Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll- a  data

Mélin, Frédéric; Vantrepotte, Vincent; Chuprin, Andrei; Grant, Michael; Jackson, T. J.; Sathyendranath, Shubha

doi:10.1016/j.rse.2017.03.039

Cited by 82 publications

(79 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Ocean Color Climate Change Initiative (OC-CCI) dataset has been produced by the European Space Agency (ESA) to address this need [34]. The dataset merges retrievals from SeaWiFS; MODIS-Aqua; the MEdium Resolution Imaging Spectrometer (MERIS), which flew on Envisat-1; and the Visible Infrared Imaging Radiometer Suite (VIIRS), which flies on the Suomi National Polar-orbiting Partnership (NPP) satellite [35]. Critical steps for achieving data consistency include band-shifting and empirical bias correction [34][35][36].…”

Section: The Ocean Color Climate Change Initiative (Oc-cci) Datamentioning

confidence: 99%

“…The dataset merges retrievals from SeaWiFS; MODIS-Aqua; the MEdium Resolution Imaging Spectrometer (MERIS), which flew on Envisat-1; and the Visible Infrared Imaging Radiometer Suite (VIIRS), which flies on the Suomi National Polar-orbiting Partnership (NPP) satellite [35]. Critical steps for achieving data consistency include band-shifting and empirical bias correction [34][35][36]. The OC-CCI dataset has been used by other researchers in the Red Sea and shows good consistency with in situ observations along with substantially improved coverage, particularly for the southern region [26,30,31].…”

Section: The Ocean Color Climate Change Initiative (Oc-cci) Datamentioning

confidence: 99%

“…However, the scale difference did not affect the matching of blooms' occurrences in the same regions using both datasets. Note that, while the OC-CCI dataset includes MODIS-Aqua, due to differences from band shifting and empirical bias correction [34][35][36], the specific values of Chl-a in the left and right sets of panels are not directly comparable, but it is only the relative temporal and spatial changes that are important. Figure 2 also demonstrates the coverage differences between the blended OC-CCI dataset and the MODIS-Aqua dataset alone.…”

Section: Chl-a Climatology In the Read Sea And Anomaly Identificationmentioning

confidence: 99%

“…Figure 4c shows the mean Chl-a values for June 2015 from MODISTerra. Recall that MODIS-Terra is not included in the OC-CCI dataset [35], but the Chl-a values show good consistency with MODIS-Aqua Chl-a [25,26], although there might be some bias in the Red Sea [27]. The agreement between the OC-CCI monthly mean Chl-a values (Figure 4b) and the MODIS- [17,22,31], and the existence of large, persistent eddies was identified in hydrographic surveys of the region as far back as 1993 [55].…”

Section: Chl-a Climatology In the Read Sea And Anomaly Identificationmentioning

confidence: 99%

“…Figure 4c shows the mean Chl-a values for June 2015 from MODIS-Terra. Recall that MODIS-Terra is not included in the OC-CCI dataset [35], but the Chl-a values show good consistency with MODIS-Aqua Chl-a [25,26], although there might be some bias in the Red Sea [27]. The agreement between the OC-CCI monthly mean Chl-a values (Figure 4b) and the MODIS-Terra Chl-a values (Figure 4c) is acceptable, with the MODIS-Terra data showing regionally higher values of Chl-a and a greater frequency of missing data, indicated by the white regions [26,30,31].…”

Section: Chl-a Climatology In the Read Sea And Anomaly Identificationmentioning

confidence: 99%

See 4 more Smart Citations

Synergistic Use of Remote Sensing and Modeling to Assess an Anomalously High Chlorophyll-a Event during Summer 2015 in the South Central Red Sea

El-Askary

Manikandan

et al. 2017

Remote Sensing

View full text Add to dashboard Cite

An anomalously high chlorophyll-a (Chl-a) event (>2 mg/m 3 ) during June 2015 in the South Central Red Sea (17.5 • to 22 • N, 37 • to 42 • E) was observed using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellite platforms. This differs from the low Chl-a values (<0.5 mg/m 3 ) usually encountered over the same region during summertime. To assess this anomaly and possible causes, we used a wide range of oceanographical and meteorological datasets, including Chl-a concentrations, sea surface temperature (SST), sea surface height (SSH), mixed layer depth (MLD), ocean current velocity and aerosol optical depth (AOD) obtained from different sensors and models. Findings confirmed this anomalous behavior in the spatial domain using Hovmöller data analysis techniques, while a time series analysis addressed monthly and daily variability. Our analysis suggests that a combination of factors controlling nutrient supply contributed to the anomalous phytoplankton growth. These factors include horizontal transfer of upwelling water through eddy circulation and possible mineral fertilization from atmospheric dust deposition. Coral reefs might have provided extra nutrient supply, yet this is out of the scope of our analysis. We thought that dust deposition from a coastal dust jet event in late June, coinciding with the phytoplankton blooms in the area under investigation, might have also contributed as shown by our AOD findings. However, a lag cross correlation showed a two-month lag between strong dust outbreak and the high Chl-a anomaly. The high Chl-a concentration at the edge of the eddy emphasizes the importance of horizontal advection in fertilizing oligotrophic (nutrient poor) Red Sea waters.

show abstract

Section: The Ocean Color Climate Change Initiative (Oc-cci) Datamentioning

confidence: 99%

Section: The Ocean Color Climate Change Initiative (Oc-cci) Datamentioning

confidence: 99%

Section: Chl-a Climatology In the Read Sea And Anomaly Identificationmentioning

confidence: 99%

Section: Chl-a Climatology In the Read Sea And Anomaly Identificationmentioning

confidence: 99%

Section: Chl-a Climatology In the Read Sea And Anomaly Identificationmentioning

confidence: 99%

See 3 more Smart Citations

Synergistic Use of Remote Sensing and Modeling to Assess an Anomalously High Chlorophyll-a Event during Summer 2015 in the South Central Red Sea

El-Askary

Manikandan

et al. 2017

Remote Sensing

View full text Add to dashboard Cite

show abstract

Assimilation of Ocean‐Color Plankton Functional Types to Improve Marine Ecosystem Simulations

et al. 2018

View full text Add to dashboard Cite

We assimilated phytoplankton functional types (PFTs) derived from ocean color into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error‐characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton, and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical‐biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998–2003. The skill of the reference and reanalysis simulations in estimating ocean color and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean‐color PFTs (except nanoplankton), as well as the not‐assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not‐assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air‐sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf‐sea ecosystems.

show abstract

Massive circumpolar biomass of Southern Ocean zooplankton: Implications for food web structure, carbon export, and marine spatial planning

Yang

Atkinson

Pakhomov

et al. 2022

Limnology & Oceanography

View full text Add to dashboard Cite

With rapid, sector‐specific climatic changes impacting the Southern Ocean, we need circumpolar‐scale biomass data of its plankton taxa to improve food web models, blue carbon budgets and resource management. Here, we provide a new dataset on mesozooplankton biomass with 2909 records spanning the last 90 yr, and describe, in comparable carbon units, their circumpolar distribution alongside those of phytoplankton, Antarctic krill, and salps. With our datasets, we estimate total summer carbon biomasses for phytoplankton (36 MT), mesozooplankton (67 MT), krill (30 MT), and salps (1.7 MT). The mesozooplankton value is much higher than previously reported and, added to that of krill and salps, points to an enormous overall biomass of zooplankton in the Southern Ocean. This means that the pyramids of biomass are often inverted, with higher biomass of zooplankton than of phytoplankton. Such high biomasses suggest key roles of grazers in nutrient cycling and we estimate an export of ~ 50 Mt C yr−1, solely from mortality of overwintering zooplankton that typically reside at depth. Deep lipid respiration (the lipid pump), for example, would increase this export even further. While inverted biomass pyramids prevailed at mid latitudes (50°–70°S), the balance of taxa differed regionally: for example, with biomass dominance by phytoplankton (highest latitudes and Pacific sector), mesozooplankton (Kerguelen Plateau), krill (north and east Scotia Sea), and salps (Crozet area). In light of contrasting climate change impacts between these sectors, we provide data that will underpin biogeochemical and food web models, blue carbon budgets, and the planning of marine protected areas.

show abstract

Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll- a data

Cited by 82 publications

References 83 publications

Synergistic Use of Remote Sensing and Modeling to Assess an Anomalously High Chlorophyll-a Event during Summer 2015 in the South Central Red Sea

Synergistic Use of Remote Sensing and Modeling to Assess an Anomalously High Chlorophyll-a Event during Summer 2015 in the South Central Red Sea

Assimilation of Ocean‐Color Plankton Functional Types to Improve Marine Ecosystem Simulations

Massive circumpolar biomass of Southern Ocean zooplankton: Implications for food web structure, carbon export, and marine spatial planning

Contact Info

Product

Resources

About