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equatorial Pacific Ocean to the 1997–1998 El Nino. Science 286:2126–2131
Chomko RM, Gordon HR (2001) Atmospheric correction of ocean color imagery: test of the
spectral optimization algorithm with the sea-viewing wide field-of-view sensor. Appl Opt
40:2973–2984
Chomko RM, Gordon HR, Maritorena S, Siegel DA (2003) Simultaneous retrieval of oceanic and
atmospheric parameters for ocean color imagery by spectral optimization: a validation.
Remote Sens Environ 84:208–220
Cipollini P, Cromwell D, Challenor PG, Raffaglio S (2001) Rossby waves detected in global
ocean colour data. Geophys Res Lett 28:323–326
Clarke GK, Ewing GC, Lorenzen CJ (1970) Spectra of backscattered light from the sea obtained
from aircraft as a measure of chlorophyll concentration. Science 167:1119–1121
Clark DK, Gordon HR, Voss KJ, Ge Y, Broenkow W et al (1997) Validation of atmospheric
correction over the ocean. J Geophys Res 102:17209–17217
Craig S, Jones CT, Li WKW, Lazin G, Horne E, Caverhill C, Cullen JJ (2012) Deriving optical
metrics of coastal phytoplankton biomass from ocean colour. Remote Sens Envion 119:72–83
Dall’Olmo G, Gitelson AA, Rundquist DC, Leavitt B, Barrow T, Holz JC (2005) Assessing the
potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid
productive waters using red and near-infrared bands. Remote Sens Environ 96(2):176–187
Dandonneau Y, Vega A, Loisel H, du Penhoat Y, Menkes C (2003) Oceanic Rossby waves acting
as a ‘‘hayrake’’ for ecosystem floating by-products. Science 302:1548–1551
Dandonneau Y, Menkes C, Gorgues T, Madec G (2004) Reponse to comment on ‘‘Oceanic
Rossby waves acting as a ‘hay rake’ for ecosystem floating by-products’’. Science 304:390c
Darecki M, Stramski D (2004) An evaluation of MODIS and SeaWiFS bio-optical algorithms in
the Baltic Sea. Remote Sens Environ 89:326–350
Dierssen HM (2010) Perspectives on empirical approaches for ocean color remote sensing of
chlorophyll in a changing climate. Proc Nat Acad Sci 107:17073–17078
Doney SC, Glover DM, McCue SJ, Fuentes M (2003). Mesoscale variability of sea-viewing wide
field-of-view sensor (SeaWiFS) satellite ocean color: Global patterns and spatial scales.
J Geophys Res 108(C2):3024. doi:10.1029/2001JC000843
D’Ortenzio F, Marullo S, Ragni M, d’Alcala MR, Santoleri R (2002) Validation of empirical
SeaWiFS algorithms for chlorophyll-a retrieval in the Mediterranean Sea: a case study of
oligotrophic seas. Remote Sens Environ 82:79–84
D’Sa EJ, Miller RL (2003) Bio-optical properties in waters influenced by the Mississippi River
during low flow conditions. Remote Sens Environ 84:538–549
Dzwonkowski B, Yan X (2005) Development and application of a neural network based ocean
colour algorithm in coastal waters. Int J Remote Sens 26:1175–1200
Fargion GS, Franz BA, Kwiatkowska EJ, Pietras CM, Bailey SW, Gales J, et al (2004) SIMBIOS
program in support of ocean color missions: 1997–2003. In: Frouin RJ, Gilbert GD, Pan D
(eds) Ocean remote sensing and imaging: II. Proceedings SPIE, vol 5155.The Society of
Photo-Optical Instrumentation Engineers, pp 49–60
Fishman J, Al-Saadi J, Bontempi P et al (2012). Fulfilling the Mandate and Meeting the
Challenges of the Nation’s Next Generation of Atmospheric Composition and Coastal
Ecosystem Measurements: NASA’s Geostationary Coastal and Air Pollution Events (GEOCAPE) Mission. Bull Am Meteorol Soc 93:1457–1566
Franz BA, Bailey SW, Werdell PJ, McClain CR (2007) Sensor-independent approach to the
vicarious calibration of satellite ocean color radiometry. Appl Opt 46:5068–5082
Frouin R, Schwindling M, Deschamps P.-Y (1996). Spectral reflectance of sea foam in the visible
and near-infrared: In situ measurements and remote sensing implications. J Geophys Res
101:14361–14371
196
C. Hu and J. Campbell
cells uplifting hypothesis in the South Atlantic Subtropical Convergence Zone. Geophys Res
Lett 30(3):1125. doi:10.1029/2002GL016390
Chavez FP, Strutton PG, Friederich CE et al (1999) Biological and chemical response of the
equatorial Pacific Ocean to the 1997–1998 El Nino. Science 286:2126–2131
Chomko RM, Gordon HR (2001) Atmospheric correction of ocean color imagery: test of the
spectral optimization algorithm with the sea-viewing wide field-of-view sensor. Appl Opt
40:2973–2984
Chomko RM, Gordon HR, Maritorena S, Siegel DA (2003) Simultaneous retrieval of oceanic and
atmospheric parameters for ocean color imagery by spectral optimization: a validation.
Remote Sens Environ 84:208–220
Cipollini P, Cromwell D, Challenor PG, Raffaglio S (2001) Rossby waves detected in global
ocean colour data. Geophys Res Lett 28:323–326
Clarke GK, Ewing GC, Lorenzen CJ (1970) Spectra of backscattered light from the sea obtained
from aircraft as a measure of chlorophyll concentration. Science 167:1119–1121
Clark DK, Gordon HR, Voss KJ, Ge Y, Broenkow W et al (1997) Validation of atmospheric
correction over the ocean. J Geophys Res 102:17209–17217
Craig S, Jones CT, Li WKW, Lazin G, Horne E, Caverhill C, Cullen JJ (2012) Deriving optical
metrics of coastal phytoplankton biomass from ocean colour. Remote Sens Envion 119:72–83
Dall’Olmo G, Gitelson AA, Rundquist DC, Leavitt B, Barrow T, Holz JC (2005) Assessing the
potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid
productive waters using red and near-infrared bands. Remote Sens Environ 96(2):176–187
Dandonneau Y, Vega A, Loisel H, du Penhoat Y, Menkes C (2003) Oceanic Rossby waves acting
as a ‘‘hayrake’’ for ecosystem floating by-products. Science 302:1548–1551
Dandonneau Y, Menkes C, Gorgues T, Madec G (2004) Reponse to comment on ‘‘Oceanic
Rossby waves acting as a ‘hay rake’ for ecosystem floating by-products’’. Science 304:390c
Darecki M, Stramski D (2004) An evaluation of MODIS and SeaWiFS bio-optical algorithms in
the Baltic Sea. Remote Sens Environ 89:326–350
Dierssen HM (2010) Perspectives on empirical approaches for ocean color remote sensing of
chlorophyll in a changing climate. Proc Nat Acad Sci 107:17073–17078
Doney SC, Glover DM, McCue SJ, Fuentes M (2003). Mesoscale variability of sea-viewing wide
field-of-view sensor (SeaWiFS) satellite ocean color: Global patterns and spatial scales.
J Geophys Res 108(C2):3024. doi:10.1029/2001JC000843
D’Ortenzio F, Marullo S, Ragni M, d’Alcala MR, Santoleri R (2002) Validation of empirical
SeaWiFS algorithms for chlorophyll-a retrieval in the Mediterranean Sea: a case study of
oligotrophic seas. Remote Sens Environ 82:79–84
D’Sa EJ, Miller RL (2003) Bio-optical properties in waters influenced by the Mississippi River
during low flow conditions. Remote Sens Environ 84:538–549
Dzwonkowski B, Yan X (2005) Development and application of a neural network based ocean
colour algorithm in coastal waters. Int J Remote Sens 26:1175–1200
Fargion GS, Franz BA, Kwiatkowska EJ, Pietras CM, Bailey SW, Gales J, et al (2004) SIMBIOS
program in support of ocean color missions: 1997–2003. In: Frouin RJ, Gilbert GD, Pan D
(eds) Ocean remote sensing and imaging: II. Proceedings SPIE, vol 5155.The Society of
Photo-Optical Instrumentation Engineers, pp 49–60
Fishman J, Al-Saadi J, Bontempi P et al (2012). Fulfilling the Mandate and Meeting the
Challenges of the Nation’s Next Generation of Atmospheric Composition and Coastal
Ecosystem Measurements: NASA’s Geostationary Coastal and Air Pollution Events (GEOCAPE) Mission. Bull Am Meteorol Soc 93:1457–1566
Franz BA, Bailey SW, Werdell PJ, McClain CR (2007) Sensor-independent approach to the
vicarious calibration of satellite ocean color radiometry. Appl Opt 46:5068–5082
Frouin R, Schwindling M, Deschamps P.-Y (1996). Spectral reflectance of sea foam in the visible
and near-infrared: In situ measurements and remote sensing implications. J Geophys Res
101:14361–14371
196
C. Hu and J. Campbell