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Reducing uncertainty in satellite ocean color products with measurements made from gliders and floats M.J. Perry, UMaine Herve Claustre, LOV Ken Johnson,

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Presentation on theme: "Reducing uncertainty in satellite ocean color products with measurements made from gliders and floats M.J. Perry, UMaine Herve Claustre, LOV Ken Johnson,"— Presentation transcript:

1 reducing uncertainty in satellite ocean color products with measurements made from gliders and floats M.J. Perry, UMaine Herve Claustre, LOV Ken Johnson, MBARI Craig Lee & Eric D’Asaro, UW Emmanuel Boss, UMaine Brandon Sackmann, WDOE NASA Ocean Color Research Team Meeting 4-6 May 2009, New York City The ocean below –

2 What can gliders and floats do for NASA’s Ocean Biology and Biogeochemistry Program ? CSZC in 1978 : first ‘big’ picture, synoptic view ––> major advances in understanding phytoplankton processes, inter-annual variability, bio-physical connectivity, global primary production, etc. ‘Arrays’ of gliders and floats: * persistent presence (unlike ships) * spatial information (unlike moorings) * vertical presence (unlike satellites) Combined sensing w / satellites ––> new opportunities for major advances

3 Update since ALPS meeting in 2003 – Iridium 2-way communications – unattended Gliders (directional, but slow) – long endurance ~ 9.5 mo. – depths to 1,000+ m; hurricanes – 450 miles under ice – always adding new sensors Floats (go w/ the flow; diversity) – bio-ARGO floats, 3+ yr – Lagranigan floats, pick- up truck load of bio-optical & other sensors Sensors –– need to be small, low-power, robust; issues of cal, drift, fouling: CTD, chl and CDOM fluorescence, optical backscatter ( ), beam c, O 2, nitrate, PAR, Ed ( ), Lu ( ), LOPC, sediment traps, turbulence, current meter, carbon flux, PIC, etc. Near term, add other C-cycle sensors.

4 1) Data even when cloudy, vertical distribution of variables, mixed layer depth, etc. 2) Validation of remote sensing products (requires calibrated sensors) Temp, optical backscatter, radiances (physical properties; SI units ); S – own issues; CDOM (requires conversion from F to absorption); Chl (requires fluorescence quench correction or 3-  absorption) 3) Validation of biogeochemical models by providing link between in situ processes and satellite-based models: primary productivity – improved input to biomass/light models: validate biomass and provide vertical distribution of biomass; PS coefficients (Cullen approach for Ek from fluorescence) particle production – diel changes in particles (b b, c, LOPC, etc.) net community production from changes in O 2 and other stoichiometric conversions – nitrate drawdown (pCO 2 ……) role of physics in export and other processes 4) Discovery – of unexpected or unknown phenomena and/or forcings Reducing uncertainty in ocean color products

5 1a) Data even when cloudy – satellite & gliders subpolar N.A. 100% clear NAB08 – D’Asaro, Lee, Sackmann Perry, Fennel 50 25

6 1b) Vertical distribution of biomass & mixed layer depth Seaglider off Washington – Perry, Sackmann, Eriksen, Lee (2008) L&O sp. issue Density Chlorophyll January through Nov 2004

7 2) Validation of remote sensing products Motivation: * S. Maritorena’s talk yesterday on MEASURES products and links to biogeochemical products. * Proxy relationships: b b and c to POC particle size and species detrital material, CDOM, DOC First, need validation of primary products (b b, etc.)

8 T & S & density bb Ed c 412 chl 490 CDOM 555 Boussole mooring PROVBIO : PROVOR float in Mediterranean Sea; 22 May 2008 2) Validation of remote sensing products Claustre et al., unpub. Advantage of deploying w/ reasonable accessibility to validate sensors while learning (location, location, location)

9 2) Toward validation of remote sensing products Bio-optical ARGO float – 3+ years in Labrador Sea Boss et al. 2008 Hybrid ‘validation’ – need to move toward better sensor calibrations and cross calibrations

10 fluorescence absorption CDOM absorption is a primary ocean color variable, but CDOM fluorescence requires conversion to absorption What sensors? How to quantify relationships? 2) Toward validation of remote sensing products Is there a better in situ sensor? CDOM a-meter?

11 Chlorophyll absorption is a primary ocean color variable, but float and glider sensors measure chlorophyll fluorescence. Requires conversion from fluorescence to chlorophyll concentration (but that is still not absorption) What sensors? How to quantify relationships? 2) Toward validation of remote sensing products extracted chlorophyll Is there a better in situ sensor? Chl a-meter? fluorescence Roesler, unpubl.

12 Chlorophyll absorption is a primary ocean color variable. Would 3-wavelength chlorophyll absorption be an improvement? What sensors? How to quantify relationships? 2) Toward validation of remote sensing products extracted chlorophyll Red peak absorption Roesler, unpubl. Figure containing unpublished data was removed

13 3) Validation of biogeochemical models primary productivity – improved input to models validate biomass; vertical distribution; real Temp. from ARGO PS coefficients (Cullen – Ek ) (not climatologies) fluorescence particulate backscatter Vertical distributions Temperature for PP models Perry, unpub.http://flux.ocean.washington.edu/ Bay of Bengal, 29 April 2009

14 Net community production – O 2 ARGO floats ARGO floats near Hawaii. Riser & Johnson. 2008. Nature 451: 323 3) Validation of biogeochemical models

15 Stoichiometric measures of community production with well-characterized and calibrated sensors D’Asaro, Lee, Perry, Fennel – North Atlantic Bloom

16 every time you look at the ocean in a new way, you learn something new – paraphrased from Russ Davis 4) Discovery Chl S T Inshore offshore 25 Mar 09

17 Two types of potential applications for floats & gliders: 1) experiment scale – weeks to months to ~ year, mesoscale to basin scale [this scale also part of process to go to next step, below; sensor calibration and characterization critical to ‘getting it right’.] 2) operational scale – bio-ARGO or BGC-ARGO floats ( note: existing ARGO Program is considering using gliders as well as floats )

18 Sensor issues (and there are many) Multiple sensors for same process Start where you know the processes: work first with the known –> then move to the unknown. Better sensors Etc., etc., etc. But...

19 The way forward: IOCCG BIO-Argo WG (Claustre) O 2 -ARGO (Johnson, Riser, Gruber, Körtzinger) Ocean Obs 09 White Paper (Perry, Claustre, Testor) OCB scoping workshop on observing BG cycles on global scates with floats and gliders (Johnson; reports being written) Proposed standing committees, US and international Motivation: Reduce uncertainty 1) Validation of remote sensing products 2) Validation of biogeochemical models 3)Discovery 4)Data even when cloudy


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