370 likes | 499 Views
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.
E N D
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 SeminarTriestre 24/01/2014
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.
Biogeochemical parameters are under sampled:example with chlorophyll-a All chlorophyll-a observations available in the World Ocean Database 2009
From Argo… to Bio-Argo • Chl and CDOM fluorescence, Oxygen, Irradiance, PAR, Nitrates, back scattering. • High vertical resolution • Changeable time lagbetweentwo profiles • Temperature and salinity • Low vertical resolution • Fixed time lagbetweentwo profiles
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.
Evolution of the Bio-Argo net work • October2005 • October2009 • December2013
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
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).
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.
Scientific objectives of NAOS WP3 To confirm the bio-regionalization of the Med. 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. To assess the temporal variability of this bio-regionalization over 10 years. D’Ortenzio and Ribera d’Alcalà (2009)
33 floats with biogeochemical sensors deployed in the NAOS WP3 O2 sensor Iridium antenna CTD Irradiance + PAR Optical active sensors: Fluorometer CDOM FluorometerChla Backscatterometer Nitrate sensors
The iridium two ways transmission Real time observations Make the decision to change the samplingstrategy New commands are takeintoaccount by the float.
Floats deployments January 2014: 12 floats deployed (2 recovered) + 2 additional floats in the Ionian Sea. In 2016: 15 additional floats will be deployed.
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
The Mediterranean spring bloomAs observed by ocean color satellite Bosc et al., 2004. Monthly [chl-a] averaged. Year 1999 Spring bloom Normalized seasonal cycle of [Chl-a] in the blooming North-Western Mediterranean Sea. From D’Ortenzio and Ribera D’Alcalà (2009)
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.
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?
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, [NO3-] (PRONUTS) • N_001i: T, S, [Chl-a], [NO3-] (NAOS) • N_035b: T, S, [Chl-a] (NAOS) • N_017b: T, S, [Chl-a], [NO3-] (NAOS)
Calibration of the chlorophyll fluorescence data Chlorophyll fluorescence is only a proxy for [Chl-a]. A calibration procedure has to applied on fluorescence data. • Correction for Non Photochemical Quenching • Correction of the offset and slope. Checking for no sensor drift. First, α i and βi 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 βi
The calibration procedure (Lavigne et al., 2012) Applied on each individual fluorescence profile and based on satellite ocean color observations Empirical relationship (Uitz et al., 2006) Step 3: α correction Step 1: NPQ correction Step 2: β correction Deep fluorescence values used to compute β
Validation of the calibration procedure with concomittant HPLC profiles at deployment. __ before calibration __ after calibration + HPLC
QC and calibration of [NO3-] dataPrinciple of the measurement Measurement cell Absorption of ultra violet wavelength UV NO3- Br- CDOM UV We can retrieve [NO3-], e, f and S by fitting this equation for λ ranging between 217 and 242 nm. SUNA (SATLANTIC) According to the Beer-Lambert law Measured by SUNA Baseline, contained CDOM absorption Nitrate concentration Salinity Extinction coefficients
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 [NO3-] equals the concentration measured from water sampling at deployment (about 8.5µM).
Validation of the [NO3-] calibration __ after calibration __ before calibration + water sampling
Results • Data • 4 Bio-Argofloatsthatdrifted in the Bloom – NW bioregionduring the nov 2012 – june 2013 period • P_SUNA : T, S, [NO3-] (PRONUTS) • N_001i: T, S, [Chl-a], [NO3-] (NAOS) • N_035b: T, S, [Chl-a] (NAOS) • N_017b: T, S, [Chl-a], [NO3-] (NAOS)
Focus on MLD and [NO3-]MLD • During the autumn and winter period, a deepening of the MLD up to ~70m drives to a significant increase in [NO3-]MLD. However, the [NO3-]MLD increase is not linear. • During the bloom period, the MLD versus [NO3-]MLD relationship is very complex. • During the oligotrophic period, [NO3-] is close to 0µM and MLD range between 10 to 50m. • The transition between oligotrophic ([NO3-] = 0µM) and autumn ([NO3-] = 0.5µM) condition could not be observed.
Focus on [CHL]surf and <CHL>int • Globally, [CHL]surf and <CHL>int seasonal cycles are consistent. • Underestimation of [CHL]surf compared to <CHL>int during deep winter mixing. • During spring bloom, [CHL]surf peaks are not necessary reproduced by <CHL>int peaks.
From mixed to stratified profiles « Mixed » shape Chlorophyll profiles during bloom. These examples can explain the high variability and sometime the inconsistency between [CHL]surf peaks and <CHL>int peaks. « Stratified » shape
Relatively shallow MLD during a long period Focus on bloom initiation March It clearly appears that MLD shallowing drives to an increase of [Chl-a]surf. However, the impact of MLD variability on <Chl>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 March
Focus on bloom evolution March March March April April April May May May 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.
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.
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.
Thank you for your attention Any question?
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 modellingwith Bio-Argo time-series to betterunderstandwhatexplainsphytoplanktondynamicatseasonalscale. • Assess the impact of non measured variable (i.e. zooplanktongrazing pressure). • Assess fluxes betweencompartments. • Test scenarios.