The Use of VGPM to Estimate Oceanic Primary Production: A “Tango” Difficult to Dance

Lee, Zhongping; Marra, John

doi:10.34133/2022/9851013

Cited by 7 publications

(8 citation statements)

References 33 publications

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“…The higher rates of NPP estimated from the CbPM are more comparable to the long‐term mean of in situ NPP measured at Station ALOHA (577 mg C m −2 d −1 ) (Karl & Church, 2017). These spatial patterns and comparisons further highlight the uncertainties in NPP estimated from satellite data using either VGPM or CbPM (Z. Lee & Marra, 2022; Song et al., 2023).…”

Section: Spatial and Seasonal Variations In The Npsgmentioning

confidence: 66%

Upper Ocean Biogeochemistry of the Oligotrophic North Pacific Subtropical Gyre: From Nutrient Sources to Carbon Export

Dai,

Luo,

Achterberg

et al. 2023

Reviews of Geophysics

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Subtropical gyres cover 26%–29% of the world's surface ocean and are conventionally regarded as ocean deserts due to their permanent stratification, depleted surface nutrients, and low biological productivity. Despite tremendous advances over the past three decades, particularly through the Hawaii Ocean Time‐series and the Bermuda Atlantic Time‐series Study, which have revolutionized our understanding of the biogeochemistry in oligotrophic marine ecosystems, the gyres remain understudied. We review current understanding of upper ocean biogeochemistry in the North Pacific Subtropical Gyre, considering other subtropical gyres for comparison. We focus our synthesis on spatial variability, which shows larger than expected dynamic ranges of properties such as nutrient concentrations, rates of N2 fixation, and biological production. This review provides new insights into how nutrient sources drive community structure and export in upper subtropical gyres. We examine the euphotic zone (EZ) in subtropical gyres as a two‐layered vertically structured system: a nutrient‐depleted layer above the top of the nutricline in the well‐lit upper ocean and a nutrient‐replete layer below in the dimly lit waters. These layers vary in nutrient supply and stoichiometries and physical forcing, promoting differences in community structure and food webs, with direct impacts on the magnitude and composition of export production. We evaluate long‐term variations in key biogeochemical parameters in both of these EZ layers. Finally, we identify major knowledge gaps and research challenges in these vast and unique systems that offer opportunities for future studies.

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Section: Spatial and Seasonal Variations In The Npsgmentioning

confidence: 66%

Upper Ocean Biogeochemistry of the Oligotrophic North Pacific Subtropical Gyre: From Nutrient Sources to Carbon Export

Dai,

Luo,

Achterberg

et al. 2023

Reviews of Geophysics

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“…CbPM uses spectrally resolved light attenuation and is based on a semi-analytical algorithm (Garver-Siegel-Maritorena, GSM, Maritorena et al, 2002) which tries to distinguish optical signatures from phytoplankton, particles and dissolved organic matter. Nevertheless, both algorithms are subject to large uncertainties (Lee and Marra, 2022). When compared with VGPM, the model simulation generally underestimated the remotely sensed NPP estimations (Table 3), especially in the subtropical Pacific.…”

Section: Modeled Versus Satellite-based Chlorophyl Amentioning

confidence: 99%

“…350as a standard NPP estimation from ocean color for the last 20 years(Lee and Marra, 2022). VGPM therefore carries uncertain-ties related to the global Chlorophyll algorithm (OC4) adapted to CASE-I waters (low influence of dissolved organic matter https://doi.org/10.5194/gmd-2023-2 Preprint.…”

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confidence: 99%

Ocean biogeochemistry in the coupled ocean-sea ice-biogeochemistry model FESOM2.1-REcoM3

Gürses¹,

Oziel

Karakuş

et al. 2023

Preprint

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Abstract. The cycling of carbon in the oceans is affected by feedbacks driven by changes in climate and atmospheric CO2. Understanding these feedbacks is therefore an important prerequisite for projecting future climate. Marine biogeochemical models are a useful tool there, but as any model is a simplification, need to be continually improved. In this study, we coupled the Finite-volumE Sea ice-Ocean Model (FESOM2.1) to the Regulated Ecosystem Model version 3 (REcoM3). FESOM2.1 is an update of the Finite Element Sea ice-Ocean Model (FESOM1.4) and operates on variable mesh resolution. Unlike standard structured-mesh ocean models, the mesh flexibility allows for a realistic representation of small-scale dynamics in key regions at affordable computational cost. Compared to the previous coupled model version FESOM1.4-REcoM2, the model FESOM2.1-REcoM3 utilizes a new dynamical core based on a finite volume discretization instead of finite elements, but retains central parts of the biogeochemistry model. As a new feature, carbonate chemistry including water vapor correction is computed by mocsy-2.0. Moreover, REcoM3 has an extended food web that includes macrozooplankton and fast-sinking detritus. Dissolved oxygen is added as a new tracer. In this study we assess the ocean and biogeochemical state simulated with FESOM2.1-REcoM3 in a global setup at relatively low spatial resolution forced with JRA55-do atmospheric reanalysis. The focus is on the recent period 1958–2021, to assess how well the model can be used for present-day and future climate change scenarios on decadal to centennial timescales. A bias in global ocean-atmosphere preindustrial CO2 flux present in the previous model version FESOM1.4-REcoM2 could be significantly reduced. In addition, the computational efficiency is 2–3 times higher than that of FESOM1.4-REcoM. Overall, it is found that FESOM2.1-REcoM3 is a skillful tool for ocean biogeochemical modelling applications.

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“…Currently, an inversion strategy for NPP that could be used in all seas has yet to be established. A series of model comparison exercises demonstrated that the same model has different accuracy in different regions (Campbell et al, 2002;Carr et al, 2006), and that some results could not simulate the variability of NPP accurately (Lee YJ et al, 2015;Lee and Marra, 2022). In particular, the ocean color chlorophyll-a (CHL) algorithm is challenged by optically complex Case-2 waters, which could affect the performance of NPP models (Saba et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…However, the results of the VGPM might include large errors or even show contrasting variability in some areas of the SCS (Xie et al, 2020;Lee and Marra, 2022). For example, Xie et al (2020) reversed the seasonal pattern in NPP in northern shelf waters of the SCS by replacing the CHL-based euphotic depth with that based on the inherent optical properties and by optimizing the model parameters using the nearest neighbor method.…”

Section: Introductionmentioning

confidence: 99%

Seasonal variability of satellite-derived primary production in the South China Sea from an absorption-based model

Wang²,

Xu³

et al. 2023

Front. Mar. Sci.

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Seasonal patterns of marine net primary production (NPP) are crucial for understanding the marine ecosystem and biogeochemical cycles. Uncoupling of seasonal variations between NPP and phytoplankton chlorophyll-a over different areas has attracted much attention. In this study, following a review of previous studies, monthly climatological NPP data from 2003 to 2020, estimated using the Size-fractioned Phytoplankton Pigment Absorption (aph)-based NPP Model (SABPM), were selected to study the seasonal variability of NPP in the South China Sea (SCS). Results showed the spatial differences of NPP seasonality and its departures from climatology in extreme El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) years. Cluster analysis for climatological monthly data identified significant differences of NPP seasonality in five typical regions. In coastal regions along the northern SCS and off eastern Vietnam, NPP exhibited the most obvious seasonal cycle with maximum (minimum) values in summer (winter), attributable mainly to river discharge and summer upwelling. In regions off northwestern Luzon and coast of southern SCS, NPP showed peaks in winter, which were related to strong mixing and upwelling. In northwestern SCS, NPP was high during May–September in phase with sea surface temperature and the primary controlling factors were found to be shallow nutricline depth and wind-driven mixing. Owing to the deep nutricline depth in the central basin, NPP exhibited little seasonal variability; only a weak signal was observed in spring in phase with photosynthetically active radiation. Local dynamics on regulating the nutrient supply and light availability contribute to these regional differences in NPP seasonality, which could also be affected by extreme climate events. The largest anomalies of the NPP seasonal cycle coincide with 2015/2016 ENSO and super IOD in 2020. During these events, enhanced (weakened) westerly winds caused fall (rise) of SLA and increase (decrease) of NPP in coastal regions along the northern SCS and that off eastern Vietnam. Overall, the aph-based model shows a new perspective to study the spatiotemporal variations of NPP in the SCS.

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The Use of VGPM to Estimate Oceanic Primary Production: A “Tango” Difficult to Dance

Cited by 7 publications

References 33 publications

Upper Ocean Biogeochemistry of the Oligotrophic North Pacific Subtropical Gyre: From Nutrient Sources to Carbon Export

Upper Ocean Biogeochemistry of the Oligotrophic North Pacific Subtropical Gyre: From Nutrient Sources to Carbon Export

Ocean biogeochemistry in the coupled ocean-sea ice-biogeochemistry model FESOM2.1-REcoM3

Seasonal variability of satellite-derived primary production in the South China Sea from an absorption-based model

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