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Robert Frouin

Publications and source records attributed to Robert Frouin.

10 records
All sourcesNASA NTRSDOE OSTI
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 NTRS2022

Estimates of Diurnal and Daily Net Primary Productivity Using the Geostationary Ocean Color Imager (GOCI) Data

For the past three decades, polar-orbiting ocean color satellites have provided local, regional to global scale estimates of oceanic net primary production that have greatly aided studies of ocean carbon cycling, food web dynamics and climate change. Despite considerable progress, accurate estimates of daily ocean productivity from space have not been realized because polar-orbiting satellites are unable to account for variations in phytoplankton physiology and carbon fixation rates from changing incident irradiance levels over the course of the day. Here we have attempted to exploit the unique short-temporal measurements provided by the Korean Geostationary Ocean Color Imager (GOCI), to obtain for the first time, diurnal and daily measurements of surface- and euphotic-column integrated Net Primary Productivity (NPP). These estimates are based on the Absorption Based Productivity Model (AbPM), and are calibrated with a bio-optical database of measurements made at different times of the day during the Korea-US Ocean Color (KORUS-OC) cruise in May–June 2016. Photo-physiological rate estimates, varied across different water types encountered around the Korean Peninsula, but on account of their limited number, were regionally scaled through the use of dynamic optical-biogeochemical (O-BGC) Biomes. Comparisons of GOCI derived estimates of daily and weekly integrated NPP against in-situ measurements, clearly underscore the superiority of geostationary over polar-orbiting ocean color satellites, which consider the strong short-term fluctuations in phytoplankton light absorption and incident irradiance fields over the course of the day.

Diurnal productivity↗
NASA NTRS2021

NASA's Surface Biology and Geology Designated Observable: A Perspective on Surface Imaging Algorithms

The 2017–2027 National Academies’ Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a “Designated Targeted Observable” (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380–2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3–5 μm; TIR: 8–12 μm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algo-rithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. This effort synthesizes the findings of more than 130 scientists.

Aquatic↗
NASA NTRS2019

Testbed Results for Scalar and Vector Radiative Transfer Computations of Light in Atmosphere-Ocean Systems

We generate and tabulate reflectance values of the Stokes parameters I, Q, and U of upwelling radiance just above a rough ocean surface and at the top of the atmosphere (TOA) for 100 scattering geometries, four atmosphere-ocean systems, and four wavelengths. The atmosphere-ocean systems increase in complexity from (a) a molecular atmosphere above a rough ocean surface (AOS-I model); to (b) a pure water body below a rough ocean surface (AOS-II model); to (c) a fully-coupled simple atmosphere-ocean system (AOS-III model) containing a molecular atmosphere, rough ocean surface, and pure water; to (d) a fully-coupled complex atmosphere-ocean system (AOS-IV model) that includes scattering by molecules, rough ocean surface, pure water, and hydrosols. Our wavelengths (350, 450, 550, and 650 nm) capture the ultraviolet-visible range. Our tables provide radiative transfer (RT) testbed results for atmosphere-ocean systems with an accuracy that surpasses the measurement accuracy of state-of-the-art polarimeters. To validate the accuracy of these tables we performed computations using three independent RT codes that provide deterministic numerical solutions for the RT equation. The agreement is 10(exp –5) for AOS-IV model, and 10(exp –6) for the other models. The degree of linear polarization computed by these RT codes differs by ≤0.2% for 15 isolated cases of tabulated reflectance values, and by ≤0.1% for all remaining cases. We also provide comparisons with results obtained by a stochastic RT code for AOS-I model. The agreement between the deterministic and stochastic results for this model is 10(exp –5) at TOA, and 10(exp –6) above the ocean surface.

Polarimeters↗
NASA NTRS2019

Retrieving Aerosol Characteristics From the PACE Mission, Part 1: Ocean Color Instrument

NASA’s Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) satellite mission is scheduled to launch in 2022, with the Ocean Color Instrument (OCI) on board. For the first time reflected sunlight from the Earth across a broad spectrum from the ultraviolet (UV: 350 nm) to the short wave infrared (SWIR: 2260 nm) will be measured from a single instrument at 1 km spatial resolution. While seven discrete bands will represent the SWIR, the spectrum from 350 to 890 nm will be continuously covered with a spectral resolution of 5 nm. OCI will thus combine in a single instrument (and at an enhanced spatial resolution for the UV) the heritage capabilities of the Moderate resolution Imaging Spectroradiometer (MODIS) and the Ozone Monitoring Instrument (OMI), while covering the oxygen A-band (O2A). Designed for ocean color and ocean biology retrievals, OCI also enables continuation of heritage satellite aerosol products and the development of new aerosol characterization from space. In particular the combination of MODIS and OMI characteristics allows deriving aerosol height, absorption and optical depth along with a measure of particle size distribution. This is achieved by using the traditional MODIS visible-to-SWIR wavelengths to constrain spectral aerosol optical depth and particle size. Extrapolating this information to the UV channels allows retrieval of aerosol absorption and layer height. A more direct method to derive aerosol layer height makes use of O2A absorption methods, despite the relative coarseness of the nominal 5 nm spectral resolution of OCI. Altogether the PACE mission with OCI will be an unprecedented opportunity for aerosol characterization that will continue climate data records from the past decades and propel aerosol science forward toward new opportunities.

PACE↗
NASA NTRS2019

A Compilation of Global Bio-Optical in Situ Data for Ocean-Colour Satellite Applications – Version Two

A global compilation of in situ data is useful to evaluate the quality of ocean-colour satellite data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (including, inter alia, MOBY, BOUSSOLE, AERONETOC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO) and span the period from 1997 to 2018. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficients and total suspended matter. The data were from multi-project archives acquired via open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were propagated throughout the work and made available in the final table. By making the metadata available, provenance is better documented, and it is also possible to analyse each set of data separately. This paper also describes the changes that were made to the compilation in relation to the previous version (Valente et al., 2016). The compiled data are available at https://doi.org/10.1594/PANGAEA.898188.

Andre Valente↗