Ocean Color Lesson I: Energy and Color

Total Page:16

File Type:pdf, Size:1020Kb

Ocean Color Lesson I: Energy and Color Ocean Color Ocean Color Lesson I: Energy and Color Keywords: algorithm, photosynthetic organisms, chlorophyll, particulate matter, ocean color data, MODIS, global carbon cycle, backscatter, electromagnetic spectrum, water-leaving radiance Why is Ocean Color Important? The major reason scientists plants in the ocean also tells us measure ocean color is to study where nutrient levels are high, and phytoplankton, the microscopic shows where pollutants poison the ocean plants which form the base ocean and prevent plant growth. of the oceanic food web. Other conditions can also affect Phytoplankton use sunlight and phytoplankton growth, such as carbon dioxide to produce organic subtle changes in the climate due carbon. This process, called to seasons and variations in photosynthesis, is possible salinity in coastal areas. Since because plants contain phytoplankton depend upon chlorophyll, a green-colored specific conditions for growth, they compound which traps the energy frequently become the first from sunlight. Chlorophyll is also indicator of a change in their responsible for giving most marine environment. Comparing images and land plants a green color. taken at different periods tells us about changes that occur over Because different types of time. Because phytoplankton drift phytoplankton have different with the water, patterns in ocean concentrations of chlorophyll, color can also be used to study measuring the color of an area of ocean currents. the ocean allows us to estimate the amount and general type of Why are phytoplankton so phytoplankton in that area. important? These small plants are the beginning of the food chain for Looking at ocean color also tells most of the planet. As us about the health and chemistry phytoplankton grow and multiply, of the ocean. In addition to light small fish and other animals eat and carbon dioxide, phytoplankton them as food. Larger animals then also require nutrients such as eat these smaller ones. The ocean nitrogen and phosphorus. The fishing industry finds good fishing distribution of spots by looking at ocean color images to locate areas rich in ã Project Oceanography 1999 5 Spring Series Ocean Color Ocean Color phytoplankton. Ocean color is for the study of ocean biology, therefore a valuable research tool chemistry, and physics. ã Project Oceanography 6 Spring Series 1999 - Ocean Color Ocean Color What is Ocean Color? The "color" of the ocean is inorganic particles, dissolved determined by the interactions of organic chemicals, and the water incident light with substances itself. Phytoplankton contain present in the water. We see chlorophyll, which absorbs light at color when light is reflected by blue and red wavelengths and objects around us. White light is reflects green wavelengths. made up of a spectrum or Particles can reflect and absorb combination of colors, as in a light, which reduces the clarity rainbow. When light hits the (light transmission) of the water. surface of an object, these Dissolved organic matter strongly different colors can be absorbed, absorbs blue light, and its transmitted through the presence can interfere with substance, scattered, or reflected measurements of chlorophyll. in differing intensities. The color we see depends on which colors When we look at the ocean or are reflected. For example, a observe it from space, we see that book that appears red to us the ocean is blue because water absorbs more of the green and absorbs red and reflects blue light. blue parts of the white light Using instruments that are more shining on it, and reflects the red sensitive than the human eye, we parts of the white light. The light can measure a wide array of blue which is scattered or transmitted shades, which reveal the presence by most objects is usually not of varying amounts of apparent to our eyes. phytoplankton, sediments, and dissolved organic chemicals. The substances in seawater Excerpted from: http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/OCDST/se which most affect the color awifs_raq.html#Q1 reflected are the phytoplankton, Ocean Color and Global Warming Besides acting as the first link in The carbon dioxide in the the food chain, phytoplankton are atmosphere is in balance with a critical part of ocean chemistry. carbon dioxide in the ocean. ã Project Oceanography 7 Spring Series 1999 - Ocean Color Ocean Color During photosynthesis atmosphere, and therefore may phytoplankton remove carbon contribute to global warming. dioxide from sea water, and Sources of carbon dioxide in the release oxygen as a by-product. Earth's atmosphere include This allows the oceans to absorb decomposition of organic matter additional carbon dioxide from the (such as trees), the carbon dioxide atmosphere. If fewer that animals and people exhale, phytoplankton existed, volcanic activity, and human atmospheric carbon dioxide would activities such as the burning of increase. fossil fuels and wood. Phytoplankton also affect carbon No one yet knows how much dioxide levels when they die and carbon the oceans and land can sink to the ocean floor. The carbon absorb. Nor do we know how the in the phytoplankton is soon Earth's environment will adjust to covered by other material sinking increasing amounts of carbon to the ocean bottom. In this way, dioxide in the atmosphere. the oceans may store excess Studying the distribution and global carbon, which otherwise changes in global phytoplankton would accumulate in the using ocean color and other tools atmosphere as carbon dioxide. will help scientists find answers to these questions. Excerpted from: Carbon dioxide acts as a http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/OCDST/se awifs_raq.html#Q1 "greenhouse" gas in the How is Ocean Color Measured? The color of ocean water and its from a ship or moored in place on constituents (phytoplankton, a buoy and left to collect data for particles, and dissolved organic long periods of time. Absorption matter) can be measured in a and scatter measurements can variety of ways, and many also be made on discrete water sensitive instruments have been samples, by either placing the designed for this purpose. sample in the sample chamber of Instruments which measure the the spectophotometer or by having light absorbed, transmitted, and the seawater flow continuously scattered can be placed in the through the instrument while the water, either lowered on a cable ship is underway. Still other ã Project Oceanography 8 Spring Series 1999 - Ocean Color Ocean Color instruments which measure property known as water-leaving reflectance, called radiometers, radiance – the amount and color are used above the sea surface, (spectral distribution) of light re- either from the deck of the ship, entering the atmosphere from the or from an airplane or satellite. ocean surface. This last type measures a Water-Leaving Radiance The radiance received at Some of it is eventually scattered spacecraft altitudes is actually back up through the surface. This controlled more strongly by the light is called the water-leaving atmosphere than by the ocean. radiance, and it can be detected Solar irradiance (the full from space. Generally, much less spectrum of light emitted by the than 10% of the total light detected sun) is scattered and absorbed by a satellite sensor will be water- by the gases in the atmosphere, leaving radiance. Because such a including water vapor (molecular large part of the radiance signal [Rayleigh] scattering), from the satellite detects comes from particles suspended in the air the atmosphere, the atmospheric (aerosol scattering), and ozone correction factors are extremely (selective absorption). It is this important for generating accurate scattered light which is ocean color data. In fact, the responsible for the blue color of atmospheric effect is so large that the sky. Sea surface reflections if we were able to look at the (sun and sky glitter) also ocean from the height of the decrease the amount of sunlight satellite, it would appear to us to which enters the ocean. The be blue even if the actual color of mathematical equations used to the ocean were black. Scientists correct the water-leaving are continuing to research how radiances for these interactions best to design the atmospheric in the atmosphere are called correction algorithms. "atmospheric correction algorithms." Because there is a strong relationship between the color of After light enters the ocean, it most of the open ocean and the interacts with the phytoplankton, phytoplankton chlorophyll dissolved organic matter, concentration, it is possible to particles, and water molecules. develop a water-leaving radiance ã Project Oceanography 9 Spring Series 1999 - Ocean Color Ocean Color equation (algorithm) for satellite data. Excerpted from: calculating phytoplankton http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/OCDST/se awifs_raq.html#Q1 biomass in the ocean from ã Project Oceanography 10 Spring Series 1999 - Ocean Color Ocean Color Activities Activity I. Internet Ocean Productivity Ocean color sensors measure the amount of plant biomass by measuring the color due to the presence of chlorophyll. The concentration of phytoplankton chlorophyll and other pigments is related to phytoplankton growth rate, also called productivity. Thus, ocean color gives us an indirect measure of ocean productivity. In this activity, you can use images and data available on the internet to draw some conclusions about where and why productivity is high or low. 1.Print out a blank map from internet (http://seawifs.gsfc.nasa.gov/SEAWIFS/LIVING_OCEAN/LIVING_OCEAN.html) and outline the ocean regions with higher productivity. 2. Consider the colors in the legend from green to red to be areas high in productivity. Color these areas red on your map using a colored pencil, pen or crayon. 3. Color the less productive areas on your map in blue. 4. Compare/contrast productivity near the coastal areas with that in the mid-ocean regions. 5. Compare the productivity of ocean water near the equator with that in the northern and southern latitudes in these areas: · the mid-Atlantic · the mid-Pacific · eastern coastline of North and South America · western coastline of North and South America · western coastline of Asia Discussion Questions: 1.
Recommended publications
  • A Comparison of Global Estimates of Marine Primary Production from Ocean Color
    ARTICLE IN PRESS Deep-Sea Research II 53 (2006) 741–770 www.elsevier.com/locate/dsr2 A comparison of global estimates of marine primary production from ocean color Mary-Elena Carra,Ã, Marjorie A.M. Friedrichsb,bb, Marjorie Schmeltza, Maki Noguchi Aitac, David Antoined, Kevin R. Arrigoe, Ichio Asanumaf, Olivier Aumontg, Richard Barberh, Michael Behrenfeldi, Robert Bidigarej, Erik T. Buitenhuisk, Janet Campbelll, Aurea Ciottim, Heidi Dierssenn, Mark Dowello, John Dunnep, Wayne Esaiasq, Bernard Gentilid, Watson Greggq, Steve Groomr, Nicolas Hoepffnero, Joji Ishizakas, Takahiko Kamedat, Corinne Le Que´re´k,u, Steven Lohrenzv, John Marraw, Fre´de´ric Me´lino, Keith Moorex, Andre´Moreld, Tasha E. Reddye, John Ryany, Michele Scardiz, Tim Smythr, Kevin Turpieq, Gavin Tilstoner, Kirk Watersaa, Yasuhiro Yamanakac aJet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr, Pasadena, CA 91101-8099, USA bCenter for Coastal Physical Oceanography, Old Dominion University, Crittenton Hall, 768 West 52nd Street, Norfolk, VA 23529, USA cEcosystem Change Research Program, Frontier Research Center for Global Change, 3173-25,Showa-machi, Yokohama 236-0001, Japan dLaboratoire d’Oce´anographie de Villefranche, 06238, Villefranche sur Mer, France eDepartment of Geophysics, Stanford University, Stanford, CA 94305-2215, USA fTokyo University of Information Sciences 1200-1, Yato, Wakaba, Chiba 265-8501, Japan gLaboratoire d’Oce´anographie Dynamique et de Climatologie, Univ Paris 06, MNHN, IRD,CNRS, Paris F-75252 05, France hDuke University
    [Show full text]
  • Euphotic Zone Depth: Its Derivation and Implication to Ocean-Color Remote Sensing" (2007)
    University of South Florida Scholar Commons Marine Science Faculty Publications College of Marine Science 3-16-2007 Euphotic Zone Depth: Its Derivation and Implication to Ocean- Color Remote Sensing ZhongPing Lee Stennis Space Center Alan Weidemann Stennis Space Center John Kindle Stennis Space Center Robert Arnone Stennis Space Center Kendall L. Carder University of South Florida, [email protected] See next page for additional authors Follow this and additional works at: https://scholarcommons.usf.edu/msc_facpub Part of the Marine Biology Commons Scholar Commons Citation Lee, ZhongPing; Weidemann, Alan; Kindle, John; Arnone, Robert; Carder, Kendall L.; and Davis, Curtiss, "Euphotic Zone Depth: Its Derivation and Implication to Ocean-Color Remote Sensing" (2007). Marine Science Faculty Publications. 11. https://scholarcommons.usf.edu/msc_facpub/11 This Article is brought to you for free and open access by the College of Marine Science at Scholar Commons. It has been accepted for inclusion in Marine Science Faculty Publications by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Authors ZhongPing Lee, Alan Weidemann, John Kindle, Robert Arnone, Kendall L. Carder, and Curtiss Davis This article is available at Scholar Commons: https://scholarcommons.usf.edu/msc_facpub/11 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112, C03009, doi:10.1029/2006JC003802, 2007 Euphotic zone depth: Its derivation and implication to ocean-color remote sensing ZhongPing Lee,1 Alan Weidemann,1 John Kindle,1 Robert Arnone,1 Kendall L. Carder,2 and Curtiss Davis3 Received 6 July 2006; revised 12 October 2006; accepted 1 November 2006; published 16 March 2007. [1] Euphotic zone depth, z1%, reflects the depth where photosynthetic available radiation (PAR) is 1% of its surface value.
    [Show full text]
  • Special Topics in Ocean Optics Protocols, Part 2
    NASA/TM-2004- Ocean Optics Protocols For Satellite Ocean Color Sensor Validation, Revision 5, Volume VI: Special Topics in Ocean Optics Protocols, Part 2 James L. Mueller and Giulietta S. Fargion and Charles R. McClain, Editors J. L. Mueller, S. W. Brown, D. K. Clark, B. C. Johnson, H. Yoon, K. R. Lykke, S. J. Flora, M. E. Feinholz, N. Souaidia, C. Pietras, T. C. Stone, M. A. Yarbrough, Y. S. Kim, R. A. Barnes, Authors. National Aeronautics and Space administration Goddard Space Flight Space Center Greenbelt, Maryland 20771 February 2004 NASA/TM-2004- James L. Mueller1 and Giulietta S. Fargion2 Editors Ocean Optics Protocols For Satellite Ocean Color Sensor Validation, Revision 5, Volume VI, Part 2: Special Topics in Ocean Optics Protocols, Part 2 James L Mueller, CHORS, San Diego State University, San Diego, California Giulietta S. Fargion, Science Applications International Corporation, Beltsville, Maryland Charles R. McClain, NASA Goddard Space Flight Center, Greenbelt, Maryland B. Carol Johnson, Steven W. Brown, Howard Yoon, Keith Lykke, Nordine Souaidia, National Institute of Standards and Technology, Gaithersburg Maryland Dennis K. Clark, National Oceanic and Atmospheric Administration, National Environmental Satellite Data and Information Service, Camp Springs, Maryland Stephanie Flora, Michael E. Feinholz, Mark Yarbrough, Moss Landing Marine Laboratories, San Jose State University, Moss Landing, California Yong Sung Kim, STG Inc., Rockville, Maryland Christophe Pietras, Robert A. Barnes, SAIC General Sciences Corporation, Beltsville,
    [Show full text]
  • Advances in the Monitoring of Algal Blooms by Remote Sensing: a Bibliometric Analysis
    applied sciences Article Advances in the Monitoring of Algal Blooms by Remote Sensing: A Bibliometric Analysis Maria-Teresa Sebastiá-Frasquet 1,* , Jesús-A Aguilar-Maldonado 1 , Iván Herrero-Durá 2 , Eduardo Santamaría-del-Ángel 3 , Sergio Morell-Monzó 1 and Javier Estornell 4 1 Instituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, C/Paraninfo, 1, 46730 Grau de Gandia, Spain; [email protected] (J.-A.A.-M.); [email protected] (S.M.-M.) 2 KFB Acoustics Sp. z o. o. Mydlana 7, 51-502 Wrocław, Poland; [email protected] 3 Facultad de Ciencias Marinas, Universidad Autónoma de Baja California, Ensenada 22860, Mexico; [email protected] 4 Geo-Environmental Cartography and Remote Sensing Group, Universitat Politècnica de València, Camí de Vera s/n, 46022 Valencia, Spain; [email protected] * Correspondence: [email protected] Received: 20 September 2020; Accepted: 4 November 2020; Published: 6 November 2020 Abstract: Since remote sensing of ocean colour began in 1978, several ocean-colour sensors have been launched to measure ocean properties. These measures have been applied to study water quality, and they specifically can be used to study algal blooms. Blooms are a natural phenomenon that, due to anthropogenic activities, appear to have increased in frequency, intensity, and geographic distribution. This paper aims to provide a systematic analysis of research on remote sensing of algal blooms during 1999–2019 via bibliometric technique. This study aims to reveal the limitations of current studies to analyse climatic variability effect. A total of 1292 peer-reviewed articles published between January 1999 and December 2019 were collected.
    [Show full text]
  • An Overview of the Seawifs Project and Strategies for Producing a Climate Research Quality Global Ocean Bio-Optical Time Series
    ARTICLE IN PRESS Deep-Sea Research II 51 (2004) 5–42 An overview of the SeaWiFS project andstrategies for producing a climate research quality global ocean bio-optical time series Charles R. McClain*, Gene C. Feldman, Stanford B. Hooker Code 970.2, Office for Global Carbon Studies, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA Received1 April 2003; accepted19 November 2003 Abstract The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project Office was formally initiated at the NASA Goddard Space Flight Center in 1990. Seven years later, the sensor was launched by Orbital Sciences Corporation under a data- buy contract to provide 5 years of science quality data for global ocean biogeochemistry research. To date, the SeaWiFS program has greatly exceeded the mission goals established over a decade ago in terms of data quality, data accessibility andusability, ocean community infrastructure development,cost efficiency, andcommunity service. The SeaWiFS Project Office andits collaborators in the scientific community have madesubstantial contributions in the areas of satellite calibration, product validation, near-real time data access, field data collection, protocol development, in situ instrumentation technology, operational data system development, and desktop level-0 to level-3 processing software. One important aspect of the SeaWiFS program is the high level of science community cooperation andparticipation. This article summarizes the key activities andapproaches the SeaWiFS Project Office pursuedto define,achieve, and maintain the mission objectives. These achievements have enabledthe user community to publish a large andgrowing volume of research such as those contributedto this special volume of Deep-Sea Research. Finally, some examples of major geophysical events (oceanic, atmospheric, andterrestrial) capturedby SeaWiFS are presentedto demonstratethe versatility of the sensor.
    [Show full text]
  • Derivation of Red Tide Index and Density Using Geostationary Ocean Color Imager (GOCI) Data
    remote sensing Article Derivation of Red Tide Index and Density Using Geostationary Ocean Color Imager (GOCI) Data Min-Sun Lee 1,2, Kyung-Ae Park 2,3,* and Fiorenza Micheli 1,4,5 1 Hopkins Marine Station, Stanford University, Pacific Grove, CA 93950, USA; [email protected] (M.-S.L.); [email protected] (F.M.) 2 Department of Earth Science Education, Seoul National University, Seoul 08826, Korea 3 Research Institute of Oceanography, Seoul National University, Seoul 08826, Korea 4 Department of Biology, Stanford University, Stanford, CA 94305, USA 5 Stanford Center for Ocean Solutions, Stanford University, Pacific Grove, CA 93950, USA * Correspondence: [email protected]; Tel.: +82-2-880-7780 Abstract: Red tide causes significant damage to marine resources such as aquaculture and fisheries in coastal regions. Such red tide events occur globally, across latitudes and ocean ecoregions. Satellite observations can be an effective tool for tracking and investigating red tides and have great potential for informing strategies to minimize their impacts on coastal fisheries. However, previous satellite- based red tide detection algorithms have been mostly conducted over short time scales and within relatively small areas, and have shown significant differences from actual field data, highlighting a need for new, more accurate algorithms to be developed. In this study, we present the newly developed normalized red tide index (NRTI). The NRTI uses Geostationary Ocean Color Imager (GOCI) data to detect red tides by observing in situ spectral characteristics of red tides and sea water using spectroradiometer in the coastal region of Korean Peninsula during severe red tide events. The bimodality of peaks in spectral reflectance with respect to wavelengths has become the basis for developing NRTI, by multiplying the heights of both spectral peaks.
    [Show full text]
  • Remote Sensing of Euphotic Depth in Lake Naivasha
    REMOTE SENSING OF EUPHOTIC DEPTH IN LAKE NAIVASHA NOBUHLE PATIENCE MAJOZI February, 2011 SUPERVISORS: Dr. Ir. Mhd, S, Salama Prof. Dr. Ing., W, Verhoef REMOTE SENSING OF EUPHOTIC DEPTH IN LAKE NAIVASHA NOBUHLE PATIENCE MAJOZI Enschede, The Netherlands, February, 2011 Thesis submitted to the Faculty of Geo-Information Science and Earth Observation of the University of Twente in partial fulfilment of the requirements for the degree of Master of Science in Geo-information Science and Earth Observation. Specialization: Water Resources and Environmental Management SUPERVISORS: Dr. Ir. Mhd, S., Salama Prof. Dr. Ing., W., Verhoef THESIS ASSESSMENT BOARD: Dr. Ir., C.M.M., Mannaerts (Chair) Dr, D.M., Harper (External Examiner, Department of Biology - University of Leicester – UK) DISCLAIMER This document describes work undertaken as part of a programme of study at the Faculty of Geo-Information Science and Earth Observation of the University of Twente. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent those of the Faculty. ABSTRACT Euphotic zone depth is a fundamental measurement of water clarity in water bodies. It is determined by the water constituents like suspended particulate matter, dissolved organic matter, phytoplankton, mineral particles and water molecules, which attenuate solar radiation as it transits down a water column. Primary production is at its maximum within the euphotic zone because there is sufficient Photosynthetically Active Radiation (PAR) for photosynthesis to take place. The study was conducted in Lake Naivasha, Kenya. Rich in biodiversity, it supports a thriving fishery, an intensive flower-growing industry and geothermal power generation, thereby contributing significantly to local and national economic development.
    [Show full text]
  • Satellite Remote Sensing: Ocean Color☆ P Jeremy Werdell and Charles R Mcclain, NASA Goddard Space Flight Center, Greenbelt, MD, United States
    Satellite Remote Sensing: Ocean Color☆ P Jeremy Werdell and Charles R McClain, NASA Goddard Space Flight Center, Greenbelt, MD, United States © 2019 Elsevier Ltd. All rights reserved. Introduction 444 Ocean Color Theoretical and Observational Basis 444 Satellite Ocean Color Methodology 446 Sensor Design and Performance 447 Postlaunch Sensor Calibration Stability 449 Atmospheric Correction 449 Bio-optical Algorithms 450 Product Validation 450 Satellite Ocean Color Example Applications 451 Conclusions and Future Directions 454 References 454 Nomenclature Symbol Description (Units) À a Absorption coefficient (m 1) À1 aCDOM Absorption coefficient for colored dissolved organic matter (m ) À1 aNAP Absorption coefficient for nonalgal particles (m ) À1 aph Absorption coefficient for phytoplankton (m ) À1 aw Absorption coefficient for seawater (m ) À1 bb Backscattering coefficient (m ) À1 bb,NAP Backscattering coefficient for nonalgal particles (m ) À1 bb,ph Backscattering coefficient for phytoplankton (m ) À1 bb,w Backscattering coefficient for seawater (m ) À [Chla] Concentration of chlorophyll-a (mg m 3) À2 À1 Ed Downwelling irradiance (mWcm nm ) À2 À1 Eu Upwelling irradiance (mWcm nm ) f Factor that relates R to a and bb (unitless) À2 À1 F0 Solar irradiance (mWcm nm ) À1 Kd Diffuse attenuation coefficient of downwelling irradiance (m ) À1 KLu Diffuse attenuation coefficient of upwelling radiance (m ) À2 À1 À1 La Aerosol radiance (mWcm nm sr ) À2 À1 À1 Lf Foam (white cap) radiance (mWcm nm sr ) À2 À1 À1) Lg Sun glint radiance (mWcm nm sr À2
    [Show full text]
  • Algorithm Theoretical Basis Document
    ALGORITHM THEORETICAL BASIS DOCUMENT FOR MODIS PRODUCT MOD-27 OCEAN PRIMARY PRODUCTIVITY (ATBD-MOD-24) WAYNE E. ESAIAS Code 971 Goddard Space Flight Center November 15, 1996 1. INTRODUCTION 4 1.1 Background 5 1.2 Empirical Algorithms 5 1.3 Analytic Algorithms 6 2. THE EMPIRICAL ANNUAL OCEAN PRODUCTIVITY 8 2.1 Algorithm Description 8 2.1.1 Global Classification Approach 9 2.1.2 Treatment for other regions 13 2.2 Mathematical Description 14 2.3 Variance or uncertainty estimates. 15 2.4 Merged data from multiple satellite sensors 16 2.5 Instrument characteristics 17 2.6 Practical Considerations 18 2.6.1 -Programming and procedural considerations 18 2.6.2 -Calibration, validation, initialization 18 2.6.3 - Quality control and diagnostics 19 2.6.4 - Exception handling 20 2.6.5 - Data dependencies (error propagation from ancillary data) 20 2.6.6 -Output products 20 3. THE DAILY PRODUCTIVITY ALGORITHM 21 3.1 INTRODUCTION 21 3.2 Algorithm Description 22 3.3 Mathematical Description 23 3.4 Variance or uncertainty estimates 23 3.5 Data from multiple satellite sensors. 24 3.6 Ancillary data required 24 3.7 Instrument characteristics 24 3.8 Practical Considerations 24 3.8.1 Programming and procedural considerations 24 3.8.2 Calibration, validation and initialization 25 3.8.3 Quality control and diagnostics 25 3.8.4 Exception handling 25 3.8.5 Data dependencies (error propagation from ancillary data). 25 2 3.8.6 Inputs and Output products 25 4. IMPLEMENTATION SCHEDULE 26 5. LIST OF TABLES 28 6. LIST OF FIGURES 29 7.
    [Show full text]
  • Satellite Ocean Color Data Products for Marine Biogeochemical Research Applications
    Satellite ocean color data products for marine biogeochemical research applications Jeremy Werdell NASA Goddard Space Flight Center Science Systems & Applications, Inc. 18 January 2010 @ NIO PJW, NASA/SSAI, 18 Jan 2010 @ NIO professional background NASA Goddard Space Flight Center - Jun 99 to present oceanographer @ Ocean Biology Processing Group ocean color from all instruments & SST from MODIS & VIIRS located in Maryland near Washington D.C. academic background biology & environmental science @ University of Virginia - 1996 oceanography @ the University of Connecticut - 1998 oceanography @ the University of Maine - Sep 09 to present PJW, NASA/SSAI, 18 Jan 2010 @ NIO 1. why use satellites for oceanographic applications? 2. why study ocean color? 3. ocean color @ NASA 4. the NASA Ocean Biology Processing Group (OBPG) 5. international collaborations PJW, NASA/SSAI, 18 Jan 2010 @ NIO 1. why use satellites for oceanographic applications? 2. why study ocean color? 3. ocean color @ NASA 4. the NASA Ocean Biology Processing Group (OBPG) 5. international collaborations PJW, NASA/SSAI, 18 Jan 2010 @ NIO why use satellites? NASA funds in situ sampling programs in support of its cal/val programs bio-optical data collected during the MODIS-Aqua era (June 2002 to present) PJW, NASA/SSAI, 18 Jan 2010 @ NIO why use satellites? SeaWiFS, MODIS-Aqua, & others provide a daily, synoptic view of the Earth MODIS-Aqua observations for one day (1 February 2008) PJW, NASA/SSAI, 18 Jan 2010 @ NIO why use satellites? Chesapeake Bay Program PJW, NASA/SSAI, 18 Jan
    [Show full text]
  • Status and Plans for Satellite Ocean-Colour Missions: Considerations for Complementary Missions
    Reports of the International Ocean-Colour Coordinating Group An Affiliated Program of the Scientific Committee on Oceanic Research (SCOR) Supporting the Committee on Earth Observing Satellites (CEOS) IOCCG Report Number 2, 1999 Status and plans for Satellite Ocean-Colour Missions: Considerations for Complementary Missions. Report of an IOCCG working group held in Halifax, Nova Scotia, Canada, June 16-18, 1998, chaired by Mr. Tasuku Tanaka (NASDA). Edited by James A. Yoder (URI); Based on contributions from: Watson W. Gregg, Nicolas Hoepffner, John Parslow, Trevor Platt, Michael Rast, Shubha Sathyendranath, Tasuku Tanaka and James A. Yoder. Please cite this report as IOCCG (1999), with the complete bibliographic citation as follows: IOCCG (1999). Status and Plans for Satellite Ocean-Colour Missions: Considerations for Complementary Missions. Yoder, J. A. (ed.), Reports of the International Ocean-Colour Coordinating Group, No. 2, IOCCG, Dartmouth, Canada. ISSN: 1098-6030 The International Ocean-Colour Coordinating Group (IOCCG) is an international group of experts in the field of satellite ocean colour, which acts as a liaison and communication channel between users, managers and agencies in the ocean-colour arena. The IOCCG is sponsored by NASA (National Aeronautics and Space Administration), NASDA (National Space Development Agency of Japan), ESA (European Space Agency), CNES (Centre National d’Etudes Spatiales), JRC (Joint Research Centre, EC), Canadian Space Agency (CSA), and SCOR (Scientific Committee on Oceanic Research). http://www.ioccg.org Published by the International Ocean-Colour Coordinating Group, PO Box 1006, Dartmouth, Nova Scotia, Canada, B2Y 4A2 Printed by MacNab Print, Dartmouth, Canada © IOCCG 1999 Contents Executive Summary ................................................................................................................ 1 1. Introduction ..................................................................................................................5 2.
    [Show full text]
  • Unit I: Ocean Color
    Ocean Color Ocean Color Lesson II: Data Processing and Imagery Ocean color observations made in the world's oceans. In this from an Earth orbit allow an lesson we will discuss how the oceanographic viewpoint that is data collected by the satellite impossible from ship or shore -- a sensor are processed to obtain global picture of biological activity useful products for researchers. Ocean Color Viewed from Space: What Does the Satellite See? The satellite radiometer “sees” waters. The sensor has the light entering the sensor. In the capability of making case of ocean color measurements at several visible measurements, the satellite is and infra-red (IR) wavelengths, viewing some portion of the corresponding to different bands earth’s surface and measuring of electromagnetic energy. These the amount and color are called the spectral bands of (wavelength) of sunlight the sensor. The earliest ocean reflected from the earth’s color sensor had 6 bands, surface. As ocean color intensity SeaWiFS (Sea-viewing Wide is related to the amount of each Field-of-view Sensor) has 8 of the constituents in seawater, bands, or channels. Future data from the satellite sensor sensors are planned with many may therefore be used to more spectral bands, which will calculate the concentrations of allow scientists to determine more particulate and dissolved seawater constituents and to do materials in surface ocean so more accurately. What data do the satellite collect? Data received from an ocean Sensor (SeaWiFS), a global ocean color satellite like the Sea- color mission launched in August viewing Wide Field-of view 1997, is stored and transmitted in ã Project Oceanography 15 Spring Series 1999 -Ocean Color Ocean Color several forms.
    [Show full text]