malika kheireddine and david antoine [email protected]

Diurnal variability of particulate matter from observations of beam attenuation and backscattering coefficients in the Northwestern

Mediterranean sea (BOUSSOLE site)

Malika KHEIREDDINE and David ANTOINE

[email protected]

Laboratoire d’Océanographie de Villefranche (LOV)(UMR7093) FranceObservatoire Océanologique de Villefranche (OOV) France

Introduction

1. The diel variability of optical properties results from the cyclical solar forcing. It is a phenomenon which is observed in situ and can be replicated in laboratory. (Claustre et al., 1999; 2002, Siegel et al., 1988 , Gernez et al., 2011).

2. Numerous laboratory measurements have shown that the diel variations of cp are mainly caused by changes of the refractive index and cell size. (Stramski and Reynolds, 1993)

3. The origin of this variability is still badly known.

4. In contrast to cp diel cycles, diurnal variations in bbp are poorly documented. (Loisel et

al., 2011)

LimitationsIn situ studies (cruises): often limited to a few days.Laboratory studies: schematically represent the natural environment.

Motivations

Ocean optics 2012October 10th

Introduction

5. The backscattering coefficient is derivable from satellite ocean color.

6. Current (GOCI) and future geostationary satellite ocean color instruments will provide new opportunities to infer biogeochemical processes from space with an increased temporal resolution.

A better understanding of bbp diel cycles is of particular interest.

to analyse and characterize the bbp and cp diel cycles associated to different environmental conditions. to compare cp and bbp diel cycles.

Objectives

Suggested solution: Continuous measurement, at high-frequency, on an instrumented mooring (BOUSSOLE).


BOUSSOLE project

1. Mooring site in open ocean, weak ocean currents.2. Continuous acquisition (15 min day and night) in surface.3. Optical measurements: cp (660 nm) bbp (442, 555 nm) 4. Physical information (CTD): Temperature (T) Salinity (S) Buoy depth (Zbuoy)5. Monthly cruises: CTD profiles Discrete sampling (HPLC)

Antoine et al., (2006, 2008b).

The BOUSSOLE project


5 years from 2006 to 2010 (cp, bbp & [chl])

Seasonal variations

4 seasons, corresponding to situations of winter mixing, development of the bloom, collapse of the bloom, and summer and fall oligotrophy, have been differenciated for each year.

Results


5 years from 2006 to 2010 (cp, bbp & [chl])

Seasonal variations

Are the diel variations changing with seasons ?

Results


A. Winter mixing

B. Development of the bloom

C. Collapse of the bloom

D. Oligotrophy

Zoom on five days during each season

Characterization of the diel variability:1. A diel cycle appears to be a

recurrent feature in the cp and bbp signal.

2. Differences in shape and amplitude at different period of the years are observed.

Results


Diurnal variability by season

ΔX(k) = 100 [X(k) / X1 - 1] X1 = value at sunrisek= fraction of day

cp

•cp starting increase at dawn and decreasing at sunset.

•Amplitude varies with seasons: 10 - 20% during mixing, collapse and oligotrophy and 20% - 50% during bloom.

cp diel cycles are marked by a significant seasonal variability, which is consistent with the seasonal cycle observed at BOUSSOLE, which results in seasonal changes in nutrient concentrations, phytoplankton composition and size.

Results


bbp

Diurnal variability by season

ΔX(k) = 100 [X(k) / X1 - 1] X1 = value at sunrisek= fraction of day

•bbp starts increasing at dawn. bbp starts decreasing few hours before sunset.

•Amplitude varies between 5 and 30 % according to the season.

In contrast to cp diel cycles, bbp diel cycles are not marked by a significant seasonal variability.

Results


cp bbp

Comparison of cp and bbp cycles

Results


1. cp and bbp daily oscillations appear to be slightly shifted in time. Minimum bbp values are usually synchronized to cp whereas maximum bbp are often reached few hours before than those for cp.

2. For each year, cp diel cycles are higher during the mixing, collapse, oligotrophy than bbp diel cycle by a factor up to ~1.5 and by a factor 2 to 5 during the bloom.

cp bbp

Comparison of cp and bbp cycles

Results


The ratio starts decreasing at dawn and starts increasing, generally, at sunset.

It suggests a decrease of the refractive index and/or a decreasing proportion of small particles relatively to large particles in water.

In this case, the variability observed could be arise from changes in the shape of the size distribution.

Results

The backscattering ratio diel cycles


This assumes that the particle scattering coefficient is spectrally flat [bp (λ) = cp (660 nm)].

=

Twardowski et al., 2001; Boss et al., 2004

Discussion


Origin of the diel variability ?

Origin of the differences observed between cp and bbp ?

Each of these phenomena implies a change of abundance, size (PSD) and refractive index (n) and thus IOPs.

Diurnal increaseGrowth of cells (↑PSD)Fixation of carbon (↑n)

Nocturnal decreaseRespiration and loss of cellular material (↓n, ↓PSD)Cellular division (↓PSD, ↑Number)Grazing (↓ Number)

The lower magnitude observed for diel variations of bbp might be related to the high sensitivity of bbp to changes in the small particle abundance (bacteria and detritus).

bbp is mostly influenced by submicrometer particles, whereas cp is mainly driven by

particles with diameters between 0.5 and 20 μm (Stramski and Kieffer, 1991; Pak et al., 1988).

Siegel et al., 1989; Cullen et al., 1992 ; Walsh et al., 1995; Stramski and Reynolds, 1993; Durand and Olson, 1998; Claustre et al., 2002; Durand et al., 2002; …

The Mie theory (Mie, 1908) is only used as a tool for interpretation to parameterize the dependence of cp and bbp on the daily changes in refractive index (n) and size distribution (PSD).

Mie computations


Discussion

ObjectivesUnderstand the causes of the diurnal variability observed in this study.To determine which of n or PSD is the main factor controlling the cp and bbp diel cycles.

Strategy1. Bibliography about several studies performed on the diel variability of the refractive

index, size and abundance of phytoplankton cells. (Stramski and Reynolds, 1993; Stramski et al., 1995 ; Durand et Olson, 1998; André et al., 1999; Durand et al., 2002; Claustre et al., 2002(a))

2. Establish a representative population of relatively clear oligotrophic water (BOUSSOLE). (viruses, detritus, bacteria, pico-, nano- and micro-phytoplankton)

microorganisms Concentration (m-3) Size (µm) Refractive index (n) Wavelength (nm)

Viruses 7.0 1016 [0.01-0.3] 1.08 660

Bacteria 3.0 1015 [0.1-1.2] 1.075 660

Detritus 5.0 1014 [0.02-4] 1.08 660

Picophytoplankton 1.0 1014 [0.2-2] 1.02 660

Ultra-nanoplankton 5.0 1012 [2-8] 1.02 660

Nanophytoplankton 1.5 1011 [8-20] 1.02 660

Microphytoplankton 1.0 1010 [20-100] 1.02 660

Mie computations


Discussion

Concentration, particle size distribution, refractive index and wavelength of each group of microorganisms used in Mie computations.

cp and bbp dependent only on the dynamics of phytoplankton cells (variation of PSD, n & abundance).

Base simulations

background componenttime-varying component (24h)

Mie computations


PSD n PSD, n

1. Daily changes in cp and bbp can be related to daily changes in size and refractive index.

2. The main driving factor for cp is PSD and for bbp, n.

3. It’s necessary to stimulate daily changes in PSD & n to be in agreement with in situ observations.

Discussion

Conclusion & perspectives


Investigate the impact of diurnal variations of IOPs on the diurnal variability of AOPs (Kd, R, …).

1. The cp and bbp time series show clear daily oscillations whatever the season.

2. The characteristics and the shape of the cp diel cycle vary seasonally.

3. Seasonal differences in cp diel cycles seem to be related to the trophic state of phytoplankton (nutrient availability, population composition, physiological state,…).

4. Differences between cp and bbp diel cycles can be related to the high sensitivity of bbp to changes in the small particle abundance (bacteria, detritus, etc…).

5. Use of bbp cycle to infer biogeochemical properties and carbon fluxes at diurnal scale will be questionable.

Conclusion

Perspective


Thanks

BOUSSOLE & Co

Thank you for your attention!

Without them, I wouldn't have been able to present this work.

For more information, come to see my poster (tonight, n°111)!

Data selection

Data quality control

Characterize the zone where the variability is due to unstable physical conditions

Data eliminated


malika kheireddine and david antoine [email protected]

Documents

cp diel cycles

diel variations of cp

nm bbp

resultsocean optics

bbp signal

bbp chlseasonal variationsare

motivationsocean optics

boussole projectocean