Euro-Argo Improvements for the GMES Marine Service · 2nd E-AIMS periodic report 1 . E-AIMS....

2nd E-AIMS periodic report

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E-AIMS

Euro-Argo Improvements for the GMES Marine Service

2ND PERIODIC REPORT

2014

Grant Agreement number: 312642

Project acronym: E-AIMS

Project title: Euro-Argo Improvements for the GMES Marine Service

Funding Scheme: FP7/CP/FP

Date of latest version of Annex I against which the assessment will be made: 13/12/2012

Periodic report: 1st □ 2nd 3rd □ 4th □

Period covered: from 01/01/2014 to 31/12/2014

Name, title and organisation of the scientific representative of the project's coordinator:

Dr. Pierre-Yves Le Traon

INSTITUT FRANCAIS DE RECHERCHE POUR L'EXPLOITATION DE LA MER

Tel: +33 5 61393875

Fax: +33 5 61393899

E-mail: [email protected]

Project website address: http://www.euro-argo.eu/EU-Projects-Contribution/E-AIMS

mailto:[email protected]

http://www.euro-argo.eu/EU-Projects-Contribution/E-AIMS


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Declaration by the scientific representative of the project coordinator

I, as scientific representative of the coordinator of this project and in line with the obligations as stated in Article II.2.3 of the Grant Agreement declare that:

The attached periodic report represents an accurate description of the work carried out in this

project for this reporting period; The project (tick as appropriate) 1:

□ has fully achieved its objectives and technical goals for the period.

X has achieved most of its objectives and technical goals for the period with relatively

minor deviations.

□ has failed to achieve critical objectives and/or is not at all on schedule. The public website, if applicable

X is up to date

□ is not up to date To my best knowledge, the financial statements which are being submitted as part of this report

are in line with the actual work carried out and are consistent with the report on the resources used for the project (section 4) and if applicable with the certificate on financial statement.

All beneficiaries, in particular non-profit public bodies, secondary and higher education

establishments, research organisations and SMEs, have declared to have verified their legal status. Any changes have been reported under section 3.2.3 (Project Management) in accordance with Article II.3.f of the Grant Agreement.

Name of scientific representative of the Coordinator: Mr. Pierre-Yves Le Traon INSTITUT FRANCAIS DE RECHERCHE POUR L'EXPLOITATION DE LA MER

Date: 17/01/2015

1 If either of these boxes below is ticked, the report should reflect these and any remedial actions taken.


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Publishable summary Project context and objectives

In November 2007, the international Argo programme reached its initial target of 3,000 profiling floats. These floats measure temperature and salinity throughout the deep global oceans, down to 2,000 metres and deliver data both in real time for operational users and after careful scientific quality control for climate change research and monitoring. Argo is the first-ever global, in-situ ocean-observing network in the history of oceanography, providing an essential complement to satellite systems. Argo delivers critical data (especially over the vertical dimension of the oceans) for assimilation in ocean forecasting models, climate monitoring and seasonal to decadal forecasting. Techniques are mature and fully demonstrated. Float technology will also evolve in the coming years to include new sensors (e.g. oxygen, biology) and new capabilities (e.g. under ice measurements) that are essential for climate change research and for the GMES/Copernicus Marine Service.

The Euro-Argo research infrastructure organizes and federates European contribution to Argo (www.euro-argo.eu); it is part of the European ESFRI roadmap on large research infrastructures. Euro-Argo carried out a preparatory phase project, funded through the EU 7th Framework Research Programme, whose main outcome was to agree on the legal and governance framework (Euro-Argo ERIC) under which to establish the research infrastructure. The Euro-Argo ERIC will be set up in early 2014; it will allow European countries to consolidate and improve their contribution to Argo international.

The main challenges for Argo and Euro-Argo are 1/ to maintain the global array and ensure its long term sustainability and 2/ prepare the next phase of Argo with an extension towards biogeochemistry, the polar oceans, the marginal seas and the deep ocean. Meeting such challenges is essential for the long term sustainability and evolution of the GMES/Copernicus Marine Service. This requires major improvements in Argo float technology. New floats with improved capabilities are or will be soon available from float manufacturers. They require, however, extensive testing at sea before they can be used for operational monitoring. The Euro- Argo data centers need also to be upgraded so that they can handle these new floats.

E-AIMS will organize an end-to-end evaluation of new Argo floats (from float design down to the use by GMES/Copernicus). Observing System Evaluations and Sensitivity Experiments will also be conducted to provide robust recommendations for the next phase of Argo that take into account GMES/Copernicus Marine Service, seasonal/decadal climate forecasting and satellite validation requirements. E-AIMS will thus demonstrate the capability of the Euro-Argo infrastructure to conduct R&D driven by GMES/Copernicus needs and demonstrate that procurement, deployment and processing of floats for GMES/Copernicus can be organized at European level. These are key aspects for the long term sustainability of GMES/Copernicus in-situ component. At the end of E- AIMS, Euro-Argo should agree on and start implementing the new phase of Argo. This requires demonstrating feasibility and utility which is the very objective of E-AIMS.


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Description of the work performed for year 2

The project is organized along the following workpackages (all WPs were active for year 2): • WP1: Management/Coordination (Ifremer) (T0-T0+36) • WP2: R&D on float technology (Ifremer) (T0-T0+30) • WP3: Initial requirements, synthesis of past OSE/OSSEs and impact studies, design and

start of OSE/OSSEs (Mercator Ocean) (T0-T0+24) • WP4 :Impact of Argo observations for the validation of satellite observations and for joint in-

situ/satellite analyses (CSIC) (T0-T0+24) • WP5: R&D on Euro-Argo data system and interfaces with GMES Marine Service (T0-

T0+18) (Ifremer) • WP6: Real time processing, assessment and impact (T0+18-T0+33) (OGS) • WP7: Scientific and technical coordination (Ifremer) (T0-T0+36) • WP8: Communication and dissemination (Ifremer) (T0-T0+36)

The project started on January 1st 2013. The kick off meeting was organized in Brest from January 16 to January 17. A steering committee was organized in June 2013 in Southampton. A specific WP3 workshop was organized in September 2013 in Toulouse. The first annual meeting, first annual review and 2nd steering committee were organized in Brussels in January 2014. The 3rd

steering committee meeting was held in Brest in June 2014. The WP3&WP4 final workshop was finally organized in Toulouse together with a GODAE OceanView/CLIVAR international scientific workshop in December 2014. All meeting minutes and presentations are available on the E-AIMS internal WWW site.

In 2014 work has been performed according to plans and all planned deliverables were issued. Management, scientific coordination and communication activities (WP1, 7 & 8) included preparation and running of annual meeting, annual review and steering committee meetings including writing meeting minutes, annual report preparation, interaction with REA, interaction with the Euro-Argo ERIC organization, interaction with MyOcean project, discussing with stakeholders (GMES/Copernicus bureau, EEA, DG Research, EuroGOOS) and development and maintenance of the E-AIMS WWW site (internal and external). These activities have been carried out in close cooperation with the Euro-Argo ERIC management board and program manager. Communication activities have included the preparation of leaflets on each of WP2 Tasks as well as a summary of main WP3/WP4 results. All these leaflets are available on the external E-AIMS WWW site. Short float stories will also be integrated in the Euro-Argo educational WWW site in January 2015. A project brochure was also prepared and completed in November 2014. It provides a description of the project and its workpackages with illustrations based on results and activities carried out during the first half of the project.

The objective of WP2 is to test several new Argo floats which have been recently developed, and are becoming available from float manufacturers in Europe. E-AIMS WP2 will organize an end-to- end test of these new floats: specifying float characteristics, carrying out complementary float design or sensor adaptation activities, ordering and testing them before deployment, agreeing on at sea testing procedure, deploying them, and quality control and data analysis. The main objectives for 2014 was to deploy floats that could not have been deployed in 2013 and to continue analyzing data including sensor issues as well as interacting with float manufacturers. These objectives have been almost met (two floats still remain to be deployed in 2015).


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WP3 & WP4 were completed end of December 2014. All deliverables have been submitted except the deliverable on final recommendations that will be provided after the second annual meeting (February 2015). OSE/OSSEs were conducted as initially planned and results are described in the following sections. The final WP3/WP4 workshop was held in Toulouse in December 2014 and future requirements for Argo and Euro-Argo have been discussed with the GODAE OceanView OSEVal and CLIVAR GSOP communities.

The objective of WP5 was to undertake the R&D activities necessary to improve the Euro-Argo data system to better serve the Copernicus Marine Service and adapt it to the future generation of Argo profiling floats (biogeochemical, deep, high vertical sampling). Quality control methods for oxygen and biogeochemical parameters have been integrated in the operational Argo data processing centers. The Argo data processing centers were also adapted so that they are now able to process data from the new floats. WP5 was completed in September 2014 and it is now possible to ingest E-AIMS floats in the operational Argo data management system. The operational data processing of E-AIMS float data is now carried out as part of WP6 which started in September 2014 at the end of WP5. WP6 will include in 2015 an analysis of the use of E-AIMS float data for the Copernicus Marine Service and satellite Cal/Val activities.

Expected final results and their potential impact and use

The EEA GISC project and several international and European panels (e.g. the Global Ocean Observation System, GEOSS, the World Climate Research Programme, the Global Ocean Data Assimilation Experiment, EMODNET, EUROGOOS, Marine Board) have identified Argo as one of the highest priority in-situ observing system for the global ocean and GMES/Copernicus Marine Service. Our work plan is structured along several of the priorities identified by the GISC project as bridging the gap between research projects and operational GMES services and facilitating access to in-situ data in an integrated manner. It responds to the R&D priorities identified in the GISC report, i.e. development of new observation techniques, improvement in the infrastructure and data availability, quality and timeliness of in-situ data, calculation of uncertainties, simulation experiments to optimize network design. Suck in-situ R&D tasks are required so that benefits of the EU investments in the GMES/Copernicus Satellite and Marine Service components can be realized.

Enhanced GMES/Copernicus Marine Service and better use of satellite observations

E-AIMS will develop, deploy and evaluate floats which are required for the evolution and future goals of GMES/Copernicus, including new ocean variables, as well as increased accuracy, reliability and cost-effectiveness. The main impact of the E-AIMS work will thus be on the development of enhanced GMES/Copernicus Marine Service, and hence on better products, information and services available for the downstream activities, including scientific use of its data sets. The involvement of the MyOcean and MyOcean2 global and regional monitoring and forecasting centres will ensure a full integration of the project R&D results into the operational systems. The real-time assessment planned in WP6 (from Month 18) will include a full-scale, end- to-end evaluation of this capability. The development of the use of Argo floats to calibrate/validate and complement satellite observations (sea-level, sea-surface temperature, salinity, ocean colour)


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will also allow us to improve the accuracy of satellite measurements, to quantify their uncertainties and to make a better use of satellite observations.

Instrumentation and SMEs

The R&D and tests on Argo floats (the diversity of sensors to be adapted to the instruments, the new communication capability, and the performance in deep and ice-covered seas) will also have a positive impact on the research and development and commercial activities of the European companies manufacturing the instruments (the SMEs NKE in France and Optimare in Germany).

Socio-economic impacts

E-AIMS has been elaborated to fulfil the requirements and priorities of monitoring programmes designed to support decision making in several key societal benefit areas (as identified, e.g. by GEOSS). Given the prominent role of Argo for climate change research, its contribution to, and impact for seasonal and decadal climate forecasting, socio-economic impacts of the E-AIMS activities are expected to be large on the longer run. Socio-economic impacts from Argo also include those to be handled through the GMES Marine Service (e.g. maritime transport, marine safety, fishery management, oil pollution monitoring and forecasting, offshore industry). Investing in such global ocean observations has thus potentially a high benefits /costs ratio.

Project public website

Public website address: https://www.euro-argo.eu/EU-Projects-Contribution/E-AIMS

Attached documents: In line with this, diagrams or photographs illustrating and promoting the work of the project, as well as relevant contact details or list of partners can be provided without restriction.

https://www.euro-argo.eu/EU-Projects-Contribution/E-AIMS


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Core of the report for the period: Project objectives, work progress and achievements, project management PDF

WP1 - Management/coordination

(Work package leader: Partner n°1, Ifremer, France)

Activities are reported at the end of this section.

WP2 R&D on float technology

(WP leader: partner 1, Ifremer, France)

Work package objectives for the period

The objective of WP2 is to test several new Argo floats which have been recently developed and are becoming available from float manufacturers in Europe. E-AIMS WP2 have to organize an end- to-end test of these new floats: specifying float characteristics, carrying out complementary float design or sensor adaptation activities, ordering and testing them before deployment, agreeing on at sea testing procedure, deploying them, and quality control and data analysis.

In 2014 the main objectives were to procure and deploy at sea the last floats that were not procured and/or deployed in 2013 and to analyze first data of WP2 floats.

WP2 is structured with five tasks dedicated to test different type of new floats. A 6th one will synthesise the work at the end of the project. 1) The first task deals with the testing of a new oxygen sensor by comparing it with the sensor which has been already used on floats for several years. Navis and Arvor floats are used. Among 5 floats that were planned to be deployed, three are now cycling at sea. 2) The second task deals with the testing of deep floats. Two deep-Arvor floats with 4000m depth capability were procured with E-AIMS funding and two additional floats were procured and deployed by Ifremer. 3) The objective of the third task is to test floats equipped with bio-geochemical sensors. 6 Provor floats have been deployed in 3 different areas, and five of them are still working. 4) The aim of task 4 is to test 4 floats equipped with new satellite data transmission capabilities (Iridium and Argos3) to allow transmitting high resolution profile data and receiving remote commands thanks to the downlink. Navis and Arvor floats were procured and tested at sea. Taking into account additional Apex floats procured by UKMO, five floats are now cycling. 5) Task 5 will test floats equipped with surface ice detection capabilities in order to operate in Arctic area by postponing data transmission in case of ice detection. Two Nemo floats have been deployed and one is still functioning.


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Task 2.1: Test of new oxygen sensors (Task leader: GEOMAR)

The purpose of this task is to compare the Seabird oxygen sensor SBE63 to the 4330 Aanderaa optode. Geomar uses the Navis float while Ifremer uses the Arvor. The 2 floats embark the two oxygen sensors. The optodes has been individually multipoint calibrated at factory.

GEOMAR laboratory tests

Detailed laboratory studies have been completed in year 1. The temperature- and flow-dependent time response of both Aanderaa optodes and Sea-Bird optodes (based on previous laboratory and field experiments) has been published (Bittig et al., Limnol. & Oceanogr. Methods, 2014) and allows optode users to predict and possibly correct the impact of the time response for use various platforms including floats. As shown in the previous report, there is a marked difference between the pumped Sea-Bird SBE63 optode and the unpumped Aanderaa 4330 optode and pumping in general is an effective measure to reduce the sensors’ response times.

GEOMAR field study

The GEOMAR dual oxygen sensor field study comprises three Navis floats (F0271, F0272, F0273) all of which feature an Aanderaa 4330 and Sea-Bird SBE-63 optode.

Float F0272 (WMO ID 6900890) was successfully deployed during the field trip on the Senegalese M/V Samba Laobe Fall in Sept. 2013 and since then has been active for 442 days. It has performed a total of 92 profiles (as of Dec. 17, 2015) of which Iridium transmission was incomplete on 3 and failed completely on 1 profile. The float stayed relatively close to its deployment location in Senegalese/Cape Verdean/Mauritanian waters. In fact, it returned to within 8 km of its deployment location after approx. 11 months (see figure 2.1.1).

Fig. 2.1.1: Trajectories of Navis floats F0272 (WMO ID 6900890) and F0271 (WMO ID 6900889) in the Eastern Tropical North Atlantic. The color indicates the day of the year (doy).

Float F0271 could not be deployed in Sept. 2013 because of a potential failure observed in the pre- deployment tests. After some delay due to logistical reasons, this float was returned to the manufacturer Sea-Bird and repaired at no charge. It was redeployed (WMO ID 6900889) on Nov.


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07, 2014 during R/V Polarstern cruise ANT-XXX/1.2 into the core of the oxygen minimum zone (OMZ) along 23°W. A CTD cast performed from Polarstern provided a high-quality reference profile to a depth of 1400 m with a well-calibrated (Winkler-based) SBE-43 oxygen sensor.

There have been serious logistical issues with returning the deployed and recovered float F0273 to the manufacturer for repair because of the unknown state of its lithium batteries. This made air transportation of the float impossible. As a remedy, Sea-Bird offered to provide a replacement float at no extra cost if we could remove the two oxygen sensors from the malfunctioning float and return them to Sea-Bird. Both optodes were dismounted from float F0273 in Dakar and returned to Kiel in Dec. 2014. They will undergo a new, high-quality laboratory calibration in Kiel (Jan./Feb. 2015) to assess the level of optode drift and will be forwarded to Sea-Bird in order to be assembled into the new replacement NAVIS float. Deployment of this remaining third float is planned for Oct. 2015 in the Eastern Tropical Pacific OMZ. There, oxygen concentrations reach anoxic levels which provide us with a unique opportunity to assess the sensor over the entire oxygen range and in-situ correct them at zero oxygen level.

Result of the GEOMAR field study

A full seasonal cycle was observed by float F0272 in the Eastern Tropical North Atlantic (see figure 2.1.2). Surface temperatures are highest in autumn and lowest in spring while surface salinity variability has a more episodic nature. Consequently, oxygen concentrations are high in spring and low in autumn due to the temperature dependence of solubility. Because of the proximity to a highly productive coastal upwelling region, surface waters are supersaturated with oxygen year-round.

As far as we can tell, F0272 has not been caught in a mesoscale eddy for prolonged periods. The sub-surface oxygen concentration (ca. 50 m depth) is in general in a typical range for the OMZ and did not show signs of enhanced respiration in an isolated eddy water body (see Karstensen et al., 2014). However, since the float is still in the generation region of such cyclonic and anticyclonic eddies, it may well get caught into such a mesoscale feature during its remaining lifetime.

The near-surface and in-air measurement sequence of the Aanderaa 4330 optode (described in a previous report) has now proved to be a robust and reliable way to in-situ reference and correct oxygen data during the course of a deployment. A bias exists in the in-air measurements which is due to a carry-over effect from the water phase depending on the surface water disequilibrium. However, this effect is very systematic and therefore can be corrected for, such that near-surface and in-air measurements provide an easily-implemented and a strongly-needed means of in-situ referencing of optodes which allows assessing their accuracy and correcting for any detected offsets. The Aanderaa 4330 optode on F0272 did not show a significant trend/drift during its first year of deployment. This work has been summarized in a manuscript that is currently under review (Bittig and Körtzinger, 2014).

If further corroborated by other field studies this in-air referencing technique would provide an unique opportunity to in-situ correct optodes for any sensor drift and thereby provide highest long- term accuracy of near-surface measurements. This would make well-constrained oxygen-based estimates of biological net productivity possible – a feature that would be of extreme importance and hence relevance for an operational oxygen component in Argo. On the other hand this would also have direct consequences for the operation mode of optodes on Argo floats (i.e., pumped vs. non-pumped operation).


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Fig. 2.1.2: Profile data of Float F0272 (WMO ID 6900890) in the upper 120 m: Temperature, salinity, oxygen concentration, and oxygen saturation (both panels show the Aanderaa 4330

optode data).

IFREMER field study

Two Arvor floats with dual O2 sensors (ARVOR-2DO) were tested at Ifremer pool in May 2014. Results show that, in the pool, measurements made by the Aanderaa 4330 optode were noisier than those made by the SBE63 optode. Tests show that the difference between the two sensors is about 1 µmol/L for ARVOR-2DO #1 and about 5 µmol/L for the ARVOR-2DO #1 (figure 2.1.3).

Figure 2.1.3: Comparison between the Aanderaa optode (red curves) and the SBE63 optode (blue curves) for Arvor-2DO 1 (left panel) and Arvor-2DO 2 (right panel) during tests in Ifremer pool.


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Figure 2.1.4: Comparison between the first descending profile collected by the SBE63 optode (blue curve), the first ascending profile collected by the Aanderaa optode (dashed red curves) and of a

reference profile acquired at float deployment (and not yet calibrated).

The two floats were then boarded on R/V “Pourquoi pas” for the Geovide cruise. The ARVOR-2DO #1 was deployed on June 10th. Unfortunately, the SBE63 measurements stopped at ~500m depth during the first descent. We decided to not deploy the second float to understand the cause of this early failure.

Results of this deployment reveal, however, the good consistency between the two sensors, as seen during the tests in Ifremer pool. They suggest that data are shifted toward lower DO data, compared to the reference profile, despite the multipoint calibration. The float is still active and continues sending oxygen data but from the Aanderaa optode only.

During Summer, several contacts were made to find out a solution for recovering the float. Only one potential solution was found: it was a help proposition from Bill Johns, from University of Miami who had a cruise in this area. Unfortunately, the float drifted southward, too far away from the trackline of his ship.

Elsewhere, remote commands were sent to the float, to try to get the sensor back "alive": we ordered to the float to do measurements during at descent or not, to switch on and off the SBE63 sensor, or the 4330 sensor, or the two ones. Nothing changed and the SBE63 remained silent.

The 2nd float was returned back to Ifremer (Brest) after the cruise at the end of August. Intense testing was then performed to this second float (ARVOR-2DO #2) to identify possible failure in the SBE63 sensor. 1) The firmware of the float was intensively tested on the environmental test bench during several weeks, to detect any software bug, but nothing was detected. 2) The manufacturer of the sensor was contacted for further information about the way the sensor is tested before shipping. According to them, the sensor head (oxygen + temperature + conductivity) is tested at high pressure after being built up. 3) Additional tests were done using Ifremer facilities. A realistic mission was realized at 200 bars in a pressure tank. Then, two missions were done in a 20 meter depth pool (11 cycles done). Again, nothing was detected.


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Based on those results, no malfunctioning was thus detected. We concluded that the source of the first float malfunction is most likely the failure of the SBE63 sensor. Thus we consider that the second prototype is ready for deployment. We found an opportunity to deploy the float in December 2014 but we declined this opportunity leading to a delay in this task. Indeed, this task has three objectives: (1) compare the behavior of the two sensors, (2) evaluate each of them with in mind the implementation of an Argo-O2 array, (3) define the best method to correct sensor bias or drift. A reference calibrated profile acquired at float deployment is mandatory to achieve the last two objectives. The December cruise offered no possibility to acquire such calibrated reference profile, while this is possible from a cruise planned for June 2015 on board R/V Thalassa. We therefore chose to deploy the float in June 2015, which will allow us to achieve all of our objectives but will induce a delay in the completion of this task.

References:

• Bittig, H.C., B. Fiedler, R. Scholz, G. Krahmann, and A. Körtzinger (2014). Time response of oxygen optodes on profiling platforms: Dependence on flow speed and temperature and recommendations for field applications. Limnol. Oceanogr.: Methods 12, 617-636, doi: 10.4319/lom.2014.12.617.

• Bittig, H.C. and A. Körtzinger (2014). Tackling oxygen optode drift: Near-surface and in-air

oxygen optode measurements on a float provide an accurate in-situ reference. J. Atm. Ocean. Techn., re-submitted.


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Task 2.2 Test of new deep floats (Task leader: IEO)

The IEO is leading task 2.2 test of new deep float, and during the first year, it has revised the designed tests to be done once the first deep Argo are deployed. The tests are focused on pursuing the objective of maximizing the amount and frequency of deep ocean data, but keeping it cost-effective, in the sense that the deep Argo floats should have a lifetime (three years) close to the upper ocean Argo floats. The initial implementation plan for the upper ocean (<2000m) Argo array was designated based upon the experience of the some other observational program covering the upper ocean. However the case for the deep ocean is by far very different, since there are fewer deep ocean observations. As planned, the design has been included in the deliverable D2.221 Deep float experiment design. During this period the members of task 2.2 have been in contact with the engineers that designed the deep Argo float, as well as the company that commerciality it to set up the initial configuration of the float. The deployment of the first float has been postponed to February 2015 and to July 2015 for the second float. As indicated in the Deep float experiment design (D2.221), the two floats will be deployed in the Canary Basin, at around 29ºN, 18ºW. To maximize the amount of data but keeping the floats cost-effective three sea-experiments has been designed. In the first one, to be carried out during the first three months, the floats will be parked at 1500dbar, profiling to 4000 dbar every ten days, in the same way the upper ocean Argo floats sample. This experiment will permit to assests the local variability of the deep ocean in the Canary basin, and estimate the power consumption of the prototype. In the second one, and after the initial three months, the floats will be parked at 1500dbar, profiling to 2000 dbar every ten days, and to 4000 dbar every five profiles (once a month). This experiment will permit to assests the local variability of the deep ocean in the Canary basin, and estimate the power consumption of the prototype in low power-consumption scenario that should be closer to the one for the upper ocean argo floats. In the third one, and after the initial six months, the floats will be parked at 1500dbar profiling to 2000 dbar every ten days, and to 4000 dbar every five profiles (once a month). The vertical sampling scheme will be modified from the one used in the second experiment to adapt it to the results of the first test to minimize the power consumption of the prototype.

Significant results: Design the test to be done once the deep Argo floats are deployed

Deviations from Annex I and their impact on other tasks as well as on available resources and planning In the DoW it was planned that the first deep Argo floats would be tested during October 2013, however the company commercializing the Ifremer design’s of Deep Argo had some delay in the production of the float due to problems in the coupling with the pump engine system. The deep Argo floats are second-generation prototypes and therefore it is unavoidable to find some problems during its production. The float was ready in September 2014, however, the new rules imposed in the Spanish Institute of Oceanography as consequence of the control of the national budgets has resulted in long delays in the processing of tenders and purchased orders. Once it was notified by the manufactures that the float was ready, it took several months to send them the purchase order, and the float was not purchased until December 29th. For the second float the purchase order is still processing.


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The deployment of the first float has been postponed to February 2015 and to July 2015 for the second float.

Statement on the use of resources:

0.25 man month for the design 1 travel to annual meeting There is not deviation between actual and planned person-months per work


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Task 2.3: Test of new biogeochemical floats (Task leader:IMR)

Six new biogeochemical floats were bought in 2013 from the French company NKE. These floats (PROVOR BIO-Argo CTS4) are equipped with several types of biogeochemical sensors, and all six floats had similar sensors. Beside the CTD, the floats were equipped with dissolved oxygen sensor, irradiance sensor (PAR+3 wavelengths), and chlorophyll-a and backscattering sensors.

To test and evaluate their performance and their potential for the Copernicus/GMES Marine Service the Bio-Argo floats were deployed in three different oceanic regions (figure 2.3.1) that are characterized by contrasting oceanic and ecosystem conditions. The three different regions are the North-Atlantic sub-tropical gyre (PML - UKMO), the Nordic Seas (IMR), and the Black Sea (IO-BAS - USOF).

Figure 2.3.1: Schematic view of the deployment of the six biogeochemical floats.

North-Atlantic sub-tropical gyre (PML-UKMO)

Two NKE Provor CST4 floats (metbio001b and metbio002b) were deployed by PML-UKMO during E-AIMS. In addition to the standard CTD, each float mounted the following set of biogeochemical sensors:

1) Aanderaa oxygen optode 4330 2) Satlantic Rem-A sensor including a WETLabs ECO-Triplet (with three channels to measure

chlorophyll-a fluorescence, and optical backscattering at 532 and 700 nm) and a Satlantic OCR540 (with four channels measuring downward irradiance at 380, 412, 490 nm and a channel for photosynthetically available radiation, PAR).

Both floats were deployed during the 23rd Atlantic Meridional Transect on October 13th, 2013 around 30.37ºN and 23.16ºW.


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Metbio001

This float was initially programmed to collect data over the top 1000 m. Although the physical and biogeochemical data transmitted appeared to be of good quality (figure 2.3.2), the float had problems with acquiring GPS location. From the 5th cycle, the float was set to collect data down to 2000 m. However, after descending to 2000 m, the ECO-Triplet data showed clear signs of instrument/float malfunctioning: step changes in the profiles of chlorophyll-a and backscattering appeared around 450-500 m (figure 2.3.3). As of now the causes of this problem have not been identified and, upon request, WETLabs was not able to provide the data collected during the pressure test of the instruments.

Figure 2.3.2: WETLabs ECO- Triplet data from cycle 4 (max

depth 1000 m).

Figure 2.3.3: WETLabs ECO- Triplet data from cycle 5 (max

depth 2000 m).

The problem with the ECO-Triplet has persisted since cycle 5, even though the maximum depth was re-set to 1000 m after cycle 58 (27th Feb 2014).

Data were also collected at the parking depth to monitor instrumental drift, based on the assumption that the concentration of particles in deep waters does not vary significantly over time. Figure 2.3.4 shows that two opposite trends are observed in the 532 and 700-nm optical backscattering channels.

The parking values from the green channel (532) decreased from May to September 2014 by about 30 counts. This decline is unlikely caused by bio-fouling, which instead would cause an increase in the signal. Therefore we speculate that the green channel might have drifted due to instrument degradation. Interestingly, the decline begins 2.5 months after the maximum depth of the cycle was re-set to 1000 m, therefore it is difficult to link this decline to exposure to high pressure conditions.


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The red channel (700 nm) instead showed an opposite trend which began at the same time of the decline in the parking values of the green channel and reached saturation (>4000 counts) in October 2014. In the ECO-Triplet the detector measuring light at 700 nm is shared between the 700-nm backscattering channel (700 nm light source) and the chlorophyll-a fluorescence channel (470 nm light source). However, only a minor deviation from the initial values is visible in the data from chlorophyll channel at the parking depth when the red channel saturated (blue points in Figure 2.3.4). On the other hand, values of Chl-a in the upper water column declined to very low values (not shown). This may indicate that the bio-fouling agent likely covered the 470 and 700 light sources, but not the 700 nm detector.

A proposal has been submitted to exploit a sailing boat to deploy drifter and recover floats. A letter of support was sent and we are currently waiting for the result of the review process.

Figure 2.3.4: Daily averages of data collected by metbio001b during the parking phases of its mission from October 2013 to December 2014.

Metbio002b

Unlike metbio001b, this float was programmed to sample over the upper 1000 m and its GPS worked as expected. Profiles from the ECO-Triplet did not show step changes as for the instrument deployed on metbio001b. Data collected while drifting at the parking depth showed that the green backscattering channel remained stable during the first 11 months of operation (figure 2.3.5). During the last 3 months, however, its signal at 1000 dbars has begun declining and is currently about 10 counts lower than the deployment value. No drift was instead observed for the red backscattering or for the chlorophyll-a channel.


18

Figure 2.3.5: Daily averages of data collected by metbio002b during the parking phases of its

mission from October 2013 to December 2014.

Spectral backscattering

One of the novelties of the biogeochemical instrumentation mounted on the E-AIMS floats funded under WP2 is a 2-channel optical backscattering instrument. These two channels (532 and 700 nm, figure 2.3.6) should allow us to estimate the spectral dependency of particulate backscattering (bbp), which is related to the slope of the particle size distribution in the water column. Specifically, as the ratio bbp(532):bbp(700) increases, we expect a relative increase in the concentration of small versus large particles (Kostadinov et al., 2009).

Figure 2.3.6: Particulate backscattering coefficients at 532 and 700 nm measured by metbio002b. White lines are estimates of the mixed-layer depth.


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Figure 2.3.7 shows that the bbp(532):bbp(700) ratio varied over a restricted range, suggesting that the sensitivity of the ECO-triplet was insufficient for detecting changes in spectral backscattering in the oligotrophic ocean sampled by metbio002b. Further inspection of the instrument scaling factors indicated that the sensitivity of the 532-nm channel was 2.2 times lower than that of the 700-nm channel. Nevertheless, to first order bbp(532):bbp(700) decreases as a function of depth suggesting that small particles become more abundant in the mesopelagic zone.

Figure 2.3.7: Ratio of green-to-red particulate backscattering as a function of depth and time for metbio002b. The white line is the mixed-layer depth based on a density criterion of 0.03 kg/m3

from a reference pressure of 10 dbars. Data after September 2014 are affected by drift in the bbp(532) channel.

Spectral downward irradiance measurements

Another novel instrument mounted on the experimental biogeochemical E-AIMS floats is the Satlantic OCR504. This instrument measures planar downward irradiance (Ed) at three separate wavelengths (380, 412, 490 nm) as well as integrated between 400 and 700 nm (PAR, for “photosynthetically available radiation”).

Figure 2.3.8 presents the measurements of Ed

collected by metbio002b. As expected, Ed declines exponentially with depth and a showed seasonal cycle. High-frequency variations are due to clouds.

The data also show that Ed penetrates progressively deeper into the water column as the wavelength shifts from the UV (i.e., 380 nm) to the blue spectral region (i.e., 412, 490 nm).

Figure 2.3.8: Downward irradiance from metbio002b. White lines are

the mixed-layer depth.


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To further investigate these differences, the spectral vertical diffuse attenuation coefficient for downward irradiance, Kd(λ,z) was computed by applying the following equation to smoothed Ed

data:

[Eq. 1]

Although Eq. 1 does not correct Ed profiles for contamination by clouds (Xing et al., 2011), figure 2.3.9 demonstrates that the derived Kd values provide, nevertheless, a useful view on the spectral attenuation of light in the water column. As expected from the discussion about Figure 2.3.8, Kd

was higher in the UV region than in the blue (figure 2.3.9). Moreover, Kd displayed vertical variability likely related to the different biogeochemical processes affecting the absorption coefficients (e.g., Mobley 1994) of the dissolved and particulate constituents that are optically active at in this spectral region. The most important of these constituents are pure water, coloured dissolved organic matter (CDOM) and phytoplankton cells.

Figure 2.3.9: Vertical diffuse attenuation coefficient for downward irradiance, Kd, at different wavelengths as recorded by metbio002b. White lines are estimates of the mixed-layer depth. Values at the bottom of the profiles are anomalous due to increased noise at low light levels.

The value of the absorption coefficient of pure water at 380 nm is approximately 0.01 m-1 (Pope and Fry, 1997) and is a constant, thus the variable and relatively high values of Kd(380) reported in figure 2.3.9 must be due to either CDOM or phytoplankton. The spectral shape of the absorption coefficient by CDOM increases exponentially towards shorter wavelengths. On the other hand, the spectral absorption by phytoplankton peaks around 440 nm (Bricaud et al., 2010). Thus relatively high values of Kd(380) most likely indicate the presence of relatively high concentrations of CDOM. The top plot of figure 2.3.9 shows that, as the mixed-layer deepens at the beginning of the mission, the concentration of CDOM in the mixed-layer progressively increases likely due to entrainment of CDOM from below the mixed-layer and to production of new CDOM by phytoplankton. When the mixed-layer shallows, the concentration of CDOM decreases within the mixed layer due to low CDOM production and photo-oxidation due to relatively high irradiance levels.


21

Relatively low values of Kd(380):Kd(490) indicate a relative decline in CDOM absorption with respect to the absorption by phytoplankton and pure water (e.g., figure 2.3.10 near the surface at the end of the mission).

Figure 2.3.10: Ratios of Kd at different wavelengths as measured by metbio002b. White lines are estimates of the mixed-layer depth.

Conclusions

This preliminary analysis of the data from the two PML-UKMO floats funded by WP2 of E-AIMS (metbio001b and metbio002b) allowed us to draw the following (preliminary as well) conclusions:

• The GPS signal was received only intermittently by metbio001b. • The WETLabs ECO-Triplet mounted on metbio001b failed after it was exposed to

pressures greater than 1000 dbars. • The WETLabs ECO-Triplets installed on both floats were affected by significant

instrumental drift and/or biofouling after less than one year of operation. • Spectral differences in particulate optical backscattering spanned over a very restricted

range in the North Atlantic sub-tropical gyre due to a combination of low of instrument sensitivity and lack of significant changes in signals in this oligotrophic region of the ocean.

• Downward irradiance data collected in the upper 250 m of the water column decreased, as expected, in an exponential manner with depth and displayed spectral variations that are related to the optically-active constituents that dominate the water column absorption in this spectral region (i.e., CDOM and phytoplankton).

References

• Bricaud, A., M. Babin, H. Claustre, J. Ras, and F. Tièche (2010), Light absorption properties and absorption budget of Southeast Pacific waters, J. Geophys. Res., 115, C08009, doi:10.1029/2009JC005517.

• Kostadinov, T. S., Siegel, D. A. & Maritorena, S. (2009), Retrieval of the particle size distribution from satellite ocean color observations, J. Geophys. Res., 2009, 114, C09015.


22

• Mobley, C.D. (1994), Light and Water: Radiative Transfer in Natural Waters, Academic Press.

• Pope R. M. and E. S. Fry -1997), “Absorption spectrum 380–700 nm of pure water. II. Integrating cavity measurements,” Appl. Opt. 36, 8710–8723.

• Xing, X., A. Morel, H. Claustre, D. Antoine, F. D’Ortenzio, A. Poteau, and A. Mignot (2011), Combined processing and mutual interpretation of radiometry and fluorimetry from autonomous profiling Bio‐ Argo floats: Chlorophyll a retrieval, J. Geophys. Res., 116, C06020, doi:10.1029/2010JC006899.

The Nordic Seas (IMR)

Two NKE Provor CST4 floats (imrbio001 and imrbio002) were deployed by IMR during E-AIMS. In addition to the standard CTD, each float mounted the following set of biogeochemical sensors:

Aanderaa oxygen optode 4330 (multi point calibrated) Satlantic Rem-A sensor including a WETLabs ECO-Triplet (with three channels to measure

chlorophyll-a fluorescence, and optical backscattering at 532 and 700 nm) and a Satlantic OCR540 (with four channels measuring downward irradiance at 380, 412, 490 nm and a channel for photosynthetically available radiation, PAR).

The floats were programmed to collect data over the top 1000 m. Both floats were deployed during a research cruise in January 2014; imrbio001 was deployed on 20 January around 64.66ºN and 0.50ºW and imrbio002 was deployed on 22 January around 69.13 ºN and 7.31ºE.

Imrbio001

The float passed all tests in advance and was deployed without any problem. However, after one cycle there has been no contact with the float and it is considered lost.

Imrbio002

This float transmitted data and GPS positions as expected and in December 2014 it was still active. The float drifted within a limited area in the Norwegian Sea (figure 3.2.11). The cycle time was one day for the first four profiles and five days afterwards.


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Figure 3.2.11: Drift of the imrbio002 float from 22 January 2014 to 9 December 2014.

Temperature and salinity

The temperature and salinity showed no significant drift at the parking depth (figure 3.2.12). The data revealed Atlantic Water in the upper 600-700 m. During summer low-salinity water from the Norwegian Coastal Current is observed as a thin fresh surface layer in the upper 40 m (Figure 3.2.12).

Figure 3.2.12: Temperature (oC) and salinity (psu) during 2014 from float imrbio002. Left: averages between 950-1000 dbar, middle: temperature, right: salinity. The white dashed line is the estimate

of the mixed layer depth. The numbers at the top x-axis is the profile numbers.

Dissolved Oxygen

A drift of the dissolved oxygen at the parking depth (data are averaged between 950-1000 m depth) is observed during 2014 (figure 3.2.13). The oxygen concentration at this depth decreased with about 4-5 µmol kg-1 year -1. In the beginning (February) and at the end (November in the time series) this seemed to be caused by changes in the water mass but between the decrease seemed to be caused by sensor drift (compare figures 3.2.13 and 3.2.12).


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Figure 3.2.13: Dissolved oxygen (µmol kg-1) during 2014 from float imrbio002. Left: time series of the depth averages between 950 and 1000 m. Right: dissolved oxygen, the white dashed line is

the mixed layer depth estimate.

Chlorophyll-a

The fluorescence signal are converted into chlorophyll-a (Chl-a) concentration (in mg m-3) using the linear relationship provided by the manufacturer. No trend in Chl-a at the parking depth is seen but peaks are observed at this depth and depths larger than 850 dbar (figure 3.2.14). A bias for each profile is often calculated using the deepest measurements, but as shown here the data must be carefully studied in advance. The Chl-a concentration shows that the bloom starts in mid-March (during a deep MLD) and peaks in mid-May (when the MLD shallows; figure 3.2.14).

Figure 3.2.14: Chlorophyll concentration (mg m-3) from float imrbio02 during 2014. Left: time series of Chl-a averaged between 950-1000 dbar depth, middle: all profiles of Chl-a, right: Chl-a, the

white line is the mixed layer depth estimate.

Spectral backscattering

A relatively new biogeochemical sensor mounted on the floats is a 2-channel optical backscattering instrument measuring the backscatter at wavelengths 532 nm and 700 nm. The time series at both wavelengths show no trend at the parking depth but both have a seasonal cycle with maximum during May-September (figure 2.3.15). A bias between the two different wavelengths at the parking


25

depth is also seen. Peaks at all depths are observed at profile number 12 for both channels, and at profile number 21 for only one channel (wavelength 532 nm).

Figure 2.3.15: Backscattering (log10) [m-1] at wavelength 532 nm and 700 nm during 2014. Left: Time series of the depth averages 950-1000 m depth, middle: 532 nm, right: 700 nm. The white

dashed line is the mixed layer depth estimate.

Spectral downward irradiance measurements

Another new instrument mounted on the floats is the irradiance sensor that measures the downward irradiance at 380, 412, 490 nm and the photosynthetically available radiation (PAR). Figure 2.3.16 shows the depth reduction of the irradiance. Clouds influence the temporal variability but the time within the day when the measures were taken is also important to take in account. All measurements were taken during noon except for few profiles (profiles 49-51 and 64-65) when the measurements were taken during midnight. The latter can explain the low values for these profiles.

Conclusions

Some preliminary conclusions can be drawn from our experiments:

• One of the two biogeochemical floats deployed in the Nordic Seas was lost after one profile. • A drift in the dissolved oxygen sensor is observed at the parking depth. • There were large peaks in the chlorophyll-a fluorescence sensor on the WETLabs ECO-

Triplets at 850 dbar and larger depths after four months of operation (starting in May). • Both backscattering channels (532 nm and 700 nm) showed a seasonal cycle with

maximum during May-September. There was a bias between the two channels that was constant with time.

• The downward irradiance sensor seemed to perform well the first year of operation.


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Figure 2.3.16. Downward irradiance (log10) from float imrbio002 during 2014 at wavelengths 380 nm (upper left), 412 nm (upper right), 490 nm (lower left) [W m-2 nm-1], and PAR (lower right)

[microMol m-2 s-1]. The white dashed line is the mixed layer depth estimate.

The Black Sea (IO-BAS - USOF) Two NKE Provor CST4 floats (basbio001b and basbio002b) were deployed by IO-BAS during E-AIMS. In addition to the standard CTD, each float mounted the following set of biogeochemical sensors:

1) Aanderaa oxygen optode 4330; 2) Satlantic Rem-A sensor including a WETLabs ECO-Triplet (with three channels to measure chlorophyll-a fluorescence, and optical backscattering at 532 and 700 nm) and a Satlantic OCR540 (with four channels measuring downward irradiance at 380, 412, 490 nm and a channel for photosynthetically available radiation, PAR).

Both floats were deployed during IO-BAS research cruise in December 2013; basbio001d was deployed on 16 December around 43.14ºN and 29.14ºE and basbio002d on 15 December around 42.14 ºN and 29.00ºE.


27

Basbio001d This float transmitted data and GPS positions as expected and in December 2014 it was still active. The float was programmed to collect data over the top 1000 m. The float drifted within the Western and Central open part of the Black Sea (figure 3.2.17). The cycle time of basbio1d was set up one day for the first 31 profiles, five days for the next 17 and ten days afterwards.

Figure 2.3.17: Trajectory of the basbio1d float for the period 16 December 2013 - 27 December 2014

Basbio002d This float was programmed to collect data over the top 1000 m. Although the physical and biogeochemical data transmitted appeared to be of good quality the float had problems with acquiring GPS location. The number of profiles with GPS position is 44 of 78 in total for the period of float operation. It was programmed to transmit data until the battery was dead, but it stopped transmitting less than 1 year of operation for unknown reasons. The cycle time of basbio2d was set up one day for the first 44 profiles, five days for the next 12 and ten days afterwards. The float followed the Rim current very strictly (figure 3.2.18).

Figure 2.3.18. Trajectory of the basbio2d float for the period of its operation (15 December -25 October 2014)

Temperature and salinity The temperature and salinity showed no significant drift at depths greater than 500 m for both floats (Fig 3.2.19).


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Figure 3.2.19. Temperature (C̊) and salinity (psu) data by both floats during 2014 averaged between

500-1000 dba (A-B- for basbio01d and B-D –for basbio2d).

Dissolved Oxygen Both floats registered an oxygen maximum occurring in the first 50m-depth, just above thin suboxic zone at the base (Fig, 3.2.20).

Figure 3.2.20. Oxygen function of depth from basbio1d and basbio2d

The region near Bosporus Straits shows larger oxygen values around 200 m (Fig. 3.2.21) which undoubtedly indicates the influence of the Mediterranean water coming with the Bosporus plume [Konovalov, et al., 2003]. The Bosporus Straits intrusions fingerprints could be distinguished in the temperature and to less extend in the salinity profiles (Fig. 3.2.21)

A B

C D


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Figure 3.2.20. DO, temperature and salinity profiles (15-16) of the basbio2d near the Bosporus Straits

Chlorophyll a Both floats registered a chlorophyll a maximum and minimum in distinct layers coinciding with seasonal variation of the thermocline. Nevertheless after its minimum, the chlorophyll a impressively gradually increases again with depth to concentration ranging between 0.2 to 0.35 mg/m3 (Fig 3.2.21). Тhe hypothesis about a systematic error in the chlorophyll sensor is unlikely as the Chl bellow 200 m increases with depth rather uniformly and this behavior is seen in other sensors too. Further more, there are also other physical and chemical characteristics of the deep Black Sea to increase with depth: temperature, nitrate and ammonuim. That is why we consider another hypothesis: that this reflects the microbial sulfur cycle and the Chl sensor captures the sulphate redoxing green bacteria which are likely to exist at this depth (Hashwa and Trupe, 1978, Jannasch et al, 1974, Marshal et al., 2010). However this second hypothesis needs careful checking and some preliminary contacts with relevant laboratories to investigate the deep water samples are performed.

Figure. 3.2.21. Chlorophyll a profiles from basbio1d (left) and basbio2d (right)

Conclusions Some preliminary conclusions can be drawn from our experiments:

• The GPS signal was received only intermittently by basbio002d. • On 25 October 2014 basbio002d stopped transmitting data after 78 profiles


30

• The temperature, salinity and DO sensors seemed to perform well the during first year of operation

• The performance of ECO-Triplet instrument have to be verified with laboratory analysis of water samples and fluorescence measurements

References:

Konovalov, S. K., Luther III, G.W., Friederich, G.E., Nuzzio, D.B., Tebo, B., Murray, J.W.,

Oguz, T., Glazer, B.T., Trouwborst, R.E., Clement, B.G., Murray, K.J., and A. S. Romanov, 2003, Lateral injection of oxygen with the Bosporus plume-fngers of oxidizing potential in the Black Sea. Limnology and Oceanography 48 (6), 2369-2376

2. F. A. Hashwa, H. G. Trupe, (1978), Viable phototrophic sulfur bacteria from the Black-Sea bottom, Helgoland Marine Research, Volume 31, Issue1-2, pp 249-253,

3. Marschall E., M. Jogler, U. Hensge and J. Overmann, (2010) Large-scaledistribution and activity patterns of an extremely low-light-adaptedpopulation of green sulfur bacteria in the Black Sea, EnvironmentalMicrobiology, 12(5), 1348–1362, doi:10.1111/j.1462-2920.2010.02178.x

4. Jannasch, H. W., H. G. Thuper, and J. H. Tuttle. (1974). Microbial sulfurcycle in Black Sea, p. 419-425. In E. T. Degens and D. A. Ross [eds.], TheBlack Sea-geology, chemistry and biology. Am. Assoc. Pet. Geol. Mem. 20.


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Task 2.4: Test of floats with Iridium/Argos3 transmission (Task leader: OGS)

UKMO Under the coordination of UKMO, two SeaBird Navis floats with Iridium transmission were deployed in the tropical North Atlantic, in the North Atlantic Gyre, during the Atlantic Meridional Transect (AMT-23) cruise in October 2013. Two NKE-biogechemical floats (under Task 2.3) and two Iridium Apex floats were also deployed around the same time. The Apex and Navis floats were all set to the standard Argo mission (10 day cycle, 1,000m park and profiling from 2,000m depth).

The status of the floats is as shown below.

Float type WMO# Serial# # cycles completed (as at

11 December 2014) Apex 6901153 6605 43 Apex 6901154 6606 43 Navis 6901155 F0243 42 Navis 6901156 F0248 42

As these are all Iridium floats enabling two-way communications it is possible to change the mission while the floats are at sea. When the float surfaces at the end of a profile the transceiver registers with the Iridium system, the float then disconnects from Iridium and acquires a GPS position fix. The float then reconnects to Iridium, uploads its hydrographic and engineering data and downloads any changes to its mission parameters. For both the Apex and Navis floats this can be achieved by placing an updated mission configuration file on the host server; this file (mission.cfg) needs only include the parameters to be changed. For complex mission changes it is recommended to first verify the new mission.cfg file with the chkconfig utility.

Earlier configuration changes to (non E-AIMS) Apex floats were made to switch the floats from their regular profile levels (the specified depth table) to high resolution continuous sampling to full (2,000m) depth. However, this has led to problems in the data processing at BODC whereby the processed NetCDF data for these floats only contained a single data point. This was related to the merging of the low and high resolution profiles in generating the NetCDF v2 files and will be corrected when BODC migrates to NetCDF v3 early in 2015 and when the older data are re- processed. Similar processing problems have occurred for the Navis floats, whereby only the lower half of the profiles were being reported in the NetCDF, even though the floats are transmitting full profiles; this will similarly be resolved when BODC moves to NetCDF v3.

As a result of these processing issues it was decided to delay any mission changes to the floats until these problems were resolved. NetCDF v3 data are now being generated by BODC (although not yet to the GDACs), such that the profiles can be accessed. Updated missions, switching to continuous profiling on a 5 day cycle were uploaded to the two Apex floats (6901153 and 6901154) on 11th December, however it is too early to verify that the changes have been successful. It is planned to upload similar mission profile changes to the two Navis floats before the end of the year.


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OGS OGS has acquired two Arvor floats with Argos-3 telemetry from NKE. These were delivered to colleagues in the Balearic Islands (Spain) and Cyprus, for deployments in the Western and Eastern Mediterranean, respectively.

The float shipped to the Balearic Islands was deployed on 25 May 2014 at 18:59 GMT in the eastern Alboran Sea during the ALBOREX campaign (Poulain et al., 2014) by colleagues from IMEDEA/CSIC (figure 2.4.1). ALBOREX was planned as part of WP3 of the F7 PERSEUS project to measure the mesoscale and submesoscale variability in the eastern Alboran Sea using multi- platforms (research vessels, drifters, floats and gliders).

Figure 2.4.1: Deployment of the Arvor-A3 float from R/V SOCIB on 25 May 2014.

The trajectories of the Arvor-A3 are shown in figure 2.4.2, along with the positions of the CTD profiles executed by the float. It drifted to the southeast and arrived in the vicinity of the Algerian coast by mid-June 2014. After deployment, the transmission of the dataset was done in one satellite pass, as expected. But after each transmission, the float was unexpectedly set in a backup mode, intended to recover the latest ephemerides and the location of the float. This behaviour led to a time spent at surface of a few hours after each profile. Because of this non-optimum transmission performance, we reset the float, using the Argos-3 downlink on 19 June 2014.


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Figure 2.4.2: Trajectories of the Arvor-A3 with black dots indicating the positions of the CTD profiles: first part between deployment on 25 May 2014 and 17 June 2014 (top), second part after

reset between 19 June 2014 and 16 Dec 2014 (bottom).

Since the reset, the transmission performance is very satisfying. All profiles dataset are transmitted in only one satellite pass, in about 3 minutes ! In comparison, a float fitted with the Argos-2 system requires 10 hours in the Mediterranean Sea.

Moreover, the cycling period of 2 days was successfully changed to 5 days using the Argos-3 downlink (starting on 24 July 2014).

The float shipped to Cyprus will be deployed in early 2015 in the Levantine Basin (South of Cyprus Island) by our colleagues from the Oceanography Center of the University of Cyprus.

References:

Poulain P.-M., Menna M., Notarstefano G. and Bussani A. (2014) Lagrangian measurements in Alborex 2014 campaign. OGS Technical Report 2014/53 OCE 18 MAOS.


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Task 2.5: Test of new Arctic floats (Task leader: IOPAS)

In 2014 the Institute of Oceanology PAN (IOPAS) continued activities aimed at preparing and deployment two Arctic floats.

Ordering and sensor installation

In the beginning of 2014 the offers from various floats manufacturers were analysed and floats specifications were developed. Due to the financial limitations (high costs of floats), we decided to develop and order two different floats: one ‘standard’ Arctic float and one item with the Inertial Measurements Unit (IMU). Since the lack of RAFOS sources in the Fram Strait region, we skipped installation of RAFOS receivers to cut down the costs.

In January 2014 the first float specifications were prepared and the tenders were announced. The company OPTIMARE GmbH was selected as the manufacturer of the first, less sophisticated float. This company has the biggest experience in manufacturing the Artic floats. After financial problems in 2013, in 2014 OPTIMARE was operational again.

The IRIDIUM float with Ice Detection Algorithm was delivered by OTIMARE to IOPAS in May 2014.

In the meantime the concept of the second, more sophisticated float was developed. The idea was to implement the IMU sensor and processor into the float. Three various IMU devices were tested by IOPAS. Various modes of IMU work were analysed. The negotiations with floats manufacturers to implement the IMU sensor into a float were also conducted. Finally the OPTIMARE GmbH as the float producer and the FORKOS Ltd. (SME) as the IMU module (IMU sensor, processor, software and data storage module) provider were selected. OPTIMARE agreed to apply necessary changes in their float and install the IMU sensor. The update of the float by installing the IMU sensor was longer and more expensive than planned, but finally operation was successful. The experiment with the IMU sensor was developed. Due to the high power consumption (mostly by the data processor) we decided to switch off the sensor two months after deployment to save batteries for the usual float functions.

Fieldwork and launching

Both floats were deployed in summer 2014 from the IOPAS research vessel ‘Oceania’. The first float was deployed on 1st July, 17:20 GMT at the position 75°0.025’N, 012°29.650’E, and got WMO# 6902041. The second float, with IMU sensor was deployed at position 76°29.864’N, 007°32.284’E on 10th July, 20:00 GMT and got WMO# 6902042.

The technical problems have been encountered with the first float. The first data package was sent 59 days after deployment, however data were incomplete. Finally, the float sent 10 incomplete sets of data and stopped to transmit on 9th October. All in all, the float did 33 profiles (part of them has not been sent).

Deployment of the second, IMU float was successful. By the date of 19th December the full set of hydrographic data has been transmitted. The IMU data were transmitted as planned for the first 17


35

days (16 profiles with IMU data were received). Two way communications via IRIDIUM was tested and changes in the float working mode were successful (IMU sensor was stopped). So far, the float did 45 profiles and it is still working. Obtained profiles have been sent to the Coriolis database.

Results and limitations

As the result of this experience the idea, hardware and software for the IMU data processing, storage and transmission were developed. Data were transmitted and received during the first field test. The accuracy of the available IMU devices is still low, but development of this technology is very fast. Even now there are IMU devices (based on the laser technology) with accuracy, needed for application in floats, but they are still too big, too expensive and consume too much power. In the future IOPAS, in cooperation with other interested institutions, is going to continue development of the Arctic float with IMU sensor as the alternative way of the under ice navigation.

Figure 2.5.1: Surfacing position of two Argo floats deployed south and west of Spitsbergen in July 2014. The first (green line) sent incomplete data from 10 profiles while the second (yellow line) has

sent data from 45 profiles including 16 datasets from IMU and is still working.


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Figure 2.5.2: Sea ice concentration near Spitsbergen on 18th December 2014 (from the website http://polarview.met.no/). It shows possible space for float surviving.

Figure 2.5.3: Distribution of temperature, salinity and density in the upper 600 dbar layer based on profiles collected by the second float (WMO 6902042) west of Spitsbergen.

http://polarview.met.no/


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Task 2.6: Synthesis (Task leader: Ifremer) This task has not started yet.


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WP3 Impact and design studies from GMES Marine Service and seasonal/decadal modeling and forecasting

(WP leader: partner 11, Mercator Ocean, France)


The main objective of WP3 is to perform Observing System Experiments (with real data) and Observing System Simulation Experiments (simulate and assimilate observations to test new observing capacities with the GMES/Copernicus Marine Service assimilative systems to assess the potential of Argo and its extensions.

WP3 is divided into 4 tasks:

• Task 3.1 led by Mercator Ocean is dealing with the global uncoupled prediction system. • Task 3.2 led by the Met Office is dealing with coupled prediction systems (from days to

decades). • Task 3.3 led by INGV is dealing with regional (Mediterranean and Black Sea) analysis and

prediction systems. • Task 3.4 led by Mercator Ocean and CLS will synthetize the results. A final workshop will

be organized jointly with GODAE OceanView and CLIVAR GSOP.

The total duration of WP3 is 24 months. The deliverables are scheduled as follows. For all regions (Global, Mediterranean and Black seas) and all applications:

• T0+3: Initial requirements (April 2013). • T0+9: OSE/OSSE plans (October 2013). • T0+21: OSE/OSSEs results and recommendations (October 2014). • T0+24: Final report (December 2014).

The work carried out for this second year included the following tasks:

Conduct OSEs (Observing System Evaluations) to estimate the role of the current Argo floats in different type of analysis and forecasting services (R/T forced and coupled, seasonal and decadal).

Simulate pseudo-observations mimicking the future possible deployment of new Argo

floats, conduct OSSEs (Observing System Simulation Experiments) in different context of analysis and forecasting services (R/T forced and coupled, seasonal and decadal).

Synthetize the different experimental results to draw recommendations on the Argo

array evolution in the framework of analysis and forecasting services.

The WP3 (and WP4) final workshop was organized in December 2014 jointly with GODAE OceanView and GSOP/CLIVAR international meeting in Toulouse.


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Task 3.1: Impact of Argo on the Mercator Ocean global ocean analysis and forecasts

Impact of Argo on Mercator Ocean global ocean analysis and forecasts

The sensitivity of the global ¼° Mercator Ocean analysis and forecasts to Argo float assimilation is assessed with a series of OSEs and OSSEs.

During this second year of the E-AIMS project, we finalized the analysis of the OSE experiments and a scientific paper was written and will be soon submitted the Ocean Science journal. OSSEs were also carried out to test the impact of deep Argo measurements in the framework of a global eddy-permitting ocean analysis and forecasting system.

The 1-year OSE experiments on the Argo current array impact on the global ¼° ocean analysis shows that the present spatial coverage allows a significant reduction of the model-observation misfit at all depths up to 2000 meters compared to a simulation without Argo data assimilation. A reduction of only half of the floats degrades significantly the results. Figure 3.1.1 presents the mean RMS error profile for those different OSE experiments. The results are also compared to an experiment where only the altimeter and SST observations were assimilated and to an experiment without any data assimilated (figure 3.1.1).

Figure 3.1.1: Vertical structure of RMS of temperature innovations (left) and normalized RMS temperature innovations (right) from 0-2000m for Run-Ref (blue), Run-Argo2 (yellow), Run-NoArgo

(green) and Free Run (red).

Keeping only half of the Argo floats is not sufficient at all depths to have a good estimation of the temperature and salinity fields. A strong impact is also seen on heat and salt content estimation. This later quantity is of primary importance in multi-year climate related ocean reanalyses.

The OSE experiments thus show that a sparser spatial coverage of the Argo array than the present one will lead to a degradation of the global ¼° analysis and forecasts of the Mercator Ocean system. The Argo floats are crucial in the system to control the water properties, especially at depth up to 2000m. Below 2000 m the lack of observations does not allow us to estimate the quality of our analysis.


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During 2014, 1-year OSSEs were also prepared and conducted. Such experiments allow a full 3D comparison between the “true” simulated ocean and the estimated fields after assimilation. The in situ observations were simulated using a 1/12° global forced simulation. The 2009 Argo coverage was simulated with all profiles extending to the ocean bottom. Then several OSSEs were performed to test the impact of deep Argo floats up to 4000 m and 6000 m depth and their density on the global ¼° ocean forecast and analysis system. We simulated an Argo observation array with all floats going to 2000 m depth, to simulate the present situation; we then expanded the assimilated profiles up to 4000 m depth for all the floats. We also simulated the case were only a one third of the floats will make measurements up to 4000 m (or 6000 m), and only one over third profiles. The density of observation between 2000 m and 4000 m was then reduced by a factor of 9. We only assimilate the in situ simulated observations to focus on their contribution without introducing the problem of the coherency between the sea level observation and the in situ observation, both of them constraining the dynamic height in different ways.

These OSSE experiments show the ability of the current system to assimilate deep profiles up to 4000 m depth. The large biases simulated at depth are reduced compared to an experiment with float profiles going up to 2000 m depth only (figure 3.1.2). A sparse coverage, simulated with keeping only one over nine float profiles up to 4000 m depth appears to be efficient as the space and time scales in the deep ocean are large.

Main conclusions are as follows:

Increasing the depth of Argo floats profiles up to 4000 m depth instead of 2000m reduces

the bias between 2000 up to the bottom where it was large,

Increasing the depth of Argo floats profiles up to 4000 m depth instead of 2000 m for only 1/9 of them gives comparable results than if all are going up to 4000m. This is consistent with the fact we found a low temporal variability but significant bias in some regions.

increasing the depth of Argo floats profiles up to 6000 m depth instead of 2000 m for only

1/9 of them degrades the model solution. This shows that our present system is not tuned to handle observations up to the bottom. A deep bias slowly appears under 4000 m depth and reach 0.5°C after one year simulation.

Those conclusions are based on model simulation only. As models themselves are poorly validated at depth due to the lack of observation, these results should be taken with some caution.


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Bias temp 2000m-4000m Bias temp 4000m-6000 m

Run

with

Arg

o up

to 2

000

m

Run

with

1/9

Arg

o up

to 4

000

m

Run

with

all

Arg

o up

to 4

000

m

Figure 3.1.2: Mean deep ocean temperature errors in the different OSSEs for two different depth ranges: 2000-4000 m (left) and 4000-6000 m (right).

Impact of Argo on CLS multivariate data analysis system

CLS has developed a multivariate data analysis system that merges satellite (altimetry and sea surface temperature) and in situ observations (Argo, moorings, CTDs, XBTs, etc) through linear regression and optimal interpolation (ARMOR3D system described in Guinehut et al., 2012). This observation-based system is the result of more than ten years of work during which OSE and OSSEs have been conducted (Guinehut et al., 2002; Guinehut et al., 2004; Guinehut et al., 2012).


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The ARMOR3D observation-based system is used as part of E-AIMS to assess the impact of Argo observations to map temperature and salinity fields with satellite observations using Degree of Freedom of Signal (DFS) diagnostics. DFS is an influence matrix diagnostics that provides a measure of the gain in information brought by the observations. Several experiments have been conducted and two DFS metrics have been studied.

When two datasets are considered: in situ (including Argo, XBTs, moorings,...) and satellite, results for the temperature field at 100 m and the 1993-2012 period show that for the global ocean, 1/3 of the overall information comes from the in situ dataset at the beginning of the period and that this number increases to 2/3 when the Argo observing system is fully deployed. The satellite dataset completes the information with 2/3 at the beginning of the period and then 1/3.

When three datasets are considered: Argo, other in situ (including XBTs, moorings,...) and satellite, results for the temperature field at 100 m and the 2008-2009 period show that for the 65°S-65°N area, most of the information comes from the Argo observing system (67 %), then the information comes from the satellite dataset (21 %) and finally from the other in situ instruments (11 %) (figure 3.1.3). Almost no redundancy is found in the Argo dataset, apart from the Bay of Bengale and the very west part of the tropical Pacific Ocean where the density of Argo network is very high. Redundant information is found in the other in situ dataset in the three tropical oceans and in the Gulf Stream and Kuroshio regions. This dataset nevertheless complement well the Argo observing system in mid latitude regions. For the satellite dataset, only 20 to 30 % of the information content is exploited by the ARMOR3D method meaning that most of the information is lost because of duplicate data and high measurement error.

Results vary slightly between the surface and 1500 m depth but main conclusions still remain. Moreover, it has been showed that a better representation of the errors on the synthetic fields (i.e. satellite dataset) induces a more realistic vertical structure of the results.

Recommendations

Results from these works show that:

the existing Argo observing system should be as much as possible stabilized,

the Argo observing system should continue to equally sample the entire world ocean,

the existing spatial and temporal coverage of Argo network should be at least maintained,

deeper measurements are needed to control model temperature and salinity fields. 1/3 of the floats profiling up to 4000 m one cycle over three would already very significantly reduce biases in model deep fields.


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From

sat

ellit

e da

tase

t Fr

om in

situ

oth

er d

atas

et

From

in s

itu A

rgo

data

set

Fraction of information content

0.67 ± 0.19

Fraction of information content exploited by OI system

0.82 ± 0.08

0.11 ± 0.13 0.49 ± 0.24

0.21 ± 0.19 0.20 ± 0.06

Figure 3.1.3: DFS metrics for the T field at 100 m of the 04/06/2008 analysis - 65°S-65°N means

+/- 1 std are also indicated (Units: x100%).


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Task 3.2: Weather, seasonal and decadal forecasting (Task leader: UKMO)

We have used an observing system experiment (OSE) and two Observing System Simulation Experiments (OSSEs) to investigate the effect of assimilating Argo profiles in coupled analyses and short-range forecasts using the Met Office weakly-coupled data assimilation system. As with all observing system experiments, the impacts shown here are specific to the forecast model, data assimilation system and observations used. The results cannot necessarily be generalised to other systems, but apply only to our prototype weakly-coupled data assimilation system.

An analysis of the ocean innovation statistics (figure 3.1.4) has shown that removing the assimilation of Argo profiles from our system causes a large degradation in the temperature RMS error throughout the sub-surface water column and an increase in the bias, especially near the thermocline. A similar degradation in the salinity RMS error is seen throughout the water column as there are no additional surface observations with which to constrain salinity. The greatest differences in the upper ocean seem to build over the first 6-months, but it is not clear if the full effects are realised by the end of the 13-month runs. Consequently, any OSE run over a shorter period is likely to under-estimate the impact of profile assimilation, especially for the deeper ocean.

A similar analysis of the atmosphere observation-analysis statistics showed negligible systematic global impacts on the atmospheric analyses. However, this was not unexpected due to the continued assimilation of all available atmosphere and sea surface temperature observations in both experiments. On the other hand, case study forecasts of Hurricane Sandy highlighted that the assimilation of Argo profiles has an impact on the analysed position of the Gulf Stream (as seen in figure 3.1.5), with consequent impacts on forecasts after the hurricane passes over the Gulf Stream. Although no systematic improvements in the position or intensity of the hurricane were found in a comparison against the available observations, it was noted that there was a better agreement between the control forecast tracks at different lead-times than for no-Argo forecast tracks. This is potentially a consequence of the broadly lower upper-ocean heat content seen in the control experiment, relative to the no-Argo experiment, as shown in figure 3.1.6.

The results of the OSE indicate that the current Argo network can have an effect on the atmosphere leading to impacts on forecasts in specific case studies. However, results from our OSSEs indicate that there is a substantial amount of work necessary before we could make use of the extra information gathered by a greatly expanded Argo array. The OSE and OSSEs run here have been useful in further highlighting possible deficiencies in the balance involved in the assimilation of both altimeter and profile observations. The OSSEs, in particular, have also highlighted a problem in making use of a higher density of profile observations than is currently available. Although a greater density of observations should allow an improved estimate of the ocean state, and hence improve forecasts, such observations will not have an immediate impact without more effort to improve the assimilation. Given the proposed increase in profile density in particular regions, this will need to be addressed in the near future.


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Figure 3.1.4: Global temperature (left) and salinity (right) profile innovation statistics (RMS error shown as solid line, mean error shown as dashed line). The black lines show the statistics over the

13-month experiment for the control run and the blue line the statistics for the no-Argo run.

Figure 3.1.5:: The mean SST observation-background differences binned to 0.25º for the control (left) and no-Argo experiment (right) over the period 22-30 October 2012. The best-track positions

of Hurricane Sandy are show every 12 hours from 12Z on 22-10-2012 to 12Z on 30-10-2012


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Figure 3.1.6: Upper-ocean heat content difference (J, of top 300m) between the control analyses and the no-Argo analyses averaged over October 2012 (control – no-Argo).

Decadal forecasting time-scales – Royal Netherlands Meteorological Institute (KNMI)

As part of Task 3.2 we here investigate the impact of the geographic distribution of observations on the skill of decadal climate forecasts. The analysis is limited to the subpolar gyre (SPG) in the North Atlantic, as this is the only region where forecast skill goes beyond the forced trend (Van Oldenborgh et al. 2012).

All experiments have been performed with EC-Earth v2.3 (Hazeleger et al. 2012, Sterl et al. 2012). Restart files were chosen from the decadal prediction runs of Wouters et al. (2013) and from the ORAS4 ocean reanalysis (Balmaseda et al. 2013). For each of the eight start dates three ocean restart files were combined with five atmosphere files each.

To test the impact of initialization in different parts of the ocean, two experimental ensembles are performed. In the first the fc0 ocean restart files are used, but all values (T, S, velocity) below 2 km are replaced by the time-mean of the eight different restart dates. The purpose of this ensemble (vert) is to assess the importance of deep observations on the hindcasts.

The second experiment is set up in the same manner, but now all values outside of the sub-polar gyre (roughly 90°W-15°W, 42°N-65°N) are replaced (spg). Here the impact of initialization in different horizontal areas is investigated. This run has not been investigated in detail yet, and no results are presented here.

The runs are initialized from full fields. Therefore, the model starts to drift from the initial state to its own climatology. The common drift is determined by averaging the model output over all ensemble members and restart dates and subtracted from the model output.


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Results

Model runs started from the same, or at least nearly the same, initial conditions should develop similar anomaly patterns in order to have forecast skill. The similarity is measured by the pattern correlation coefficient (PCC) and the area-averaged normalized root-mean-square differences (RMSD) between runs. Both are calculated at each model layer at each time step of the forecast, resulting in time series for each depth. To eliminate noise we calculate them for all combinations of ensemble members and average the results.

PCC and RMSD for temperature for one start date are shown in figure 3.1.7. The PCC (RMSD) decreases (increases) with time, indicating increasing divergence of the ensemble. The development is faster near the surface than at depth. Near the surface the coherent signal has

disappeared after 2 years.

Figure 3.1.7: PCC (left) and RMSD (right) for temperature in the NAtl, averaged over all

combinations of runs from ensemble fc0 with start date 1970, and after subtraction of the common drift.


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Figure 3.1.8: Average PCC of heat flux over the SPG for one start date (1990).

The ocean affects the atmosphere via its surface, especially the heat flux. The fast deterioration of a coherent signal at the surface suggests that each ensemble member creates its individual interaction with the atmosphere, regardless of the ocean’s initial state. This is confirmed by figure 3.1.8 showing the heat flux PCC averaged over all pairs of runs. It starts with high values, indicating a common development, but after about two years it drops off to near-zero, suggesting limited predictability.

Figure 3.1.9: Evolution of T-anomalies, integrated over the 1-2 km depth range in the subpolar gyre. Black curve is ORAS4 reconstruction (member 0; linear trend and annual cycle removed). The coloured curves are the hindcasts. For each start date the average for three ensembles (fc0,

fc1 and vert) (bold lines) and their ±1 stdv range (dashed) are given. The curve for the vert ensemble is extra thick.


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Figure 3.1.9 shows the evolution of temperature anomalies averaged over the SPG in the 1-2 km depth range. The curve from the detrended ORAS4 data is plotted as a reference. For some start dates (1970, 1985, 1990, 1995) the evolution of the hindcast runs shows some resemblance to that of ORAS4. However, for some other start dates (2000 and 2005) they evolve in a direction opposite to the reanalysis.

The curves for the vert ensemble are highlighted in figure 3.1.9. They are not distinguishable from the other two ensembles. Clearly, the altered initial conditions below 2 km have no systematic impact on the performance of the mode

Although the runs need to be further analysed, some preliminary conclusions can be drawn:

1. After removing the common drift, the different members of an ensemble evolve similarly

and only diverge slowly at depth.

2. At the surface the divergence is fast. After less than two years anomalous surface fields have no resemblance between ensemble members.

3. This is especially true for the heat flux, through which the ocean influences the atmosphere.

It can be anticipated that forecast skill for atmospheric variables is low.

4. Even at depth, where the divergence of the ensemble is small, the evolution of the ensemble is not necessarily in the direction of the observed (as represented by ORAS4) evolution.

5. Changing the initial state below 2 km has no influence.


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Task 3.3: Mediterranean & Black Sea (Task leader: INGV)

Mediterranean Sea (INGV)

During the last two years INGV carried out an investigation aimed at the understanding of the impact of the present MedARGO horizontal sampling and vertical/time sampling scheme on the quality of MyOcean Monitoring and Forecasting Center (MFC) operational analyses through Observing System Simulation Experiments (OSSE) and Observing System Simulations (OSE). The simulation results were made available also to the biochemical OSE experiments carried out by OGS.

For the study year 2012, 5 OSE have been carried out in order to study the impact of ARGO data assimilation impact and in general te observational system on the quality of operational MyOcean Med-MFC analyses (Table 1). The basic idea is to remove selectively observations from the overall observing system and assess the impact in term of MISFIT Root Mean Square Errors (RMSE) and BIAS. Misfit is defined here as the difference between the model background and the observation before the observation is assimilated.

Name

Model and Assimilation

characteristics

Satellite SLA and

SST

In-situ obs

XBT ARGO T,S

CNTRL Myocean Med-MFC analysis

system 2012

✓

✓

✓

OBS-1 MyOcean Med-MFC analysis

system 2012 without ARGO data assimilation

✓

✓

OBS-2 Myocean Med-MFC analysis

system 2012 without SLA+SST assimilation

✓

✓

SIM Simulation (MyOcean Med-MFC

model)

OBS-4 Myocean analysis system 2012 with

HALF ARGO

✓

✓

Half

Table 1: OSE characteristics

Results indicate that: 1) Argo assimilation improves the accuracy of the Temperature and Salinity analyses by 35% with respect to simulation on the whole water column; 2) half of the present Argo array increases the analysis bias of 30% for salinity between 0-100 m and 10% in terms of RMSE (7% for T and 12% for S).

The OSSE methodology used here is based on the identical twin experiment approach, which uses synthetic data extracted from a ‘Nature run’ and the inserted in a ‘perturbed run’ (Table 2).


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Name

Model and Assimilation characteristics Assimilated data set: synthetic Argo

SIM-TRUTH

Simulation (MyOcean Med-MFC model) for 2012

NO

SIM-PERT Simulation (MyOcean Med-MFC model) for 2012, perturbed physics and initial conditions

NO

OSSE-1

SIM-PERT with 3Dvar 5 days drift, parking depth 350

OSSE-2


OSSE-3


OSSE-4


OSSE-5


OSSE-6

SIM-PERT with 3Dvar

5 days drift, parking depth 350,

“perfect” vertical sampling

Table 2: OSSE characteristics

Vertical profiles of RMSE (figure 3.3.1) show an improvement when the simulated float drifted with a parking depth of 700m and when probes had a surfacing time of 3 days. Positive impact of perfect sampling has been evaluated to reduce the RMSE error of misfit around the 10-15% in the entire water column.

Figure 3.3.1: OSSE Root Mean Square Error (RMSE) for Temperature (left) and Salinity (right)


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The OSSE study has shown that the assimilation of temperature and salinity data from synthetic Argo monitoring system in the Mediterranean Sea can improve the quality of analyses if a deeper drfiting depth and a shorter drifting time is considered in future Argo sampling schemes. Full profile transmission could be considered also as a major improvement for MyOcean operational analyses.

Black Sea (USOF)

An observing system in the Black Sea combining remote sensing data such as sea level anomalies from altimetry, sea surface temperature from satellite radiometer and data from Argo floats has been analyzed by the USOF with the aim to quantify the contribution of different information sources when reconstructing the ocean state. The investigated period is 2005-2012. The basic questions addressed during this project-phase can be formulated as follows:

do the Argo float measurements substantially impact the quality of estimates of

thermohaline fields in the Black Sea;

what is the dependence of this quality upon the amount of used profiles and different sampling strategies;

what are the specific aspects which have to be considered for the Black Sea when planning

future Argo deployments.

Of particular importance for the Black Sea, where the circulation is largely dependent on horizontal and vertical salinity gradients, is that there is no alternative to Argo data, which can be used operationally.

The OSE experiments designed to quantify the quality of temperature and salinity reconstruction as a function of the amount of deep data support the overall understanding that the dynamic information from the deep observations does not strongly propagate onto the whole state vector. However without using deep profiles one cannot well account for the spatial structures of temperature to the east of Bosporus Straits where, if deep-ocean intrusions are not well sampled, the errors increase.

The benefit of using the OSSE as a tool to estimate what impact a new observing system may have on ocean forecasts and analysis and how to maximize the information content of the data collected by observing networks has also been demonstrated. For this type of experiments synthetic observations provided by the model (including synthetic Argo float trajectories) have been used. The accuracy of the pressure sensor which is important for the better resolution of the extremely sharp stratification in the upper layers appeared as one important issue specific to the Black Sea. At the moment the weakest point of the Argo observation network is the representation error due to the pressure sensor accuracy. Increasing this accuracy would have a very high potential to further increase the reconstruction quality.

Experiments with different deployment strategies demonstrated that increasing the amount of Argo floats performs better than increasing the frequency of surfacing. Without Argo data the estimates in the upper mixed layer suffer from large errors. However profiling float measurements are


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especially important for depth below the seasonal thermocline because the transition from thermo- to-haline-dominated stratification shows only short spatial covariance length.

One major conclusion from this research is that the present abundance of Argo floats operating in the Black Sea of about 10 seems optimal for operational purposes. Further increase of this number could be beneficial when addressing specific research questions.

The experiments presented in this work depicted a remarkable sensitivity of the performance of observing network to seasonal changes. The resulting variations in the relative reconstruction errors appeared equal or even greater than the variations due to the enhanced network configuration. Therefore there is a further potential for improving the observation network performance by temporal adaption of its configuration.

Task 3.4: Synthesis (Task leader: Mercator Ocean and CLS)

A GODAE OceanView/CLIVAR GSOP/E-AIMS international workshop was organized in December 2014 to analyze results from OSE/OSSEs carried out by international teams (including E-AIMS W¨P3 partners) and provide recommendations to agencies in charge of satellite and in-situ observing systems. It was followed by the final WP3 workshop where the main results obtained for the different WP3 tasks and recommendations for the evolution of Argo were discussed. All the presentations given for these two events are available on the E-AIMS WWW site.

The next step will be to prepare the final WP3 report which will summarize the recommendations for the evolution of the Argo array based on E-AIMS OSE/OSSE results. This report will be delivered by the end of January 2015.


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WP4 Impact for the validation of satellite observations and for joint in- situ/satellite analyses (WP leader: partner 15, CSIC, Spain)

Work package objectives for the period The activities in this WP have aimed to better understand the robustness of the remote sensing validation when Argo data are used. Moreover, the studies performed during this WP have focused in providing a set of suggestions about the evolution of the Argo array to improve remote sensing validation. The fields under consideration are: Sea level (Task 4.1), ocean colour (Task 4.2), sea surface temperature (Task 4.3), and sea surface salinity (Task 4.4). The total duration of this WP is 24 months (starting on month one). Each task has provided a set of three deliverables, two of which were delivered during the first year period and the last one delivered during the second year.

The activities during the current period have focused on providing a summary of the various impact studies performed and a set of recommendations and a final synthesis. The results were discussed in the WP3 and WP4 Final Workshop held at the CLS premises in Toulouse on December 12, 2014.

Task 4.1 Altimetry (Task leader: CLS)

A Deliverable (D4.413, Altimetry: impact study results and Recommendations) has been delivered. It describes the sensitivity analysis assessing the impact of changes in the processing of Argo in- situ data in the validation of altimeter measurements. This study has been presented in the E-AIMS WP3 & WP4 final Workshop held in Toulouse on December 12, 2014.

In this study, in-situ steric Dynamic Height is computed by the integration of the Argo Temperature and Salinity vertical profiles. The calculation requires a reference depth. The associated steric Dynamic Height Anomaly (DHA) is calculated by removing a climatology field. The following selection rules are applied to the Argo profiles:

• JULD_QC = 0 | 1 | 5 | 8

• POSITION_QC = 0 | 1 | 5 | 8

• DATA_MODE = ‘R’ is used and if DATA_MODE = ‘A’ | ‘D’, the “adjusted“ DHA are used.

Sea level measurements are available along the track of single altimeter missions (Envisat, Jason- 1 & 2, SARAL AltiKa...) and as gridded merged products (SSALTO/DUACS products: http://www.aviso.altimetry.fr/ or ESA/SL-CCI products: http://www.esa-sealevel-cci.org).

The comparison of altimeter measurements with the Argo-derived in-situ steric heights allows the detection of altimeter drift or anomalies at global and regional scales and the assessment of new altimeter standards or products. The present studies have focused on:

http://www.aviso.altimetry.fr/

http://www.esa-sealevel-cci.org/


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Sensitivity to the spatial sampling of the Argo floats. The altimeter drift detection and the global statistics between both types of data are not affected by a reduction of the number of Argo floats and a reduced spatial coverage of the in-situ network.

Sensitivity to the temporal sampling of the Argo profiles. The Argo floats provide T/S vertical

profiles every 10 days. A reduced temporal sampling of the floats (>10 days) can prevent us from detecting the impact of new altimeter standards in some specific situations.

Sensitivity to the reference depth for the integration of the Argo dynamic heights. The

choice of the Reference Depth of Argo profiles impacts the ocean coverage by the network, the physical content (variance) of the sampled water column and the analysis of the altimeter sea level closure budget. Detection of the altimeter drift and the quality assessment of new altimeter standards or products are sensitive to the Reference Depth. A balance has to be found between the vertical sampling of the ocean and the spatial coverage (horizontal sampling) and the choice of the Reference Depth may vary according to the case of study. However, we recommend that the vertical extension of the Argo profiles should be extended to deeper levels.

Sensitivity to the regions of high ocean variability: The observations in these regions

significantly contribute to the global statistics computed between altimetry and Argo data. However, the results do not allow us to determine whether an increased sampling of these regions by the Argo network would improve the results of altimetery validation.

Additional recommendations can be mentioned:

The network coverage should be enlarged at high latitudes and over shallow waters

The quality control of the Argo data should be improved and delayed-mode quality-

controlled data should be made available more frequently.

Task 4.2 Ocean Colour (Task leader: ACRI-ST) During this year, the document D4.422 about past studies and plan for E-AIMS was completed and submitted. We also went further into the elaboration of techniques to derive cross-validation of bioprofilers and Ocean Colour.

It appeared Bio-Argo may have a significant impact on ocean colour remote sensing verification and validation. As seen on the figure 4.2.1 below, matchups between Chl-A from remote sensing and Chl-A integrated over the upper layer measured by Bio-Argo are very good and will be improved with new adjustments during the next period.


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Figure 4.2.1: 875 matchups between Bio-Argo and remote sensing Chl-A (Globcolour)

Indeed, thanks to an increasing number of floats and to the quality of their measurements, the possibility to use Bio-Argo profilers to validate/verify remote sensing data seems realistic. Programing the float to perform its profiling process at the same time the satellite is passing over it could be one of the proposed recommendations to improve the reliability.

Nevertheless, remote sensing only offers a 2D perspective of the studied biochemical variables as the in-depth information is not available. A combination of remote sensing with biogeochemical models (such as the ones used for GMES/Copernicus marine service) already focuses a lot of attention but Bio-Argo could be a very valuable additional input of this kind of assimilation. A constant adjustment between a wide network of in-situ data, model and remote sensing would increase both the amount of trusty data and the consistency. Such merged data will compose a strong tool for assessing biochemical status of our oceans.

Task 4.3 Sea Surface Temperature (Task leader: UKMO) The work carried out for this task comprises:

• An assessment of sampling requirements for the use of Argo to validate SST in daily

situ/satellite analyses • The implementation of the first routine assessment of OSTIA and GMPE SST products

using near-surface Argo data as a reference

Validation of the new OSTIA diurnal product using high vertical resolution Argo data will be completed by March 2015 as planned.

The sampling error associated with the monthly mean difference between the OSTIA analysis and near-surface Argo observations (using the shallowest observations between 3-5 m depth) has been investigated. Figure 4.3.1 demonstrates that the monthly total number of near-surface Argo


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observations is suitable for a sampling error of <0.03 K for most major ocean regions, for the representative example month of December 2013. The exceptions are western boundary current regions, with sampling errors up to 0.082 K, and the Polar regions, with sampling errors up to 0.200 K. Higher sampling errors in western boundary current regions are due to larger standard deviations of Argo-analysis differences in these areas, whereas the higher sampling errors in Polar regions are due to a lack of Argo observations of the ocean under sea ice. The sampling errors in these regions can be a high proportion of the Argo-analysis mean difference statistics. In order to achieve a sampling error of 0.02 K across the global ocean, the number of Argo observations in the western boundary current regions would need to be increased by up to 1300 observations per month (figure 4.3.2).

Figure 4.3.1: Monthly sampling error for recent distribution of Argo observations (from SST: Results and

Recommendations, Figure 3)

Figure 4.3.2: Total number of Argo near-surface observations for December 2013 minus monthly number

of observations required to achieve sampling error of 0.02 K in all ocean areas (from SST: Results and

Recommendations, Figure 4)

The largest increase in the number of observations per month would be required in the region of the Falklands/Malvinas current off the coast of Argentina. This region has a similar standard deviation to that of the Gulf Stream, but fewer observations means the sampling error is correspondingly higher (at 0.082 K compared to 0.042 K for the Gulf Stream region). In order for the sampling error of the Falklands/Malvinas region to match that of the Gulf Stream region (the next highest globally), an increase of ~300 observations per month would be required.

The number of available Argo observations is sufficient that regional standard deviations are not dependent on this number when calculating monthly statistics. The North Atlantic is a possible exception, suggesting more floats are needed in this region. At numbers of observations available for calculation of weekly or daily statistics, standard deviation is dependent on this number and is therefore unreliable. The number of observations needed for convergence towards a reliable standard deviation varies with ocean region, depending on the variability of the region.

The monthly total number of near-surface Argo observations currently available is sufficient to identify a statistically significant difference in standard deviation between two analyses where large differences have been previously demonstrated. Regions with larger standard deviations require more observations to determine statistical significance of differences between analyses. The Pacific has comfortably enough observations to demonstrate statistical differences between the


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analyses, whereas the maximum number of observations available in the South Atlantic is only just high enough to produce a consistent “statistically significantly different” result. This demonstrates a requirement for more floats in the South Atlantic.

The results from the assessments of standard deviation reliability and detection of statistically significant differences between analyses illustrate that more floats are needed in the North and South Atlantic respectively. These results were not broken down into smaller regions but it is reasonable to assume that the results are due to the high variability in the Gulf Stream and Falklands/Malvinas regions respectively.

The uncertainty on mean and standard deviation statistics of analysis differences to Argo can be quantified using a bootstrap method. It is recommended that it should become standard to present these statistics with uncertainty estimates, to take into account that some regions will have high sampling errors.

The size of ocean area used to calculate assessment statistics is a trade-off between the ability to identify regional issues and the need to obtain sufficient observations to produce reliable statistics. An increase in the number of near-surface Argo observations available would be required to validate SST analyses on weekly or daily frequencies, or monthly over smaller regions than those defined by MyOcean. The current distribution of Argo floats (nominally 3x3o) should be maintained in order to allow their use for monthly validation of SST analyses over the MyOcean regions to continue.

Routine monthly validation of OSTIA and GMPE SST products using quality-controlled Argo observations from the EN4 database2 has now been set up. Timeseries of global and regional statistics (using the MyOcean region definitions) are freely available on the web:

http://ghrsst-pp.metoffice.com/pages/latest_analysis/sst_monitor/argo

Statistics will be updated on a monthly basis. Uncertainty estimates are shown on plots of both mean and standard deviation of the differences between the analyses and Argo, obtained from 95% confidence intervals using a bootstrap method.

Task 4.4 Sea Surface Salinity (Task leader: CSIC) The work done during the second period of twelve months of this task has focused on the actual results of using Argo data to validate the SMOS sea surface salinity (SSS) products. This study has been summarized in the third Deliverable provided by this task (D4.443: Results and Recommendations) and were presented in the E-AIMS WP3 & WP4 final Workshop held in Toulouse on December 12, 2014.

2 Good, S. A., Martin, M. J. and Rayner, N. A. (2013), EN4: quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates. J. Geophys. Res. 118, 6704-6716, DOI: 10.1002/2013JC009067.

http://ghrsst-pp.metoffice.com/pages/latest_analysis/sst_monitor/argo


59

These validation activities have relied on the match-up pairs between the estimate of the SSS provided by the products generated at the SMOS-BEC (http://cp34-bec.cmima.csic.es/) and an estimate of the SSS estimated from an Argo salinity profile.

Three SSS products have been used for the validation activities. All these products are defined on a 0.25 degree grid and correspond to nine-day time averages (every three days). The three products are: i) A binned product (called L3) constructed from the weighted average of all the Level 2 SSS retrievals produced by ESA; ii) An optional interpolation product (called OI) that is used to extrapolate and reduce the noise of the L3 product; and iii) A data-fusion product (called L4) that merges the L3 salinity information with the information from OSTIA sea surface temperature data.

In the case of the Argo profilers, the following selection rules are applied to estimate the SSS value:

• The profile must contain Delayed Mode quality controlled data. • Only the primary CTD measurements from each profile is used. • Pressure, Temperature and Salinity must have an associated Quality Control of “good”. • The Quality Control of geographical position and date position is accepted if it has been set

to 1 (good), 2 (probably good), 5 (Value changed) or 8 (Interpolated value). • The salinity value used will be the closest one to the surface (although values shallower

than 0.5 m are disregarded). • Salinity data from PROVOR, SOLO (as well as for those profilers where the profile type

variable is set the UNKNOWN) instruments are not considered at depths shallower than 5 m. These profilers did not pump water at a depth shallower than 5 m].

It has been noticed that the number of available Delayed Mode profiles has been decreasing during the validation period (2011-2013). If in January 2011 more than 6000 Argo salinity profiles are available, by December 2013, less than 1000 Argo salinity profiles are available.

After a series of sensitivity experiments, the following criteria are used to account for a match-up between SMOS and Argo:

• The Argo data must have been taken no deeper than 10 m below the ocean surface. • The match-up has to be located farther than 1000 km away from the coast. • The surface temperature estimated from the in-situ Argo must be between 5C and 28C. • The average precipitation for the corresponding match-up than 1 mm/day. • The difference between the SST value used during the SSS retrieval and the uppermost

measure of temperature obtained by the Argo profile should be smaller than 1C.

The results indicate that robust estimates of the difference between SMOS and Delayed Argo have been found. The standard deviation of the differences are of the order of 0.29 and 0.23 (in the practical salinity scale) depending if the comparison is done in the latitudinal band of 60S-60N or in the 30S-30N band respectively. A slight negative bias (SMOS fresher) has been systematically found: -0.01 and -0.03, respectively. In the tropical region, the systematic bias becomes even more negative when match-up pairs under the influence of rain are included. On the other hand, studies in which the match-up is restricted to those Argo profiles where salinity measurement is shallower than 4 meters, the sign of the bias changes from negative to positive. The raison of such behavior is still unclear and additional research and information is required.

http://cp34-bec.cmima.csic.es/


60

Thus, further increase in the understanding of the error sources contaminating the SMOS retrievals and the improvement of the monitoring of the satellite quality would benefit from:

Speed up of the scientific calibration (Delayed Mode) process of Argo data. Increase the number of measurements in the upper four meters of the ocean

Task 4.5 Synthesis (Task leader: CSIC) The E-AIMS WP3 & WP4 Final Workshop was held at CLS, Toulouse on December 12, 2014. It was organized after the international OSE/OSSE workshop organized jointly by the GODAE OceanView OSE Task Team, GSOP/CLIVAR and E-AIMS. The workshop introduced the final results of the impact studies from the Copernicus Marine Service and from the seasonal/decadal forecasting centers (Mercator Ocean, UKMO, and INGV). It also introduced the final results and recommendations from the validation of remote sensing data (Altimetry, Ocean Colour, Sea Surface Temperature and Sea Surface Salinity).

Our plans for the year 2015 is to produce the final report summarizing the results presented at the Workshop and the final set of deliverables issued by the four tasks of the WP. The main goal of the final report will be the discussion of made by the task members about the recommendations for the evolution of Argo.


61

WP5 R&D on Euro-Argo data system and interfaces with GMES M a r i n e Service

(WP leader: partner 1, Ifremer, France)


The objective of this WP is to undertake the R&D activities necessary to improve the Euro-Argo data system to better serve the Copernicus Marine Service and adapt it to the future generation of Argo profiling floats (biogeochemical, deep, high vertical sampling). It is divided in 3 tasks which are dedicated to:

• The development of Real Time and Delayed mode QC procedure for oxygen variable;

• The development of Real Time and Delayed mode QC procedure for other biogeochemical

variables;

• Enhancement of the European DACS to process the new generation floats tested in WP2.

Task 5.1: Define, prototype and test real time and delayed mode data processing techniques for oxygen variable (Task leader: Ifremer)

The objective of this task is to reach an international consensus on the real-time and delayed- mode quality control procedures of oxygen data from autonomous profiling instruments. In 2014, the following sub-tasks have been achieved:

The manual describing the management of oxygen data has been updated (Thierry et al., 2014) to take into account evolutions in oxygen sensors and in calibration equations. This manual will continue to be updated when needed. A new format for Argo data has been defined. The core parameters (p, T, S) are in the so-called c-file. Oxygen data, as well as other biogeochemical data, are in the so-called b-file (see http://www.argodatamgt.org/Documentation).

Real-time quality control tests for oxygen data were defined and validated by the Argo Data Management Team in 2012 (Wong et al., 2014). They are now implemented in most DAC (see Table below):

AOML BODC CORIOLIS CSIO CSIRO INCOIS JMA KMA KORDI MEDS NMDIS

done done done ? Done done no End of 2014

no floats

No (no more active floats)

No floats

Table 1 : Status of implementation of Real Time QC tests on O2 data.

In terms of delayed mode, the existing methods are based on adjustments from climatology, from reference calibrated in situ data and from “in air” measurements. The first method is useful when in situ or “in air” measurements are not available. Using reference in situ data provides much better

http://www.argodatamgt.org/Documentation)


62

results, especially in areas where the climatology is not well defined or subject to large interannual variability (e.g., North Atlantic Ocean). The adjustment from “in air” measurements have been done by few groups and provide very good results in agreement with Winkler values to within 2 µmol kg-1

near surface. This method is very promising and the ADMT for Bio-Argo float suggests that all Argo floats with O2 sensor should acquire “in air” measurements (see Bio-Argo ADMT15 meeting report, http://www.argodatamgt.org/Data-Mgt-Team/Meetings-and-reports). Finally, some optodes are probably subject to drift and this should be investigated in the future. The “in air” measurements would allow us to detect and correct those drifts.

The optimal interpolation tool ISAS initially developed for temperature and salinity data (Gaillard et al., 2008) was adapted to oxygen data. This tool is useful for a careful secondary quality control procedure and for interpolating data on isobaric levels. A first analysis of all Argo oxygen data available since 2004 and adjusted from the WOA climatology or from a reference calibrated in situ data was done (figure 5.1.1).

Figure 5.1.1: Dissolved oxygen concentration anomaly at 300 m depth compared to the WOA09. All Argo oxygen data available at Coriolis GDAC were interpolated with ISAS. The real-time and

delayed mode QC procedure was applied to the data before the interpolation.

http://www.argodatamgt.org/Data-Mgt-Team/Meetings-and-reports)


63

References • Gaillard F., E. Autret, V. Thierry, P. Galaup, C. Coatanoan, T. Loubrieu, 2009: Quality

control of large Argo datasets. Journal of Atmospheric and Oceanic Technology, 26, 337- 351, doi: 10.1175/2008JTECHO552.1.

• Thierry V., D. Gilbert, T. Kobayashi and C. Schmidt, 2013: Processing Argo-oxygen data at

the DAC level, v1.3. Available at http://www.argodatamgt.org/Documentation

• Wong, A., R. Keeley, T. Carval and the Argo Data Management Team, 2014: Argo quality control manual, version 2.9.1, November 18th 2014 : http://dx.doi.org/10.13155/33951

Task 5.2: Define and test real time and delayed mode data processing techniques for other biogeochemical variables (Task leader: ACRI-ST)

The tasks completed during the second year of the E-AIMS project were split into one task dealing with the Real Time QC (RT-QC) and one task dealing with the Delayed Mode QC (DM-QC).

The RT-QC has to be performed automatically, e.g. every day before data is released and made available through the Coriolis data centre. The tasks in E-AIMS have been to define and tune QC tests and, once validated, to produce a technical note addressed to Coriolis for implementation. Five tests have been established in partnership with the experts in LOV. These tests follow a sequential procedure (allowing different flagging score at the end of the process) that is summarized on figure 5.2.1.

The tests are mainly addressing: the dark value (which is the value of Chlorophyll value at high depth which should be equal to zero), a range value out of which the Chlorophyll is considered as non-valid, a negative spike filtering and a correction of quenching. This last correction is rather sensitive and is still subject of fine tuning at the end of the second year of E-AIMS – there seems to be an over-correction when compared to available information from satellite.

QC-RT procedures have also been derived for bbp and nitrates (NO3). They mainly consist in a flagging and in an optionally correction if the data is not lying in a predefined range of values.

These procedures have been specified and documented to be implemented at Coriolis. Thresholds values are still subject to modification/tuning

http://www.argodatamgt.org/Documentation

http://dx.doi.org/10.13155/33951


64

Figure 5.2.1: RT-QC tests for biogeochemical variables

.

A number of investigations and research works have been performed to define the QC in Delayed Mode. These tasks cover the following items:

• Proposition of metrics/indicators and technics to assess quality of observations (and to

make use of QC-RT status and outcomes). • Production of synthesis of these metrics and checking them vs acceptable thresholds. • Proposition of threshold values above/under which operators need to be

alerted/warned/informed. • Feedback to QC-RT about relevance/tuning of QC-RT tests. • Documentation on the whole QC-DM.


65

These works were more specifically focused on: • Computation of level of noise on each profile of the same cruise/floats. Noise is computed

as the residual of the signal after adapted filtering, this noise should be rather stable unless it indicates an anomaly.

• Screening of the large depth Chlorophyll value (dark value). This output of the QC-RT shall be stable unless it points towards a sensor trouble.

• Computation of Cross-Correlation of several successive profiles; it is assumed that successive profiles in a reasonably narrow time/space window have to be correlated.

• Matchups with coincident ocean colour (Globcolour); Different temporal window (+/-1j, 3j..) and macropixel size (3x3, 5x5) are used to check temporal-spatial variability. Also time series of differences (sat-float) are analysed.

• Comparison with climatology under the form of bio-regions: this last point is still under examination- the outcomes will more likely be recommendation on the type of bio-regions of use for this QC-DM and the methodology for comparison and validation

All these indicators have been made available through a dedicated web site offering large flexibility to the experts for QC and validation (seasiderendezvous.eu). An example of expert dashboard is displayed on figure 5.2.2.

Figure 5.2.2: Expert dashboard for Delayed Mode QC of biogeochemical variables.

The relevance of every test and indicators is examined with a statistical approach. According to this analysis, these quality indicators might be slightly adapted in the near future.

Task 5.3: Develop the Euro-Argo DACs for the new Argo floats (Task leader: Ifremer) Within WP2, new types of floats have been deployed that implement new data transmission schemas, enhancement of the floats format to integrate the new variables and therefore upgrade of the Euro-Argo data centres processing chains. These changes have been tested at Euro-Argo


66

level and discussed with the International Argo Data Management partners at the Argo Data Management meetings held on November each year as it is important to maintain coherency between the European Argo fleet data and the international Argo fleet. Because of this constraint, the delay between procedure development by scientists and implementation at DACs is slightly longer but the processing chains are set up in a more sustained manner as they are agreed by the community and went through validation both at European and International scale. Final agreements were reached at the Argo Data Management meeting (ADMT) in Ottawa in November 2014.

The two Euro-Argo DACs (Ifremer/Coriolis and BODC) have upgraded their processing chains to process deep floats and high resolution surface profiles coming from multiple float providers (NKE, WEBB, SeaBird, METOCEAN). For Bio-Argo data management, Ifremer/Coriolis and BODC took a leading role in the definition of Bio-Argo data format at the Argo Data Management Meeting that was held in November 2013 in Liverpool and in November 2014 in Ottawa. The implementation of 2013 agreement in Ifremer and BODC processing chains for biogeochemical floats both in Artic and Ice free oceans have been turned into operation and finalized during summer and autumn 2014.

Real time data processing and quality control for Oxygen have been implemented both at BODC and Ifremer/Coriolis and results reported at last ADMT meeting. Real time processing of biogeochemical variables has been implemented at Ifremer/Coriolis and BODC and Quality control procedures are under implementation as the agreement was only reached in November 2014 during the International Bio-Argo meeting that was preceding the ADMT in Ottawa. This activity will be continued and monitored within WP6.


67

WP6 Real time processing, impact and final assessment (WP leader: partner 3, OGS, Italy)


The objective of WP6 is to demonstrate that Euro-Argo data centres can process in real time the data of the new floats developed and tested in WP2, distribute them to MyOcean modelling and forecasting centres and satellite Cal/Val teams and that these teams can effectively use these new data sets. Float data will be either directly assimilated or used for validation. The impact will be limited given the limited number of floats but the objective here is mainly an end-to-end assessment. The WP also includes the final assessment of the project (synthesis of all WPs and final recommendations).

WP6 is divided into 4 tasks:

• Task 6.1 : Real time data processing of new Argo floats and interfaces with MyOcean

(T0+18 - T0+36)

• Task 6.2 : Impact and use for GMES Marine Service (T0+24 - T0+33)

• Task 6.3 : Impact and use for satellite Cal/Val (T0+24 - T0+33)

• Task 6.4 : Final assessment (T0+33 - T0+36)

The total duration of the WP is 18 months, starting at T0+18. The deliverables and milestones are scheduled as follows:

• T0+18 (June 2014): New floats deployed in WP2 are processed in real time and delivered

to MyOcean and satellite Cal/Val (milestone MS611)

• T0+33 (September 2015): Report of new float data real time processing by Euro-Argo data centers (deliverable D6.611)

• T0+33 (September 2015): Use and impact of new floats for GMES Marine Service

(deliverable D6.621)

• T0+33 (September 2015): Use and impact of new floats for satellite Cal/Val (deliverable D6.631)

• T0+36 (December 2015): Final synthesis report (deliverable D6.641)

The work carried out during the second year of the project was essentially part of Task 6.1 about the processing in real time of the data provided by new floats and the data delivery to MyOcean and satellite Cal/Val. The activities of the other tasks will be performed during the third year of the project. Details about the work accomplished during the second year in Task 6.1 are provided below.


68

Task 6.1: Real time data processing of new Argo floats and interfaces with MyOcean (lead: Ifremer, participants: Ifremer, NERC)

The purpose of this task is to process the new floats deployed within E-AIMS using the updated processing chains and Quality Control procedures set up in WP5.

Both BODC and Ifremer/Coriolis have set up the processing chains to decode the WP2 floats. The processing chains have been turned to operation and the data delivered to the Argo DACs. Since summer 2014 the floats can be delivered to the Argo GDAC that have been updated to accept these extensions to Argo. Following the Argo Data Management meeting in Ottawa last November, both Coriolis and BODC are updating their processing chain to take into account the meeting recommendation.

Concerning the RTQC procedure, they have been implemented in both DACs for oxygen and need to be implemented for chlorophyll-a, backscatter and nitrate as they were only validated at the Bio- Argo international meeting last November.

The temperature and salinity measurements are sent to the GTS as well as the near surface temperature. For oxygen they will be distributed in BUFR format when validated by WMO. For the other bio-Argo parameters it will take longer and it is likely to happen after the end of the project (action at WMO level). All the floats available on GDAC are integrated in the MyOcean In-situ Thematic Assembly Centre for distribution to the MyOcean Modelling and Forecasting Centres.

A WWW page (http://www.coriolis.eu.org/Data- Products/Maps-corner/Argo- Projects/Europe/E_AIMS) has been set up on Coriolis WWW site that allows viewing and downloading the E-AIMS floats

Task 6.2: Impact and use for GMES Marine Service (lead: Mercator Ocean, participants: Mercator Ocean, Met Office, INGV, USOF)

Task not active in 2014.

http://www.coriolis.eu.org/Data-Products/Maps-corner/Argo-Projects/Europe/E_AIMS






69

Task 6.3: Impact and use for satellite Cal/Val (lead: CLS, participants: CLS, ACRI-ST, UKMO, CSIC)

. Task not active in 2014.

Task 6.4: Final assessment (lead:OGS, participants: OGS, Ifremer)

Task not active in 2014.

WP7 Scientific and technical coordination (WP leader: partner 1, Ifremer, France)


WP8 Communication and dissemination (WP leader: partner 1, Ifremer, France)



70

Project management during the period

The project started on January 1st 2013. The kick off meeting was organized in Brest from January 16 to January 17. A steering committee was organized in June 2013 in Southampton. A specific WP3 workshop was organized in September 2013 in Toulouse. The first annual meeting, first annual review and 2nd steering committee were organized in Brussels in January 2014. The 3rd steering committee meeting was held in Brest on June 2014. The WP3&WP4 final workshop was finally organized in Toulouse together with a GODAE OceanView/CLIVAR international scientific workshop in December 2014. All meeting minutes and presentations are available on the E-AIMS internal WWW site.

In 2014 work has been performed according to plans and all planned deliverables for 2014 were issued. Management, scientific coordination and communication activities (WP1, 7 & 8) included preparation and running of annual meeting, annual review and steering committee meetings including writing meeting minutes, annual report preparation, interaction with REA, interaction with the Euro- Argo ERIC organization, interaction with MyOcean project, discussing with stakeholders (GMES/Copernicus bureau, EEA, DG Research, EuroGOOS) and development and maintenance of the E-AIMS WWW site (internal and external). These activities have been carried out in close cooperation with the Euro-Argo ERIC management board and program manager.

Communication activities have included the preparation of leaflets on each of WP2 Tasks as well as a summary of main WP3/WP4 results. All these leaflets are available on the external E-AIMS WWW site. Short float stories will also be integrated in the Euro-Argo educational WWW site in January 2015.

A project brochure was also prepared and completed in November 2014. It provides a description of the project and its workpackages with illustrations based on results and activities carried out during the first half of the project.

Work has been performed according to plans and all planned deliverables for 2014 (except for three deliverables that will be submitted end of January instead of end of December, i.e. a one month shift) were issued. The project team worked very well during the second year of the project and the main objectives of the project have been met. There is still a time shift for two tasks of WP2 (see previous sections). This does not impact the DOW and deliverables. WP3 and WP4 are completed and deliverables were submitted. It is expected, however, that as the scientific analyses of results are extended, new versions of deliverables could be submitted by mid 2015.

The project public WWW site was set up at the start of the project. It is embedded in the Euro-Argo research infrastructure WWW site (www.euro-argo.eu) to highlight that E-AIMS is a project that contributes to the development of the Euro-Argo research infrastructure. Specific WWW pages for the project are available at the following address (www.euro-argo.eu/eaims). A summary of the project, its workpackage structure and its organization is given. The WWW was recently updated to provide a summary of project achievements for the second year and include presentations from the final WP3 and WP4 workshop (December 2014). An internal part provides access to all internal documentations (e.g. meeting reports, meeting presentations, deliverables).

http://www.euro-argo.eu/

http://www.euro-argo.eu/eaims

1st E-AIMS periodic report

Deliverables and milestones tables Deliverables Already updated on Participant Portal. Comments added

Del. no.

Deliverable name

Version

WP no.

Lead beneficiary

Nature

Dissemination

level

Delivery date from

Annex I (proj

month)

Actual / Forecast

delivery date Dd/mm/yyyy

Status No submitted/ Submitted

Comments

1

D5.1.1

Real-time and delayed mode methods for oxygen

2

5

IFREMER

R

PU

Mo12

22/12/2014

Submitted

New version submitted on December 2014

2

D5.2.1

Real-time and delayed mode methods for biogeochemical parameters

2

5 ACRI-ST

R

PU

Mo12

22/12/2014

Submitted

New version submitted on December 2014

3

D5.3.1

Upgrades of the Euro-Argo data centers

1

5

IFREMER

R

PU

Mo 18

30/06/2014

Submitted

4

D3.1.3

Global ocean analysis and forecasting: OSE/OSSEs results and recommendations

1

3

Mercator Ocean

R

PU

Mo 21

10/12/2014

Submitted

5

D3.2.3

Weather, seasonal and decadal forecasting: OSE/OSSEs results and recommendations

1

3

UKMO

R

PU

Mo 21

10/12/2014

Submitted

6

D3.3.3

Mediterranean and Black Sea: OSE/OSSEs results and recommendations

1

3

INGV

R

PU

Mo 21

10/12/2014

Submitted

1st E-AIMS periodic report

Del. no.

Deliverable name

Version

WP no.

Lead beneficiary

Nature

Dissemination

level

Delivery date from

Annex I (proj

month)

Actual / Forecast delivery

date Dd/mm/yyyy

Status No submitted/ Submitted

Comments

Comments

7

D4.1.3

Altimetry: impact study results and recommendations

1

4

CLS

R

PU

Mo 21

10/12/2014

Submitted

Submission of deliverables D4.413, D4.423, D4.433, and D4.443 by December 10, 2014 instead of Sept 30. Any update required for these deliverables may be submitted as an internal deliverable by March 2015.

8

D4.2.3

Ocean Colour: impact study results and recommendations

1

4

ACRI-ST

R

PU

Mo 21

10/12/2014

Submitted


Del D4.2.3 has been named by error in Annex 1"SST:result and recomandations" instead of "Ocean Colour: impact study results and recommendations"

9

D4.3.3

SST: results and recommendations

1

4

UKMO

R

PU

Mo 21

10/12/2014

Submitted


Del D4.3.3 has been named by error in Annex 1 as "Ocean Colour: impact study results and recommendations" instead of "SST: results and recommendations"

10

D4.4.3

Sea Surface Salinity: impact study results and recommendations

1

4

CSIC

R

PU

Mo 21

10/12/2014

Submitted


11 D3.4.1 Final synthesis report 1 3 Mercator R PU Mo 24 31/12/2014

Submitted

12 D4.5.1 Final synthesis 1 4 CSIC R PU Mo 24 31/12/2014 Submitted

13 D8.1.2 Float stories in 1 8 IFREMER O PU Mo 24 31/12/2014

Not submitted To be submitted in March 2015

report

WWW site

Ocean

Milestones To fill in directly on Participant Portal


Milestone number

Milestone name

WP number

Lead beneficiary number

Delivery date from Annex I

Achieved Yes/No

Actual / Forecast achievement date dd/mm/yyyy

Comments

MS11

Deployment of 4 floats with two oxygen sensors

WP2

10

12

Yes

31/07/2014

2 NAVIS deployed, 1 Arvor deployed, 1 Arvor not deployed was sent back to Ifremer test facility where it underwent extensive tests. It will be deployed mid 2015 during the Ovide mission.

MS21

Deployment of 2 deep floats

WP2

6

12

No

28/02/2015

Floats will be deployed February 2015

MS41

Deployment of 4 floats with improved satellite communication

WP2

3

12

Yes

31/03/2014 2 NAVIS float deployed, 2 Apex deployed

1 ARVOR A3 deployed mid 2014 1 ARVOR A3 to be deployed in early 2015

MS51

Deployment of 1 Arctic float

WP2

9

12

Yes

31/07/2014 1 NEMO float deployed during Summer 2014

MS611

New floats deployed in WP2 are processed in real time and delivered to MyOcean and satellite Cal/Val

WP6

1

18

Yes

31/10/2014

MS311

WP3 workshop (held together with WP4 workshop)

WP3

11

21

Yes

12/12/2014

Workshop was held on December 12 in Toulouse

MS411

WP4 workshop (held together with WP3 workshop)

WP4

15

21

Yes

12/12/2014

Workshop was held on December 12 in Toulouse

MS52

Deployment of 1 Arctic float

WP2

9

24

Yes

31/07/2014

1 NEMO float deployed during Summer 2014

70

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