NRL09/21/2004_Davis.1 Monterey Bay Experiment Plan COAST.

Slides:



Advertisements
Similar presentations
High Resolution Time Series Measurements of Bio- optical and Physical Variability in the Coastal Ocean as Part of HyCODE Dickey Mooring.
Advertisements

CHRIS (Compact High Resolution Imaging Spectrometer) sira group sira electro-optics Dr Mike Cutter EO & Technology Business Manager.
Satellite Ocean Color Overview Dave Siegel – UC Santa Barbara With help from Chuck McClain, Mike Behrenfeld, Bryan Franz, Jim Yoder, David Antoine, Gene.
P R I S M Portable Remote Imaging SpectroMeter Pantazis “Zakos” Mouroulis, JPL Robert Green, JPL Heidi Dierssen, Uconn Bo-Cai Gao, Marcos Montes, NRL.
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.
August 5 – 7, 2008NASA Habitats Workshop Optical Properties and Quantitative Remote Sensing of Kelp Forest and Seagrass Habitats Richard C. Zimmerman -
NRL09/21/2004_Davis.1 GOES-R HES-CW Atmospheric Correction Curtiss O. Davis Code 7203 Naval Research Laboratory Washington, DC 20375
Seasonal to Interannual Variability in Phytoplankton Biomass and Diversity on the New England Shelf Heidi M. Sosik Hui Feng In Situ Time Series for Validation.
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.
OSU_08/1/2005_Davis.1 COAST Risk Reduction Activities Curtiss O. Davis College of Oceanic and Atmospheric Sciences Oregon State University, Corvallis,
1 Remote sensing applications in Oceanography: How much we can see using ocean color? Martin A Montes Ph.D Rutgers University Institute of Marine and Coastal.
NRL09/21/2004_Davis.1 GOES-R HES-CW Requirements Curtiss Davis COAS, Oregon State university.
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.
Center for Remote Sensing and Computational Ecology January16-18, 2003ONR HyCODE Workshop Miami, FL IOP and Rrs Predictive Modeling.
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.
12/28/2001 #1 LEO 2001 IN SITU DATA Profiling Optics and Water Return (POWR) Package Joe Rhea and Gia Lamela.
NRL09/21/2004_Davis.1 CIOSS/COAST GOES-R Risk Reduction Activities for HES-CW CIOSS: Cooperative Institute for Oceanographic Satellite Studies, College.
SIO RAS activities in O. Kopelevich, Lab. Of Ocean Optics SIO RAS, Moscow.
Using HyspIRI at the Land/Sea Interface to Identify Phytoplankton Functional Types There are many properties of biological interest in the coastal ocean,
Visible Satellite Imagery Spring 2015 ARSET - AQ Applied Remote Sensing Education and Training – Air Quality A project of NASA Applied Sciences Week –
UNH Coastal Observing Center NASA GEO-CAPE workshop August 19, 2008 Ocean Biological Properties Ru Morrison.
A.B. VIIRS (Nov. 20, 2013).
Digital Imaging and Remote Sensing Laboratory Hyperspectral Water Quality 1 EOCAP-HSI FINAL Briefing RIT Technical Activities John Schott, RIT PI
Sherwin Ladner 1, Robert Arnone 2, Ryan Vandermeulen 2, Paul Martinolich 3, Adam Lawson 1, Jennifer Bowers 3, Richard Crout 1, Michael Ondrusek 4,Giulietta.
In situ science in support of satellite ocean color objectives Jeremy Werdell NASA Goddard Space Flight Center Science Systems & Applications, Inc. 6 Jun.
Coastal Water Quality Remote Sensing Welcome Dr. Jeff Payne Deputy Director NOAA Coastal Services Center October 7, 2003.
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.
Atmospheric Correction Algorithms for Remote Sensing of Open and Coastal Waters Zia Ahmad Ocean Biology Processing Group (OBPG) NASA- Goddard Space Flight.
First Flight of NASA’s Coastal and Ocean Airborne Science Testbed (COAST) L. Guild 1, J. Dungan 1, M. Edwards 1, P. Russell 1, J. Morrow 2, S. Hooker 3,
Retrieving Coastal Optical Properties from MERIS S. Ladner 1, P. Lyon 2, R. Arnone 2, R. Gould 2, T. Lawson 1, P. Martinolich 1 1) QinetiQ North America,
Spectral Requirements for Resolving Shallow Water Information Products W. Paul Bissett and David D. R. Kohler.
Ocean Color Remote Sensing Curt Davis and Pete Strutton, COAS/OSU
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
Ocean Color Radiometer Measurements of Long Island Sound Coastal Observational platform (LISCO): Comparisons with Satellite Data & Assessments of Uncertainties.
Soe Hlaing *, Alex Gilerson, Samir Ahmed Optical Remote Sensing Laboratory, NOAA-CREST The City College of the City University of New York 1 A Bidirectional.
1 Applications of Remote Sensing: SeaWiFS and MODIS Ocean Color Outline  Physical principles behind the remote sensing of ocean color parameters  Satellite.
Chlorophyll Results Ocean Optics 2004 Mike Sauer & Eric Rehm.
Towards a Hydrodynamic and Optical Modeling System with Remote Sensing Feedback Yan Li Dr. Anthony Vodacek Digital Imaging and Remote Sensing Laboratory.
Ocean Color Remote Sensing Pete Strutton, COAS/OSU.
Title page. “ Possible Geocape Capabilities Measurements of Diurnal Variability with Requirements of hours to days……………. “
Ocean Color Products: The challenge of going from stocks to rates
Optical Water Mass Classification for Interpretation of Coastal Carbon Flux Processes R.W. Gould, Jr. & R.A. Arnone Naval Research Laboratory, Code 7333,
Rick Reynolds and Dariusz Stramski Measurements of IOPs and Characterization of Particle Assemblages for Monterey Bay Experiment Marine Physical Laboratory.
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:
Examples of Closure Between Measurements and HydroLight Predictions Curtis D. Mobley Sequoia Scientific, Inc. Bellevue, Washington Maine 2007.
Kelley Bostrom University of Connecticut NASA OCRT Meeting May 12, 2010.
NRL 7343 Nov’97 Remote Sensing in the Japan East Sea Robert ArnoneRichard Gould Chistine Chan Sherwin Ladner Naval Research Laboratory Stennis Space Center.
Impact of Watershed Characteristics on Surface Water Transport of Terrestrial Matter into Coastal Waters and the Resulting Optical Variability:An example.
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.
Fluorescence Line Height (FLH) Ricardo Letelier, Mark Abbott, Jasmine Nahorniak Oregon State University.
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,
Lecture 19: Linking in situ IOP with biogeochemistry, case studies (multi-instructor presentation and discussion) Concept of optical proxies.
Radiometry and Uncertainties from SORTIE (Spectral Ocean Radiance Transfer Investigation and Experiment) Kenneth Voss and Howard Gordon, Univ. of Miami.
SeaWiFS Calibration & Validation Strategy & Results Charles R. McClain SeaWiFS Project Scientist NASA/Goddard Space Flight Center February 11, 2004.
Optical Properties in coastal waters change rapidly on very fine spatial scales. The existence of multiple ocean color systems provides a unique capability.
CIOSS Ocean Optics Aug 2005 Ocean Optics, Cal/Val Plans, CDR Records for Ocean Color Ricardo M Letelier Oregon State University Outline - Defining Ocean.
Seasonal to Interannual Variability in Phytoplankton Biomass and Diversity on the New England Shelf Heidi M. Sosik Hui Feng In Situ Time Series for Validation.
IRS-P4 OCM (Ocean Colour Monitor) Current Status of the Mission OCM is functioning normally and data is received at four ground stations.
Hydrolight Lab: Part 1 July 18th, 2013.
NASA’s Coastal and Ocean Airborne Science Testbed (COAST) L. Guild 1, J. Dungan 1, M. Edwards 1, P. Russell 1, J. Morrow 2, S. Hooker 3, J. Myers 4, R.
Building an Integrated Ocean Color Sensor Web at the Land-Sea Interface UCSC UARC/ARC Ames GSFC BSI SARP.
E d ( ) L u ( ) c = a + b b tot = b f + b b IOP- Inherent optical property eg. absorption (a), scattering (b), attenuation (c) AOP- Apparent optical property.
The Dirty Truth of Coastal Ocean Color Remote Sensing Dave Siegel & St é phane Maritorena Institute for Computational Earth System Science University of.
Monitoring Water Chlorophyll-a Concentration (Chl-a) in Lake Dianchi,China from 2003 ~ 2009 by MERIS Data.
Jian Wang, Ph.D IMCS Rutgers University
Ecosystem Breakout Summary
Presentation transcript:

NRL09/21/2004_Davis.1 Monterey Bay Experiment Plan COAST

NRL09/21/2004_Davis.2 Monterey Experiment to Collect Simulated HES-CW data There are no existing data sets that include all the key attributes of HES-CW data: –Spectral coverage (.38 – 1.0 mm) –High signal-to-noise ratio (>300:1 prefer >900:1, for ocean radiances for 300 m binned data) –High spatial resolution (<150 m, bin to 300 m) –Hourly or better revisit Propose field experiments in FY to develop the required data sets for HES-CW algorithm and model development. Airborne system: –Hyperspectral imager that can be binned to the HES-CW bands –Flown at high altitude for minimum of 10 km swath –Endurance to collect repeat flight lines every half hour for up to 6 hours –SAMSON Proposed experimental site: –August-September 2006 Monterey Bay (coastal upwelling, HABs)

NRL09/21/2004_Davis.3 Monterey Experiment to collect simulated HES-CW data Experimental Design –Choose sites with IOOS or other long term monitoring and modeling activities –Intensive effort for 2 weeks to assure that all essential parameters are measured: -Supplement standard measurements at the site with shipboard or mooring measurements of water-leaving radiance, optical properties and products expected from HES-CW algorithms, -Additional atmospheric measurements as needed to validate atmospheric correction parameters, -As needed, enhance modeling efforts to include bio-optical models that will utilize HES-CW data. –Aircraft overflights for at least three clear days and one partially cloudy day (to evaluate cloud clearing) during the two week period. -High altitude to include 90% or more of the atmosphere -30 min repeat flight lines for up to 6 hours to provide a time series for models and to evaluate changes with time of day (illumination, phytoplankton physiology, etc.) All data to be processed and then distributed over the Web for all users to test and evaluate algorithms and models.

NRL09/21/2004_Davis.4 Experiment Resources Aircraft for 6 flight days 6 hrs per day. R/V John Martin 7 ship days? Small boats for the entire two weeks? Lab space (14 C, HPLC, pad absorptions, instrument prep, etc. Space for basing the gliders? Space for instrument repair and calibration. Space for basing the aircraft? Space for daily group meeting in evening to review data and plan next day experiment? Lodging, motels or rent a house or some of both

NRL09/21/2004_Davis.5 One Day in the Experiment Assume clear morning and sunrise at 0700 Aircraft takes off at 0700 –First data at 0730 –Repeat 20 km square (approximately ½ of the Bay) every 30 min -0730, 0800, 0830, Skip one repeat and do staked collection -1000,1030,1100,1130,1200 -Additional measurements for atmospheric correction, etc. –Land at 1300 R/V Martin –Occupy one Station for profiles for each overflight? –Alternatively underway data collection or combination of stations every other overflight and underway in between. Glider collecting underway data. Mooring data Seagrass beds should be part of the overflight area. Data processed and in data system in 48? Hrs. Models later.

NRL09/21/2004_Davis.6 Atmospheric Measurements NRL Monterey lidar, etc. UCSC Sun Photometers on ship Aircraft staked measurements Other sensors on aircraft?

NRL09/21/2004_Davis.7 Airborne Measurements Paul Bissett (FERI, 2 people on plane) –SAMSON –Cover 20 x 20 km area (roughly ½ the Bay) in 28 min. –6 hr flight, repeat every 30 min, except for special staked imaging, or other for atmospheric correction. –Data binned to 10 m spatial and 10 nm spectral resolution (or HES-CW channels. –Data geolocated –Data calibrated –Data atmospherically corrected using Tafkaa (Marcos Montes, NRL ) Airport for plane? lab space for processing system including two operators (FERI) and 1 NRL (for atmospheric correction) for data processing and analysis?

NRL09/21/2004_Davis.8 Gliders Oscar Schofield (launch from a small boat) Particle Glider

NRL09/21/2004_Davis.9 In-Water Optics Bob Arnone (NRL group, 2 people on ship) POWR IOP profiling package –Filtered and unfiltered a-c9s –a-cS –Hydroscatt-6 –CTD –Water bottles –fluorometer –CDOM fluorometer Above water remote sensing reflectance Water samples are available for HPLC, etc. but NRL will not be doing those measurements. Ken Voss (1) NURADS Mike Ondrusek (1) AOPs

NRL09/21/2004_Davis.10 Chlorophyll, fluorescence and productivity Ricardo Letelier (2) Heidi Sosik (1) On the R/V John Martin: –FRRF (flow thru mode) and PAM (discrete mode) –FLH –Imaging flow system Water samples collected, filtered and frozen for: –HPLC pigments –Chlorophyll fluorometry –Filter absorption pads –POC? –Nutrients (Kudela) – 14 C productivity, P vs. I curves?

NRL09/21/2004_Davis.11 Benthic productivity Heidi Dierssen –Independent in Small Boat –Seagrass productivity –Kelp?

NRL09/21/2004_Davis.12 Coastal Carbon Budget Pete Strutton –One person on R/V Martin –Flow though PCO 2 system –one on shore

NRL09/21/2004_Davis.13 R/V John Martin NRL (2 people) –IOP profiling package –Above Water Rrs –Water samples for Chl, Pad absorptions productivity, etc. Voss (1 person) NURADS Ondrusek (1 person) AOPs Sosik (1 person) –Imaging flow system Letelier (1 person) – 14 C productivity –FRRF underway, FLH, chlorophyll fluorometry, Strutton (1 person) –Underway PCO 2 (maintain underway system) Kudela (1 person) –Underway system –Nutrients from bottles (shore lab) Chief Scientist? Total 8-9

NRL09/21/2004_Davis.14 R/V John Martin Wire Time POWR package and water retrieval (15 min) –Can operate as a free fall package or on a wire NURADS floats away from the ship (2 min to deploy and recover) HTSRB floats away from the ship (2 min to deploy and recover) APO profiler (10 min?) Others?

NRL09/21/2004_Davis.15 R/V John Martin Water For each bottle sample depth need water for: HPLC (50 mls) Fluorometric Chlorophyll (50 mls) Filter pad absorptions (200 mls) POC (500 mls) Suspended Sediments (500 mls) Nutrients (50 mls) Microscopy (50 mls) 14 C productivity (200 mls)

NRL09/21/2004_Davis.16 Additional Small Boats Dierssen –Seagrasses and kelp Schofield –Gliders Others??

NRL09/21/2004_Davis.17 Lab Requirements Space to store and process samples for: Pigments –Fluorometric –HPLC 14 C productivity Nutrients Pad absorptions POC Suspended Sediments Flow Cytometer Others?? Ship instrument preparation and service Glider preparations and service. Space for data analysis and processing ship, and aircraft data. Where will we have lab space?

NRL09/21/2004_Davis.18 Bio-Optical Models John Kindle (NRL) Others??

NRL09/21/2004_Davis.19 Demo Data System Paul BIssett (FERI) to host, OSU (Letelier) to have mirror site SAMSON data –Geolocated –Calibrated –Atmospherically corrected –binned to 10 m GSD and 10 nm spectral (or HES-CW channels) In-water data –All types –Geolocated to the images Atmospheric data Links to associated data from existing moorings, models, etc.

NRL09/21/2004_Davis.20 HABs Identify HABs during experiment and link to the experimental data. –Look for unique signature, algorithm to identify HABs from the data collected –Feed into the development of HAB models