The nature (peculiarities) of biooptical/biogeochemical. measurements in the context of Argo QC and data management.

Transcription

1 The nature (peculiarities) of biooptical/biogeochemical data and of their measurements in the context of Argo QC and data management Hervé Claustre

2 Prerequisite for Bio-Argo DM: We should follow as much as possible what has been defined by Argo, and that is working fine for T and S. «Do not reinvent the wheel» However: specificities of some Bio-data might require some minimal «flexibility» and «adaptation»

3 Outline «Bio-data» : how they differ from T and S? «Bio-data» : specificity of sampling (sometimes) «Bio-data» : link with remote sensing of Ocean Color Radiometry «Bio-data» : possible use of other data to improve QC

4 Outline «Bio-data» : how they differ from T and S? «Bio-data» : specificity of sampling (sometimes) «Bio-data» : link with remote sensing of Ocean Color Radiometry «Bio-data» : possible use of other data to improve QC

5 Bio-data: how they differ from T and S? Bio is generally driven by physics : a float example Range of variation: e.g. of Chla concentration The nature of the measurement : e.g. of Chla fluorescence Spike / noise (useful for science!) Decorrelation scales

6 Bio-data is generally driven by physics (T, S) an Argo float exemple SOLO

7 Bio-data is generally driven by physics (T, S) an Argo float exemple #2 MLD (m) mg Chla m -3 Temperature Salinity Density 0 10/31/00 10/31/01 10/31/02 10/31/03 See IOCCG report (2011)

8 Bio-data: how they differ from T and S? range of variation : e.g. Chla concentration surface open ocean : 0.01 mg m -3 (sub-tropical gyres) to 20 mg m -3 (upwelling) at depth (>500m) [Chla] = 0

9 Bio-data: how they differ from T and S? the nature of the measurement; e.g. Chla fluoresence Chla is measured through a physical measurement, fluorescence, the amount of red photon emitted by Chla when exited by a certain amount of blue photons. Nevertheless, Chla fluorescence is a proxy of Chla concentration: fluoresence varies (sometimes by more than 100%...!) with the taxonomic composition (e.g diatoms ) as well as the physiological status (light and nutrient). Calibration: relationship between in vivo Chlorophyll fluorescence to absolute chlorophyll concentration (Scale factor) is determined using a pure culture of one single phytoplankton species (generally a diatom). Issue of natural condition representativity.

10 Bio-data: how they differ from T and S? #2 the nature of the measurement; e.g. Chla fluorescence In situ HPLC measurement of Chla when the float is deployed is only representative of the location and the time of this deployment. Extrapolation over the float life-time involves significant uncertainties. How representative/useful are factory calibration and/or HPLC Chla measurement? Chla concentration with an accuracy of 50% is a target. Develop methods to make Chla dataset from different floats consistent.

11 Bio-data: how they differ from T and S? e.g. data are spiky and noisy Mixed layer. Physics rather smooth and monotonic Biological properties not necessarily mixed Inhibition of fluorescence Spike noise Radiometry: exponential decrease with depth Clouds wave

12 Bio-data: how they differ from T and S? e.g. data are spiky and noisy but the spikes have a scientific value Briggs et al., DSR, 2012

13 Bio-data: how they differ from T and S? e.g. data are spiky and noisy but the noise may have a scientific value While the mean contains information about concentration, the variance contains size information Courtesy of N. Briggs; Univ. of Maine

14 Bio-data: how they differ from T and S? e.g. data are spiky and noisy but the noise may have a scientific value Spikes and noise in Bio-data may have a scientific value. Do not bin / average / despike without keeping trace of the raw values Courtesy of N. Briggs; Univ. of Maine

15 Bio-data: how they differ from T and S? e.g. decorrelation scale Biology might react faster than physics => potentiel impact on time resolution of measurements (iridium) Boss et al., 2008

16 Bio-data: specificity of sampling (sometimes) temporal resolution 1-day resolution, 3 profile a day The Argo 10 day interval sampling might not be as useful as for biology / biogeochemistry Xing and Claustre., unpublished

17 Bio-data: specificity of sampling (sometimes) Changing temporal resolution to better characterize the bloom dynamics in the North Atlantic 10-day resolution 2-day resolution The Argo 10 day interval sampling might not be the only rule for biology / biogeochemistry Mignot et al., in prep.

18 Bio-data: specificity of sampling (sometimes) Measurement at drift: important source of information It might be useful to adapt the float parking depth for the measurement of particulate fluxes. Bishop and Wood, 2009

19 Bio-data: how they differ from T and S? The pecularities of in water-radiometric data exponential decrease with depth impacted by surface conditions : seasons, time of the day, clouds, sea state impacted by the presence of particle (e.g. phytoplankton / Chla) and dissolved material (CDOM)

20 Specificity of Bio-data Link with remote sensing of Ocean Color Radiometry OCR is the reference Identify problems => QC float measurement Calibration of the surface measurement by the satellite before extending it at depth In situ float data are the reference Identify (regional) anomalies in the satellite data Increase data base required for improving bio-optical (regional) algorithms Establishing 3D view of the biological Ocean Develop merging methods..

21 Specificity of Bio-data Link with remote sensing of Ocean Color Radiometry Ocean Color Radiometry remote sensing was initially developed for Chla retrieval. Now, (many) new biogeochemical / ecosystems products can be retrieved from space; some of them are also measured in situ by profiling floats. proxies for POC /b bp proxies for the composition of particles proxies for CDOM Particle size: Loisel et al., 2006 Phytoplankton size: Uitz et al., 2006 Siegel et al et al., 2002 POC : Stramski et al., 2008

22 [Chla] retrieval at surface: floats vs MODIS Med Sea North Atlantic gyre North Pacific gyre South Pacific gyre Float [Chla] MODIS [Chla] Xing et al., JGR, 2011

23 b bp (POC proxy) retrieval at the surface: floats vs MODIS Med Sea North Atlantic gyre North Pacific gyre South Pacific gyre Float b bp (532) MODIS b bp (443) Xing et al., unpublished

24 a CDOM (412) retrieval at surface: floats vs MODIS Med Sea North Atlantic gyre North Pacific gyre South Pacific gyre Float a y (412) MODIS a y (412) via GSM a dg (443) Xing et al., JGR, 2012

25 «Bio-data» : possible use of other data to improve QC e.g. Fluoresence quenching issue Sackman et al, BGD 2008 Xing et al., L &O Methods, 2012

26 Conclusions Ocean biology and biogeochemistry generally depend on physics (but the reciprocal is generally not true).` => T and S data are important for bio data interpretation. In term of science, Bio-Argo definitively needs Argo. In term of data management and QC, Bio-Argo has the chance that, since a decade, Argo has worked on the definition and regular improvement of good practices. Bio-Argo needs to develop data management and QC procedures that (1) are as much as possible «Argo-compliant» ( do not reinvent the wheel principle) (2) when required, take into account the specificity of these data

27 The Bio-Argo Data Management principles 1. The Bio-Argo data must contribute to Argo (i.e. the protocols and the T&S data must match Argo requirements) 2. The Bio-Argo data must be organized and processed with the same structure than for the Argo T&S. 3. The Bio-Argo data must be stored in the same format than for the Argo T&S. 4. The Bio-Argo data must have the same distribution policy than for the Argo T&S. 5. The Bio-Argo data processing protocols have to be based on established (i.e. published) methods.