environmenal variations were investigated. The relationships between satellite-derived DOC and land cover variations (1985–2011) derived from Landsat-5 TM supervised classification indicate soil loss in the salt marsh to be an important DOC source in the wetland-estuary system, and overall strong land use/land loss impact on the long-term DOC trends in the Barataria Basin

Impact of the spatial resolution of satellite remote sensing sensors in the quantification of total suspended sediment concentration: A case study in turbid waters of Northern Western Australia

The impact of anthropogenic activities on coastal waters is a cause of concern because such activities add to the total suspended sediment (TSS) budget of the coastal waters, which have negative impacts on the coastal ecosystem. Satellite remote sensing provides a powerful tool in monitoring TSS concentration at high spatiotemporal resolution, but coastal managers should be mindful that the satellite-derived TSS concentrations are dependent on the satellite sensor's radiometric properties, atmospheric correction approaches, the spatial resolution and the limitations of specific TSS algorithms. In this study, we investigated the impact of different spatial resolutions of satellite sensor on the quantification of TSS concentration in coastal waters of northern Western Australia. We quantified the TSS product derived from MODerate resolution Imaging Spectroradiometer (MODIS)-Aqua, Landsat-8 Operational Land Image (OLI), and WorldView-2 (WV2) at native spatial resolutions of 250 m, 30 m and 2 m respectively and coarser spatial resolution (resampled up to 5 km) to quantify the impact of spatial resolution on the derived TSS product in different turbidity conditions. The results from the study show that in the waters of high turbidity and high spatial variability, the high spatial resolution WV2 sensor reported TSS concentration as high as 160 mg L-1 while the low spatial resolution MODIS-Aqua reported a maximum TSS concentration of 23.6 mg L-1. Degrading the spatial resolution of each satellite sensor for highly spatially variable turbid waters led to variability in the TSS concentrations of 114.46%, 304.68% and 38.2% for WV2, Landsat-8 OLI and MODIS-Aqua respectively. The implications of this work are particularly relevant in the situation of compliance monitoring where operations may be required to restrict TSS concentrations to a pre-defined limit

Remote sensing of sea surface glacial meltwater on the Antarctic Peninsula shelf

Glacial meltwater is an important environmental variable for ecosystem dynamics along the biologically productive Western Antarctic Peninsula (WAP) shelf. This region is experiencing rapid change, including increasing glacial meltwater discharge associated with the melting of land ice. To better understand the WAP environment and aid ecosystem forecasting, additional methods are needed for monitoring and quantifying glacial meltwater for this remote, sparsely sampled location. Prior studies showed that sea surface glacial meltwater (SSGM) has unique optical characteristics which may allow remote sensing detection via ocean color data. In this study, we develop a first-generation model for quantifying SSGM that can be applied to both spaceborne (MODIS-Aqua) and airborne (PRISM) ocean color platforms. In addition, the model was prepared and verified with one of the more comprehensive in-situ stable oxygen isotope datasets compiled for the WAP region. The SSGM model appears robust and provides accurate predictions of the fractional contribution of glacial meltwater to seawater when compared with in-situ data (r = 0.82, median absolute percent difference = 6.38%, median bias = −0.04), thus offering an additional novel method for quantifying and studying glacial meltwater in the WAP region

Radiometric validation of atmospheric correction for MERIS in the Baltic Sea based on continuous observations from ships and AERONET-OC

The Baltic Sea is a semi-enclosed sea that is optically dominated by coloured dissolved organic material (CDOM) and has relatively low sun elevation which makes accurate ocean colour remote sensing challenging in these waters. The high absorption, low scattering properties of the Baltic Sea are representative of other optically similar water bodies including the Arctic Ocean, Black Sea, coastal regions adjacent to the CDOM-rich estuaries such as the Amazon, and highly absorbing lakes where radiometric validation is essential in order to develop accurate remote sensing algorithms. Previous studies in this region mainly focused on the validation and improvementofstandardChlorophyll-a (Chla)andattenuation coefficient(kd)ocean colourproducts.Theprimary input to derive these is the water-leaving radiance (Lw) or remote sensing reflectance (Rrs) and it is therefore fundamental toobtainthemostaccurate Lw orRrs beforederivinghigherlevelproducts.Tothisend,theretrieval accuracy of Rrs from Medium Resolution Imaging Spectrometer (MERIS) imagery using six atmospheric correction processors was assessed through above-water measurements at two sites of the Aerosol Robotic Network for Ocean Colour (AERONET-OC; 363 measurements) and a shipborne autonomous platform from which the highest number of measurements were obtained (4986 measurements). The six processors tested were the CoastColour processor (CC), the Case 2 Regional processor for lakes (C2R-Lakes), the Case 2 Regional CoastColour processor (C2R-CC), the FUB/WeW water processor (FUB), the MERIS ground segment processor (MEGS) andPOLYMER. Allprocessorsexceptfor CChadsmallaverage absolutepercentage differences(ψ)inthe wavelength rangefrom 490 nmto 709 nm(ψ 60%. Compared to in situ values, the Rrs(709)/Rrs(665) band ratio had ψ 0.6. Using a score system based on all statistical tests, POLYMER scored highest, while C2R-CC, C2RLakesandFUBhadlowerscores.ThisstudyrepresentsthelargestdatabaseofinsituRrs,themostcomprehensive analysis of AC models for highly absorbing waters and for MERIS, conducted to date. The results have implications for the new generation of Copernicus Sentinel ocean colour satellites

Recent multivariate changes in the North Atlantic climate system, with a focus on 2005-2016

Major changes are occurring across the North Atlantic climate system, including in the atmosphere, ocean and cryosphere, and many observed changes are unprecedented in instrumental records. As the changes in the North Atlantic directly affect the climate and air quality of the surrounding continents, it is important to fully understand how and why the changes are taking place, not least to predict how the region will change in the future. To this end, this article characterizes the recent observed changes in the North Atlantic region, especially in the period 2005–2016, across many different aspects of the system including: atmospheric circulation; atmospheric composition; clouds and aerosols; ocean circulation and properties; and the cryosphere. Recent changes include: an increase in the speed of the North Atlantic jet stream in winter; a southward shift in the North Atlantic jet stream in summer, associated with a weakening summer North Atlantic Oscillation; increases in ozone and methane; increases in net absorbed radiation in the mid‐latitude western Atlantic, linked to an increase in the abundance of high level clouds and a reduction in low level clouds; cooling of sea surface temperatures in the North Atlantic subpolar gyre, concomitant with increases in the western subtropical gyre, and a decline in the Atlantic Ocean's overturning circulation; a decline in Atlantic sector Arctic sea ice and rapid melting of the Greenland Ice Sheet. There are many interactions between these changes, but these interactions are poorly understood. This article concludes by highlighting some of the key outstanding questions

Perspectives and Integration in SOLAS Science

Why a chapter on Perspectives and Integration in SOLAS Science in this book? SOLAS science by its nature deals with interactions that occur: across a wide spectrum of time and space scales, involve gases and particles, between the ocean and the atmosphere, across many disciplines including chemistry, biology, optics, physics, mathematics, computing, socio-economics and consequently interactions between many different scientists and across scientific generations. This chapter provides a guide through the remarkable diversity of cross-cutting approaches and tools in the gigantic puzzle of the SOLAS realm. Here we overview the existing prime components of atmospheric and oceanic observing systems, with the acquisition of ocean–atmosphere observables either from in situ or from satellites, the rich hierarchy of models to test our knowledge of Earth System functioning, and the tremendous efforts accomplished over the last decade within the COST Action 735 and SOLAS Integration project frameworks to understand, as best we can, the current physical and biogeochemical state of the atmosphere and ocean commons. A few SOLAS integrative studies illustrate the full meaning of interactions, paving the way for even tighter connections between thematic fields. Ultimately, SOLAS research will also develop with an enhanced consideration of societal demand while preserving fundamental research coherency. The exchange of energy, gases and particles across the air-sea interface is controlled by a variety of biological, chemical and physical processes that operate across broad spatial and temporal scales. These processes influence the composition, biogeochemical and chemical properties of both the oceanic and atmospheric boundary layers and ultimately shape the Earth system response to climate and environmental change, as detailed in the previous four chapters. In this cross-cutting chapter we present some of the SOLAS achievements over the last decade in terms of integration, upscaling observational information from process-oriented studies and expeditionary research with key tools such as remote sensing and modelling. Here we do not pretend to encompass the entire legacy of SOLAS efforts but rather offer a selective view of some of the major integrative SOLAS studies that combined available pieces of the immense jigsaw puzzle. These include, for instance, COST efforts to build up global climatologies of SOLAS relevant parameters such as dimethyl sulphide, interconnection between volcanic ash and ecosystem response in the eastern subarctic North Pacific, optimal strategy to derive basin-scale CO2 uptake with good precision, or significant reduction of the uncertainties in sea-salt aerosol source functions. Predicting the future trajectory of Earth’s climate and habitability is the main task ahead. Some possible routes for the SOLAS scientific community to reach this overarching goal conclude the chapter

Carbon from Space: determining the biological controls on the ocean sink of CO2 from satellites, in the Atlantic and Southern Ocean

Increasing anthropogenic carbon dioxide (CO2) emissions to the atmosphere have partially been absorbed by the global oceans. The role which the plankton community contributes to this net CO2 sink, and how it may change under climate change has been identified as a key issue to address within the United Nations decade of ocean science (2021-2030) Integrated Ocean Carbon Research (IOC-R) programme. This thesis sets out to explore how the net community production (NCP; the balance between photosynthesis and respiration) of the plankton community contributes to the variability in air-sea CO2 flux in the South Atlantic Ocean. In Chapter 2, NCP is shown to be accurately and precisely estimated from satellite measurements with respect to in situ observations. For this, weighted statistics are used to account for satellite, in situ and model uncertainties. The accuracy of satellite NCP could be improved by up to 40% by reducing uncertainties in net primary production (NPP). In Chapter 3, these satellite NCP observations were then used within a feed forward neural network scheme (SA-FNN) to extrapolate partial pressure of CO2 in seawater (pCO2 (sw)) over space and time, which is a key component to estimating the CO2 flux. NCP improved the accuracy and precision of pCO2 (sw) fields compared to using chlorophyll a (Chl a); the primary pigment in phytoplankton which is often used as a proxy for the biological CO2 drawdown. Compared to in situ observations, the seasonal variability in pCO2 (sw) was improved using the SA-FNN in key areas such as the Amazon River plume and Benguela upwelling, which make large regional contributions to the air-sea CO2 flux in the South Atlantic Ocean. In Chapter 4, these complete pCO2 (sw) fields were used with a timeseries decomposition method to determine the drivers of air-sea CO2 flux over seasonal, interannual and multi-year timescales. NCP was shown to correlate with the variability in CO2 flux on a seasonal basis. At interannual and mutli-year timescales, NCP became a more important contributor to variability in CO2 flux. This has not been previously analysed for this region. Mesoscale eddies in the global ocean can modify the biological, physical, and chemical properties and therefore may modify the CO2 flux. In Chapter 5, the cumulative CO2 flux of 67 long lived eddies (lifetimes > 1 year) was estimated using Lagrangian tracking with satellite observations. The eddies could enhance the CO2 flux into the South Atlantic Ocean by up to 0.08 %, through eddy modification of biological and physical properties. Collectively this research has shown that the plankton community plays a more significant role in modulating the air-sea CO2 flux in the South Atlantic Ocean, which has significant implications for the global ocean