Publications
Following publications have been announced by our department Optical Oceanography. For further information please contact Dr. Martin Hieronymi, co-author of the publications:
Brewin, R.J.W., Sathyendranath, S., Kulk, G., Rio, M.-H., Concha, J.A., Bell, T.G., Bracher, A., Fichot, C., Frölicher, T.L., Galí, M., Hansell, D.A., Kostadinov, T.S., Mitchell, C., Neeley, A.R., Organelli, E., Richardson, K., Rousseaux, C., Shen, F., Stramski, D., Tzortziou, M., Watson, A.J., Addey, C.I., Bellacicco, M., Bouman, H., Carroll, D., Cetinić, I., Dall’Olmo, G., Frouin, R., Hauck, J., Hieronymi, M., Hu, C., Ibello, V., Jönsson, B., Kong, C.E., Kovač, Z., Laine, M., Lauderdale, J., Lavender, S., Livanou, E., Llort, J., Lorinczi, L., Nowicki, M., Pradisty, N.A., Psarra, S., Raitsos, D.E., Ruescas, A.B., Russell, J.L., Salisbury, J., Sanders, R., Shutler, J.D., Sun, X., Taboada, F.G., Tilstone, G.H., Wei, X., & Woolf, D.K. (2023): Ocean carbon from space: Current status and priorities for the next decade. Earth-Science Reviews, Volume 240, 104386, doi:10.1016/j.earscirev.2023.104386
Abstract:
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.
Bi, S., Röttgers, R., & Hieronymi, M. (2023): Transfer model to determine the above-water remote-sensing reflectance from the underwater remote-sensing ratio. Optics Express Vol. 31, Issue 6, pp. 10512-10524, doi:10.1364/OE.482395
Abstract:
Remote-sensing reflectance, Rrs(λ, θ, Δϕ, θs), contains the spectral color information of the water body below the sea surface and is a fundamental parameter to derive satellite ocean color products such as chlorophyll-a, diffuse light attenuation, or inherent optical properties. Water reflectance, i.e., spectral upwelling radiance, normalized by the downwelling irradiance, can be measured under- or above-water. Several models to extrapolate this ratio from underwater “remote-sensing ratio”, rrs(λ), to the above-water Rrs, have been proposed in previous studies, in which the spectral dependency of water refractive index and off-nadir viewing directions have not been considered in detail. Based on measured inherent optical properties of natural waters and radiative transfer simulations, this study proposes a new transfer model to spectrally determine Rrs from rrs for different sun-viewing geometries and environmental conditions. It is shown that, compared to previous models, ignoring spectral dependency leads to a bias of ∼2.4% at shorter wavelengths (∼400 nm), which is avoidable. If nadir-viewing models are used, the typical 40°-off nadir viewing geometry will introduce a difference of ∼5% in Rrs estimation. When the solar zenith angle is higher than 60°, these differences of Rrs have implications for the downstream retrievals of ocean color products, e.g., > 8% difference for phytoplankton absorption at 440 nm and >4% difference for backward particle scattering at 440 nm by the quasi-analytical algorithm (QAA). These findings demonstrate that the proposed rrs-to-Rrs model is applicable to a wide range of measurement conditions and provides more accurate estimates of Rrs than previous models.
El Kassar, J., Juhls, B., Hieronymi, M., Preusker, R., Morgenstern, A., Fischer, J., & Overduin, P.P. (2023): Optical remote sensing (Sentinel-3 OLCI) used to monitor dissolved organic carbon in the Lena River, Russia. Front. Mar. Sci., 10:1082109, doi:10.3389/fmars.2023.1082109
Abstract:
In the past decades the Arctic has experienced stronger temperature increases than any other region globally. Shifts in hydrological regimes and accelerated permafrost thawing have been observed and are likely to increase mobilization of organic carbon and its transport through rivers into the Arctic Ocean. In order to better quantify changes to the carbon cycle, Arctic rivers such as the Lena River in Siberia need to be monitored closely. Since 2018, a sampling program provides frequent in situ observations of dissolved organic carbon (DOC) and colored dissolved organic matter (CDOM) of the Lena River. Here, we utilize this ground truth dataset and aim to test the potential of frequent satellite observations to spatially and temporally complement and expand these observations. We explored all available overpasses (~3250) of the Ocean and Land Colour Instrument (OLCI) on Sentinel-3 within the ice-free periods (May – October) for four years (2018 to 2021) to develop a new retrieval scheme to derive concentrations of DOC. OLCI observations with a spatial resolution of ~300 m were corrected for atmospheric effects using the Polymer algorithm. The results of this study show that using this new retrieval, remotely sensed DOC concentrations agree well with in situ DOC concentrations (MAPD=10.89%, RMSE=1.55 mg L−1, r²=0.92, n=489). The high revisit frequency and wide swath of OLCI allow it to capture the entire range of DOC concentrations and their seasonal variability. Estimated satellite-derived DOC export fluxes integrated over the ice-free periods of 2018 to 2021 show a high interannual variability and agree well with flux estimates from in situ data (RMSD=0.186 Tg C, MAPD=4.05%). In addition, 10-day OLCI composites covering the entire Lena River catchment revealed increasing DOC concentration and local sources of DOC along the Lena from south to north. We conclude that moderate resolution satellite imagers such as OLCI are very capable of observing DOC concentrations in large/wide rivers such as the Lena River despite the relatively coarse spatial resolution. The global coverage of remote sensing offers the expansion to more rivers in order to improve our understanding of the land-ocean carbon fluxes in a changing climate.
