Multi-satellite time series of inherent optical properties in the California Current

[1]  S. Maritorena,et al.  Atmospheric correction of satellite ocean color imagery: the black pixel assumption. , 2000, Applied optics.

[2]  S. Maritorena,et al.  Merged satellite ocean color data products using a bio-optical model: Characteristics, benefits and issues , 2010 .

[3]  M. Ohman,et al.  A double-integration hypothesis to explain ocean ecosystem response to climate forcing , 2013, Proceedings of the National Academy of Sciences.

[4]  E. Boss,et al.  Relationship of light scattering at an angle in the backward direction to the backscattering coefficient. , 2001, Applied optics.

[5]  B. Franz,et al.  Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach , 2007 .

[6]  M. Kahru,et al.  Influence of the 1997–98 El Niño on the surface chlorophyll in the California Current , 2000 .

[7]  R. Kudela,et al.  Trends in primary production in the California Current detected with satellite data , 2009 .

[8]  Lisa R. Moore,et al.  Determination of spectral absorption coefficients of particles, dissolved material and phytoplankton for discrete water samples , 2000 .

[9]  Nedjeljko Frančula.  The National Academies Press , 2013 .

[10]  John P. Dunne,et al.  Enhanced nutrient supply to the California Current Ecosystem with global warming and increased stratification in an earth system model , 2010 .

[11]  Mati Kahru,et al.  Ocean Color Reveals Increased Blooms in Various Parts of the World , 2008 .

[12]  B. G. Mitchell,et al.  Algorithms for determining the absorption coefficient for aquatic particulates using the quantitative filter technique , 1990, Defense, Security, and Sensing.

[13]  D. Siegel,et al.  Seasonal dynamics of colored dissolved material in the Sargasso Sea , 1998 .

[14]  B. Franz,et al.  Sensor-independent approach to the vicarious calibration of satellite ocean color radiometry. , 2007, Applied optics.

[15]  P. J. Werdell,et al.  A multi-sensor approach for the on-orbit validation of ocean color satellite data products , 2006 .

[16]  M. Conkright,et al.  Global seasonal climatologies of ocean chlorophyll: Blending in situ and satellite data for the Coastal Zone Color Scanner era , 2001 .

[17]  F. D’Ortenzio,et al.  Climate-Driven Basin-Scale Decadal Oscillations of Oceanic Phytoplankton , 2009, Science.

[18]  M. Kahru,et al.  Ocean Color Chlorophyll Algorithms for SEAWIFS , 1998 .

[19]  Raphael M. Kudela,et al.  Development of synthetic salinity from remote sensing for the Columbia River plume , 2009 .

[20]  Stéphane Maritorena,et al.  Optimization of a semianalytical ocean color model for global-scale applications. , 2002, Applied optics.

[21]  B. Mitchell,et al.  Empirical ocean color algorithms for estimating particulate organic carbon in the Southern Ocean , 2010 .

[22]  R. Kudela,et al.  Optical characterization of water masses within the Columbia River plume , 2012 .

[23]  Raphael M. Kudela,et al.  Estimating labile particulate iron concentrations in coastal waters from remote sensing data , 2012 .

[24]  Rachel M. Jeffreys,et al.  Deep-Sea Research II , 2008 .

[25]  Menghua Wang,et al.  Seawifs Postlaunch Calibration and Validation Analyses , 2013 .

[26]  Edward J. Kearns,et al.  Production regimes in four Eastern Boundary Current systems , 2003 .

[27]  Temilola Fatoyinbo,et al.  Remote Sensing Of Biomass: Principles And Applications , 2014 .

[28]  Andrew C. Thomas,et al.  Interannual variability in chlorophyll concentrations in the Humboldt and California Current Systems , 2009 .

[29]  Lian Feng,et al.  Uncertainties of SeaWiFS and MODIS remote sensing reflectance: Implications from clear water measurements , 2013 .

[30]  C. McClain.  A decade of satellite ocean color observations. , 2009, Annual review of marine science.

[31]  B. Worm,et al.  Global phytoplankton decline over the past century , 2010, Nature.

[32]  James J. Simpson,et al.  The California Current system: The seasonal variability of its physical characteristics , 1987 .

[33]  P. Falkowski,et al.  Photosynthetic rates derived from satellite‐based chlorophyll concentration , 1997 .

[34]  Are trends in SeaWiFS chlorophyll time-series unusual relative to historic variability , 2010 .

[35]  A. Barnard,et al.  Under the hood of satellite empirical chlorophyll a algorithms: revealing the dependencies of maximum band ratio algorithms on inherent optical properties. , 2012, Optics express.

[36]  W. Esaias,et al.  An empirical approach to ocean color data: Reducing bias and the need for post-launch radiometric re-calibration , 2009 .

[37]  S. Maritorena,et al.  Consistent merging of satellite ocean color data sets using a bio-optical model , 2005 .

[38]  Dennis A. Hansell,et al.  Global distribution and dynamics of colored dissolved and detrital organic materials , 2002 .

[39]  Mark D. Ohman,et al.  Multi‐decadal shoaling of the euphotic zone in the southern sector of the California Current System , 2009 .

[40]  M. Kahru,et al.  Seasonal and nonseasonal variability of satellite‐derived chlorophyll and colored dissolved organic matter concentration in the California Current , 2001 .

[41]  M. Conkright,et al.  Global Seasonal Climatologies of Ocean Chlorophyll: Blending In situ and Satellite Data for the CZCS Era , 1999 .

[42]  Frédéric Mélin,et al.  Comparison of global ocean colour data records , 2010 .

[43]  R. Maffione,et al.  Instruments and methods for measuring the backward-scattering coefficient of ocean waters. , 1997, Applied optics.

[44]  Sheldon Drobot,et al.  Climate Data Records from environmental satellites , 2004 .

[45]  M. Kahru,et al.  Empirical chlorophyll algorithm and preliminary SeaWiFS validation for the California Current , 1999 .

[46]  R. Murtugudde,et al.  Global correlations between winds and ocean chlorophyll , 2010 .

[47]  A. Morel.  Optical properties of pure water and pure sea water , 1974 .

[48]  R. Kudela,et al.  Trends in the surface chlorophyll of the California Current: Merging data from multiple ocean color satellites , 2012 .

[49]  M. Perry,et al.  Estimating primary production at depth from remote sensing. , 1996, Applied optics.

[50]  P. J. Werdell,et al.  An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation , 2005 .

[51]  Scott A. Freeman,et al.  An assessment of optical properties and primary production derived from remote sensing in the Southern Ocean (SO GasEx) , 2011 .

[52]  N. Nelson,et al.  Seasonal dynamics of colored dissolved organic matter in the Sargasso Sea , 1998 .

[53]  J. Largier,et al.  Observations of increased wind‐driven coastal upwelling off central California , 2010 .

[54]  F. D’Ortenzio,et al.  Assessment of uncertainty in the ocean reflectance determined by three satellite ocean color sensors (MERIS, SeaWiFS and MODIS-A) at an offshore site in the Mediterranean Sea (BOUSSOLE project) , 2008 .

[55]  W. Gregg,et al.  Improving the consistency of ocean color data: A step toward climate data records , 2010 .

[56]  R. Arnone,et al.  Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters. , 2002, Applied optics.

[57]  M. Kahru,et al.  Influence of the El Niño - La Niña cycle on satellite-derived primary production in the California Current , 2002 .

[58]  M. Ohman,et al.  CalCOFI in a Changing Ocean , 2003 .

[59]  Melanie Abecassis,et al.  Ocean's least productive waters are expanding , 2008 .

[60]  E. Fry,et al.  Absorption spectrum (380-700 nm) of pure water. II. Integrating cavity measurements. , 1997, Applied optics.

[61]  F. James Rohlf,et al.  Biometry: The Principles and Practice of Statistics in Biological Research , 1969 .

[62]  Andrew C. Thomas,et al.  Phytoplankton Scales of Variability in the California Current System: 2. Latitudinal Variability , 2007 .

[63]  David A. Siegel,et al.  Assessing requirements for sustained ocean color research and operations , 2011 .

[64]  Robert L. Smith,et al.  Two coastal upwelling domains in the northern California Current system , 2005 .

[65]  M. Kahru,et al.  Influence of the El Niño‐La Niña cycle on satellite‐derived primary production in the California Current , 2002 .

[66]  David A. Siegel,et al.  Climate-driven trends in contemporary ocean productivity , 2006, Nature.

[67]  Scott C. Doney,et al.  Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity , 2010 .

[68]  P. Sen.  Estimates of the Regression Coefficient Based on Kendall's Tau , 1968 .

[69]  Andrew C. Thomas,et al.  Phytoplankton scales of variability in the California Current System: 1. Interannual and cross-shelf variability , 2007 .

[70]  C. Carlson,et al.  Biogeochemical and hydrographic controls on chromophoric dissolved organic matter distribution in the Pacific Ocean , 2009 .

[71]  M. Tratani,et al.  What is “atmospheric correction”? , 2013 .

[72]  W. Peterson,et al.  An unusual bloom of the dinoflagellate Akashiwo sanguinea off the central Oregon, USA, coast in autumn 2009 , 2011 .

[73]  Motoaki Kishino,et al.  Estimation of the spectral absorption coefficients of phytoplankton in the sea , 1985 .

[74]  M. Behrenfeld,et al.  MODIS observed phytoplankton dynamics in the Taiwan Strait: an absorption-based analysis , 2010 .

[75]  M. Behrenfeld,et al.  Independence and interdependencies among global ocean color properties: Reassessing the bio‐optical assumption , 2005 .