1. First results of the NAOS project: Analysis of the interactions between mixed layer depth, nitrate and chlorophyll during a spring bloom event in the North-Western Mediterranean Sea Héloïse Lavigne (Laboratoire d’Océanographie de Villefranche) OGS Seminar Triestre 24/01/2014

2. Part 1: Description of the NAOS project

3. The Argo project Argo is a global array of 3,000 free- drifting profiling floats that measures the temperature and salinity of the upper 2000 m of the ocean.

4. Biogeochemical parameters are under sampled: example with chlorophyll-a All chlorophyll-a observations available in the World Ocean Database 2009

5. Temperature and salinity Low vertical resolution Fixed time lag between two profiles Temperature and salinity Low vertical resolution Fixed time lag between two profiles Chl and CDOM fluorescence, Oxygen, Irradiance, PAR, Nitrates, back scattering. High vertical resolution Changeable time lag between two profiles Chl and CDOM fluorescence, Oxygen, Irradiance, PAR, Nitrates, back scattering. High vertical resolution Changeable time lag between two profiles From Argo… to Bio-Argo

6. Definition and Goals Bio-Argo An oceanic observing system based on a large array of profiling floats equipped with biogeochemical sensors. Bio-Argo data share a unique data management and Bio-Argo floats represent a fully, inter- operating, sub-set of the Argo T/S network. Goal Providing systematic biogeochemical observations that would greatly reduce the uncertainties in our estimation of elemental (C, N, O) fluxes at global scale and increase our ability to detect changes in these fluxes.

7. Evolution of the Bio-Argo net work October 2009 December 2013 October 2005

8. The NAOS project Novel Argo Ocean observing System A French long-term project (EQUIPEX 2009-2019) to consolidate and improve the French and European contribution to the international Argo observing system and to prepare the next decade of Argo. (PI P.Y. Le Traon) A whole WP dedicates to the implementation of a Bio-Argo pilot network in the Mediterranean Sea

9. Mains NAOS objectives The first objective of NAOS is thus to strengthen the French contribution to the Argo core mission. Each year, France contributes to the deployment of 65 floats. Thank to NAOS,10 to 15 additional floats will be deployed each year over the period 2012- 2019 (110 floats in total). NAOS aims to sustain innovative technological evolutions. The aim is to improve the reliability, lifetime, energy savings and costs of the floats designed for the Argo core mission. NAOS is going to develop, validate and deploy the next generation of Argo profiling floats (biogeochemical floats and deep floats). 70 new generation floats will be deployed in three pilot areas (Mediterranean, Arctic and North Atlantic).

10. NAOS organisation WP1: Consolidation of the French contribution to Argo (Ifremer) WP2: Developpement of the next generation of the French Argo floats (Ifremer). WP3: Biogeochemical floats in the Mediterranean Sea (LOV/UPMC) WP4: Biogeochemical floats in the arctic Sea (CNRS/UMI Takuvik) WP5: Deep oxygen floats in the North Atlantic (UBO/IUEM/LPO)

11. Mains goals of the NAOS WP3: Biogeochemical floats in the Mediterranean Sea  The NAOS WP3 is dedicated to the deployement to 33 Bio-Argo floats in the Mediterranean Sea over the 2013-2016 period.  The NAOS WP3 aims to design a « prototype » for the Bio-Argo network: strategies for deployments and sampling, Quality Control, synergies with satellite observations and modeling are considered in the WP.

12. Scientific objectives of NAOS WP3 1. To confirm the bio-regionalization of the Med. 2. To characterize forcing responsible of this bio-regionalization (physical and chemical). The impact of physical and chemical forcing have been already characterized at climatological scale (Lavigne et al., 2013). However, the climatological scale showed its limits. Bio-Argo data will help to go further. 3. To assess the temporal variability of this bio-regionalization over 10 years. D’Ortenzio and Ribera d’Alcalà (2009)

13. 33 floats with biogeochemical sensors deployed in the NAOS WP3 Nitrate sensors O2 sensor Iridium antenna Irradiance + PAR Optical active sensors: Fluorometer CDOM Fluorometer Chla Backscatterometer CTD

14. The iridium two ways transmission Real time observations Make the decision to change the sampling strategy New commands are take into account by the float.

15. Floats deployments January 2014: 12 floats deployed (2 recovered) + 2 additional floats in the Ionian Sea. In 2016: 15 additional floats will be deployed.

16. Part 2: First results of the NAOS program Analysis of the interactions between mixed layer depth, nitrate and chlorophyll during a spring bloom event in the North-Western Mediterranean Sea

17. The Mediterranean spring bloom As observed by ocean color satellite Bosc et al., 2004. Monthly [chl-a] averaged. Year 1999 Normalized seasonal cycle of [Chl-a] in the blooming North-Western Mediterranean Sea. From D’Ortenzio and Ribera D’Alcalà (2009) Spring bloom

18. Impact of MLD on the N-W Mediterranean Spring bloom Some hypotheses (results of my Ph.D. work) ~30 days interval between the date of MLD-Max and the date of CHL-Max Increase in [Chl-a] SAT due to surface nutrient inputs brought by mixing Limitation of phytoplankton growth due to a deficit of light (in agreement with Sverdrup, 1953, theorie). The deficit of light is due to deep water mixing. Bloom: A rapide increase in [Chl-a] SAT because light and nutrients are both presents.

19. Some questions remained open Spring bloom or winter bloom? Is the seasonal [Chl- a] surf cycle observed by satellite is misleading? Is it representative of the seasonal cycle of total chlorophyll content? (Behrenfeld, 2010) Does MLD shallowing effectively triggers the spring bloom? (Sverdrup, 1953, critical depth hypothesis) What is the impact of the high frequence MLD variability on phytoplankton dynamic?

20. Float data available Data 4 Bio-Argo floats that drifted in the Bloom – NW bioregion during the nov 2012 – june 2013 period P_SUNA : T, S, [NO 3 - ] (PRONUTS) N_001i: T, S, [Chl-a], [NO 3 - ] (NAOS) N_035b: T, S, [Chl-a] (NAOS) N_017b: T, S, [Chl-a], [NO 3 - ] (NAOS)

21. Calibration of the chlorophyll fluorescence data Chlorophyll fluorescence is only a proxy for [Chl-a]. A calibration procedure has to applied on fluorescence data. 1.Correction for Non Photochemical Quenching 2.Correction of the offset and slope. First, α i and β i are determined individually for each fluorescence profile (quoted i) using the Lavigne et al., 2012 procedure. A unique set of α and β coefficients are determined for each float by computing the median of the α i and β i Checking for no sensor drift.

22. The calibration procedure (Lavigne et al., 2012) Applied on each individual fluorescence profile and based on satellite ocean color observations Deep fluorescence values used to compute β Empirical relationship (Uitz et al., 2006) Step 1: NPQ correction Step 2: β correction Step 3: α correction

23. Validation of the calibration procedure with concomittant HPLC profiles at deployment. __ before calibration __ after calibration + HPLC

24. QC and calibration of [NO 3 - ] data Principle of the measurement UV Absorption of ultra violet wavelength NO 3 - Br - CDOM According to the Beer-Lambert law Nitrate concentration Salinity Measured by SUNA Extinction coefficients Baseline, contained CDOM absorption SUNA (SATLANTIC) Measurement cell We can retrieve [NO 3 - ], e, f and S by fitting this equation for λ ranging between 217 and 242 nm.

25. Sensor drift Offset correction As nitrate concentration is supposed to be relatively constant at depth (deeper than 800m), each profile was off-setted in order that the average [NO 3 - ] equals the concentration measured from water sampling at deployment (about 8.5µM).

26. Validation of the [NO 3 - ] calibration __ after calibration __ before calibration + water sampling

27. Results Data 4 Bio-Argo floats that drifted in the Bloom – NW bioregion during the nov 2012 – june 2013 period P_SUNA : T, S, [NO 3 - ] (PRONUTS) N_001i: T, S, [Chl-a], [NO 3 - ] (NAOS) N_035b: T, S, [Chl-a] (NAOS) N_017b: T, S, [Chl-a], [NO 3 - ] (NAOS)

29. Focus on MLD and [NO 3 - ] MLD During the autumn and winter period, a deepening of the MLD up to ~70m drives to a significant increase in [NO 3 - ] MLD. However, the [NO 3 - ] MLD increase is not linear. During the bloom period, the MLD versus [NO 3 - ] MLD relationship is very complex. During the oligotrophic period, [NO 3 - ] is close to 0µM and MLD range between 10 to 50m. The transition between oligotrophic ([NO 3 - ] = 0µM) and autumn ([NO 3 - ] = 0.5µM) condition could not be observed.

30. Focus on [CHL] surf and int Globally, [CHL] surf and int seasonal cycles are consistent. Underestimation of [CHL] surf compared to int during deep winter mixing. During spring bloom, [CHL] surf peaks are not necessary reproduced by int peaks.

31. From mixed to stratified profiles « Mixed » shape« Stratified » shape Chlorophyll profiles during bloom. These examples can explain the high variability and sometime the inconsistency between [CHL] surf peaks and int peaks.

32. Focus on bloom initiation It clearly appears that MLD shallowing drives to an increase of [Chl-a] surf. However, the impact of MLD variability on int is less evident. To my mind, it could be the relatively long period of shallow MLD (ranging between 20 and 100m) that triggers the bloom. March Relatively shallow MLD during a long period March

33. Focus on bloom evolution Small mixing events during bloom, which are associated to nitrate injections in surface waters, are followed by [CHL] surf increase. These events could explained the duration of the bloom. In this case bloom lasted about 45 days. MarchAprilMay MarchAprilMay MarchAprilMay

34. Conclusions Qualitative analysis of very recent data (preliminary results) Although Bio-Argo time-series globally confirmed the climatological analyses, they provide relevant additional information. Observation of vertical chlorophyll distribution and integrated content. Contrast with satellite surface observations. Intra-seasonal variability can be studied over a completed annual cycle. Relative importance of rapid mixing events during the bloom period. Limits: The Lagrangian drift of the profiling for the interpretation of time-series.

35. Perspectives Completed annual NAOS Bio-Argo time-series are now available : quantitative analyses can start. 2 PhD students at LOV (Orens and Nicolas) Other perspective work: Combine 0D modeling with Bio-Argo time-series to better understand what explains phytoplankton dynamic at seasonal scale.  Assess the impact of non measured variable (i.e. zooplankton grazing pressure).  Assess fluxes between compartments.  Test scenarios.

36. Thank you for your attention Any question?

37. Conclusions Qualitative analysis of very recent data (preliminary results) Illustrate the potential of Bio-Argo time-series to better understand biogeochemical processes and to encounter NAOS WP3 scientific objectives. Observation of vertical chlorophyll distribution and integrated content. Contrast with satellite surface observations. Combination of high frequency observations over a whole seasonal cycle. Observation of intra-seasonal variability for a better understanding of main biogeochemical processes occurring in the Med. Potential perspective work: Combine 0D modelling with Bio-Argo time-series to better understand what explains phytoplankton dynamic at seasonal scale.  Assess the impact of non measured variable (i.e. zooplankton grazing pressure).  Assess fluxes between compartments.  Test scenarios.