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NASA NTRSDate not supplied

Advancing Satellite-Constrained Modeled Air-Sea CO 2 Fluxes With a Focus on the Strength of the Southern Ocean Carbon Sink

Challenge and Motivation: The ocean plays a critical role in mitigating climate change by removing approximately a quarter of annual anthropogenic CO 2 emissions from the atmosphere. Model-based estimates point to the Southern Ocean as a key marine region, responsible for approximately 40 % of the anthropogenic carbon uptake by the global ocean. However, the contemporary strength of the Southern Ocean carbon sink has recently come into question. On the one hand, airborne-based observations of atmospheric CO 2 gradients indicate that the Southern Ocean represents a strong net sink of atmospheric CO 2 , consistent in magnitude with atmospheric inversion estimates and surface-ocean partial pressure of CO 2 (pCO 2 )-based products. On the other hand, estimates of pCO 2 based on in situ pH measurements taken by biogeochemical profiling floats yield strong wintertime outgassing fluxes that greatly reduce the Southern Ocean’s annually integrated CO 2 uptake. This uncertainty in the strength of the Southern Ocean air-sea CO 2 flux and its role in the global carbon cycle hinders our ability to constrain global carbon fluxes, one of the major goals of NASA’s Carbon Monitoring System (CMS). Opportunity: The NASA Ocean Biogeochemical Model (NOBM) produces near-global pCO 2 and air-sea CO 2 flux estimates that are currently included into the NASA’s Goddard Earth Observing System (GEOS) models in support of the CMS effort to monitor global carbon fluxes. The NOBM assimilates ocean color data to improve the representation of biogeochemical fluxes and overcome spatial and temporal gaps in the space-based retrievals. Here, we propose to advance the satellite-constrained flux estimates by investigating the uncertainties in the Southern Ocean air-sea CO 2 flux produced by the NOBM, and assess the value that remote sensing ocean color data can have in providing improved estimates of carbon fluxes in the ocean. Our proposed work includes the delivery of refined in situ float-based carbon fluxes to serve as a constraint on the model-based estimates. Taking advantage of the model’s integration of satellite ocean color data to represent multiple phytoplankton groups, we propose to deliver maps of biogenic carbon export specific to each modeled phytoplankton type and investigate the role of ecological plankton complexity in regulating marine carbon uptake and export. Goals: (a) Delivery of seasonally-adjusted float-based Southern Ocean air-sea CO 2 fluxes: We will produce updated and improved float-based air-sea CO 2 fluxes that will serve as a bias-reduced float-based constraint to evaluate our model-based estimates of the NOBM. (b) Investigation of uncertainties in Southern Ocean air-sea CO 2 flux from the NOBM: Modeled air-sea carbon fluxes will be evaluated against the updated float product as well as ship- and airborne-based data to identify uncertainties and potential model deficiencies. (c) Delivery of model-based carbon export partitioning by phytoplankton functional types (PFTs): We will produce depth-resolved maps of particulate organic export production integrated for all phytoplankton groups and allocated to each individual PFT in the model. The expected significance of this goal is to quantify the role that the functional-oriented diversity in phytoplankton groups represented in the NOBM plays in regulating air-sea CO 2 fluxes in the Southern Ocean.

Lionel A. Arteaga↗
NASA NTRS2011

Deep Ocean Warming Assessed from Altimeters, GRACE, 3 In-situ Measurements, and a Non-Boussinesq OGCM

Observational surveys have shown significant oceanic bottom water warming, but they are too spatially and temporally sporadic to quantify the deep ocean contribution to the present-day sea level rise (SLR). In this study, altimetry sea surface height (SSH), Gravity Recovery and Climate Experiment (GRACE) ocean mass, and in situ upper ocean (0-700 m) steric height have been assessed for their seasonal variability and trend maps. It is shown that neither the global mean nor the regional trends of altimetry SLR can be explained by the upper ocean steric height plus the GRACE ocean mass. A non-Boussinesq ocean general circulation model (OGCM), allowing the sea level to rise as a direct response to the heat added into the ocean, is then used to diagnose the deep ocean steric height. Constrained by sea surface temperature data and the top of atmosphere (TOA) radiation measurements, the model reproduces the observed upper ocean heat content well. Combining the modeled deep ocean steric height with observational upper ocean data gives the full depth steric height. Adding a GRACE-estimated mass trend, the data-model combination explains not only the altimetry global mean SLR but also its regional trends fairly well. The deep ocean warming is mostly prevalent in the Atlantic and Indian oceans, and along the Antarctic Circumpolar Current, suggesting a strong relation to the oceanic circulation and dynamics. Its comparison with available bottom water measurements shows reasonably good agreement, indicating that deep ocean warming below 700 m might have contributed 1.1 mm/yr to the global mean SLR or one-third of the altimeter-observed rate of 3.11 +/- 0.6 mm/yr over 1993-2008.

sea level↗
NASA NTRS1992

Methods of testing parameterizations: Vertical ocean mixing

The ocean's velocity field is characterized by an exceptional variety of scales. While the small-scale oceanic turbulence responsible for the vertical mixing in the ocean is of scales a few centimeters and smaller, the oceanic general circulation is characterized by horizontal scales of thousands of kilometers. In oceanic general circulation models that are typically run today, the vertical structure of the ocean is represented by a few tens of discrete grid points. Such models cannot explicitly model the small-scale mixing processes, and must, therefore, find ways to parameterize them in terms of the larger-scale fields. Finding a parameterization that is both reliable and plausible to use in ocean models is not a simple task. Vertical mixing in the ocean is the combined result of many complex processes, and, in fact, mixing is one of the less known and less understood aspects of the oceanic circulation. In present models of the oceanic circulation, the many complex processes responsible for vertical mixing are often parameterized in an oversimplified manner. Yet, finding an adequate parameterization of vertical ocean mixing is crucial to the successful application of ocean models to climate studies. The results of general circulation models for quantities that are of particular interest to climate studies, such as the meridional heat flux carried by the ocean, are quite sensitive to the strength of the vertical mixing. We try to examine the difficulties in choosing an appropriate vertical mixing parameterization, and the methods that are available for validating different parameterizations by comparing model results to oceanographic data. First, some of the physical processes responsible for vertically mixing the ocean are briefly mentioned, and some possible approaches to the parameterization of these processes in oceanographic general circulation models are described in the following section. We then discuss the role of the vertical mixing in the physics of the large-scale ocean circulation, and examine methods of validating mixing parameterizations using large-scale ocean models.

Tziperman, Eli↗
NASA NTRS1996

Four-Dimensional Oceanic and Atmosperic Data Assimilation with Tropical Rainfall Measuring Mission Data

An oceanic data assimilation system which allows to utilize the forthcoming Tropical Rainfall Measuring Mission (TRMM) data has been developed and applied to the Pacific Ocean to produce the velocity field. The assimilated data will be indispensable to examine the effects of rainfall and its variability on the structure and circulation of the tropical oceans and to assess the impact of global warming due to the increase of carbon dioxide on the ocean circulation system and the marine pollution caused by oil spill and ocean damping of radionuclide. The data will also provide the verification for the oceanic and ocean-atmosphere coupled General Circulation Models (GCM's). The system consists of oceanic GCM, analysis scheme and data. In the system the flow field has been determined to be physically consistent with the observed density field and the sea surface winds derived from the Special Sensor Microwave Imagery (SSM/I) data which drive the ocean current. The time integration has been performed for five years until the flow field near the surface attained the steady state starting from the rest ocean with observed temperature and salinity fields, and the SSM/I surface wind velocity. The resultant flow field showed high producibility of the system. Especially the flow near the ocean surface agreed well with available observed data. The system, for the first time, succeeded to produce the eastward subtropical current which has been discovered in the joint investigation on Kuroshio current (CSK) in the 1960s. To verify the quality of the flow field a trajectory analysis has been carried out and compared with the Algos buoy data. BRIEF DESCRIPTION OF THE DATA ASSIMILATION SYSTEM ## Oceanic GCM and analysis scheme--The basic equations are much the same as used for the GCM's, except for the Newtonian damping terms introduced into the prediction equations for the potential temperature and salinity to maintain these fields as observed. The C grid of 2'lat. by 2'long. in horizontal and the 11 vertical levels are applied to the entire Pacific Ocean. At the east and west ocean boundaries the periodic boundary conditions are applied creating fictitious ocean there. The SMAC Method is used to increase the accuracy of mass conservation. * Data--The JODC temperature and salinity data obtained from 1906 to 1988 are used in the system between Long.100'E. and 60'W. The surface wind data are derived from the SSM/I data by Dr-R. Atlas of NASA/GSFC. The data set contains every 6 hours data from July 1987 to June 1989 on the grid of 2'lat. by 2.5'long. The averaged for the whole period and then interpolated into the 2'lat. by 2'long. grid data are used to force the system. The sea bottom topography data was based on the General Bathymetric Chart of the Ocean (GEBCO) supplied by the Canadian Hydrographic Service under contract with the International Hydrographic Organization and International Oceanographic Commission of UNESCO.

Takano, Kenji↗
DOE OSTI2026

Results of the second Ice Shelf–Ocean Model Intercomparison Project (ISOMIP+)

Ocean-driven basal melting of Antarctic ice shelves plays an important role in the mass loss of the Antarctic Ice Sheet. Ice shelf cavity-resolving ocean models are a valuable tool for understanding ice shelf-ocean interactions and for simulating projections of ice shelf and ocean states under future climate. Designed to assess the current state of ice shelf–ocean modelling, the second Ice Shelf–Ocean Model Intercomparison Project, ISOMIP+, consists of 12 ocean model configurations submitted with a common, idealised experimental setup. Here, we focus on the experiments Ocean0–2 (Asay-Davis et al., 2016), which are ocean models with idealised, static ice shelf geometries, but where the ocean reaches a balance with prescribed far-field ocean conditions. Different thermal transfer coefficient values (ranging from 0.011 to 0.2) are used for each model in the melting parameterisation to achieve a common, tuned melt rate since the models cover a range of types of vertical coordinates, ice–ocean boundary layer treatments, and numerical schemes. These model differences lead to spread in the resultant ocean properties, circulation, boundary-layer structure and spatial distribution of melting. We also highlight similarities between models, such as a shared linear relationship across most models between melt rate and overturning and barotropic streamfunctions during the spin-up and spin-down, demonstrating a robust relationship between melt and circulation across models and forcing conditions. The ISOMIP+ results provide a systematic comparison of ice shelf cavity-capable ocean models. However, we also demonstrate the need for realistic ice shelf–ocean model intercomparison projects (some already underway) to assess model biases and inter-model variation against sparse observations. Further research is needed to understand the differences between models and further improve our modelled representations of the ice–ocean boundary layer and ice shelf cavity circulation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Natural Ocean Carbon Cycle Sensitivity to Parameterizations of the Recycling in a Climate Model

Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10 %) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34 %, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which eventually resurfaces with the global thermohaline circulation especially in the Southern Ocean. Because of the reduced primary production and carbon export in GISSEH compared to GISSER, the biological pump efficiency, i.e., the ratio of primary production and carbon export at 75 m, is half in the GISSEH of that in GISSER, The Southern Ocean emerges as a key region where the CO2 flux is as sensitive to biological parameterizations as it is to physical parameterizations. The fidelity of ocean mixing in the Southern Ocean compared to observations is shown to be a good indicator of the magnitude of the biological pump efficiency regardless of physical model choice.

Antarctic Ocean↗
NASA NTRS2018

The NASA Roadmap to Ocean Worlds

In this article, we summarize the work of the NASA Outer Planets Assessment Group (OPAG) Roadmaps to Ocean Worlds (ROW) group. The aim of this group is to assemble the scientific framework that will guide the exploration of ocean worlds, and to identify and prioritize science objectives for ocean worlds over the next several decades. The overarching goal of an Ocean Worlds exploration program as defined by ROW is to “identify ocean worlds, characterize their oceans, evaluate their habitability, search for life, and ultimately understand any life we find.” The ROW team supports the creation of an exploration program that studies the full spectrum of ocean worlds, that is, not just the exploration of known ocean worlds such as Europa but candidate ocean worlds such as Triton as well. The ROW team finds that the confirmed ocean worlds Enceladus, Titan, and Europa are the highest priority bodies to target in the near term to address ROW goals. Triton is the highest priority candidate ocean world to target in the near term. A major finding of this study is that, to map out a coherent Ocean Worlds Program, significant input is required from studies here on Earth; rigorous Research and Analysis studies are called for to enable some future ocean worlds missions to be thoughtfully planned and undertaken. A second finding is that progress needs to be made in the area of collaborations between Earth ocean scientists and extraterrestrial ocean scientists.

Hendrix, Amanda R.↗
NASA NTRS2018

Consequences of Different Air-Sea Feedbacks on Ocean Using MITgcm and MERRA-2 Forcing: Implications for Coupled Data Assimilation Systems

Ocean surface flux estimates from atmospheric and oceanic reanalyses contain errors that compensate for inaccuracies in the respective atmosphere and ocean models used to generate these reanalyses. A conundrum for climate studies is the discrepancy between surface fluxes that minimize model-data differences for an atmosphere-only model vs surface fluxes that minimize model-data differences for an ocean model. As a first step towards a consistent coupled ocean-atmosphere data-assimilation (DA) system, we compare surface net heat flux from a state-of-the-art atmospheric reanalysis, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), to net heat flux from a state-of-the-art ocean state estimate, the Estimating the Circulation and Climate of the Ocean Version 4 (ECCO-v4). The possible impacts of the MERRA-2 and ECCO-v4 air-sea net heat flux difference in a coupled DA system were assessed using a set of experiments designed to imitate different “flavors” of a coupled DA system in an ocean-only setup. This was done by forcing the ECCO-v4 underlying ocean model - the Massachusetts Institute of Technology general circulation model (MITgcm) - with different sets of MERRA-2 fields and utilizing different forcing methods. By doing so we were able to turn off different air-sea feedbacks which, in a coupled DA setup, are partially muted by the constraining observations. The set of experiments, therefore, represents a range of active feedbacks in different “flavors” of coupled data-assimilation systems. For the period 1992–2011, MERRA-2 net heat flux has a global mean difference of -4.9 Wm(exp -2) relative to ECCO-v4. When MERRA-2 surface fields are used to force MITgcm, imbalances in the energy and the hydrological cycles of MERRA-2, which are directly related to the fact that MERRA-2 was created without an interactive ocean, propagate to the ocean. The experiment in which MITgcm is forced with MERRA-2 fluxes (MERRA-2-flux experiment) results in a 2.5°C global mean Sea Surface Temperature (SST) cooling, a 1m reduction in global mean sea level, and other drastic changes in the large scale ocean circulation relative to those resulting when the MITgcm is forced with the optimized ECCO-v4 net heat flux (the ECCO-v4 experiment itself). When MITgcm is forced with MERRA-2 state variables (MERRA-2-state experiment), the SST is somewhat restored to the observed SST, but the errors are shifted to the water cycle, resulting in a global mean sea level increase of 2.7 m. To further explore the pros and cons of these two approaches, we introduce a new intermediate forcing method in which the ocean is forced with turbulent fluxes but has a long wave feedback. This method, unlike MERRA-2 state, preserves the MERRA-2 water and salinity cycles, and it reduces the SST error compared to the MERRA-2-flux experiment, but the SST is not as good as that in the MERRA-2-state experiment. Our results have implications for ocean-model forcing recipes and clearly reveal the undesirable consequences of limiting the feedbacks in either these types of experiments or in coupled DA.

Ehud Strobach↗
NASA NTRS2023

The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) Project: A Review

The Southern Ocean serves as the primary gateway through which the intermediate, deep, and bottom waters of the ocean interact with the surface ocean (and thus the atmosphere), and it has a profound influence on the oceanic uptake of anthropogenic carbon and heat as well as nutrient resupply from the abyss to the surface. Yet it has been the least observed and understood region of the world ocean. The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project was implemented in 2014 with a goal to help remedy this deficit in observations and understanding. The SOCCOM project is based on two major advances that have the potential to transform understanding of the Southern Ocean. The first is the development of new biogeochemical sensors mounted on autonomous profiling floats that allow sampling of ocean biogeochemistry in 3-dimensional space. Floats may detect processes with a temporal resolution that ranges from hours to years. The second is that the climate modeling community finally has the computational resources and physical understanding to develop fully coupled climate models that can represent crucial, mesoscale processes in the Southern Ocean, as well as corresponding models that assimilate observations to produce a state estimate. The observational component, based on deployment of profiling floats with oxygen, nitrate, pH and bio-optical sensors, is generating vast amounts of new biogeochemical data that provide a year-round view of the Southern Ocean from the surface to 2000 m. The modeling effort is applying these observations and enhancing our understanding of the current ocean, and reducing uncertainty in projections of future carbon and nutrient cycles and climate. After nine years of operation, including a project renewal in the sixth year, the SOCCOM project has deployed more than 260 profiling floats. These floats have collected over 27,000 vertical profiles throughout the Southern Ocean. A data-assimilating biogeochemical state estimate model has been implemented. Here, the design of the SOCCOM project is reviewed and the scientific results that have been obtained are described. The project’s capability to help meet the observing system priorities outlined for a notional UN Decade for Ocean Sciences Southern Ocean observing system is assessed.

Jorge L. Sarmiento↗
NASA NTRS2019

Going Beyond Standard Ocean Color Observations: Lidar and Polarimetry

Passive ocean color images have provided a sustained synoptic view of the distribution of ocean optical properties and color and biogeochemical parameters for the past 20-plus years. These images have revolutionized our view of the ocean. Remote sensing of ocean color has relied on measurements of the radiance emerging at the top of the atmosphere, thus neglecting the polarization and the vertical components. Ocean color remote sensing utilizes the intensity and spectral variation of visible light scattered upward from beneath the ocean surface to derive concentrations of biogeochemical constituents and inherent optical properties within the ocean surface layer. However, these measurements have some limitations. Specifically, the measured property is a weighted-integrated value over a relatively shallow depth, it provides no information during the night and retrievals are compromised by clouds, absorbing aerosols, and low Sun zenithal angles. In addition, ocean color data provide limited information on the morphology and size distribution of marine particles. Major advances in our understanding of global ocean ecosystems will require measurements from new technologies, specifically lidar and polarimetry. These new techniques have been widely used for atmospheric applications but have not had as much as interest from the ocean color community. This is due to many factors including limited access to in-situ instruments and/or space-borne sensors and lack of attention in university courses and ocean science summer schools curricula. However, lidar and polarimetry technology will complement standard ocean color products by providing depth-resolved values of attenuation and scattering parameters and additional information about particle morphology and chemical composition. This review aims at presenting the basics of these techniques, examples of applications and at advocating for the development of in-situ and space-borne sensors. Recommendations are provided on actions that would foster the embrace of lidar and polarimetry as powerful remote sensing tools by the ocean science community.

Jamet, Cedric↗
NASA NTRS2023

Ocean Carbon From Space: Current Status and Priorities for the Next Decade

The ocean plays a central role in modulating the Earth’s carbon cycle. Monitoring how the ocean carbon cycle is changing is fundamental to managing climate change. Satellite remote sensing is currently our best tool for viewing the ocean surface globally and systematically, at high spatial and temporal resolutions, and the past few decades have seen an exponential growth in studies utilising satellite data for ocean carbon research. Satellite-based observations must be combined with in-situ observations and models, to obtain a comprehensive view of ocean carbon pools and fluxes. To help prioritise future research in this area, a workshop was organised that assembled leading experts working on the topic, from around the world, including remote-sensing scientists, field scientists and modellers, with the goal to articulate a collective view of the current status of ocean carbon research, identify gaps in knowledge, and formulate a scientific roadmap for the next decade, with an emphasis on evaluating where satellite remote sensing may contribute. A total of 449 scientists and stakeholders participated (with balanced gender representation), from North and South America, Europe, Asia, Africa, and Oceania. Sessions targeted both inorganic and organic pools of carbon in the ocean, in both dissolved and particulate form, as well as major fluxes of carbon between reservoirs (e.g., primary production) and at interfaces (e.g., air-sea and land–ocean). Extreme events, blue carbon and carbon budgeting were also key topics discussed. Emerging priorities identified include: expanding the networks and quality of in-situ observations; improved satellite retrievals; improved uncertainty quantification; improved understanding of vertical distributions; integration with models; improved techniques to bridge spatial and temporal scales of the different data sources; and improved fundamental understanding of the ocean carbon cycle, and of the interactions among pools of carbon and light. We also report on priorities for the specific pools and fluxes studied, and highlight issues and concerns that arose during discussions, such as the need to consider the environmental impact of satellites or space activities; the role satellites can play in monitoring ocean carbon dioxide removal approaches; economic valuation of the satellite based information; to consider how satellites can contribute to monitoring cycles of other important climatically-relevant compounds and elements; to promote diversity and inclusivity in ocean carbon research; to bring together communities working on different aspects of planetary carbon; maximising use of international bodies; to follow an open science approach; to explore new and innovative ways to remotely monitor ocean carbon; and to harness quantum computing. Overall, this paper provides a comprehensive scientific roadmap for the next decade on how satellite remote sensing could help monitor the ocean carbon cycle, and its links to the other domains, such as terrestrial and atmosphere.

oceanography↗
NASA NTRSDate not supplied

Visioning a Global Carbon Monitoring System That Can Quantify and Attribute Ocean Carbon Dioxide Removal: Where Are We Now and How Might We Get There?

As atmospheric greenhouse gas concentrations and the resulting social costs rise, it is increasingly important to conduct research on technical approaches to remove carbon dioxide from the atmosphere at the gigaton scale. One highly uncertain but perhaps plausible solution is ocean carbon dioxide (CO2) removal (CDR), which encompasses a suite of proposed techniques for increasing the net flux of CO2 from the atmosphere to the ocean. As reflected in a 2022 National Academy of Sciences report, interest in ocean CDR is rapidly growing, and new stakeholders from a wide range of fields want access to air-sea CO2 flux and ocean carbon information to understand the potential risks and benefits of ocean CDR. Moreover, there is an urgent need for research to develop a scientific basis to support these societal needs. At the same time, there is a growing need to vision a global carbon monitoring system that can quantify natural and anthropogenic perturbations in the air-sea CO2 flux to quantify and attribute the impacts of ocean CDR efforts on the ocean carbon sink. Here, we propose to present nascent efforts at the Ames Research Center to leverage NASA's unique remote sensing and computational capabilities and expertise in basic and applied Earth science to meet the needs of the ocean CDR stakeholder community as represented by the OceanVisions network. Specifically we aim to develop a global ocean CDR scenario explorer with two objectives: 1) to make quantitative estimates of the air-sea CO2 flux and its uncertainty more accessible to a wide range of users, and 2) to enable these diverse users to interactively explore the uncertain impacts on air-sea CO2 fluxes in a wide range of ocean CDR scenarios. The information would be provided to users via a public graphical user interface, and the results would be based on a new synthesis of scientific observations and knowledge in a global ocean mixed layer inverse model run on supercomputers. The proposed tool aims to fill a unique and valuable niche for users and the scientific community by balancing tradeoffs between user interests, scientific knowledge, and technical capabilities. We will conclude by visioning the potential implications for a global carbon monitoring system in a world with gigaton scale ocean CDR.

Global↗
NASA NTRS2022

Using Machine Learning for Timely Estimates of Ocean Color Information From Hyperspectral Satellite Measurements in the Presence of Clouds, Aerosols, and Sunglint

Retrievals of ocean color from space are important for better understanding of the ocean ecosystem but can be limited under conditions such as clouds, aerosols, and sunglint. Many ocean color algorithms use a few selected spectral bands to perform an atmospheric correction and then derive the upwelling radiance from the ocean. The limitations in the atmospheric correction under certain conditions lead to many gaps in daily spatial coverage of ocean color retrievals. To address these limitations, we introduce a new approach that uses machine learning to estimate ocean color from top of atmosphere radiances or reflectance measurements. In this approach, a principal component analysis is used to decompose the hyperspectral measurements into spectral features that describe the scattering and absorption of the atmosphere and the underlying surface. The coefficients of the principal components are then used to train a neural network to predict ocean color properties derived from the MODIS atmospheric correction algorithm. This machine learning approach is independent of a priori information and does not rely on any radiative transfer modeling. We apply the approach to two hyperspectral UV/VIS instruments, the ozone monitoring instrument (OMI) and the TROPOspheric Monitoring Instrument (TROPOMI), using measurements from 320–500 nm to show that it can be used to reproduce ocean color properties in less-than-ideal conditions. This machine learning approach complements the current atmospheric correction ocean color retrievals by filling in the gaps resulting from cloud, aerosol, and sunglint contamination. This method can be applied to the future hyperspectral Ocean Color Instrument (OCI), which will be onboard NASA’s Plankton, Aerosol Cloud, ocean Ecosystem (PACE) ocean color satellite set to launch in 2024.

Ocean color↗
DOE OSTI2025

Acidification in the Southern Ocean – current state and future challenges

The Southern Ocean is especially sensitive to ocean acidification, a process where carbon dioxide in the atmosphere is absorbed by the ocean, thereby changing its acidity levels. Observations show that open ocean waters across the Southern Ocean experienced faster rates of acidification over the past four decades than non-polar waters. Model simulations project more severe ocean acidification in Antarctic coastal waters than in the open ocean. Ocean acidification negatively impacts many Southern Ocean species, but our understanding of whole-ecosystem impacts is incomplete. Furthermore, it is important that we both maintain and expand observational capabilities and mechanistic experiments in this rapidly changing and vulnerable region of the ocean to understand the impacts of ocean acidification on Southern Ocean ecosystems.

Nissen, Cara [University of Amsterdam (The Netherl↗
NASA NTRS1992

The Global Ocean Observing System

A Global Ocean Observing System (GOOS) should be established now with international coordination (1) to address issues of global change, (2) to implement operational ENSO forecasts, (3) to provide the data required to apply global ocean circulation models, and (4) to extract the greatest value from the one billion dollar investment over the next ten years in ocean remote sensing by the world's space agencies. The objectives of GOOS will focus on climatic and oceanic predictions, on assessing coastal pollution, and in determining the sustainability of living marine resources and ecosystems. GOOS will be a complete system including satellite observations, in situ observations, numerical modeling of ocean processes, and data exchange and management. A series of practical and economic benefits will be derived from the information generated by GOOS. In addition to the marine science community, these benefits will be realized by the energy industries of the world, and by the world's fisheries. The basic oceanic variables that are required to meet the oceanic and predictability objectives of GOOS include wind velocity over the ocean, sea surface temperature and salinity, oceanic profiles of temperature and salinity, surface current, sea level, the extent and thickness of sea ice, the partial pressure of CO2 in surface waters, and the chlorophyll concentration of surface waters. Ocean circulation models and coupled ocean-atmosphere models can be used to evaluate observing system design, to assimilate diverse data sets from in situ and remotely sensed observations, and ultimately to predict future states of the system. The volume of ocean data will increase enormously over the next decade as new satellite systems are launched and as complementary in situ measuring systems are deployed. These data must be transmitted, quality controlled, exchanged, analyzed, and archived with the best state-of-the-art computational methods.

Kester, Dana↗
NASA NTRS1992

Atmospheric correction of AVIRIS data in ocean waters

Hyperspectral data offers unique capabilities for characterizing the ocean environment. The spectral characterization of the composition of ocean waters can be organized into biological and terrigenous components. Biological photosynthetic pigments in ocean waters have unique spectral ocean color signatures which can be associated with different biological species. Additionally, suspended sediment has different scattering coefficients which result in ocean color signatures. Measuring the spatial distributions of these components in the maritime environments provides important tools for understanding and monitoring the ocean environment. These tools have significant applications in pollution, carbon cycle, current and water mass detection, location of fronts and eddies, sewage discharge and fate etc. Ocean color was used from satellite for describing the spatial variability of chlorophyll, water clarity (K(sub 490)), suspended sediment concentration, currents etc. Additionally, with improved atmospheric correction methods, ocean color results produced global products of spectral water leaving radiance (L(sub W)). Ocean color results clearly indicated strong applications for characterizing the spatial and temporal variability of bio-optical oceanography. These studies were largely the results of advanced atmospheric correction techniques applied to multispectral imagery. The atmosphere contributes approximately 80 percent - 90 percent of the satellite received radiance in the blue-green portion of the spectrum. In deep ocean waters, maximum transmission of visible radiance is achieved at 490nm. Conversely, nearly all of the light is absorbed by the water at wavelengths greater than about 650nm and thus appears black. These spectral ocean properties are exploited by algorithms developed for the atmospheric correction used in satellite ocean color processing. The objective was to apply atmospheric correction techniques that were used for procesing satellite Coastal Zone Color Scanner (CZCS) data to AVIRIS data. Quantitative measures of L(sub W) from AVIRIS are compared with ship ground truth data and input into bio-optical models.

Terrie, Gregory↗
NASA NTRS1997

Oceanic Observations

For many years, merchant ships and the naval fleets of various countries have been the major source of data over and in the open ocean. Oceanographic research experiments and process studies in the field have also contributed to the climatological data bases for the global ocean, but, for the most part, these have been limited in duration and extent. However, over the last 10 years under the auspices of the World Climate Research Program and the International Geosphere Biosphere Program the role of the oceans in global and climate change has taken on increased significance. This has created a need for a considerably improved understanding of the seasonal, interannual, decadal and longer time-scale variability of the physical and biogeochemical attributes of the global ocean. As a result, over the past 10 years several major international field programs have been implemented and have had a tremendous impact on the number of in situ observations obtained for the global ocean. The Tropical Ocean Global Atmosphere (TOGA) program, the World Ocean Circulation Experiment (WOCE), and the Joint Global Ocean Flux Study (JGOFS) were designed with observational, modelling, and process study components aimed at analyzing different aspects of the ocean's role in the coupled climate system. In parallel with the field programs, continuous space-based observations of sea surface temperature, sea surface topography, and sea surface winds spanning nearly a decade or longer have become a reality. During this same time period, numerical ocean models and computational power have advanced to the point where the oceanographic observations, both in situ and remotely sensed, can be assimilated into numerical ocean models in order to provide a four-dimensional (x-y-z-t) depiction of the evolving state of the global ocean.

Busalacchi, Antonio J.↗
NASA NTRS2001

Merging Ocean Color Data from Multiple Missions

Oceanic phytoplankton may play an important role in the cycling of carbon on the Earth, through the uptake of carbon dioxide in the process of photosynthesis. Although they are ubiquitous in the global oceans, their abundances and dynamics are difficult to estimate, primarily due to the vast spatial extent of the oceans and the short time scales over which their abundances can change. Consequently, the effects of oceanic phytoplankton on biogeochemical cycling, climate change, and fisheries are not well known. In response to the potential importance of phytoplankton in the global carbon cycle and the lack of comprehensive data, the National Aeronautics and Space Administration (NASA) and the international community have established high priority satellite missions designed to acquire and produce high quality ocean color data. Seven of the missions are routine global observational missions: the Ocean Color and Temperature Sensor (OCTS), the Polarization and Directionality of the Earth's Reflectances sensor (POLDER), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectrometer-AM (MODIS-AM), Medium Resolution Imaging Spectrometer (MERIS), Global Imager (GLI), and MODIS-PM. In addition, there are several other missions capable of providing ocean color data on smaller scales. Most of these missions contain the spectral band complement considered necessary to derive oceanic pigment concentrations (i.e., phytoplankton abundance) and other related parameters. Many contain additional bands that can provide important ancillary information about the optical and biological state of the oceans. Any individual ocean color mission is limited in ocean coverage due to sun glint and clouds. For example, one of the first proposed missions, the SeaWiFS, can provide about 45% coverage of the global ocean in four days and only about 15% in one day.

Gregg, Watson W.↗