Introduction

Introduction 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 Shelves, Arctic, Baltic, Mediterranean, Iberian-Biscay-Ireland (IBI) and Black Seas) high quality ocean colour products OCTAC will focus on the global to regional European scales integrating the pre-existing pre-operational systems developed in the framework of European, ESA and National Projects into a component of MyOcean service OCTAC will generate products directly useful to intermediate users and downstream service providers; in addition, OCTAC will provide specific products to MyOcean MFCs (both global and regional)

Introduction The R&D activity within the OCTAC mainly focuses on the quality assessment of the OC core products, either through validation with field measurements or inter-comparison of satellite products associated with different space missions Data interpolation and merging constituted one of the main aims of the OCTAC R&D activity The development of accurate and reliable monitoring systems was also part of the OCTAC R&D scope, as described in detail into the scientific calibration plan document

Introduction The main scientific challenges are to establish reliable error bars for each of the core products, to improve the quality of ocean colour products for the European Seas and to develop specific OC products for data assimilation by ecosystem models All activities require tailored (for regional and global applications) methodologies. In fact, as a direct consequence of the complexity (from the OC perspective) of the regional waters, standard global ocean OC products have to be revised to meet the uncertainty requirements at regional scale The quality improvement of regional products requires tailored OC processing chains in addition to the standard OC processing system. The regional OC processing chains will use region-specific algorithms for satellite product retrieval and will generate products adapted to the specific requirements of the regional forecasting system Since also Cal/Val and intercalibration/bias correction have regional characteristics all the R&D activities are distributed among OC partners

Introduction Nevertheless, the Cal/Val activity is coordinated at OCTAC level to ensure the harmonization of the procedures and the comparison of the results among PU’s The main tasks of WP12 R&D are: Characterization of OC data uncertainties of the core* products at both global and regional scales …………………..…..involves all OC partners Improvement of global and regional products ...involves all OC partners Development of OC products for validation/assimilation into ecosystem models ………………………………...involves CNR, ACRI, PML, Ifremer Development of European products on the basis of regional characteristics ……………………………………under JRC responsibility *: Chlorophyll a and Remote Sensing Reflectance at all bands and for each satellite mission (see Scientific Calibration Plan: MYO-OCTAC-ScCP-1.0.doc)

Main R&D achievements during first year Within the first year of the project, WP12 R&D activity has focused on tasks 1 to 3 The main objective was to improve the quality of the V0 OC products and to define specific products for assimilation/validation into ecosystem models The R&D activity of the entire OCTAC was mainly devoted to V1 product set up, including improvements to existing V0 products, and to start the characterization of the error associated with core products A research work on specific products for assimilation/validation into ecosystem models was also carried out by all PU’s Finally, R&D activity aimed to develop new approaches (missing data reconstruction, merging techniques) to build L4 chlorophyll product

Data One of the main scope of the R&D activity was to validate existing products using in situ data from public access archives as well as from single institution databases As for the latter, data acquired from fixed and accurately chosen permanent stations (IBI area, North Adriatic, DYFAMED) or based on episodic cruises have been used In situ data

Data Satellite data Core stands for mandatory while BE stands for best effort A = ACRI C = CNR J = JRC P = PML After the OCTAC consultation meeting in Sophia-Antipolis on February 2010

Results – JRC for task 1 These results are consistent (actually slightly improved) with respect to the SeaWiFS results presented by Gregg and Casey (2004, RSE)

Results – JRC for task 1 SeaWiFS MODIS Aqua y: satellite data x: in situ data Absolute and Relative difference [%]

Results – JRC for task 1 Global distribution of the random uncertainty associated with log-transformed Chla from SeaWiFS and MODIS (from Mélin, 2010)

Results – ACRI for task 1 SeaWiFS only Aqua only MERIS only SeaWiFS + MERIS MERIS + Aqua SeaWiFS + Aqua SeaWiFS + Aqua + MERIS • Matchup for the GSM CHL merged product. • Insitu datasets used are: • NOMAD for the 1997-2003 time period (Werdell and Bailey, 2005) • SeaBASS for the 2003-2007 time period (Maritorena et al, 2010)

Results – ACRI for task 1 The centered variable (retrieval/error) shows a normal distribution for CHL Comparisons of the predicted and actual uncertainties using the NOMAD data set (CHL) If the predicted uncertainties are accurate, about 2/3 of the data points should be below the 1:1 line (Maritorena et al, 2010)

Results – Ifremer for task 2 The Ifremer’s R&D activity for MyOcean products focused on: the selection of reference stations along the shore for calibration of the L3 MERIS and MODIS products (chlorophyll and mineral SPM) the improvement of the cloud mask to obtain better merged L4 MODIS/MODIS Chlorophyll and mineral SPM maps the finalization of a publication describing in detail the method (geostatistics) used for the merging and the delivering of the L4 product

Results – Ifremer for task 2 The 28 in situ selected stations in the IBI domain with the limits of the coastal water bodies of the Water Framework Directive

Results – Ifremer for task 2 The validation of the MyOcean product is made by comparison of the satellite and in situ ANNUAL CYCLES at the 28 selected stations from 2003 to 2009 Filiere 10 1 0.1 Chla Pointe St. Gildos Large 5 10 15 20 25 Fortnight 10 1 0.1 Chla 5 10 15 20 25 Fortnight

Results – Ifremer for task 2 The validation of the MyOcean product is made by comparison of the satellite and in situ ANNUAL CYCLES at the 28 selected stations from 2003 to 2009 Men er Roue 10 1 0.1 Chla La Carrelere 5 10 15 20 25 Fortnight 10 1 0.1 Chla 5 10 15 20 25 Fortnight

Results – Ifremer for task 2 The comparison is also carried out on the MEAN and PERCENTILE 90 of the productive season (March to October) as the percentile 90 has been chosen as an indicator of the eutrophication risk for the Water Framework Directive 90th Percentile MEAN 20 15 10 5 0 10 8 6 4 2 0 MODIS MODIS 0 5 10 15 20 0 2 4 6 8 10 In situ In situ

Results – Ifremer for task 2 After calibration of MODIS (on the newly reprocessed NASA reflectance- May 2010) and MERIS (rolling archive) chl and SPM, the quality of the merged product has been improved 2010/08/10 merged L4 MODIS/MERIS chlorophyll for MyOcean

Results – PML for task 2 PML have implemented a new regional algorithm for Chlorophyll in the NWS area using MODIS data The chlorophyll algorithm chosen was OC5, an algorithm that outperforms NASA's OC3 in turbid waters while giving similar results to OC3 in case 1 waters The IDL code for this algorithm was adapted to the PML operational ocean colour processing system Software issues that became evident with the operational use of this algorithm were resolved and updates to the algorithm by the original writers were ported to the operational version Validation of the algorithm with in situ measurements is ongoing (PML is on stream 2)

Results – PML for task 2 Using visual inter-comparison of OC3 and OC5 it is obvious that estuarine and coastal waters with HIGH SEDIMENT show up as having HIGH Chla in OC3 and a more realistic LOWER Chla in OC5 imagery MERIS MODIS Standard Regional Standard Regional A comparison of various Chlorophyll algorithms on the NEODAAS FlexiView web site

Results – CNR for task 1 The validation activity of both MODIS and MERIS Chla products relies on the in situ dataset owned by CNR MERIS MODIS Spatial distribution of the in situ-satellite matchups There is an overall good correspondence between in situ and delayed-mode regional satellite products over the Mediterranean

Results – CNR for task 1 To highlight the possible disagreement between in situ and satellite derived values as a function of the season and hence of the trophic regime, sample measurements in correspondence of the four seasons are highlighted by different colours Slight overestimations of high Chla values (in winter in correspondence to the maximum Po river runoff) is likely due to the presence of Case 2 water in the Adriatic Sea Performance of the Mediterranean-specific Chla products

Results – CNR for task 1 RPD for the Rrs at 443 nm (the most sensitive band, that is used in Chla algorithms, to atmospheric correction It is clear that there is a slight satellite underestimation of the in situ values for MODIS. On the other hand, the most common outcome of the MERIS statistics is centred on the zero line

Results – CNR for task 1 Other than the off-line validation, CNR is implementing an on-line validation based on the time consistency of data

Results – CNR for task 3 One of the challenges of the OCTAC R&D activity is to provide MFCs with reliable satellite data covering the entire model domains CNR has developed ad hoc operational product for Chla and Kd with reduced spatial (from 1.1 km to 1/16°, ca. 6.5 km) and temporal (from daily to 5 days) resolution and matching the Mediterranean Forecasting System (MFS) model grid This product and the first validation of the Mediterranean ecosystem model result are presented in Lazzari et al. (2010, Ocean Science) The production of merged L4 products and in order to provide satellite images with no data voids an interpolation scheme based on EOF analysis has been adopted

Results – CNR for task 3 The reconstruction of missing data was performed iteratively following the Data INterpolating Empirical Orthogonal Functions (DINEOF) method developed by Beckers and Rixen (2003, J. Atmos. Oceanic Tech. ) with some caveat Conceptual scheme The time average of each marine is removed from valid observations EOF input Climatology Time series

Results – CNR for task 3 The reconstruction of missing data was performed iteratively following the Data INterpolating Empirical Orthogonal Functions (DINEOF) method developed by Beckers and Rixen (2003, J. Atmos. Oceanic Tech. ) with some caveat Conceptual scheme The time average of each marine is removed from valid observations Anomaly data are stored into a matrix X and missing data are then set to zero (which is the equivalent of using the climatology as first guess) EOF iterations were performed over matrix X until the variance explained by the ith mode was equal to the variance explained by the first mode of an EOF analysis performed over a random-filled matrix of the same dimensions as X, i.e. noise The interpolated dataset was obtained by reconstructing the time series using this truncated set of modes (20 iterations).

Results – CNR for task 3 Average number (%) of missing pixels in the SeaWiFS 1/16° spatial resolution time series Which actually prompts for the need of an interpolation scheme …

Results – CNR for task 3 Matchup between in situ Chl & DINEOF input DINEOF output + + 1km daily SeaWiFS data DINEOF does NOT introduce any significant source of error, with the advantage of filling in data voids

Conclusions Apart from task 3, there still remain issues about all of the four tasks Characterization of OC data uncertainties of the core* products at both global and regional scales …………………..…..involves all OC partners Improvement of global and regional products ...involves all OC partners Development of OC products for validation/assimilation into ecosystem models ………………………………...involves CNR, ACRI, PML, Ifremer Development of European products on the basis of regional characteristics ……………………………………under JRC responsibility

Conclusions • For task 1 • the characterization of all core products uncertainties is planned for the next project phase according to the specification of the scientific calibration plan document • This activity will still focus on the assessment of the reprocessed SeaWiFS and MODIS series • Upcoming results shall include refined assessments of the uncertainties associated with nRrs and inherent optical properties in European seas • PML is developing a system to compare the new OC5 data and model output for the NWS (the system provides a quick visual comparison and some statistical analyses of the overall image/model)

Conclusions • For task 2 • As many data of the water clarity are obtained from turbidity measurements from the coastal in situ network, a new product of turbidity from satellite is tested • For consistency with the actual products delivered by the MyOcean OCTAC for the IBI-ROOS region, this turbidity product is determined from Chl and mineral SPM • CNR effort in the improvement of Chla products from MERIS, MODIS and SeaWiFS over the Mediterranean Sea will continue for the next project phase to ensure high quality products with the latest software version as well

Conclusions • For task 4 • Is the only task which no R&D activity has been undertaken yet • Its general purpose is to provide a unique product for the pan-European domain taking into account the peculiarities of each region • The effort will certainly focus on Chla product, and a complete list of the products that will be included is yet to be confirmed and under evaluation

Introduction

Introduction

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Introduction to introduction to introduction to … Optimization

INTRODUCTION/ INTRODUCTION

Introduction

INTRODUCTION

Introduction

Introduction