Presentation on theme: "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."— Presentation transcript:
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 from Mark Abbott, Bob Arnone, Paul Menzel, Chris Brown, Ed Howard, et al.
GOES-R Coastal Water Imager CW will provide first ocean color capability from geo orbit –Can make measurements in constant tidal conditions CW enables more frequent views of U.S. coastal ocean –Necessary to resolve rapid changes due to tides and coastal currents CW provides more opportunities for cloud-free viewing –Better detect/monitor/track rapidly changing phenomena such as Harmful Algal Blooms, sediment plumes, and chaotic coastal zone currents magnitude that could be underestimated due to diurnal behavior CW offers higher spatial resolution ( 300 meters) –Fisheries researchers are limited by spatial resolution of current systems—better than 1 km needed to improve measurement and modeling of small scale phenomena such as migration pathways for salmon fisheries
Visible Infrared Imaging Radiometer Suite (VIIRS) Being built by Raytheon SBRS –SeaWiFS and MODIS heritage First flight on NPOESS Preparatory Project (NPP) in 2007 then NPOESS satellites starting in 2009 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 (+/- 1500 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 (+/- 1500 km) –Designed to meet global ocean imaging requirements at 1 km GSD –Maximum revisit frequency of twice a day at 1030 and 1530
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 have the ability to rapidly sample coastal waters providing a unique capability to observe the dynamic coastal ocean environment. HES-CW will provide higher spatial resolution (300 m vs. 1000 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 sampling coastal waters.
Coastal Remote Sensing Applications A. Coastal Development 1. Mapping Floodplains 2. Hurricane Forecasts 3. Identifying At-Risk Properties 4. Managing Nuisance Plants 5. Mapping Oceanfront Setbacks B. Habitat 6. Mapping Coral Reefs (Hawaii & U.S. Territories) 7. Monitoring the Spread of Brown Marsh 8. Mapping Kelp Beds 9. Preserving Wetlands and Riparian Areas 10. Determining Marine Protected Boundaries C. Water Quality 11. Monitoring Storm Water Runoff 12. Monitoring Water Quality 13. Monitoring Red Tides 14. Mitigating Oil Spills 15. Monitoring Sewage Outfall Impacts D. Living Resources 16. Mapping Sea Turtle Habitat 17. Damage to Submerged Aquatic Vegetation 18. Controlling Invasive Marsh Grasses 19. Mapping Oyster Beds 20. Impacts of Commercial Shellfish Harvesting E. Waterways 21. Nautical Charts for Recreational Boaters 22. Stabilizing a Fluctuating Shoreline 23. Protecting Cultural Resources 24. Siting a Marine Outfall Pipeline 25. Identifying Channel Obstructions (Courtesy Ed. Howard, NOAA)
More Requirements Sampling Frequency: –Threshold requirement is to sample the entire U.S. coastal waters once every three hours –Goal is hourly –Additional sampling for selected regions at higher frequency –Daylight hours only –May be adjusted for cloud cover; use Advanced Baseline Imager (ABI) to select cloud free areas for imaging Many other requirements for simultaneity, stability, jitter, etc.
Prioritizing Goal Requirements HES-CW built to the threshold requirements will meet the basic needs and provide a dramatic improvement over present capabilities for coastal imaging. Goal requirements compete with each other, e.g. higher spatial resolution makes it harder to increase sampling frequency or SNR. Top priority goals are: –Higher frequency of sampling –Additional channels for atmospheric correction –Hyperspectral instead of multispectral
Frequency of Sampling Threshold requirement is to sample all U. S. coastal waters (except Alaska) 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 Frequency of sampling may be tied to HES architecture –If HES is one instrument then sampling of coastal waters will be strictly limited to fit around the Disk Sounding task. –Separate HES-CW instrument could offer much more flexibility. May mean accepting threshold requirements for SNR, etc.
Multispectral or Hyperspectral? The threshold 14 channels are adequate for the proposed applications when you do not image the bottom. Hyperspectral is strongly recommended –When the bottom is visible, e.g. on the entire West Florida Shelf to 30 km offshore, hyperspectral data is required to resolve the increased complexity of the scene. –Polar orbiting ocean color imagers all have different wavelength channels. A hyperspectral HES-CW would make cross calibration of all ocean color sensors possible.
Resolving the Complexity of Coastal Optics Requires Hyperspectral Remote Sensing Extensive studies using shipboard measurements and airborne hyperspectral imaging have shown that visible hyperspectral imaging is the only tool available to resolve the complexity of the coastal ocean from space. (Lee and Carder, Appl. Opt., 41(12), 2191 – 2201, 2002.)
Spatial Resolution The spatial resolution is at Nadir (over the Equator) so it degrades by latitude in U. S. coastal waters. The threshold requirement is 300 m at nadir; order 400- 450 m in U. S. Coastal waters. –Considered adequate for water column properties The goal requirement is 150 m (200 m over U. S.). It will be very expensive to achieve this higher resolution. –Cost goes as the square of the spatial resolution improvement –May not be possible for ocean SNR, etc. –Will compete with frequency of coverage, SNR, and number of bands.
Spatial Resolution Comparison 6 km 20 km 30 m150 m300 m 0.65 m 0.55 m 0.45 m Hyperion Data RGB Composite The effect of spatial degradation from 30 m to 150 m and 300 m is illustrated Detailed coastal features are compromised at coarser resolutions Overall characteristics retained even at 300 m resolution (Courtesy Ed. Howard, NOAA)
MODIS 1 km water clarity Modeled HES-CW (250 m) HES-CW higher spatial resolution critical to monitor complex coastal waters
Signal-to-Noise Ratio (SNR) Threshold requirement is 300:1 for ocean radiances –Initial requirement for SeaWiFS; but SeaWiFS performance greatly exceeded this (more like 450:1) Goal requirement is 900:1 for ocean radiances –Exceeds MODIS SNR –Difficult and costly to achieve –SNR goes up as the square root of the signal The main noise source is shot noise Do we need more than the threshold 300:1? If so are we happy with 400:1?, 500:1? Is the threshold ok for some channels, but not others? If so which channels do we need more SNR?
HES-CW Ocean and Cloud Radiance Values SNR is calculated based on the ocean radiances (blue line) Sensor must not saturate on the cloud radiances (pink line)
SeaWiFS 1 km dataPHILLS-2 9 m data mosaic Sand waves in PHILLS-1 1.8 m data Fronts in AVIRIS 20 m data Near-simultaneous data from 5 ships, two moorings, three Aircraft and two satellites collected to address issues of scaling in the coastal zone. (HyCODE LEO-15 Experiment July 31, 2001.) Existing Data Sets Are Available to Demonstrate Science and Products Credit: Curt Davis, NRL
HES-CW Products The primary products are calibrated at sensor radiances for all channels –The threshold 14 channels and any additional goal channels The other required ocean product is chlorophyll –This requires atmospheric correction to provide water leaving radiances used in this calculation Additional products proposed include reflectance, turbidity, particulate and dissolved absorption, backscatter and fluorescence. Products are geo-located to approximately 1 Ground Sample Distance (GSD) Issues to be addressed: –Methods for on-orbit calibration and validation of products. –Methods for atmospheric correction.
Fluorescence provides better phytoplankton measurements in optically-complex coastal waters MODIS Terra l2 scene from 3 October 2001. The ratio of fluorescence line height to chlorophyll changes as a function of the physiological state of the phytoplankton. This can be exploited to assess the health and productivity of the phytoplankton populations. Fluorescence line height not available from VIIRS. MODIS Terra l2 scene from 3 October 2001. The ratio of fluorescence line height to chlorophyll changes as a function of the physiological state of the phytoplankton. This can be exploited to assess the health and productivity of the phytoplankton populations. Fluorescence line height not available from VIIRS.
NOAA HES-CW Applications Water quality monitoring Coastal hazard assessment Navigation safety Human and ecosystem health awareness Natural resource management in coastal and estuarine areas Climate variability prediction (e.g., carbon cycle) Landscape changes Coral reef detection and health appraisal Development of Nowcast and Forecast models of the coastal ocean
Harmful Algal Blooms (HABs) In the Gulf of Mexico, blooms of the toxic algae Karenia brevis result in shellfish bed closures and lost tourism that cost the state of Florida millions of dollars each year. Similar problems in other parts of the country with other toxic species. Ship based monitoring very expensive and time consuming Inadequate data frequently leads to unnecessary closings. HABSOS system is being developed to provide early warnings using SeaWiFS data and models HES-CW will greatly improve warning systems like HABSOS –More frequent data for cloud clearing –Higher spatial resolution to assess conditions closer to the shell fish beds and beaches In the Gulf of Mexico, blooms of the toxic algae Karenia brevis result in shellfish bed closures and lost tourism that cost the state of Florida millions of dollars each year. Similar problems in other parts of the country with other toxic species. Ship based monitoring very expensive and time consuming Inadequate data frequently leads to unnecessary closings. HABSOS system is being developed to provide early warnings using SeaWiFS data and models HES-CW will greatly improve warning systems like HABSOS –More frequent data for cloud clearing –Higher spatial resolution to assess conditions closer to the shell fish beds and beaches
When K. brevis Blooms, conditions tend to be calm. Under these Conditions the cells exhibit a dramatic diel migration. The net result is a 10X increase in cells at the air-sea interface over a several hour period. This unique feature will be readily detected in HES-CW data. Frequent sampling can assist in detection and classification of HABs
HABSOS can utilize improved spatial resolution and frequency of coverage from HES-CW
GOES-R HES-CW Schedule and COAST In June 2004 NOAA selected three contractors (BALL, BAE and ITT) to conduct two year evaluation of requirements and design studies for HES. A contractor will be selected to build HES in 2006. Launch of GOES-R is planned for 2012. NOAA has formed the Coastal Ocean Applications and Science Team (COAST) to: –Evaluate HES-CW threshold and goal requirements and recommend priorities for the goals –Involve the broader oceanographic community to help NOAA achieve their objectives for HES-CW –Mark Abbott is the COAST team leader and Curt Davis is the COAST Executive Director.
HES-CW Summary HES-CW will allow a major advance in our ability to monitor and manage the coastal ocean. HES-CW built to the threshold requirements will meet the basic needs for coastal imaging. –Meeting the goal requirements of hourly imaging and hyperspectral imaging would provide significant additional benefits. Much as the introduction of GOES imagery in the 1960s revolutionized weather prediction, HES-CW data will be key for the planned development of nowcast and forecast models for the coastal ocean.
The COAST Team Mark Abbott, OSU, COAST Team Leader Curtiss Davis, OSU (June 2005) COAST Executive Director Bob Arnone, NRL Barney Balch, BLOS Robert Bidigare, UHPaul Bissett, FERI Janet Campbell, UNH Heidi Dierssen, U Conn. Larry Harding, HPL, UMCES Victor V. Klemas, UD Raphael Kudela, UCSC Ricardo Letelier, OSU Steve Lohrenz, USM Oscar Schofield, Rutgers David Siegel, UCSBHeidi Sosik, WHOI Dariusz Stramski, SIOPeter Strutton, OSU Jan Svejkosvky, Ocean Imaging Kenneth Voss, U Miami Nan D. Walker, LSUJames Yoder, URI NOAA: Stan Wilson, NESDIS, John Pereira, NESDIS, Mike Ondrusek, ORA, Menghua Wang, ORA, Rick Stumpf, NOS, Mary Culver, CSC, Cara Wilson, NMFS, Christopher Brown, CICS NASA: Paula Bontempi, NASA HQ, Antonio Mannino, GSFC Navy: Steve Ackleson, ONR, Robert Winokur, Technical Director, CNO
Contacts and Further Information Mark Abbott, Dean of the College of Oceanic and Atmospheric Sciences at Oregon State University is the COAST Chairman firstname.lastname@example.org email@example.com Curtiss Davis, U.S. Naval Research Laboratory, is the Coast Executive Director firstname.lastname@example.org@nrl.navy.mil NOAA Contacts: –John Pereira, NOAA NESDIS John.Pereira@noaa.govJohn.Pereira@noaa.gov –Stan Wilson, NOAA NESDIS Stan.Wilson@noaa.govStan.Wilson@noaa.gov –Mike Ondrusek, NOAA NESDIS Michael.Ondrusek@noaa.govMichael.Ondrusek@noaa.gov –Mary Culver, NOAA NOS Mary.Culver@noaa.govMary.Culver@noaa.gov –Rick Stumpf, NOAA NOS Richard.Stumpf@noaa.govRichard.Stumpf@noaa.gov –Chris Brown, NOAA Cooperative Institute for Climate Studies Christopher.W.Brown@noaa.gov Christopher.W.Brown@noaa.gov GOES-R Web Site COAST web site Brochure