NRL09/21/2004_Davis.1 GOES-R HES-CW Requirements Curtiss Davis COAS, Oregon State university.

Slides:



Advertisements
Similar presentations
NOAA National Geophysical Data Center
Advertisements

September 17-18, 2008 Tokyo International Exchange Center SIT-22 Tokyo, Japan Ocean Color Radiance (OCR) Virtual Constellation (VC) Image from ESA’s GlobColour.
Satellite Ocean Color Overview Dave Siegel – UC Santa Barbara With help from Chuck McClain, Mike Behrenfeld, Bryan Franz, Jim Yoder, David Antoine, Gene.
Satellite Capabilities for Water Resource/Quality Mapping 27 May 2013 Mark Kapfer C-Core 1.
Ecology, Climate, Physical Oceanography. Bering Sea, Alaska SeaWifs Image (Norman Kuring image, NASA, April 25, 1998) Turquoise = phytoplankton bloom.
Exploiting New Sensors on NOAA NPP – VIIRS for Ocean Applications Beyond the VIIRS -- SST And Ocean Color University of Southern Mississippi May Arnone.
The GOES-R Coastal Waters Imager; a new Capability for Monitoring the Coastal Ocean Curtiss O. Davis Naval Research Laboratory Washington, D. C. USA Contributions.
NRL09/21/2004_Davis.1 GOES-R HES-CW Atmospheric Correction Curtiss O. Davis Code 7203 Naval Research Laboratory Washington, DC 20375
2 Remote sensing applications in Oceanography: How much we can see using ocean color? Adapted from lectures by: Martin A Montes Rutgers University Institute.
OSU_08/1/2005_Davis.1 GOES-R Coastal Waters Imaging and the COAST Risk Reduction Activities Curtiss O. Davis College of Oceanic and Atmospheric Sciences.
REMOTE SENSING PLATFORMS
Water Level Sensor Physical processes related to bio-optical properties on the New York Bight inner continental shelf Grace C. Chang 1, Tommy D. Dickey.
OSU_08/1/2005_Davis.1 COAST Risk Reduction Activities Curtiss O. Davis College of Oceanic and Atmospheric Sciences Oregon State University, Corvallis,
Temporal and Spatial Variability of Physical and Bio-optical Properties on the New York Bight Inner Continental Shelf G. C. Chang, T. D. Dickey Ocean Physics.
GOES-R 3 : Coastal CO 2 fluxes Pete Strutton, Burke Hales & Ricardo Letelier College of Oceanic and Atmospheric Sciences Oregon State University 1. The.
OSU_2/20/2006_Davis.1 Geostationary Coastal Waters Imaging as a Component of IOOS Curtiss O. Davis College of Oceanic and Atmospheric Sciences Oregon State.
Satellite Imagery Meteorology 101 Lab 9 December 1, 2009.
NRL09/21/2004_Davis.1 Monterey Bay Experiment Plan COAST.
Fundamentals of Satellite Remote Sensing NASA ARSET- AQ Introduction to Remote Sensing and Air Quality Applications Winter 2014 Webinar Series ARSET -
UNH Coastal Observing Center NASA GEO-CAPE workshop August 19, 2008 Ocean Biological Properties Ru Morrison.
GEO-CAPE Ocean Color STM Measurement Instrument Platform Other Science Questions Approach Requirements Requirements Requirements Needs How do short-term.
Ocean Measurements from Space: Past, Present, and Future Mark R. Abbott College of Oceanic and Atmospheric Sciences Oregon State University 7 November.
Km’s; hours to weeks 100-km; years 1000-km, decades Two-Way Interactions Global ocean and climate dynamics strongly influence processes at local scales.
OSU_08/1/2005_Davis.1 GOES-R Coastal Waters Imaging and the COAST Risk Reduction Activities Curtiss O. Davis and Mark Abbott College of Oceanic and Atmospheric.
NRL09/21/2004_Davis.1 GOES-R and the Hyperspectral Environmental Sensor (HES) Suite Curtiss O. Davis Code 7203 Naval Research Laboratory Washington, DC.
Green-1 9/17/2015 Green Band Discussion Satellite Instrument Synergy Working Group September 2003.
Satellite Data Resources for Atmospheric Science Applications.
Applications and Limitations of Satellite Data Professor Ming-Dah Chou January 3, 2005 Department of Atmospheric Sciences National Taiwan University.
UNCLASSIFIED Navy Applications of GOES-R Richard Crout, PhD Naval Meteorology and Oceanography Command Satellite Programs Presented to 3rd GOES-R Conference.
Light Absorption in the Sea: Remote Sensing Retrievals Needed for Light Distribution with Depth, Affecting Heat, Water, and Carbon Budgets By Kendall L.
Analysis of GOCI data in Preparation for GEO-CAPE Curtiss O. Davis 1 ZhongPing Lee 2 1 COAS, Oregon State University, Corvallis, OR USA
Remote Sensing & Satellite Research Group
Remote sensing of aerosol from the GOES-R Advanced Baseline Imager (ABI) Istvan Laszlo 1, Pubu Ciren 2, Hongqing Liu 2, Shobha Kondragunta 1, Xuepeng Zhao.
GOES-R, May 2004 Coastal Ocean Science Harmful Algal Blooms and GOES-R GOES-R Users Conference, 2004 SeaWiFS data from OrbImage, Inc. Richard P. Stumpf.
Ocean Color Radiometer Measurements of Long Island Sound Coastal Observational platform (LISCO): Comparisons with Satellite Data & Assessments of Uncertainties.
1 Applications of Remote Sensing: SeaWiFS and MODIS Ocean Color Outline  Physical principles behind the remote sensing of ocean color parameters  Satellite.
Satellite-derived Sea Surface Temperatures Corey Farley Remote Sensing May 8, 2002.
History / Impact EM Radiation Ocean Features Orbits / Satellites / Sensors Trends Earth Remote Sensing* Definition: The use of.
MERIS US Workshop, Silver Springs, 14 th July 2008 MERIS US Workshop, 14 July 2008, Washington (USA) Henri LAUR Envisat Mission Manager.
Hurricane Intensity Estimation from GOES-R Hyperspectral Environmental Suite Eye Sounding Fourth GOES-R Users’ Conference Mark DeMaria NESDIS/ORA-STAR,
Ocean Color Remote Sensing Pete Strutton, COAS/OSU.
What is the key science driver for using Ocean Colour Radiometry (OCR) for research and applications? What is OCR, and what does it provide? Examples of.
Optical Water Mass Classification for Interpretation of Coastal Carbon Flux Processes R.W. Gould, Jr. & R.A. Arnone Naval Research Laboratory, Code 7333,
Improvements of the Geostationary Operational Environmental Satellites (GOES)-R series for Climate Applications GOES-R data and products will support applications.
NRL09/21/2004_Davis.1 CIOSS/COAST GOES-R Risk Reduction Activities for HES-CW CIOSS: Cooperative Institute for Oceanographic Satellite Studies, College.
Mirza Muhammad Waqar HYPERSPECTRAL REMOTE SENSING - SENSORS 1 Contact:
Impact of Watershed Characteristics on Surface Water Transport of Terrestrial Matter into Coastal Waters and the Resulting Optical Variability:An example.
Science Questions Societal Relevance Observational Requirements Observational Strategies Satellite Missions Scientific Basis for NASA OBB Mission Planning.
NASA/NOAA/Navy/Forest Service/USDA Cooperative Mission for DEEP Instrument DEEP: Diurnal Earth Explorer Probe NASA: Instrument, Enhanced Telemetry, Data.
OSU_08/1/2005_Davis.1 COAST GOES-R Coastal Waters Imaging (CWI) Risk Reduction Activities Curtiss O. Davis College of Oceanic and Atmospheric Sciences.
NASA’s Coastal and Ocean Airborne Science Testbed (COAST) L. Guild 1 *, J. Dungan 1, M. Edwards 1, P. Russell 1, S. Hooker 2, J. Myers 3, J. Morrow 4,
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Satellite Observation and Model Simulation of Water Turbidity in the Chesapeake.
Satellites Storm “Since the early 1960s, virtually all areas of the atmospheric sciences have been revolutionized by the development and application of.
Goddard Earth Sciences Data and Information Services Center, NASA/GSFC, Code 902, Greenbelt, Maryland 20771, USA INTRODUCTION  NASA Goddard Earth Sciences.
Ocean Color Research Team Meeting May 1, 2008 NPOESS Preparatory Project (NPP) Status Jim Gleason NPP Project Scientist.
1 GLIMPSING THE FIRST PRODUCTS FROM VIIRS Dr. Wayne Esaias NASA GSFC Thomas F. Lee Jeffrey Hawkins Arunas Kuciauskas Kim Richardson Jeremy Solbrig Naval.
Overview of Climate Observational Requirements for GOES-R Herbert Jacobowitz Short & Associates, Inc.
Cal/Val at CIOSS Ted Strub – CIOSS/COAS/OSU Cooperative Institute for Oceanographic Satellite Studies College of Oceanic and Atmospheric Sciences Oregon.
OC3522Summer 2001 OC Remote Sensing of the Atmosphere and Ocean - Summer 2001 Ocean Color.
SCM x330 Ocean Discovery through Technology Area F GE.
Chapter 13 Biological Productivity and Energy Transfer
Remote Sensing of the Ocean and Coastal Waters
Hyperspectral Sensing – Imaging Spectroscopy
GOES-8 thru GOES-15 NPP VIIRS MSG SEVIRI AVHRR GOES Sounder MTG FCI
Primary Production and Satellite Remote Sensing
Jian Wang, Ph.D IMCS Rutgers University
GOES visible (or “sun-lit”) image
Coastal CO2 fluxes from satellite ocean color, SST and winds
Generation of Cloud Products from NOAA’s Operational Satellite Imagers
GOES Sounder Meteorology 415 Fall 2007.
Presentation transcript:

NRL09/21/2004_Davis.1 GOES-R HES-CW Requirements Curtiss Davis COAS, Oregon State university

NRL09/21/2004_Davis.2 Visible Infrared Imaging Radiometer Suite (VIIRS) Being built by Raytheon SBRS –SeaWiFS and MODIS heritage First flight on NPOESS Preparatory Project (NPP) in 2008 then NPOESS satellites starting in 2010 Seven ocean color channels and 2 SST channels Approximately 1 km GSD ocean color –742 m GSD and Nadir, 1092 m at +/- 850 km, 1597m at End of Scan (+/ km) –Designed to meet global ocean imaging requirements at 1 km GSD –Maximum revisit frequency of twice a day at 1030 and 1530 Approximately 1 km GSD ocean color –742 m GSD and Nadir, 1092 m at +/- 850 km, 1597m at End of Scan (+/ km) –Designed to meet global ocean imaging requirements at 1 km GSD –Maximum revisit frequency of twice a day at 1030 and 1530

NRL09/21/2004_Davis.3 Why HES-CW given VIIRS? Tides, diel winds (such as the land/sea breeze), river runoff, upwelling and storm winds drive coastal currents that can reach several knots. Furthermore, currents driven by diurnal and semi-diurnal tides reverse approximately every 6 hours. VIIRS daily sampling at the same time cannot resolve tides, diurnal winds, etc. HES-CW will provide the capability to view coastal waters from a geostationary platform that will provide the management and science community with a unique capability to observe the dynamic coastal ocean environment. HES-CW will provide higher spatial resolution (300 m vs m) HES-CW will provide additional channels to measure solar stimulated fluorescence, suspended sediments, CDOM and improved atmospheric correction. Example tidal cycle from Charleston, OR. Black arrows VIIRS sampling, red arrows HES-CW sampling. Example tidal cycle from Charleston, OR. Black arrows VIIRS sampling, red arrows HES-CW sampling. These improvements are critical for the analyses of coastal waters.

NRL09/21/2004_Davis.4 HES-PORD Channel Specifications

NRL09/21/2004_Davis.5 COAST proposed new HES-CW Channel Specifications

NRL09/21/2004_Davis.6 Wavelength (  m) Application (THRESHOLD)Colored dissolved organic Matter (CDOM) (THRESHOLD)Chlorophyll a, CDOM Particulate Organic Carbon (POC) (THRESHOLD) XXXChlorophyll a and Chlorophyll b, O 2 :O 2 dimmer (THRESHOLD)Chlorophyll a and accessory pigments (THRESHOLD)Accessory Pigments (THRESHOLD)Accessory pigments, Suspended sediment (THRESHOLD)Chlorophyll a, accessory pigments, suspended sediments, (POC) new thresholdAccessory pigments, suspended sediments, water clarity new thresholdSuspended sediments, water clarity (THRESHOLD)Suspended sediments, coccolith concentration (THRESHOLD)Chlorophyll a, Fluorescence (THRESHOLD)Chlorophyll a fluorescence new threshold if no 1.00Atmospheric correction, chlorophyll fluorescence (THRESHOLD)Atmospheric correction (THRESHOLD) XXXO 2 A band (THRESHOLD)Atmospheric correction, cloud clearing (THRESHOLD) XXXColumn water new threshold (40 nm)Atmospheric Correction to.987 in 10 nm channels (GOAL)Hyperspectral imaging for discrimination of in-water and bottom features new goal (20 nm)Atmospheric correction in coastal waters new goal (20 nm)CDOM, Atmospheric correction in coastal waters GOAL (40 nm)Atmospheric Correction 1.38 (GOAL)Daytime cirrus cloud 1.61 (GOAL)Daytime cloud water 2.26 (GOAL)Daytime cloud properties 11.2 (GOAL)Total water for Sea Surface Temperature (SST) (GOAL)Sea Surface Temperature (SST) 1

NRL09/21/2004_Davis.7 Frequency of Sampling and Prioritizing Goal Requirements COAST top priority goals are: –Higher frequency of sampling –Goal channels for atmospheric correction –Hyperspectral instead of multispectral Threshold requirement is to sample all Hawaii and Continental U. S. coastal waters once every three hours during daylight –Plus additional hourly sampling of selected areas Goal requirement is hourly sampling of all U.S. coastal waters is strongly recommended, for cloud clearing and to better resolve coastal ocean dynamics. Goal requirements compete with each other, e.g. higher spatial resolution makes it harder to increase sampling frequency or SNR. Threshold requirement is to sample all Hawaii and Continental U. S. coastal waters once every three hours during daylight –Plus additional hourly sampling of selected areas Goal requirement is hourly sampling of all U.S. coastal waters is strongly recommended, for cloud clearing and to better resolve coastal ocean dynamics. Goal requirements compete with each other, e.g. higher spatial resolution makes it harder to increase sampling frequency or SNR. HES-CW built to the threshold requirements will be a dramatic improvement over present capabilities for coastal imaging.