Physics Further Testing/Validation of the Satellite f/Q correction Kenneth J. Voss, Nordine Souaidia, and Albert Chapin Department of Physics, Univ. of.

Slides:



Advertisements
Similar presentations
Robin Hogan, Richard Allan, Nicky Chalmers, Thorwald Stein, Julien Delanoë University of Reading How accurate are the radiative properties of ice clouds.
Advertisements

Atmospheric Correction Algorithm for the GOCI Jae Hyun Ahn* Joo-Hyung Ryu* Young Jae Park* Yu-Hwan Ahn* Im Sang Oh** Korea Ocean Research & Development.
UPRM Lidar lab for atmospheric research 1- Cross validation of solar radiation using remote sensing equipment & GOES Lidar and Ceilometer validation.
Using a Radiative Transfer Model in Conjunction with UV-MFRSR Irradiance Data for Studying Aerosols in El Paso-Juarez Airshed by Richard Medina Calderón.
Sherwin D. Ladner 1, Robert A. Arnone 2, Richard W. Gould, Jr. 2, Alan Weidemann 2, Vladimir I. Haltrin 2, Zhongping Lee 2, Paul M. Martinolich 3, and.
Satellite Ocean Color Overview Dave Siegel – UC Santa Barbara With help from Chuck McClain, Mike Behrenfeld, Bryan Franz, Jim Yoder, David Antoine, Gene.
Phytoplankton absorption from ac-9 measurements Julia Uitz Ocean Optics 2004.
Characterization of radiance uncertainties for SeaWiFS and Modis-Aqua Introduction The spectral remote sensing reflectance is arguably the most important.
Optical variability and optical « anomalies » in Mediterranean waters André Morel, David Antoine and Hervé Claustre Laboratoire d’Océanographie de Villefranche.
Characterisation of the BRDF (HDRF) of snow surfaces at Dome C, Antarctica, for the inter-calibration and validation of satellite remote sensing products.
Evaluation of atmospheric correction algorithms for MODIS Aqua in coastal regions Goyens, C., Jamet, C., and Loisel, H. Atmospheric correction workshop.
Liang APEIS Capacity Building Workshop on Integrated Environmental Monitoring of Asia-Pacific Region September 2002, Beijing,, China Atmospheric.
D. Antoine, E. Leymarie, A. Morel, B. Gentili Laboratoire d'Océanographie de Villefranche, France J.P. Buis, N. Buis, S. Victori, S. Meunier, M Canini.
The GSM merging model. Previous achievements and application to GlobCOLOUR Globcolour / Medspiration user consultation, Dec 4-6, 2006, Villefranche/mer.
Atmospheric effect in the solar spectrum
Constraining aerosol sources using MODIS backscattered radiances Easan Drury - G2
Calibration and Status of MOBY Dennis Clark, NOAA/NESDIS Carol Johnson, NIST Steve Brown, NIST Mark Yarbrough, MLML Stephanie Flora, MLML Mike Feinholz,
Surface Skin Temperatures Observed from IR and Microwave Satellite Measurements Catherine Prigent, CNRS, LERMA, Observatoire de Paris, France Filipe Aires,
Presented At AMS Meeting, Long Beach, CA, 2003 Aerosol Phase Function And Size Distributions From Polar Nephelometer Measurements During The SEAS Experiment.
ESTEC July 2000 Estimation of Aerosol Properties from CHRIS-PROBA Data Jeff Settle Environmental Systems Science Centre University of Reading.
NOAA Research and Operations Marine Optical Buoy Design Review July 18-19, 2006 Plan for calibration and maintenance of AHAB Uncertainty Budget: Laboratory.
Rrs Modeling and BRDF Correction ZhongPing Lee 1, Bertrand Lubac 1, Deric Gray 2, Alan Weidemann 2, Ken Voss 3, Malik Chami 4 1 Northern Gulf Institute,
A Comparison of Particulate Organic Carbon (POC) from In situ and Satellite Ocean Color Data Off the Coast of Antarctica Amanda Hyde Antonio Mannino (advisor)
The IOCCG Atmospheric Correction Working Group Status Report The Eighth IOCCG Committee Meeting Department of Animal Biology and Genetics University.
Atmospheric Correction and Adjacency effect (a little) Ken Voss, Ocean Optics Class, Darling Center, Maine, Summer 2011.
SeaDAS Training ~ NASA Ocean Biology Processing Group 1 Level-2 ocean color data processing basics NASA Ocean Biology Processing Group Goddard Space Flight.
IOP algorithm OOXX, Anchorage, September 25, 2010 Some (basic) considerations on our capability to derive b bp from AOPs (R and K d ), in situ.
Blue: Histogram of normalised deviation from “true” value; Red: Gaussian fit to histogram Presented at ESA Hyperspectral Workshop 2010, March 16-19, Frascati,
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,
Xiong Liu, Mike Newchurch Department of Atmospheric Science University of Alabama in Huntsville, Huntsville, Alabama, USA
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.
GOES and GOES-R ABI Aerosol Optical Depth (AOD) Validation Shobha Kondragunta and Istvan Laszlo (NOAA/NESDIS/STAR), Chuanyu Xu (IMSG), Pubu Ciren (Riverside.
 Introduction  Surface Albedo  Albedo on different surfaces  Seasonal change in albedo  Aerosol radiative forcing  Spectrometer (measure the surface.
ASSESSMENT OF OPTICAL CLOSURE USING THE PLUMES AND BLOOMS IN-SITU OPTICAL DATASET, SANTA BARBARA CHANNEL, CALIFORNIA Tihomir S. Kostadinov, David A. Siegel,
Backscattering Lab Julia Uitz Pauline Stephen Wayne Slade Eric Rehm.
Aerosol Optical Depth during the Northern CA Fires of 2008 In situ aerosol light scattering and absorption measurements in Reno Nevada, 2008, indicated.
The Second TEMPO Science Team Meeting Physical Basis of the Near-UV Aerosol Algorithm Omar Torres NASA Goddard Space Flight Center Atmospheric Chemistry.
Hyperspectral Infrared Alone Cloudy Sounding Algorithm Development Objective and Summary To prepare for the synergistic use of data from the high-temporal.
Approach: Assimilation Efficiencies The Carbon based model calculates mixed layer NPP (mg m -3 ) as a function of carbon and phytoplankton growth rate:
Fluorescence Line Height (FLH) Ricardo Letelier, Mark Abbott, Jasmine Nahorniak Oregon State University.
GlobColour / Medspiration user consultations, Nov 20-22, 2007, Oslo Validation of the GlobColour Full product set ( FPS ) over open ocean Case 1 waters.
In situ data in support of (atmospheric) ocean color satellite calibration & validation activities How are my data used? Part 2 Ocean Optics Class University.
New Fluorescence Algorithms for the MERIS Sensor Yannick Huot and Marcel Babin Laboratoire d’Océanographie de Villefranche Antoine Mangin and Odile Fanton.
TOMS Ozone Retrieval Sensitivity to Assumption of Lambertian Cloud Surface Part 1. Scattering Phase Function Xiong Liu, 1 Mike Newchurch, 1,2 Robert Loughman.
Retrieval of biomass burning aerosols with combination of near-UV radiance and near -IR polarimetry I.Sano, S.Mukai, M. Nakata (Kinki University, Japan),
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Satellite Observation and Model Simulation of Water Turbidity in the Chesapeake.
Estimating the uncertainties in the products of inversion algorithms or, how do we set the error bars for our inversion results? Emmanuel Boss, U. of Maine.
Validation strategy for aerosol retrievals of the future Lorraine Remer and J. Vanderlei Martins Dec
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.
Satellite Derived Bathymetry GEBCO Cookbook
IOP algorithm OOXX Jeremy Werdell & Bryan Franz NASA Ocean Biology Processing Group 25 Sep 2010, Anchorage, AK
Status of MOBY and Future Plans Dennis Clark Carol Johnson, NIST Steve Brown, NIST Mark Yarbrough, MLML Stephanie Flora, MLML Mike Feinholz, MLML.
1 Retrieval of ocean properties using multispectral methods S. Ahmed, A. Gilerson, B. Gross, F. Moshary Students: J. Zhou, M. Vargas, A. Gill, B. Elmaanaoui,
Coastal Optical Characterization Experiment (COCE) Activities at STAR NOAA 2013 Satellite Conference, April 7-12, 2013 M. Ondrusek,
Some refinements for global IOPs products ZhongPing Lee IOPs Workshop, Anchorage, AK, Oct 25, 2010.
Hydrolight Lab: Part 1 July 18th, 2013.
International Ocean Color Science Meeting, Darmstadt, Germany, May 6-8, 2013 III. MODIS-Aqua normalized water leaving radiance nLw III.1. R2010 vs. R2012.
Lab 4 Scattering. Samples: Platymonas * Chaetoceros * Arizona 'Dust' *Wikipedia Damariscotta River Estuary.
The study of cloud and aerosol properties during CalNex using newly developed spectral methods Patrick J. McBride, Samuel LeBlanc, K. Sebastian Schmidt,
Physics Plans and Progress Kenneth Voss Howard Gordon Department of Physics University of Miami For Modis Science Team Meeting July 2004.
VIIRS-derived Chlorophyll-a using the Ocean Color Index method SeungHyun Son 1,2 and Menghua Wang 1 1 NOAA/NESDIS/STAR, E/RA3, College Park, MD, USA 2.
Group Presentation, July 17, 2013
PROBA scenes acquired over our study sites
DCC inter-calibration of Himawari-8/AHI VNIR bands
Absolute calibration of sky radiances, colour indices and O4 DSCDs obtained from MAX-DOAS measurements T. Wagner1, S. Beirle1, S. Dörner1, M. Penning de.
Inter-satellite Calibration of HIRS OLR Time Series
GOES -12 Imager April 4, 2002 GOES-12 Imager - pre-launch info - radiances - products Timothy J. Schmit et al.
Lunar Observation Activities with a Small Satellite and a Planetary Exploration Satellite. Hodoyoshi-1 Hayabusa-2 Toru Kouyama, AIST
Presentation transcript:

Physics Further Testing/Validation of the Satellite f/Q correction Kenneth J. Voss, Nordine Souaidia, and Albert Chapin Department of Physics, Univ. of Miami Andre Morel and David Antoine Laboratoire d’Oceanographie de Villefranche Dennis Clark and Mike Ondrusek NOAA/NESDIS Thank NASA for their support (under our MODIS validation work)

Physics Test of Q(  o, ,  ) portion of Morel, Antoine, Gentili (2002) f/Q algorithm Tests Q through the measurement of the upwelling radiance distribution, as: Q (  o, ,  ) = Eu/L(  o, ,  ) A single measurement of the upwelling spectral radiance distribution gives Eu [through integration of Lu (  o, ,  ) ] and L (  o, ,  ), with the same instrument, so is an accurate method to get Q (  o, ,  ). Note that f is not available, as it requires simultaneous measurement of E d, a and b b.

Physics Previous experimental tests Morel, Voss, and Gentili, 1995 (JGR) used the first generation electro-optic RADS system. One Chl value (0.3 mg/m 3 ) and  o from o. Voss and Morel, 2005 (L&O) used the next generation RADS-II. Chl from 0.2 to 10 mg/m 3, but  o only from o deg. Both from cruises off of San Diego and into Gulf of California, rather restricted geographically.

Physics New data set uses NuRADS Smaller system Only upwelling 6 wavelengths 2 minutes per spectral set Much better optical characteristics

Physics Morel, Antoine and Gentili (2002) model features Index is Chl,  o,  v, and  –Important that Chl is just a convenient index into the tables…could do something else, but this works. Includes Raman scattering (inelastic process). Radiance distribution depends critically on the phase function. –Includes a phase function which varies with Chl, not just a single particle phase function to match observed b b variation with Chl. –Calculation uses spheroids, and not spheres (which can be anomalous in the backscattering direction.

Physics Data reduction Process radiance distribution images according to Voss and Zibordi (1989). –Immersion test critical in underwater measurement, with curved windows not straight forward. Additional steps to locate geometry required.

Physics Example image and reduced product AOPEX, 8/11/04, 521 nm  o = 35 o, Chl = 0.1 mg/m 3 Average of 4 images (plus 2 Sides) L u =0.64  W/(cm 2 sr nm) Q u = 3.72,  u = 0.44

Physics Important to understand the effect of environmental noise in the radiance distribution images Look at it from two views AverageNormalized St. Dev.

Physics Alternatively… % Std. Dev. Histogram. Illustrates that it is unlikely that Std Dev. of pixel matchups with a model will be better than 3% or so…..radiance distribution just isn’t that stable.

Physics Extent of Data Set Used (in this study)

Physics Model-Data comparison Define: (Note: Chl= 0.11 mg/m 3, 11 o <  o <40 o )

Physics Error vs Chl, each point is one day Red dots, error; red bars, std; blue dots measurement std

Physics Error vs zenith angle (only displaying 412 nm, others show nothing significant)

Physics Conclusions To date, within the accuracy/environmental noise of data, Morel et al model works. Need more data in Chl range from 0.4 to 10 mg/m 3. Need another alternative in Case II waters, have more turbid data sets to look at this problem. Polarization? Have modified NuRADS to provide upwelling polarization data (see poster by Souidia et al.)