Abstract

Many ocean color data applications leverage global spatially composited level-3 (L3) satellite data because of their regular Earth-grid frame of reference. However, ocean color satellite retrieval performance is routinely evaluated on level-2 (L2) data at the native satellite swath resolution and geometries. This study assesses how accurately binned and gridded L3 data represent L2 satellite data products via satellite-to-in situ match-up activities. L2 and L3 satellite data retrievals of the photosynthetic pigment chlorophyll-a are compared with a common in situ dataset, revealing similar L2 and L3 satellite-to-in situ performance for both MODIS-Aqua and VIIRS-SNPP. This agreement implies that L2 validation results are generally applicable to L3 data. However, uncertainties are introduced during the generation of L3 data from L2 data. L3 data comparisons introduce a wider temporal window between the time of in situ measurement and the time of the satellite observation, which can unintentionally reflect on the quality of the satellite retrieval or algorithm performance. The choice of L3 map projection may introduce additional uncertainty by spatially distorting the true location of the satellite retrievals. Each manipulation of satellite data beyond the instrument’s native spatiotemporal reference (L2) reduces the applicability of L2 validation results to higher data processing levels.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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    [Crossref]

2018 (1)

2017 (1)

S. Sathyendranath, R. J. W. Brewin, T. Jackson, F. Mélin, and T. Platt, “Ocean-colour products for climate-change studies: What are their ideal characteristics?” Remote Sens. Environ. 203, 125–138 (2017).
[Crossref]

2012 (1)

C. Hu, Z. Lee, and B. Franz, “Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference,” J. Geophys. Res. 117(C1), C01011 (2012).

2009 (2)

C. R. McClain, “A Decade of Satellite Ocean Color Observations,” Annu. Rev. Mar. Sci. 1(1), 19–42 (2009).
[Crossref]

G. Zibordi, J. F. Berthon, F. Mélin, D. D’Alimonte, and S. Kaitala, “Validation of satellite ocean color primary products at optically complex coastal sites: Northern Adriatic Sea, Northern Baltic Proper and Gulf of Finland,” Remote Sens. Environ. 113(12), 2574–2591 (2009).
[Crossref]

2007 (2)

W. W. Gregg and N. W. Casey, “Modeling coccolithophores in the global oceans,” Deep Sea Res., Part II 54(5–7), 447–477 (2007).
[Crossref]

D. M. Goldberg and J. R. Gott, “Flexion and Skewness in Map Projections of the Earth,” Cartogr. Int. J. Geogr. Inf. Geovisualization 42(4), 297–318 (2007).
[Crossref]

2006 (1)

S. W. Bailey and P. J. Werdell, “A multi-sensor approach for the on-orbit validation of ocean color satellite data products,” Remote Sens. Environ. 102(1–2), 12–23 (2006).
[Crossref]

2005 (1)

B. A. Walther and J. L. Moore, “The definitions of bias, precision, and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance,” Ecography 28(6), 815–829 (2005).
[Crossref]

2004 (1)

W. W. Gregg and N. W. Casey, “Global and regional evaluation of the SeaWiFS chlorophyll data set,” Remote Sens. Environ. 93(4), 463–479 (2004).
[Crossref]

2001 (1)

K. A. Mulcahy and K. C. Clarke, “Symbolization of Map Projection Distortion: A Review,” Cartogr. Geogr. Inf. Sci. 28(3), 167–182 (2001).
[Crossref]

1998 (1)

S. C. Doney, D. M. Glover, S. J. McCue, and M. Fuentes, “Mesoscale variability of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite ocean color: Global patterns and spatial scales,” J. Geophys. Res. Ocean. 108, 1–15 (1998).

1995 (2)

P. G. Falkowski and Z. Kolber, “Variations in chlorophyll fluorescence yields in phytoplankton in the world oceans,” Austrian J. Plant Phys. 22, 341–355 (1995).

J. W. Campbell, “The lognormal distribution as a model for bio-optical variability in the sea,” J. Geophys. Res. 100(C7), 13237–13254 (1995).
[Crossref]

1984 (1)

W. B. Rossow and L. Garder, “Selection of a Map Grid for Data Analysis and Archival,” J. Clim. Appl. Meteorol. 23(8), 1253–1257 (1984).
[Crossref]

1973 (1)

D. A. Kiefer, “Fluorescence properties of natural phytoplankton populations,” Mar. Biol. 22(3), 263–269 (1973).
[Crossref]

Ahmad, Z.

C. D. Mobley, J. Werdell, B. Franz, Z. Ahmad, and S. Bailey, “Atmospheric Correction for Satellite Ocean Color Radiometry,” NASA Tech. Memo.73 (2016).

Bailey, S.

C. D. Mobley, J. Werdell, B. Franz, Z. Ahmad, and S. Bailey, “Atmospheric Correction for Satellite Ocean Color Radiometry,” NASA Tech. Memo.73 (2016).

Bailey, S. W.

S. W. Bailey and P. J. Werdell, “A multi-sensor approach for the on-orbit validation of ocean color satellite data products,” Remote Sens. Environ. 102(1–2), 12–23 (2006).
[Crossref]

P. J. Werdell and S. W. Bailey, “The SeaWiFS Bio-Optical Archive and Storage (SeaBASS): Current Architecture and Implementation,” NASA Tech. Memo.1–50 (2002).

Balch, William

William Balch, “AMT,” NASA SeaWiFS Bio-optical Archive and Storage System (SeaBASS), (2014) [retrieved 06 Sep 2018] http://dx.doi.org/10.5067/SeaBASS/AMT/DATA001 .

Behrenfeld, M. J.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Berthon, J. F.

G. Zibordi, J. F. Berthon, F. Mélin, D. D’Alimonte, and S. Kaitala, “Validation of satellite ocean color primary products at optically complex coastal sites: Northern Adriatic Sea, Northern Baltic Proper and Gulf of Finland,” Remote Sens. Environ. 113(12), 2574–2591 (2009).
[Crossref]

Blaisdell, J. M.

J. W. Campbell, J. M. Blaisdell, and M. Darzi, “Volume 32, Level-3 SeaWiFS Data Products : Spatial and Temporal Binning Algorithms,” SeaWiFS Technical Report Series (NASA, 1995).

Bontempi, P. S.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Boss, E.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Brewin, R. J. W.

S. Sathyendranath, R. J. W. Brewin, T. Jackson, F. Mélin, and T. Platt, “Ocean-colour products for climate-change studies: What are their ideal characteristics?” Remote Sens. Environ. 203, 125–138 (2017).
[Crossref]

Cairns, B.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Campbell, J. W.

J. W. Campbell, “The lognormal distribution as a model for bio-optical variability in the sea,” J. Geophys. Res. 100(C7), 13237–13254 (1995).
[Crossref]

J. W. Campbell, J. M. Blaisdell, and M. Darzi, “Volume 32, Level-3 SeaWiFS Data Products : Spatial and Temporal Binning Algorithms,” SeaWiFS Technical Report Series (NASA, 1995).

Casey, N. W.

W. W. Gregg and N. W. Casey, “Modeling coccolithophores in the global oceans,” Deep Sea Res., Part II 54(5–7), 447–477 (2007).
[Crossref]

W. W. Gregg and N. W. Casey, “Global and regional evaluation of the SeaWiFS chlorophyll data set,” Remote Sens. Environ. 93(4), 463–479 (2004).
[Crossref]

Clarke, K. C.

K. A. Mulcahy and K. C. Clarke, “Symbolization of Map Projection Distortion: A Review,” Cartogr. Geogr. Inf. Sci. 28(3), 167–182 (2001).
[Crossref]

Compère, C.

M. Lehaitre and C. Compère, “Biofouling and Underwater Measurements,” in Real-Time Coastal Observing Systems for Marine Ecosystem Dynamics and Harmful Algal Blooms: Theory, instrumentation and modelling (UNESCO, 2008), pp. 463–493.

D’Alimonte, D.

G. Zibordi, J. F. Berthon, F. Mélin, D. D’Alimonte, and S. Kaitala, “Validation of satellite ocean color primary products at optically complex coastal sites: Northern Adriatic Sea, Northern Baltic Proper and Gulf of Finland,” Remote Sens. Environ. 113(12), 2574–2591 (2009).
[Crossref]

Darzi, M.

J. W. Campbell, J. M. Blaisdell, and M. Darzi, “Volume 32, Level-3 SeaWiFS Data Products : Spatial and Temporal Binning Algorithms,” SeaWiFS Technical Report Series (NASA, 1995).

Davis, G. T.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Doney, S. C.

S. C. Doney, D. M. Glover, S. J. McCue, and M. Fuentes, “Mesoscale variability of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite ocean color: Global patterns and spatial scales,” J. Geophys. Res. Ocean. 108, 1–15 (1998).

Falkowski, P. G.

P. G. Falkowski and Z. Kolber, “Variations in chlorophyll fluorescence yields in phytoplankton in the world oceans,” Austrian J. Plant Phys. 22, 341–355 (1995).

Franz, B.

C. Hu, Z. Lee, and B. Franz, “Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference,” J. Geophys. Res. 117(C1), C01011 (2012).

C. D. Mobley, J. Werdell, B. Franz, Z. Ahmad, and S. Bailey, “Atmospheric Correction for Satellite Ocean Color Radiometry,” NASA Tech. Memo.73 (2016).

Franz, B. A.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Fuentes, M.

S. C. Doney, D. M. Glover, S. J. McCue, and M. Fuentes, “Mesoscale variability of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite ocean color: Global patterns and spatial scales,” J. Geophys. Res. Ocean. 108, 1–15 (1998).

Garder, L.

W. B. Rossow and L. Garder, “Selection of a Map Grid for Data Analysis and Archival,” J. Clim. Appl. Meteorol. 23(8), 1253–1257 (1984).
[Crossref]

Gliese, U. B.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Glover, D. M.

S. C. Doney, D. M. Glover, S. J. McCue, and M. Fuentes, “Mesoscale variability of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite ocean color: Global patterns and spatial scales,” J. Geophys. Res. Ocean. 108, 1–15 (1998).

Goldberg, D. M.

D. M. Goldberg and J. R. Gott, “Flexion and Skewness in Map Projections of the Earth,” Cartogr. Int. J. Geogr. Inf. Geovisualization 42(4), 297–318 (2007).
[Crossref]

Gorman, E. T.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Gott, J. R.

D. M. Goldberg and J. R. Gott, “Flexion and Skewness in Map Projections of the Earth,” Cartogr. Int. J. Geogr. Inf. Geovisualization 42(4), 297–318 (2007).
[Crossref]

Gregg, W. W.

W. W. Gregg and N. W. Casey, “Modeling coccolithophores in the global oceans,” Deep Sea Res., Part II 54(5–7), 447–477 (2007).
[Crossref]

W. W. Gregg and N. W. Casey, “Global and regional evaluation of the SeaWiFS chlorophyll data set,” Remote Sens. Environ. 93(4), 463–479 (2004).
[Crossref]

Hasekamp, O.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Hu, C.

C. Hu, Z. Lee, and B. Franz, “Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference,” J. Geophys. Res. 117(C1), C01011 (2012).

Jackson, T.

S. Sathyendranath, R. J. W. Brewin, T. Jackson, F. Mélin, and T. Platt, “Ocean-colour products for climate-change studies: What are their ideal characteristics?” Remote Sens. Environ. 203, 125–138 (2017).
[Crossref]

Kaitala, S.

G. Zibordi, J. F. Berthon, F. Mélin, D. D’Alimonte, and S. Kaitala, “Validation of satellite ocean color primary products at optically complex coastal sites: Northern Adriatic Sea, Northern Baltic Proper and Gulf of Finland,” Remote Sens. Environ. 113(12), 2574–2591 (2009).
[Crossref]

Kiefer, D. A.

D. A. Kiefer, “Fluorescence properties of natural phytoplankton populations,” Mar. Biol. 22(3), 263–269 (1973).
[Crossref]

Knobelspiesse, K. D.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Kolber, Z.

P. G. Falkowski and Z. Kolber, “Variations in chlorophyll fluorescence yields in phytoplankton in the world oceans,” Austrian J. Plant Phys. 22, 341–355 (1995).

Lee, Z.

C. Hu, Z. Lee, and B. Franz, “Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference,” J. Geophys. Res. 117(C1), C01011 (2012).

Lehaitre, M.

M. Lehaitre and C. Compère, “Biofouling and Underwater Measurements,” in Real-Time Coastal Observing Systems for Marine Ecosystem Dynamics and Harmful Algal Blooms: Theory, instrumentation and modelling (UNESCO, 2008), pp. 463–493.

Loftin, K. A.

Mannino, A.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

Martins, J. V.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

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P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

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S. Sathyendranath, R. J. W. Brewin, T. Jackson, F. Mélin, and T. Platt, “Ocean-colour products for climate-change studies: What are their ideal characteristics?” Remote Sens. Environ. 203, 125–138 (2017).
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K. A. Mulcahy and K. C. Clarke, “Symbolization of Map Projection Distortion: A Review,” Cartogr. Geogr. Inf. Sci. 28(3), 167–182 (2001).
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Platt, T.

S. Sathyendranath, R. J. W. Brewin, T. Jackson, F. Mélin, and T. Platt, “Ocean-colour products for climate-change studies: What are their ideal characteristics?” Remote Sens. Environ. 203, 125–138 (2017).
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P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

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W. B. Rossow and L. Garder, “Selection of a Map Grid for Data Analysis and Archival,” J. Clim. Appl. Meteorol. 23(8), 1253–1257 (1984).
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S. Sathyendranath, R. J. W. Brewin, T. Jackson, F. Mélin, and T. Platt, “Ocean-colour products for climate-change studies: What are their ideal characteristics?” Remote Sens. Environ. 203, 125–138 (2017).
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B. A. Walther and J. L. Moore, “The definitions of bias, precision, and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance,” Ecography 28(6), 815–829 (2005).
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C. D. Mobley, J. Werdell, B. Franz, Z. Ahmad, and S. Bailey, “Atmospheric Correction for Satellite Ocean Color Radiometry,” NASA Tech. Memo.73 (2016).

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G. Zibordi, J. F. Berthon, F. Mélin, D. D’Alimonte, and S. Kaitala, “Validation of satellite ocean color primary products at optically complex coastal sites: Northern Adriatic Sea, Northern Baltic Proper and Gulf of Finland,” Remote Sens. Environ. 113(12), 2574–2591 (2009).
[Crossref]

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C. R. McClain, “A Decade of Satellite Ocean Color Observations,” Annu. Rev. Mar. Sci. 1(1), 19–42 (2009).
[Crossref]

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[Crossref]

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D. M. Goldberg and J. R. Gott, “Flexion and Skewness in Map Projections of the Earth,” Cartogr. Int. J. Geogr. Inf. Geovisualization 42(4), 297–318 (2007).
[Crossref]

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[Crossref]

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B. A. Walther and J. L. Moore, “The definitions of bias, precision, and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance,” Ecography 28(6), 815–829 (2005).
[Crossref]

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W. B. Rossow and L. Garder, “Selection of a Map Grid for Data Analysis and Archival,” J. Clim. Appl. Meteorol. 23(8), 1253–1257 (1984).
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M. Lehaitre and C. Compère, “Biofouling and Underwater Measurements,” in Real-Time Coastal Observing Systems for Marine Ecosystem Dynamics and Harmful Algal Blooms: Theory, instrumentation and modelling (UNESCO, 2008), pp. 463–493.

P. J. Werdell, M. J. Behrenfeld, P. S. Bontempi, E. Boss, B. Cairns, G. T. Davis, B. A. Franz, U. B. Gliese, E. T. Gorman, O. Hasekamp, K. D. Knobelspiesse, A. Mannino, J. V. Martins, C. R. McClain, G. Meister, and L. A. Remer, “The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission: Status, science, advances,” Bull. Am. Meteorol. Soc. http://dx.doi/org/10.1175/BAMS-D-18-0056.1 (2019).

C. D. Mobley, J. Werdell, B. Franz, Z. Ahmad, and S. Bailey, “Atmospheric Correction for Satellite Ocean Color Radiometry,” NASA Tech. Memo.73 (2016).

IOCCG, “Why Ocean Colour? The Societal Benefits of Ocean-Colour Technology,” T. Platt, N. Hoepffner, V. Stuart and C. Brown, eds., Reports of the International Ocean-Colour Coordinating Group, No. 7, IOCCG, Dartmouth, Canada (2008).

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NASA Goddard Space Flight Center Ocean Biology Processing Group, “Moderate Resolution Imaging Spectroradiometer onboard the Aqua Earth-observing satellite (MODIS-Aqua) Ocean Color Data,” NASA OB.DAAC (2018) [retrieved 07 Sep 2018] http://doi.org/10.5067/AQUA/MODIS/L3B/CHL/2018 .

NASA Goddard Space Flight Center Ocean Biology Processing Group, “Moderate Resolution Imaging Spectroradiometer onboard the Aqua Earth-observing satellite (MODIS-Aqua) Ocean Color Data,” NASA OB.DAAC (2018) [retrieved 07 Sep 2018] http://doi.org/10.5067/AQUA/MODIS/L3M/CHL/2018 .

NASA Goddard Space Flight Center Ocean Biology Processing Group, “Visible Infrared Radiometer Suite onboard the Suomi National Polar-orbiting Partnership weather satellite (VIIRS-SNPP) Ocean Color Data,” NASA OB.DAAC (2018) [retrieved 07 Sep 2018] http://doi.org/10.5067/NPP/VIIRS/L2/OC/2018 .

NASA Goddard Space Flight Center Ocean Biology Processing Group, “Visible Infrared Radiometer Suite onboard the Suomi National Polar-orbiting Partnership weather satellite (VIIRS-SNPP) Ocean Color Data,” NASA OB.DAAC (2018) [retrieved on 07 Sep 2018] http://doi.org/10.5067/NPP/VIIRS/L3B/CHL/2018 .

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Figures (10)

Fig. 1.
Fig. 1. A sinusoidal map-projection is shown in the upper panel, and a Plate Carrée equidistant cylindrical map projection is shown in lower panel. Note that both earth-grids are centered on the prime meridian (0-degrees longitude) and have parallels and meridians spaced 10-degrees apart at the equator. While these grids are much coarser than the 4.62-km spacing used in the L3b and L3 m data under consideration by this study, the difference in spacing between the meridians at middle and high latitudes illustrate the spatial distortion that occurs for the grid cells in the Plate Carrée projection at high latitudes compared to the sinusoidal grid cells.
Fig. 2.
Fig. 2. Locations of AMT24 in situ chlorophyll fluorescence sampling. The background shows October 2014 monthly L3 m MODIS-Aqua Chl.
Fig. 3.
Fig. 3. Comparisons of MODIS and in situ Chl. The upper right, upper left, and lower left panels show satellite-to-in situ scatterplots and comparison metrics for L2, L3b, and L3 m data, respectively. The solid black lines indicate a 1:1 relationship. Colors report the numerical density of match-ups in a region of the scatter plot. The lower left panel shows normalized, binned population distributions for the entire in situ Chl dataset (green X’s) and the matched-up MODIS L2 (black diamonds), L3b (red circles), and L3 m (blue squares) Chl retrievals.
Fig. 4.
Fig. 4. As in Fig. 3, but for VIIRS.
Fig. 5.
Fig. 5. Subsets of the MODIS and in situ Chl comparisons. The upper left panel shows only those L2 match-ups where the in situ targets also generate L3b match-ups. The upper right panel shows only those L3b match-ups where the in situ targets also generate L2 match-ups. The lower right panel shows only those L3b match-ups where the in situ targets did not generate an L2 match-up. The solid black lines indicate a 1:1 relationship. Colors report the numerical density of match-ups in a region of the scatter plot. The lower left panel shows a histogram of L2 matchup exclusion criteria that led to the in situ targets shown in the lower right panel failing to generate a L2 match-up.
Fig. 6.
Fig. 6. Subsets of the MODIS and in situ Chl comparisons. The upper left panel shows only the L3 m match-ups where the in situ targets did not generate L3b match-ups. The upper right panel shows only the L3b match-ups where the in situ targets also generate L3 m match-ups. The lower right panel shows only the L3 m match-ups where the in situ targets also generate L3b match-ups. The solid black lines indicate a 1:1 relationship. Colors report the numerical density of match-ups in a region of the scatter plot.
Fig. 7.
Fig. 7. Geographic distributions of MODIS and VIIRS satellite-to-in situ match-ups. The upper two panels show a comparison of the spatial location (left panel) and latitudinal frequency distribution (right panel) of MODIS L2 and L3b match-ups. The lower panels show the same for VIIRS. Binned in situ Chl data are shown on the secondary X-axis as green x’s of the right panels.
Fig. 8.
Fig. 8. Geographic coverage of successive L2 swaths for MODIS (left) and VIIRS (right).
Fig. 9.
Fig. 9. Maximum great-circle distances between corresponding L3b and L3 m grid cell corners, inclusive of the upper-left corners (upper left panel), upper-right corners (upper right panel), lower-left corners (lower left panel), and lower-right corners (lower right panel), stratified into 1° latitude bins on the y-axis.
Fig. 10.
Fig. 10. As in Fig. 7, but for L3b and L3 m data.

Tables (2)

Tables Icon

Table 1. Summary of l2flags applied when generating comparison match-ups with the L2 data and when generating L3b and L3m data products.

Tables Icon

Table 2. Summary of validation comparison metrics.

Equations (3)

Equations on this page are rendered with MathJax. Learn more.

mean bias = 10 ( i = 1 n lo g 10 ( R i ) lo g 10 ( O i ) n ) and
MAE = 10 ( i = 1 n | lo g 10 ( R i ) lo g 10 ( O i ) | n ) ,
UPD = 200 % ( v a l u e 2 v a l u e 1 v a l u e 2 + v a l u e 1 ) ,

Metrics