Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic

Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3MRAD), Ocean Chlorophyll 4 bands (OC4v4RAD), and Ocean Chlorophyll 2 bands (OC2v4RAD). The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS) with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3MSAT, and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01SAT), and CarderSAT. In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg/m3. In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m3 (OC2v4RAD). The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m3) than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m3, respectively). We find that rmsd values between MODIS relative to the in situ radiometric measurements are < 26%, i.e., there is a trend towards overestimation of RRS by MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed reflectance due to several errors in the bio-optical algorithm performance, in the satellite sensor calibration, and in the atmospheric-correction algorithm

Biases from incorrect reflectance convolution

Reflectance, a crucial earth observation variable, is converted from hyperspectral to multispectral through convolution. This is done to combine time series, validate instruments, and apply retrieval algorithms. However, convolution is often done incorrectly, with reflectance itself convolved rather than the underlying (ir)radiances. Here, the resulting error is quantified for simulated and real multispectral instruments, using 18 radiometric data sets (N = 1799 spectra). Biases up to 5% are found, the exact value depending on the spectrum and band response. This significantly affects extended time series and instrument validation, and is similar in magnitude to errors seen in previous validation studies. Post-hoc correction is impossible, but correctly convolving (ir)radiances prevents this error entirely. This requires publication of original data alongside reflectance.InstrumentationEnvironmental Biolog

Wind speed and mesoscale features drive net autotrophy in the South Atlantic Ocean

This is the final version. Available on open access from Elsevier via the DOI in this recordA comprehensive in situ dataset of chlorophyll a (Chl a; N = 18,001), net primary production (NPP; N = 165) and net community production (NCP; N = 95), were used to evaluate the performance of Moderate Resolution Imaging Spectroradiometer on Aqua (MODIS-A) algorithms for these parameters, in the South Atlantic Ocean, to facilitate the accurate generation of satellite NCP time series. For Chl a, five algorithms were tested using MODIS-A data, and OC3-CI performed best, which was subsequently used to compute NPP. Of three NPP algorithms tested, a Wavelength Resolved Model (WRM) was the most accurate, and was therefore used to estimate NCP with an empirical relationship between NCP with NPP and sea surface temperature (SST). A perturbation analysis was deployed to quantify the range of uncertainties introduced in satellite NCP from input parameters. The largest reductions in the uncertainty of satellite NCP came from MODIS-A derived NPP using the WRM (40%) and MODIS-A Chl a using OC3-CI (22%). The most accurate NCP algorithm, was used to generate a 16 year time series (2002 to 2018) from MODIS-A to assess climate and environmental drivers of NCP across the South Atlantic basin. Positive correlations between wind speed anomalies and NCP anomalies were observed in the central South Atlantic Gyre (SATL), and the Benguela Upwelling (BENG), indicating that autotrophic conditions may be fuelled by local wind-induced nutrient inputs to the mixed layer. Sea Level Height Anomalies (SLHA), used as an indicator of mesoscale eddies, were negatively correlated with NCP anomalies offshore of the BENG upwelling fronts into the SATL, suggesting autotrophic conditions are driven by mesoscale features. The Agulhas bank and Brazil-Malvinas confluence regions also had a strong negative correlation between SLHA and NCP anomalies, similarly indicating that NCP is forced by mesoscale eddy generation in this region. Positive correlations between SST anomalies and the Multivariate ENSO Index (MEI) in the SATL, indicated the influence of El Niño events on the South Atlantic Ocean, however the plankton community response was less clear.Natural Environment Research Council (NERC)European Space Agency (ESA)P&D ANP/BRASOILOceanographic Institute of the University of São Paulo (IOUSP

Factors affecting the identification of phytoplankton groups by means of remote sensing

A literature review was conducted on the state of the art as to whether or not information about communities and populations of phytoplankton in aquatic environments can be derived by remote sensing. In order to arrive at this goal, the spectral characteristics of various types of phytoplankton were compared to determine first, whether there are characteristic differences in pigmentation among the types and second, whether such differences can be detected remotely. In addition to the literature review, an extensive, but not exhaustive, annotated bibliography of the literature that bears on these questions is included as an appendix, since it constitutes a convenient resource for anyone wishing an overview of the field of ocean color. The review found some progress has already been made in remote sensing of assemblages such as coccolithophorid blooms, mats of cyanobacteria, and red tides. Much more information about the composition of algal groups is potentially available by remote sensing particularly in water bodies having higher phytoplankton concentrations, but it will be necessary to develop the remote sensing techniques required for working in so-called Case 2 waters. It is also clear that none of the satellite sensors presently available or soon to be launched is ideal from the point of view of what we might wish to know; it would seem wise to pursue instruments with the planned characteristics of the Moderate Resolution Imaging Spectrometer-Tilt (MODIS-T) or Medium Resolution Imaging Spectrometer (MERIS)

Aplicação de algoritmos semi-analíticos à imagens Sentinel-2 para a estimativa de Clorofila-a no Lago Paranoá-DF

Trabalho de Conclusão de Curso (especialização)—Universidade de Brasília, Instituto de Geociências, 2018.Este estudo tem como objetivo avaliar a performance de diferentes modelos semi-analíticos na obtenção da concentração de chl-a com uso de dados radiométricos de campo e, em seguida, avaliar a aplicabilidade deste modelo a imagens MSI corrigidas atmosfericamente por diferentes algoritmos. O estudo foi feito no Lago Paranoá. Localizado na capital do Brasil, Brasília, esse lago urbano é utilizado para múltiplas finalidades pela população local, tanto como receptor de efluentes domésticos, como para atividades recreativas e como fonte de água para abastecimento humano. No passado, este lago passou por fortes eventos de eutrofização, resultantes da descarga de nutrientes junto aos efluentes domésticos. Dado os usos múltiplos do lago, o seu monitoramento é ainda mais relevante

Designing, Building, and Managing an Autonomous Boat and its Transatlantic Crossing Attempt

Scout was a 13 foot long boat designed by myself and several of my friends to navigate without a crew on a 3,500 mile journey from Rhode Island to Spain using only solar power and onboard processors to complete the crossing. The project received significant media attention and was closely followed by tens of thousands of curious onlookers. Although Scout was built by a group of young college students solely for fun, execution of the project led us to begin investigation of ways that autonomous boats could be used in marine research applications. The purpose of this project is to study the entirety of the Scout project, examine potential uses of products similar to Scout, and present recommendations for future autonomous surface vessel development

Computational approaches for sub-meter ocean color remote sensing

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mechanical and Oceanographic Engineering at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2021.The satellite ocean color remote sensing paradigm developed by government space agencies enables the assessment of ocean color products on global scales at kilometer resolutions. A similar paradigm has not yet been developed for regional scales at sub-meter resolutions, but it is essential for specific ocean color applications (e.g., mapping algal biomass in the marginal ice zone). While many aspects of the satellite ocean color remote sensing paradigm are applicable to sub-meter scales, steps within the paradigm must be adapted to the optical character of the ocean at these scales and the opto-electronics of the available sensing instruments. This dissertation adapts the three steps of the satellite ocean color remote sensing paradigm that benefit the most from reassessment at sub-meter scales, namely the correction for surface-reflected light, the design and selection of the opto-electronics and the post-processing of over-sampled regions. First, I identify which surface-reflected light removal algorithm and view angle combination are optimal at sub-meter scales, using data collected during a field deployment to the Martha’s Vineyard Coastal Observatory. I find that of the three most widely used glint correction algorithms, a spectral optimization based approach applied to measurements with a 40∘ view angle best recovers the remotesensing reflectance and chlorophyll concentration despite centimeter scale variability in the surface-reflected light. Second, I develop a simulation framework to assess the impact of higher optical and electronics noise on ocean color product retrieval from unique ocean color scenarios. I demonstrate the framework’s power as a design tool by identifying hardware limitations, and developing potential solutions, for estimating algal biomass from high dynamic range sensing in the marginal ice zone. Third, I investigate a spectral super-resolution technique for application to spatially over-sampled oceanic regions. I determine that this technique more accurately represents spectral frequencies beyond the Nyquist and that it can be trained to be invariant to noise sources characteristic of ocean color remote sensing on images with similar statistics as the training dataset. Overall, the developed and critically assessed sub-meter ocean color remote sensing paradigm enables researchers to collect high fidelity sub-meter data from imaging spectrometers in unique ocean color scenarios.Ryan O’Shea was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program. This research was funded by Woods Hole Oceanographic Institution’s Edwin W. Hiam Ocean Science and Technology Award Fund, its Ocean Venture Funds, its Academic Programs Office, and the National Aeronautics and Space Administration via grant number CCE NNX17AI72G to Dr. Samuel Laney. The raw data for Figures 3-3 and 3-4 were provided through Australian Antarctic Science grants 2678 and 4390

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

Phytoplankton dynamics and bio-optical variables associated with Harmful Algal Blooms in aquaculture zones

The surveillance of Harmful Algal Blooms (HABs) in aquaculture zones is a crucial component in monitoring and mitigation of adverse effects caused by accumulation of high biomass of algal cells and/or associated toxins. Integrated findings of this thesis strongly stress the significance of synoptic bio-optical and conventional measures for efficient surveillance of HABs and their environmental triggers over required spatio-temporal scales, here shown for a case study in the Ebro Delta, NW Mediterranean. In particular, the installation of an environmental observatory in the Ebro Delta aquaculture area, and the capability of a radiometric sensor system as key component are highly motivated by study results. Yet it was clearly shown that for the interpretation of bio-optical data, detailed knowledge on bloom characteristics is crucial. By such effective coverage of bloom dynamics, combined with insights on environmental scenarios that promote the proliferation of certain taxa, public and private responses can be optimised. In a future scenario, this knowledge can be transferred to predictive models of HABs. In this sense, these future steps may advance towards preventive measures rather than mitigation actions to deal with this environmental hazard