Extreme events and impacts on organic carbon cycles from ocean color remote sensing: Review with case study, challenges, and future directions

D’Sa, Eurico J.; Tzortziou, M.; Liu, Bingqing

doi:10.1016/j.earscirev.2023.104503

Cited by 7 publications

(5 citation statements)

References 156 publications

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“…Compared to baseline conditions, this single extreme precipitation event led to dramatic changes in estuarine carbon regimes, with increases by more than a factor of two in DOC and more than a factor of three in a CDOM . This magnitude of increase in DOC loading is consistent with other studies highlighting the impact of tropical storms on aquatic carbon cycling across different estuarine systems (e.g., Cao et al., 2018; Liu et al., 2019; Cao & Tzortziou, 2021; D’Sa et al., 2023). Moreover, OLCI revealed that Tropical Storm Isaias resulted in an abrupt change in S 275−295 across LIS, consistent with other studies suggesting that extreme events drive changes not only in the quantity but also the quality of exported organic matter (Cao & Tzortziou, 2021; Fellman et al., 2009; Nguyen et al., 2010).…”

Section: Resultssupporting

confidence: 91%

“…Episodic disturbances include severe droughts, extreme flooding, and intense precipitation (e.g., Cavalcante et al., 2021; Coble et al., 2018; Guarch‐Ribot & Butturini, 2016; Hounshell et al., 2019). These forcings, coupled with anthropogenic influences, collectively contribute to the DOC and CDOM distributions observed by satellites across highly dynamic and heterogeneous urban estuaries (Joshi et al., 2017; Cao et al., 2018; Cao & Tzortziou, 2021; D'Sa et al., 2023). Here, we conducted a retrospective analysis using daily OLCI imagery, monthly composites, and monthly climatology across the Sound to assess how these different physical and biogeochemical drivers synergistically influence organic carbon plumes and dynamics in this heavily populated urban environment.…”

Section: Resultsmentioning

confidence: 99%

“…Previous studies have suggested that, due to shorter residence times, the surge of DOC associated with tropical cyclones can completely overwhelm the estuarine biogeochemical filter (Asmala et al., 2020). Such rapid, transient pulses of terrigenous DOC can, thus, have important biogeochemical and ecological implications across the estuarine–ocean continuum, shifting areas of intense carbon transformation or storage further downstream into the coastal and open ocean domains (Raymond et al., 2016; Asmala et al., 2020; D'Sa et al., 2023).…”

Section: Discussionmentioning

confidence: 99%

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Impacts of Hydrology and Extreme Events on Dissolved Organic Carbon Dynamics in a Heavily Urbanized Estuary and Its Major Tributaries: A View From Space

Cao,

Tzortziou

2024

JGR Biogeosciences

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Dissolved organic matter and its colored component, Colored Dissolved Organic Matter (CDOM), play a major role in global carbon budgets, and their fluxes provide an essential link between terrestrial and aquatic biogeochemical cycles. Satellite observations can uniquely capture the hydro‐biogeochemical connectivity of terrestrial and aquatic landscapes, across scales. Yet, accurate satellite retrievals of CDOM and dissolved organic carbon (DOC) dynamics remain challenging in urbanized estuaries and coasts. Here, we present an advanced unified algorithm for space‐based retrieval of coastal CDOM and DOC dynamics and its application in Long Island Sound—one of the world's most heavily urbanized estuaries that is becoming increasingly vulnerable to climate change stressors. A rich bio‐optical data set, encompassing a wide range of environmental conditions, was integrated into the algorithm training to retrieve DOC concentrations and CDOM spectral shape (i.e., spectral slope S275–295)—a proxy for DOC quality. The new algorithms were applied to full‐resolution satellite imagery from the Sentinel‐3 Ocean and Land Color Instrument (OLCI) after thoroughly evaluating the performance of six ocean color atmospheric correction approaches (ACOLITE, BAC, C2RCC, MUMM, l2gen, and Polymer). Evaluation of the algorithms yielded mean absolute percent differences of 28%, 12%, and 10% for aCDOM(300), S275–295, and DOC, respectively. Application of the algorithms to multi‐year satellite OLCI imagery captured, for the first time, the coupled impact of seasonal transitions, wind regimes, freshwater inputs, anthropogenic disturbances, and hydrological extremes (both intense precipitation and droughts) on DOC fluxes and CDOM quality at the ecosystem scale. Results have important implications for improved predictions of coastal biogeochemical fluxes in complex urban−estuary systems.

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Section: Resultssupporting

confidence: 91%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Impacts of Hydrology and Extreme Events on Dissolved Organic Carbon Dynamics in a Heavily Urbanized Estuary and Its Major Tributaries: A View From Space

Cao,

Tzortziou

2024

JGR Biogeosciences

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“…While the lidar technique clearly provides many advantages for improved understanding and monitoring of the global ocean, it also has limitations (e.g., near-nadir viewing only and limited spectral resolution). As our global ocean ecosystems are confronted with an increasing number of compounding stressors, including warming temperatures and acidification [49,50], strengthening water column stratification and associated shifts in nutrient stress [51][52][53], expanding fisheries exploitations [54][55][56][57][58][59], increasingly frequent regional-scale extreme events (e.g., marine heat waves) [60][61][62], thinning and retreat of seasonal sea ice [63], and proliferation of plastics pollution [64,65], a sustained and complementary global observing system is required to quantify, predict, and mitigate associated impacts. Such an observing system must be inclusive of satellite lidar, passive ocean color, and polarimetry measurements [2,4,66], modeling, and in situ observations.…”

Section: Lidar Advantagementioning

confidence: 99%

Satellite Lidar Measurements as a Critical New Global Ocean Climate Record

Behrenfeld,

Lorenzoni,

et al. 2023

Remote Sensing

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The year 2023 marked the tenth anniversary of the first published description of global ocean plankton stocks based on measurements from a satellite lidar. Diverse studies have since been conducted to further refine and validate the lidar retrievals and use them to discover new characteristics of plankton seasonal dynamics and marine animal migrations, as well as evaluate geophysical products from traditional passive ocean color sensors. Surprisingly, all of these developments have been achieved with lidar instruments not designed for ocean applications. Over this same decade, we have witnessed unprecedented changes in ocean ecosystems at unexpected rates and driven by a multitude of environmental stressors, with a dominant factor being climate warming. Understanding, predicting, and responding to these ecosystem changes requires a global ocean observing network linking satellite, in situ, and modeling approaches. Inspired by recent successes, we promote here the creation of a lidar global ocean climate record as a key element in this envisioned advanced observing system. Contributing to this record, we announce the development of a new satellite lidar mission with ocean-observing capabilities and then discuss additional technological advances that can be envisioned for subsequent missions. Finally, we discuss how a potential near-term gap in global ocean lidar data might, at least partially, be filled using on-orbit or soon-to-be-launched lidars designed for other disciplinary purposes, and we identify upcoming needs for in situ support systems and science community development.

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“…Remote sensing approaches were also used to map and monitor seagrass distribution and abundance [31,[34][35][36]; however, these applications have largely focused on seagrasses in clear coastal waters [37][38][39]. In contrast, non-marine SAV mapping presents particular challenges, especially in turbid estuarine waters where chlorophyll [40,41], dissolved organic carbon [42], and suspended minerals [43] can affect water clarity and the strength of the sensed light signal. Numerous remote sensing methods have been developed to detect SAV for large-scale and long-term monitoring.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Potential Contribution of Submerged Aquatic Vegetation to Coastal Carbon Capture in a Delta System from Field and Landsat 8/9-Operational Land Imager (OLI) Data with Deep Convolutional Neural Network

Liu,

Sevick,

Jung

et al. 2023

Remote Sensing

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Submerged aquatic vegetation (SAV) are highly efficient at carbon sequestration and, despite their relatively small distribution globally, are recognized as a potentially valuable component of climate change mitigation. However, SAV mapping in tidal marshes presents a challenge due to optically complex constituents in the water. The emergence and advancement of deep learning-based techniques in the field of habitat mapping with remote sensing imagery provides an opportunity to address this challenge. In this study, an analytical framework was developed to quantify the carbon sequestration of SAV habitats in the Atchafalaya River Delta Estuary from field and remote sensing observations using deep convolutional neural network (DCNN) techniques. A U-Net-based model, Wetland-SAV Network, was trained to identify the SAV percent cover (high, medium, and low) as well as other estuarine habitat types from Landsat 8/9-OLI data. The areal extent of SAV was up to 8% of the total area (47,000 ha). The habitat areas and habitat-specific carbon fluxes were then used to quantify the net greenhouse gas (GHG) flux of the study area for with/without SAV scenarios in a carbon balance model. The total net GHG flux was in the range of −0.13 ± 0.06 to −0.86 ± 0.37 × 105 tonne CO2e y−1 and increased up to 40% (−0.23 ± 0.10 to −0.90 ± 0.39 × 105 tonne CO2e y−1) when SAV was accounted for within the calculation. At the hectare scale, the inclusion of SAV resulted in an increase of ~60% for the net GHG sink in shallow areas adjacent to the emergent marsh where SAV was abundant. This is the first attempt at remotely mapping SAV in coastal Louisiana as well as a first quantification of net GHG flux at the scale of hectares to thousands of hectares, accounting for SAV within these sub-tropical coastal delta marshes. Remote sensing and deep learning models have high potential for mapping and monitoring SAV in turbid sub-tropical coastal deltas as a component of the increasing accuracy of net GHG flux estimates at small (hectare) and large (coastal basin) scales.

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Extreme events and impacts on organic carbon cycles from ocean color remote sensing: Review with case study, challenges, and future directions

Cited by 7 publications

References 156 publications

Impacts of Hydrology and Extreme Events on Dissolved Organic Carbon Dynamics in a Heavily Urbanized Estuary and Its Major Tributaries: A View From Space

Impacts of Hydrology and Extreme Events on Dissolved Organic Carbon Dynamics in a Heavily Urbanized Estuary and Its Major Tributaries: A View From Space

Satellite Lidar Measurements as a Critical New Global Ocean Climate Record

Quantifying the Potential Contribution of Submerged Aquatic Vegetation to Coastal Carbon Capture in a Delta System from Field and Landsat 8/9-Operational Land Imager (OLI) Data with Deep Convolutional Neural Network

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