Ocean Water Properties Research Articles

Is the Regime Shift in Gulf Stream Warm Core Rings Detected by Satellite Altimetry? An Inter‐Comparison of Eddy Identification and Tracking Products

AbstractDownstream of Cape Hatteras, the vigorously meandering Gulf Stream forms anticyclonic warm core rings (WCRs) that carry warm Gulf Stream and Sargasso Sea waters into the cooler, fresher Slope Sea, and forms cyclonic cold core rings (CCRs) that carry Slope Sea waters into the Sargasso Sea. The Northwest Atlantic shelf and open ocean off the U.S. East Coast have experienced dramatic changes in ocean circulation and water properties in recent years, with significant consequences for marine ecosystems and coastal communities. Some of these changes may be related to a reported regime shift in the number of WCRs formed annually, with a doubling of WCRs shed after 2000. Since the regime shift was detected using a regional eddy‐tracking product, primarily based on sea surface temperatures and relies on analyst skill, we examine three global eddy‐tracking products as an automated and potentially more objective way to detect changes in Gulf Stream rings. Currently, global products rely on altimeter‐measured sea surface height (SSH), with WCRs registering as sea surface highs and CCRs as lows. To identify eddies, these products use either SSH contours or a Lagrangian approach, with particles seeded in satellite‐based surface geostrophic velocity fields. This study confirms the three global products are not well suited for statistical analysis of Gulf Stream rings and suggests that automated WCR identification and tracking comes at the price of accurate identification and tracking. Furthermore, a shift to a higher energy state is detected in the Northwest Atlantic, which coincides with the regime shift in WCRs.

Variability in the relationship between light scattering and chlorophyll a concentration in oligotrophic tropical regions of the Western Pacific Ocean.

It is important to determine the relationship between the concentration of chlorophyll a (Chla) and the inherent optical properties (IOPs) of ocean water to develop optical models and algorithms that characterize the biogeochemical properties and estimate biological pumping and carbon flux in this environment. However, previous studies reported relatively large variations in the particulate backscattering coefficient (bbp(λ)) and Chla from more eutrophic high-latitude waters to clear oligotrophic waters, especially in oligotrophic oceanic areas where these two variables have little covariation. In this study, we examined the variability of bbp(λ) and Chla in the euphotic layer in oligotrophic areas of the tropical Western Pacific Ocean and determined the sources of these variations by reassessment of in-situ measurements and the biogeochemical-argo (BGC-Argo) database. Our findings identified covariation of bbp(λ) and Chla in the water column below the deep Chla maximum (DCM) layer, and indicated that there was no significant correlation relationship between bbp(λ) and Chla in the upper layer of the DCM. Particles smaller than 3.2 µm that were in the water column above the DCM layer had a large effect on the bbp(λ) in the vertical profile, but particles larger than 3.2 µm and smaller than 10 µm had the largest effect on the bbp(λ) in the water column below the DCM layer. The contribution of non-algal particles (NAPs) to backscattering is up to 50%, which occurs in the water depth of 50 m and not consistent with the distribution of Chla. Phytoplankton and NAPs were modeled as coated spheres and homogeneous spherical particles to simulate the bbp(λ) of the vertical profile by Aden-Kerker method and Mie theory, and the results also indicated that the backscattering caused by particles less than 20 µm were closer to the measured data when they were below and above the DCM layer, respectively. This relationship also reflects the bbp(λ) of particles in the upper water was significantly affected particle size, but bbp(λ) in the lower water was significantly affected by Chla concentration. This effect may have relationship with phytoplankton photoacclimation and the relationship of a phytoplankton biomass maximum with particle size distribution in the water column according to the previous relevant studies. These characteristics also had spatial and seasonal variations due to changes of Chla concentration at the surface and at different depths. There was mostly a linear relationship between Chla and bbp(700) during winter. During other seasons, the relationship between these two variables was better characterized by a power function (or a logarithmic function) in the lower layer of the DCM. The spatial and vertical relationships between the bbp(λ) and Chla and the corresponding variations in the types of particles described in this study provide parameters that can be used for accurate estimation of regional geochemical processes.

Local forcing mechanisms challenge parameterizations of ocean thermal forcing for Greenland tidewater glaciers

Abstract. Frontal ablation has caused 32 %–66 % of Greenland Ice Sheet mass loss since 1972, and despite its importance in driving terminus change, ocean thermal forcing remains crudely incorporated into large-scale ice sheet models. In Greenland, local fjord-scale processes modify the magnitude of thermal forcing at the ice–ocean boundary but are too small scale to be resolved in current global climate models. For example, simulations used in the Ice Sheet Intercomparison Project for CMIP6 (ISMIP6) to predict future ice sheet change rely on the extrapolation of regional ocean water properties into fjords to drive terminus ablation. However, the accuracy of this approach has not previously been tested due to the scarcity of observations in Greenland fjords, as well as the inability of fjord-scale models to realistically incorporate icebergs. By employing the recently developed IceBerg package within the Massachusetts Institute of Technology general circulation model (MITgcm), we here evaluate the ability of ocean thermal forcing parameterizations to predict thermal forcing at tidewater glacier termini. This is accomplished through sensitivity experiments using a set of idealized Greenland fjords, each forced with equivalent ocean boundary conditions but with varying tidal amplitudes, subglacial discharge, iceberg coverage, and bathymetry. Our results indicate that the bathymetric obstruction of external water is the primary control on near-glacier thermal forcing, followed by iceberg submarine melting. Despite identical ocean boundary conditions, we find that the simulated fjord processes can modify grounding line thermal forcing by as much as 3 °C, the magnitude of which is largely controlled by the relative depth of bathymetric sills to the Polar Water–Atlantic Water thermocline. However, using a common adjustment for fjord bathymetry we can still predict grounding line thermal forcing within 0.2 °C in our simulations. Finally, we introduce new parameterizations that additionally account for iceberg-driven cooling that can accurately predict interior fjord thermal forcing profiles both in iceberg-laden simulations and in observations from Kangiata Sullua (Ilulissat Icefjord).

Mid-Atlantic Bight cold pool based on ocean glider observations

During summer, distinctive, bottom-trapped, cold water mass of remnant local and remote winter water called Cold Pool Water (CPW) resides as a swath over the mid to outer continental shelf throughout much of the Mid-Atlantic Bight (MAB). This evolving CPW is important because it strongly influences the ecosystem, including several important fisheries. Thus, there is a priority to better understand the relevant ocean processes and develop CPW forecast capability. Over the past decade, repeated high-resolution Slocum glider measurements of ocean water properties along a New Jersey cross-shelf transect have helped to define the variability of the CPW structure off New Jersey. More recently the Mid-Atlantic Regional Association Coastal Ocean Observing System-supported ocean gliders have occupied a series of along-shelf zigzag trajectories from Massachusetts to New Jersey and New Jersey to Maryland. The comprehensive set of March through November 2007 glider measurements has been used to define the annual evolution of the 10 °C Cold Pool in terms of its distribution and water properties. The rather steady warming at the rate of 1 °C per month July through October 2007 is reflected in the 2007 CPW temperature (T) and salinity (S) properties. We describe how a three-glider fleet view of the September 2013 Cold Pool (a) confirmed the Lentz (2017) CPW cold patch and (b) the impingement of a Gulf Stream warm core ring warmed and salted the 2013 CPW. The Gulf Sream 2013 event forced our extension of the CPW T and S properties.

Offshore wind data assessment near the Iberian Peninsula over the last 25 years

Numerous processes affecting coastal ocean dynamics and water properties occur at the air-sea interface as a result of wind blowing on the ocean surface. In Earth system research, it is crucial to appropriately characterize the ocean surface wind (OSW) field because of its significance in many academic and economic activities. This study aimed to evaluate the accuracy of the most recent OSW datasets based on numerical modeling and remote sensing products in estimating in situ observations along the Atlantic coast of the Iberian Peninsula. The results are three-fold: (1) when high temporal resolutions are not necessary, remote sensing products are an excellent choice because they provide reliable OSW estimates; (2) for analyses that require high temporal resolution, numerical weather models are the best choice because they can statistically reproduce the main trend; (3) fifth generation of European ReAnalysis (ERA5) showed that, despite having a lower spatial resolution than the dynamically downscaled weather research and forecasting simulation, it captures the spatial and temporal dynamics and variability of coastal winds and may be used as forcing of the atmosphere-ocean interface modeling without compromising its accuracy.

Plankton Genes and Extracellular Organic Substances in the Ocean

Dissolved organic matter (DOM) in the ocean represents about 662 billion tons of C, 200 times more than the living biomass. It is produced mainly by microbial primary production. The largest fraction of this DOM is old (>weeks to months) and both chemically and biologically recalcitrant. The remainder is young (seconds to weeks), more labile and surface active. Part of the latter fraction changes the rheological properties in the bulk phase of the water and at interfaces including the sea surface microlayer (SML). In order of abundance, this DOM consists of sugars, amino acids, fatty acids and nucleic acids, often incorporated into complex polymers. The DOM molecules are produced by microbial genes, and are further modified by enzymes themselves produced by genes. The properties of ocean water and its interfaces as well as biogeochemical fluxes may thus be modified by ocean plankton genes. These fluxes influence ocean and atmospheric climate, which in return acts on the biota. Viral infection may furthermore modify prokaryotic and eukaryotic genes and their expression. Therefore, the ocean plankton genomes and the fluxes and climates they influence may be subject to Darwinian-type selection. Research programs need to integrate ocean ecology, rheology, biogeochemistry and genomics, to find the associations among them.

Review Article on Microbiology

Microbiology is the study of microorganisms biological entities too small to be seen with the unaided eye. Most major advances in microbiology have occurred within the past 150 years, and several important subdisciplines of microbiology have developed during this time, including microbial ecology, molecular biology, immunology, industrial microbiology and biotech- nology. Microorganisms of various types exist in all three domains of life (the Bacteria, Archaea and Eukarya), and they are by far the most abundant life forms on Earth. Microscopic biological agents include bacteria, archaea, protists (protozoa and algae), fungi, parasitic worms (helminths) and viruses. Although a small percentage of microorganisms are harmful to certain plants and animals and may cause serious disease in humans, the vast majority of microorganisms provide beneficial services, such as assisting in water purification and the production of certain foods, and many are essential for the proper functioning of Earth's ecosystems. Molecular biology has revolutionized our understanding of the diversity, function, and community structure of marine microorganisms. Increasingly, tools and techniques derived from the biomedical diagnostics and research industries are used in parallel with sensors that characterize the physical, chemical, and optical properties of ocean waters.

Review on Microbiology and Molecular Biology

Microbiology is the study of microorgan- isms biological entities too small to be seen with the unaided eye. Most major advances in microbiology have occurred within the past 150 years, and several important subdisciplines of microbiology have developed during this time, including microbial ecology, molecular biology, immunology, industrial microbiology and biotech- nology. Microorganisms of various types exist in all three domains of life (the Bacteria, Archaea and Eukarya), and they are by far the most abundant life forms on Earth. Microscopic biological agents include bacteria, archaea, protists (protozoa and algae), fungi, parasitic worms (helminths) and viruses. Although a small percentage of microor- ganisms are harmful to certain plants and animals and may cause serious disease in humans, the vast majority of microorganisms provide beneficial services, such as assisting in water purification and the production of certain foods, and many are essential for the proper functioning of Earth's ecosystems. Molecular biology has revolutionized our understanding of the diversity, function, and community structure of marine microorganisms. Increasingly, tools and techniques derived from the biomedical diagnostics and research industries are used in parallel with sensors that characterize the physical, chemical, and optical properties of ocean waters.

Measured IOPs of Jerlov water types.

Inherent optical properties (IOPs) of typical ocean waters have been derived from a worldwide database of measured parameters. The optical quality of the world's oceans can be described in terms of their Jerlov water type, ranging from the clearest Jerlov I to the most turbid Jerlov 9C. These Jerlov classifications are defined in terms of an apparent optical property known as the downwelling diffuse attenuation coefficient (Kd). There is a need to relate these Jerlov water types to their IOPs, namely their absorption coefficient, a, and scattering coefficient, b. However, robust values of a and b for Jerlov water types have not previously existed. This study used the World-wide Ocean Optics Database to derive a series of experimentally measured a and b values for six Jerlov water types. Using data science techniques to group measurements in time and space, over 13.5 million data points were consolidated into 53 measured values for a and b. Established models were subsequently applied to generate a complete table of absorption and scattering coefficients from 300 to 800 nm for Jerlov IB to Jerlov 5C. The analysis includes the influence of changes in the solar zenith angle and the scattering phase function. These data are recommended for use in applications where IOPs are required to describe Jerlov water types.

Effect of scattering phase function on underwater visible light communication channel models

Non-sequential ray tracing simulations are commonly employed to model underwater visible light communication (VLC) channels. The accuracy of such simulations highly depends on how well the optical properties of water (i.e., absorption and scattering) as well as scattering phase function (SPF) are modeled in the simulation. Existing empirical models are only a function of chlorophyll concentration and particle composition and are independent of refractive index, size and concentration of particles. In this paper, we carry out an underwater VLC channel modeling study using the Mie SPF which provides a full description of the scattering from phytoplankton particles which dominate the optical properties of most oceanic waters. We obtain the channel impulse response (CIR) based on an extensive non-sequential ray tracing study and calculate the fundamental channel parameters such as channel gain and delay spread. Comparison of CIRs reveals out that deployment of simplified SPF models results in the overestimation of path loss with respect to Mie SPF. Our results clearly demonstrate the importance of selecting realistic SPF models for an accurate underwater VLC channel modeling. While highlighting the channel models, we discuss adaptive modulation technique to maximize the data rate under the constraint of a targeted bit error rate. Besides, the maximum achievable distance is also determined both in terms of analytical guarantees and computer simulations. The results reveal that larger transmission distances can be achieved through Mie SPF channel model.

Review of underwater optical communication system

From deep oceans to coastal waterways, UOWC offers a wide range of possible uses. However, the most significant obstacle to underwater wireless communication is the fundamental properties of ocean or sea water; overcoming these obstacles necessitates a deep understanding of complicated physio-chemical biological systems. The major goal of this article is to determine the feasibility and dependability of high data rate underwater optical connections in light of different propagation phenomena that affect the system's performance. This article gives a comprehensive review of current UOWC developments. UOWC-specific noise sources, channel characterization, modulation methods, coding approaches, and different noise sources are all covered. This article intends to give not only comprehensive research in underwater optical communication, but also the creation of new concepts that will aid in the future expansion of underwater communication. All of this has spurred the rise of underwater optical wireless communication (UOWC), which provides faster data rates and lower power consumption than traditional acoustic communication systems, as well as lesser computing complexity for short-range wireless communications. UOWC has a wide range of applications, from deep seas to coastal rivers. The basic characteristics of ocean or sea water, on the other hand, are the most important impediment to underwater wireless communication; overcoming these difficulties requires a thorough understanding of complex physio-chemical biological systems.

Antarctic Water Masses and Ice Shelves: Visualizing the Physics.

High-resolution simulation of global climate physics enables us to model how the climate may change under a variety of future scenarios. Such simulations produce vast amounts of information and dense datasets. If interrogated in tandem, these datasets can provide holistic, vital information on Earth's many integrated systems by revealing the manifold interrelated properties of the atmosphere, ocean, and polar ice, framed by real-world terrain in three-dimensional space as they vary over time. To accomplish this, climate scientists have joined with computer scientists and an artist to develop techniques enabling scientists to see these relationships. The impact of ocean water properties on Antarctic ice shelves illustrates the benefit of this analysis in understanding land ice melt rates and thus sea-level rise.

A neural network approach for deriving absorption coefficients of ocean water constituents from total light absorption and particulate absorption coefficients

Inherent Optical Properties (IOPs) of oceanic and coastal waters provide useful information for studying light availability in various ocean layers, primary productivity, particulate matter, and aquatic photochemistry. The total spectral absorption coefficient, a(λ) and spectral particulate absorption coefficient, ap(λ) are the IOPs that are some of the extensively measured IOPs with the existing absorption instruments. The total spectral absorption coefficient is often expressed as the sum of subcomponent IOPs, phytoplankton (aph(λ)), combined absorption due gelbstoff and detritus (adg(λ)) and the water itself. Similarly, ap can be subdivided into aph(λ) and ad(λ), the detrital absorption coefficients. The existing models partition these IOPs into subcomponent IOPs by assuming spectral shapes for subcomponent IOPs and are computationally intensive. Hence, in this study, we implemented Neural Networks to derive the subcomponent IOPs due to their lower computational time requirement and their capability to model complex relationships. We trained and validated four Neural Networks (NN) for retrieval of IOPs from a(λ) and ap(λ). NNs - I &II are used to retrieve aph and adg at 443 nm from a(λ). Similarly, NNs - III &IV are used to derive aph(443) and ad(443) from ap(λ). The four NNs are trained and tested using synthetic data created encompassing a wide range of optical properties observed in natural waters. For validation of the four NNs, the International Ocean Color Coordinating Group (IOCCG) simulated dataset, NASA bio-Optical Marine Algorithm Dataset (NOMAD) and global bio-optical insitu dataset (GBI) are used. The R2 values obtained for GBI in the retrieval of aph(443) and adg(443) using NNs - I &II are 0.95 and 0.97, respectively. Similarly, aph and ad retrieved using NN–III & IV resulted in R2 values of 0.94 and 0.94 for the NOMAD dataset. Upon comparing the performance NNs - I &II with Quasi-Analytical Algorithm (QAA) in retrieving IOPs using the IOCCG dataset, the NNs exhibited lower errors. We also developed a hybrid algorithm, QAANN, to demonstrate the capability of NNs - I &II for remote sensing applications. QAANN resulted in 11–43% lower mean absolute percentage error (MAPE) compared to QAA, Generalized Inherent Optical Property (GIOP) and Garver-Siegel-Maritorena (GSM) models for aph(443) retrieval using remote sensing reflectance from IOCCG simulated dataset. In the case of adg(443), QAANN resulted in 5–10% less MAPE compared to other models for the same dataset. These results suggest that the developed NNs can be applied to satellite remote sensing data to retrieve subcomponent IOPs with improved accuracy.

Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters

Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.

Secular trends in water properties at Station P in the northeast Pacific: An updated analysis

Oceanographic observations collected at Station P (145°W, 50°N) in the northeast Pacific extend for over six decades, representing one of the longest available records of subsurface ocean water properties. As such, this record is well suited to examine secular trends in properties of the subarctic waters of the North Pacific. In this paper, previously published trends are reviewed and updated, based on a newly compiled dataset for the station. Vertically integrated quantities such as ocean heat content and steric height are examined, as well as local water properties through the water column including temperature, salinity and, in particular, oxygen. Consideration is also given to upper-ocean stratification, along with depths of the mixed layer and isopycnal surfaces.The results provide a comprehensive view of long-term changes to ocean conditions in the deep waters of the subarctic Pacific. Increases in 0/2000 dbar ocean heat content and steric height are evident, due primarily to ocean warming through the upper 500 dbar of the water column. However, about a third of the overall 0/2000 dbar steric height trend is due to halosteric effects. A significant freshening trend is evident through the upper layer to the top of the permanent pycnocline. Significant changes are also found below the permanent pycnocline, in particular warming on isopycnal surfaces along with downward migration of isopycnals. On the other hand, no robust trend emerges in the strength of the stratification associated with the permanent pycnocline, a result that likely has implications for turbulent exchanges between the surface mixed layer and the deep ocean, including the supply of nutrients to the euphotic zone.Statistically significant declines in dissolved oxygen are observed on isopycnals below the pycnocline, down to great depth. Column-integrated dissolved oxygen has declined at a rate of 0.72 mol m−2 y−1, representing a net loss over six decades of 11.7 ± 3.5% in total oxygen content per square metre. This is substantially greater than the global average of 2%, underscoring the northeast Pacific as a region of comparatively rapid deoxygenation. Changes in solubility due to local warming have made only a minor contribution to the observed decline.

Theoretical and Numerical Analyses on Propulsive Efficiency of Unmanned Aquatic Vehicle’s Propeller

Hydrodynamic effects are severely affecting the performance of a Marine Propeller. Basically, manuvering of an Unmanned Aquatic Vehicle’s is controlled by its propeller, which is drastically depends on the fluid. Therefore the study about fluid behaviour and its effects are mandatory to enhance the efficiency of the marine propeller. In this work deals, the hydrodynamic force estimations on the marine propeller by using both theoretical formulae and numerical analysis. The aim of this work is to obtain the fine tuned hydrodynamic forces of marine propeller for its performance enhancement. Fundamentally, complexities involved in the force estimation approaches are represent the fluid behaviour and environmental conditions. Standard formulae are used for estimations of hydrodynamic forces. CATIA is used for the generation of conceptual design on the marine propeller. ANSYS Fluent 16.2 is used for numerical simulation, in which fluid is provided the ocean water properties. Finally, the hydrodynamic forces are compared for future work.

INVERSION MODEL TO DERIVE SHALLOW WATER DEPTH OVER PIROTAN REEF, GULF OF KACHCHH REGION, INDIA

Remote sensing technology has ability to monitor bio-optical properties of ocean water surrounding the reef. Coral reefs are usually found in relatively shallow and clear waters surrounding the continents and island. The objective of this study to derive shallow water depth in coral reef environment over Pirotan reef, Gulf of Kachchh region using hyperspectral imagery. Hyperspectral sensor is one of the best options to study the coral reef environment. A semianalyticalmethodutilizeshyperspectral remote sensing data to retrieve water depth. Semi-analytical method are the most recent developing methods in shallow water remote sensing. The image of derived water depth has found ranging from 0.1 to 5.0 m. The spatial variation of model water depth has been found different over the reef because of their uneven morphological structure. The water model output of water depth is compared closely with data acquired during field survey over the reef and the root mean square (rms) error was calculated. The correlation coefficient values has been observed around 0.86.

Configuration and spin-up of ACCESS-CM2, the new generation Australian Community Climate and Earth System Simulator Coupled Model

A new version of the Australian Community Climate and Earth System Simulator coupled model, ACCESS-CM2, has been developed for a wide range of climate modelling research and applications. In particular, ACCESS-CM2 is one of Australia’s contributions to the World Climate Research Programme’s Coupled Model Intercomparison Project Phase 6 (CMIP6). Compared with the ACCESS1.3 model used for our CMIP5 submission, all model components have been upgraded as well as the coupling framework (OASIS3-MCT) and experiment control system (Rose/Cylc). The component models are: UM10.6 GA7.1 for the atmosphere, CABLE2.5 for the land surface, MOM5 for the ocean, and CICE5.1.2 for the sea ice. This paper describes the model configuration of ACCESS-CM2, documents the experimental set up, and assesses the model performance for the preindustrial spin-up simulation in comparison against (reconstructed) observations and ACCESS1.3 results. While the performance of the two generations of the ACCESS coupled model is largely comparable, ACCESS-CM2 shows better global hydrological balance, more realistic ocean water properties (in terms of spatial distribution) and meridional overturning circulation in the Southern Ocean but a poorer simulation of the Antarctic sea ice and a larger energy imbalance at the top of atmosphere. This energy imbalance reflects a noticeable warming trend of the global ocean over the spin-up period.

UV Reflectance of the Ocean from DSCOVR/EPIC: Comparisons with a Theoretical Model and Aura/OMI Observations

AbstractUltraviolet (UV) data collected over the ocean by the Earth Polychromatic Imaging Camera (EPIC) on theDeep Space Climate Observatory(DSCOVR) are used. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm adapted for EPIC processing performs cloud detection, aerosol retrievals, and atmospheric correction providing the water-leaving reflectance of the ocean at 340 and 388 nm. The water-leaving reflectance is an indicator of the presence of absorbing and scattering constituents in seawater. The retrieved water-leaving reflectance is compared with full radiative transfer calculations based on a model of inherent optical properties (IOP) of ocean water in UV. The model is verified with data collected on the Aerosol Characterization Experiments (ACE) Asia cruise supported by the NASA Sensor Intercomparison for Marine Biological and Interdisciplinary Ocean Studies (SIMBIOS) project. The model assumes that the ocean water IOPs are parameterized through a chlorophyll concentration. The radiative transfer simulations were carried out using the climatological chlorophyll concentration from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board theAquasatellite. The EPIC-derived water-leaving reflectance is also compared with climatological Lambertian-equivalent reflectivity (LER) of the ocean derived from measurements of the Ozone Monitoring Instrument (OMI) on board the NASA polar-orbitingAurasatellite. The EPIC reflectance agrees well (within 0.01) with the model reflectance except for oligotrophic oceanic areas. For those areas, the model reflectance is biased low by about 0.01 at 340 nm and up to 0.03 at 388 nm. The OMI-derived climatological LER is significantly higher than the EPIC water-leaving reflectance, largely due to the surface glint contribution. The globally averaged difference is about 0.04.

Inversion of multiangular polarimetric measurements over open and coastal ocean waters: a joint retrieval algorithm for aerosol and water-leaving radiance properties

Abstract. Ocean color remote sensing is a challenging task over coastal waters due to the complex optical properties of aerosols and hydrosols. In order to conduct accurate atmospheric correction, we previously implemented a joint retrieval algorithm, hereafter referred to as the Multi-Angular Polarimetric Ocean coLor (MAPOL) algorithm, to obtain the aerosol and water-leaving signal simultaneously. The MAPOL algorithm has been validated with synthetic data generated by a vector radiative transfer model, and good retrieval performance has been demonstrated in terms of both aerosol and ocean water optical properties (Gao et al., 2018). In this work we applied the algorithm to airborne polarimetric measurements from the Research Scanning Polarimeter (RSP) over both open and coastal ocean waters acquired in two field campaigns: the Ship-Aircraft Bio-Optical Research (SABOR) in 2014 and the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) in 2015 and 2016. Two different yet related bio-optical models are designed for ocean water properties. One model aligns with traditional open ocean water bio-optical models that parameterize the ocean optical properties in terms of the concentration of chlorophyll a. The other is a generalized bio-optical model for coastal waters that includes seven free parameters to describe the absorption and scattering by phytoplankton, colored dissolved organic matter, and nonalgal particles. The retrieval errors of both aerosol optical depth and the water-leaving radiance are evaluated. Through the comparisons with ocean color data products from both in situ measurements and the Moderate Resolution Imaging Spectroradiometer (MODIS), and the aerosol product from both the High Spectral Resolution Lidar (HSRL) and the Aerosol Robotic Network (AERONET), the MAPOL algorithm demonstrates both flexibility and accuracy in retrieving aerosol and water-leaving radiance properties under various aerosol and ocean water conditions.