Participants: CNR-ISAC Ifremer JRC-EC European COastal-shelf sea OPerational Observing and forecasting system Integrated Project WP3: “Better use of remote.

Slides:



Advertisements
Similar presentations
Globcolour, Medspiration application, 21 November 2007 Towards an integrated SST and Ocean Color dataset for coastal applications at Ifremer Bertrand Saulquin.
Advertisements

An Optically-Based Technique for Producing Merged Water-Leaving Radiances; Validation and Application for the Mediterranean Basin Motivation: Combining.
ECOOP Meeting March 14-21, 2005 ECOOP WP7 Pierre-Yves LE TRAON Better use of remote sensing and in-situ observing systems for coastal/regional seas Objective.
Weymouth (125) Lowestoft (375) RV Endeavour Smarter Marine Monitoring from Space Rodney Forster, Cefas 1- Current uses in monitoring, operations and forecasting.
GMES Marine Service MY OCEAN WP 12 Thematic Assembly Centre for Ocean Colour Rosalia Santoleri-WP12 Leader.
Welcome to the Ocean Color Bio-optical Algorithm Mini Workshop Goals, Motivation, and Guidance Janet W. Campbell University of New Hampshire Durham, New.
Beyond Chlorophyll: Ocean color ESDRs and new products S. Maritorena, D. A. Siegel and T. Kostadinov Institute for Computational Earth System Science University.
AVHRR, SeaWiFS The NRT satellite observing system for the Adriatic sea The satellite OC observing system ADRICOSM experience In the framework of ADRICOSM.
Evaluation of Trends in Chlorophyll-a Concentration in Response to Climatic Variability in the Eastern Bering Sea from MODIS Puneeta Naik a,b and Menghua.
Characterization of radiance uncertainties for SeaWiFS and Modis-Aqua Introduction The spectral remote sensing reflectance is arguably the most important.
AERONET-OC: Gloria Istanbul, November Giuseppe Zibordi.
Evaluation of atmospheric correction algorithms for MODIS Aqua in coastal regions Goyens, C., Jamet, C., and Loisel, H. Atmospheric correction workshop.
GlobColour CDR Meeting ESRIN July 2006 Merging Algorithm Sensitivity Analysis ACRI-ST/UoP.
PJW, NASA, 13 Jun 2012, AtmCorr in Wimereux Comparison of ocean color atmospheric correction approaches for operational remote sensing of turbid, coastal.
The GSM merging model. Previous achievements and application to GlobCOLOUR Globcolour / Medspiration user consultation, Dec 4-6, 2006, Villefranche/mer.
IMOS Remote Sensing Cal/Val Twin goals: Local algorithm and product development Contribute to global databases and algorithms 3 main activities SST, Helen.
1 JRC Info Day, Bucharest 11/5/06 Nicolas Hoepffner Global Environment Monitoring Unit Ecosystem Monitoring in the Black Sea.
Ocean color NATO SfPS Project Annual Meeting Istanbul November 2011.
Operational Radar and Optical MApping Partners The OROMA team consists of 7 developers and 4 end users from coastal management: Overview Beach nourishment.
UNH Coastal Observing Center NASA GEO-CAPE workshop August 19, 2008 Ocean Biological Properties Ru Morrison.
In situ science in support of satellite ocean color objectives Jeremy Werdell NASA Goddard Space Flight Center Science Systems & Applications, Inc. 6 Jun.
1 Water Framework Directive (WFD) of the European Union © Acri-st, all rights reserved – 2014 Satellite-derived data for the Water Framework Directive.
SeaDAS Training ~ NASA Ocean Biology Processing Group 1 Satellite observations of ocean color NASA Ocean Biology Processing Group Goddard Space Flight.
Ocean Color Observations and Their Applications to Climate Studies Alex Gilerson, Soe Hlaing, Ioannis Ioannou, Sam Ahmed Optical Remote Sensing Laboratory,
Atmospheric Correction Algorithms for Remote Sensing of Open and Coastal Waters Zia Ahmad Ocean Biology Processing Group (OBPG) NASA- Goddard Space Flight.
1 Istanbul, November Joint Research Centre, European Commission, Ispra, Italy AOP Measurements and NN Bio-Optical Algorithms for the Western.
Chapter 7 Atmospheric correction and ocean color algorithm Remote Sensing of Ocean Color Instructor: Dr. Cheng-Chien LiuCheng-Chien Liu Department of Earth.
1 Evaluating & generalizing ocean color inversion models that retrieve marine IOPs Ocean Optics Summer Course University of Maine July 2011.
Joint EMECO/NOOS meeting – Lowestoft – 2-3 June 2009 Some Norwegian activities relevant to EMECO and to the implementation of the MSFD Dominique Durand.
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,
Light Absorption in the Sea: Remote Sensing Retrievals Needed for Light Distribution with Depth, Affecting Heat, Water, and Carbon Budgets By Kendall L.
ISAC Contribution to Ocean Color activity Mediterranean high resolution surface chlorophyll mapping Use available bio-optical data sets to estimate the.
The development and generation of the long term Mediterranean SSR products Rosalia Santoleri, Gianluca Volpe, Cristina Tronconi, Roberto Sciarra Istituto.
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.
ISAC Contribution to Ocean Color activity Mediterranean high resolution surface chlorophyll mapping Use available bio-optical data sets to estimate the.
SEADATANET Kick-Off Meeting Heraklion 8-10 June 2006 National Institute of Geophisics and Volcanology, Italy (INGV) SEADATANET Joint Reasearch Activities.
ECOOP-WP3 Better use of remote-sensing data and in situ measurements Francis Gohin, Ifremer T3.1 Optimal synergy between altimetry and tide gauge data.
Menghua Wang, NOAA/NESDIS/STAR Remote Sensing of Water Properties Using the SWIR- based Atmospheric Correction Algorithm Menghua Wang Wei Shi and SeungHyun.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Image: MODIS Land Group,
Validation of turbidity products EuroGOOS Conference, May 20-22, 2008, Exeter Session Observations – OBS17 May 22, 2008 Validation of turbidity products.
The generation and development of the long term Mediterranean SSR products The aims are: 1.to identify and develop of an optimal algorithm for the Mediterranean.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Presented by Menghua Wang.
HEIS contribution under tasks 1.1, 1.3 and 1.5 of ADRICOSM-EXT (ADRIatic sea integrated COastal areaS and river basin Management system pilot project.
Optical Water Mass Classification for Interpretation of Coastal Carbon Flux Processes R.W. Gould, Jr. & R.A. Arnone Naval Research Laboratory, Code 7333,
Definition and assessment of a regional Mediterranean Sea ocean colour algorithm for surface chlorophyll Gianluca Volpe National Oceanography Centre, Southampton.
Development of ocean color algorithms in the Mediterranean Sea Rosalia Santoleri 1,, Gianluca Volpe 1, Simone Colella 1,3, Salvatore Marullo 2, Maurizio.
GlobColour overview and achievements after two years Globcolour / Medspiration user consultation, Nov , 2007, Oslo Session 2 – Progress with the.
NASA Ocean Color Research Team Meeting, Silver Spring, Maryland 5-7 May 2014 II. Objectives Establish a high-quality long-term observational time series.
Progresses in IMaRS Caiyun Zhang Sept. 28, SST validation over Florida Keys 2. Potential application of ocean color remote sensing on deriving.
The effect of wind on the estimated plume extension of the La Plata River Erica Darken Summer 2004.
GlobColour / Medspiration user consultations, Nov 20-22, 2007, Oslo Validation of the GlobColour Full product set ( FPS ) over open ocean Case 1 waters.
Development of ocean color algorithms in the Mediterranean Sea
Validation of Coastwatch Ocean Color products S. Ramachandran, R. Sinha ( SP Systems NOAA/NESDIS) Kent Hughes and C. W. Brown ( NOAA/NESDIS/ORA,
ISAC Contribution to Ocean Color activity Mediterranean high resolution surface chlorophyll mapping Use available bio-optical data sets to estimate the.
SeaWiFS Calibration & Validation Strategy & Results Charles R. McClain SeaWiFS Project Scientist NASA/Goddard Space Flight Center February 11, 2004.
A semi-analytical ocean color inherent optical property model: approach and application. Tim Smyth, Gerald Moore, Takafumi Hirata and Jim Aiken Plymouth.
The main mission of the OCTAC is to operate a European Ocean Colour Service for GMES marine applications providing global, pan-European and regional (NW.
NRL 7333 Rb = 1-  1+  1+  2 Non- Linear b1- b2q3 influences We developed improved SeaWIFS coastal ocean color algorithms to derived inherent optical.
“Regional” adjustments of SAA parameterization Mark Dowell & Timothy Moore EC-JRCNURC & UNH.
International Ocean Color Science Meeting, Darmstadt, Germany, May 6-8, 2013 III. MODIS-Aqua normalized water leaving radiance nLw III.1. R2010 vs. R2012.
Assessment on Phytoplankton Quantity in Coastal Area by Using Remote Sensing Data RI Songgun Marine Environment Monitoring and Forecasting Division State.
Date of download: 6/17/2016 Copyright © 2016 SPIE. All rights reserved. Location of the study area within the Bay of Biscay and oceanographic sampling.
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.
Remote Sensing of the Ocean and Coastal Waters
Study area & research’s purposes
Satellite-derived data for the Water Framework Directive (WFD) of the European Union Abstract : The application of the Water Framework Directive (WFD)
Fig. 1. Location of the study site (23-28 S, W)
Wei Yang Center for Environmental Remote Sensing
Assessment of Satellite Ocean Color Products of the Coast of Martha’s Vineyard using AERONET-Ocean Color Measurements Hui Feng1, Heidi Sosik2 , and Tim.
Presentation transcript:

Participants: CNR-ISAC Ifremer JRC-EC European COastal-shelf sea OPerational Observing and forecasting system Integrated Project WP3: “Better use of remote sensing and in situ observing systems for coastal/regional seas: Task 3.2: “Improved ocean colour algorithms and products for Case-II waters” Bay of Biscay Adriatic Sea

Validation of ocean products Ocean Colour products in the Bay of Biscay ECOOP WP3.2.1 In its use of Ocean Colour products, Ifremer has particularly developed the service to users, as encouraged by MarCoast (GMES Service Element funded by ESA) Therefore : -2 parameters are targeted for validation and assimilation in biological model : Chlorophyll and mineral SPM (for deriving K PAR ) - 3 parameters : SST, Chlorophyll and turbidity, are proposed for the operational monitoring required by the Water Framework Directive

Mean Chlorophyll-a MODIS weeks 17&18 Mean Mineral SPM MODIS weeks 17&18 Examples of products and the covered area

Validation at coastal station involved in coastal monitoring networks * * * * National in situ networks REPHY: phytoplankton & hydrology / Ifremer SOMLIT: hydrology / CNRS-INSU Some stations are shifted for the matchups

Validation of the chlorophyll concentration : The 15-day climatologies SeaWiFS ( ) + MODIS ( ) : the SRN Boulogne transect P1 (Coastal) P2 P3

Percentile 90% Cabourg Bell curve types for the chlorophyll seasonal cycle Mean Cabourg (nutrients from the Seine river) Mean Ouest Loscolo (nutrients from the Loire river) Percentile 90% Ouest Loscolo The validation of the satellite chlorophyll is not limited to the mean of the distribution but also to the variance. P90 is the parameter of interest for the WFD (eutrophic risk)

Percentile 90% Men er Roue Spring and autumn peaks for the chlorophyll seasonal cycle Mean Men er Roue Mean Men Du Percentile 90% Men Du

Same systematic validations for Turbidity (NTU) Cancale Ouest Loscolo Men er Roue Boyard Here the shift of 3 pixels has a strong effect on satellite turbidity (lower)

ECOOP – Adriatic Sea NB: Full reprocessing of the SeaWiFS European and global archive completed (Nov. 2007) The Adriatic Sea includes diverse water types, eutrophic to oligotrophic, for which the OC products are still affected by significant uncertainties. It is also covered by a wealth of field observations and is thus an ideal test bed for advanced remote sensing methods. The first year focused on validation of OC products.

A unique site and data set for validation of OC products Mélin & Zibordi, GRL, 2005 Mélin et al., JGR, 2006 Mélin et al., RSE, 2007a Clerici & Mélin, submit. Zibordi et al., IJRS, 2004, IEEE 2004, 2006, GRL, 2006, EOS 2006 Mélin & Zibordi, Appl. Opt., 2007 AAOT Acqua Alta Oceanographic Tower - aerosol optical thickness τ a (AERONET site; Jul – present) - normalized water-leaving radiances L WN : in-water optical profiles (regular campaigns since 1995) autonomous above-water radiometry (May 2002 – present) - concentrations of optically significant constituents: Chla, TSM (regular campaigns since 1995) - inherent optical properties (IOPs): phytoplankton, CDOM, detritus absorption, particulate back-scattering (regular campaigns since 1995) Mélin et al., RSE, 2005, 2007b

Validation of SeaWiFS Radiometric Products Zibordi et al., GRL, 2006, EOS 2006 Mélin & Zibordi, Appl. Opt., 2007 Mélin et al., submit. SeaWiFS SeaPRISM Similar analyses have been conducted for MODIS and MERIS. SeaPRISM

Validation of Inherent Optical Properties Mélin et al., RSE, 2005, 2007b Phytoplankton absorption a ph (λ) Absorption by CDOM and NPP a dg (λ) Particulate back-scattering b bp (λ) encouraging results SeaWiFS

Validation of OC Chlorophyll data Aims/activities: 1.Assessment of the SeaWiFS and MODIS OC chlorophyll products in the Adriatic Sea with particular attention to the coastal waters (case 2) 2.Test different bio-optical algorithms for Chla (global and Mediterranean) to select the most appropriate one. 3.Define a strategy to improve the Adriatic CNR_ISAC operational regional products in coastal waters to be implemented for ECOOP TOP phase OC data are produced in NRT by CNR-ISAC in the framework of the Adricosm Project for environmental assesment and data assimilation in models

Po river discharge Ancona-Pescara Modis Aqua 6 th july 2004 The Adriatic Ocean Color CAL/VAL DATA SETS Po river discharge heavily influences the Western Adriatic Current turbid waters Projects/cruiseStationsAreaPeriod ADRICOSM_ER1245Nord Adriatic Sea REQUISITE3528Nord and Middle ADR06 150January 2006 DART06a 159 Middle AdriaticMarch 2006 DART06b 57 Middle Adriatic August 2006 TOTAL5139 In situ data set: 3 oceanographic cruises Repeated stations acquired by regional environmental agencies. 634 SeaWiFS case 2 water matchups 340 case 2 water Modis matchups

MEDOC4 OC4v4 R2=0.52 RMS=0.49 BIAS=0.32 R2=0.52 RMS=0.52 BIAS=0.34 OC4v4 (MUMM) MEDOC4 (MUMM) R2=0.42 RMS=0.49 BIAS=0.27 R2=0.46 RMS=0.49 BIAS=0.30 CARDER CLARK R2=0.49 RMS=0.44 BIAS=0.09 R2=0.44 RMS=0.50 BIAS=0.30 JRC JRC (MUMM) R2=0.45 RMS=0.43 BIAS=0.09 R2=0.41 RMS=0.40 BIAS=0.02 Validation of SeaWiFS Chlorophyll products 1.a general overestimation of the satellite Chla in all algorithms also when the regional Adriatic algorithm (JRC) is used 2.No improvements with MUMM atmospheric correction 3.Better results using Carder Algorithm (low Bias; uniform distribution)

OC3 MEDOC3 R 2 =0.42 RMS=0.44 BIAS=0.12 R2=0.44 RMS=0.44 BIAS=0.17 OC3 (MUMM) MEDOC3 (MUMM) R2=0.35 RMS=0.42 BIAS=0.10 R2=0.39 RMS=0.42 BIAS=0.13 CARDER GSM01 R2=0.84 RMS=0.24 BIAS=-0.15 R2=0.59 RMS=0.31 BIAS=-0.08 Validation of MODIS Chlorophyll products 1.Chla overestimation using standard (OC3) and Med (MedOC3) algorithms 2.No improvements with MUMM atmospheric correction 3.Better results using Carder Algorithm (highest R2) but small bias

Conclusions An specific case 2 chla algorithm is required for the Adriatic Sea In meantime the Carder’s algorithm should be introduced in the CNR-ISAC Adriatic operational processing chain to estimate the chla in Case 2 while MEDOC3 should be maintained for case 1 We need to develop of a method that produces a single chlorophyll map of the Adriatic with a different chlorophyll algorithm for case 2 and case 1 waters without introducing artificial gradients.

D : Report on comparison between R/S and in-situ data (Adriatic Sea) D : Report on comparison between R/S and in-situ data (Bay of Biscay) D : Report on multi-sensor merging and dynamic bio-optical algorithm selection (Adriatic Sea) D : Report on the merging technique between OC R/S and in-situ data (Bay of Biscay) European COastal-shelf sea OPerational Observing and forecasting system Integrated Project Deliverables and First-Year Status completed