Optics of Marine Particles - Home - IOCCG of Marine Particles... · Optics of Marine Particles ... Morel and Prieur (1977); Gordon and Morel (1983) (Bricaud et al. 1998) Absorption

Optics of Marine Particles

Lecture 2

Scripps Institution of Oceanography

University of California San Diego

Email: [email protected]

Dariusz Stramski

IOCCG Summer Lecture Series

22 July - 2 August 2014, Villefranche-sur-Mer, France

• Plankton microorganisms

• Biogenic detrital particles

• Mineral particles

• Colloidal particles

• Air bubbles

Suspended Particulate Matter

Plankton microorganisms

(Stramski et al., 2001)

Plankton microorganisms

Interspecies

variability in

absorption

(Stramski et al. 2001)


Interspecies

variability in

scattering

Interspecies variability in

single scattering albedo

(based on data from Stramski et al. 2001)

Light wavelength [ nm ]

350 450 550 650 750

Sin

gle

scatteri

ng a

lbedo

1.0

0.8

0.6

0.4

0.2

0

Mie calculations of scattering phase function

for plankton microorganisms



Backscattering properties of plankton microorganisms

(subject to uncertainties associated with Mie scattering calculations for

homogeneous spheres)

Intraspecies variability due to irradiance - Synechocystis

(Stramski and Morel 1990)

Absorption

Cell

Chl

C

400 500 600 700

WAVELENGTH [ nm ]

Scattering

Intraspecies variability due to temperature, nitrogen,

and light limitation – Thalassiosira pseudonana


Absorption vs. growth rate Scattering vs. growth rate

Intraspecies

variability over

a diel cycle

Thalassiosira

pseudonana

(Stramski and Reynolds 1993)

Optical variability for heterotrophic bacteria

Absorption

(Stramski and Kiefer 1998)

Beam attenuation

CHB Carotenoid-rich bacteria:

grown in nutrient-enriched seawater [EX-1

(light-dark cycle), EX-2 and EX-3 (dark)],

and in nutrient-poor seawater (EX-4)

NHB Non-pigmented bacteria:

fast-growing in the absorption experiment

and starved in the attenuation experiment

Prey-predator interactions (cyanobacteria and ciliates)


Absorption spectra Particle size distributions

Scattering spectra

Examples of particulate absorption coefficients

ap, ad or NAP, aph (data from the Sargasso Sea)

(Bricaud and Stramski 1990)

aph = ap - ad or NAP

(Babin et al. 2003)

Example non-algal

particle (NAP)

absorption spectra and

the corresponding

exponential fits for

different regions

(Babin et al. 2003)

Frequency distribution of

spectral slope of NAP

absorption

NAP absorption spectra

calculated with

aNAP(443)=1 m-1 and SNAP

= 0.0123 nm-1 (±1.96

standard deviation, where

SD=0.0013 nm-1)

Mineral particles

Mongolian Cyclone 7 April 2001

Saharan dust

Cloud

Dust

Spitsbergen fjord, Arctic

Sample

ID

Description Origin

ILL1 illite Source Clay Minerals Repository,

University of Missouri (ref. IMt-1)

ILL2 as above but different PSD as above

KAO1 kaolinite (poorly crystallized) as above (ref. KGa-2)

KAO2 as above but different PSD as above

MON1 Ca-montmorillonite as above (ref. SAz-1)

MON2 as above but different PSD as above

CAL1 calcite natural crystal

CAL2 as above but different PSD as above

QUA1 quartz natural crystal

SAH1 atmospheric dust from Sahara red rain event, Villefranche-sur-Mer, France

SAH2 as above but different PSD as above

AUS1 surface soil dust cliff shore, Palm Beach near Sydney, Australia

AUS2 as above but different PSD as above

ICE1 ice-rafted particles glacier runoff, Kongsfjord, Spitsbergen

ICE2 as above but different PSD as above

OAH1 surface soil dust Oahu, Hawaii Islands

OAH2 as above but different PSD as above

KUW1 surface soil dust Kuwait (eastern part, close to ocean)

KUW2 as above but different PSD as above

NIG1 surface soil dust southwest Nigeria

SAN1 atmospheric dust San Diego, California

Terrigenous

mineral-rich

particulate

matter


Mass-specific absorption

300 400 500 600 700 800

Mass

-sp

ecif

ic a

bso

rpti

on

co

eff

icie

nt

ap*

(m

2 g

-1)

0.0

0.1

0.2

0.3

0.4

0.5

300 400 500 600 700 8000.00

0.05

0.10

0.15

0.20

a

c

300 400 500 600 700 8000.0

0.2

0.4

0.6

0.8

1.0

1.2

b

AUS2

AUS1

OAH1

OAH2

KUW1

KUW2

SAH1

SAH2

ICE1

ICE2

CAL1

KAO2

ILL2

QUA1

MON2

Light wavelength (nm)

NIG1

SAN1

300 400 500 600 700 800

Mass

-sp

ecif

ic s

catt

eri

ng c

oeff

icie

nt

bp*

(m

2 g

-1)

0.0

0.5

1.0

1.5

2.0

300 400 500 600 700 8000.0

0.5

1.0

1.5

2.0

a

c

300 400 500 600 700 8000.0

0.5

1.0

1.5

2.0

b

AUS2

AUS1

OAH1OAH2

KUW1 KUW2

SAH1

SAH2ICE1 ICE2

CAL1

KAO1

ILL2

QUA1

MON2

Light wavelength (nm)

NIG1

SAN1

MON1

KAO2

ILL1

CAL2

MON2

Mass-specific scattering


Particle Size Distributions

1 10

Part

icle

num

ber

concentr

ati

on F

N(D

) (

m-3

m

-1)

107

108

109

1010

1011

1012

1013

1014

1 10107

108

109

1010

1011

1012

1013

1014

Particle equivalent diameter D (m)

a

b

0 2 4 6 8 10 12

Part

icle

volu

me c

oncentr

ati

on F

V(D

) (

m-1

)

0

1x10-6

2x10-6

3x10-6

4x10-6

5x10-6

6x10-6

SAH1

SAH2

0 2 4 6 8 10 120

1x10-6

2x10-6

3x10-6

4x10-6

5x10-6

6x10-6

KUW1

KUW2

Particle equivalent diameter D (m)

c

dKUW2

SAH2SAH

2

SAH1

KUW1

KUW2

a


Mass-specific absorption Fe-specific absorption

(Babin and Stramski 2004)

Absorption of mineral-rich particulate assemblages

(Babin and Stramski 2004)

Asian dust - sampling locations



Asian mineral-rich dust

Colloidal particles (< 1 m in size) undergoing Brownian motion

Size distributions of colloids

Particle diameter D ( m )

Pa

rtic

le c

on

cen

tra

tio

n N

(D)d

D

( m

-3 )

0 0.05 0.10 0.15 0.20 0 0.05 0.10 0.15 0.20 0 0.05 0.10 0.15 0.20

Sargasso Sea 30 m

Sargasso Sea 50 m

Sargasso Sea 70 m

Southern Ocean shelf 40 m

S. Ocean open waters 3 m



Scotian shelf 5 m

Scotian shelf 10 m

Scotian slope 20 m

Scotian slope 40 m

1016

1015

1014

1013

1012

Wells and Goldberg (1994)

Pa

rtic

le c

on

cen

tra

tio

n N

(D)d

D

( m

-3 )

Particle diameter D ( m )

0.4 0.5 0.6 0.7 0.8 0.9 1.0

Station B 0 m

Station B 33 m

Station C 0 m

Station C 23 m

Otsuchi Bay 5 m

Otsuchi Bay 25 m

Otsuchi Bay 40 m

Station D 0 m

Station D 34 m

Station D 55 m

1012

1011

1010

109

108

0.4 0.5 0.6 0.7 0.8 0.9 0.4 0.5 0.6 0.7 0.8 0.9

Yamasaki et al. (1998)

Results for colloidal particles

300 400 500 600 700 800

Sca

tter

ing c

oef

fici

ent

b

( m

-1 )

10-4

10-3

10-2

10-1

100

Wavelength ( nm )

300 400 500 600 700 800B

acksc

atte

ring c

oef

fici

ent

bb

( m

-1 )

10-4

10-3

10-2

pure seawater

average small colloids

small + large colloids

average large colloids

Wavelength ( nm )

scattering backscattering

300 400 500 600 700 800

Sca

tter

ing c

oef

fici

ent

b (

m-1

)

10-4

10-3

10-2

10-1

100

Wavelength ( nm )

300 400 500 600 700 800B

acksc

atte

ring c

oef

fici

ent

bb (

m-1

)10-4

10-3

10-2

pure seawater

average small colloids

small + large colloids

average large colloids

Wavelength ( nm )

(Stramski and Woźniak 2005)

Light

scattering

by bubbles

entrained by

wave

breaking

(Stramski and Tęgowski 2001)

Scattering and

backscattering by

bubbles as a function

of void fraction

(Terrill et al. 2001)

IOPp() = IOPph() + IOPNAP()

IOP() = IOPw() + IOPp() + IOPCDOM()

Traditional approach

Inherent Optical Properties (IOPs) described in

terms of a few broadly-defined categories of

seawater constituents

Example IOPs:

absorption coefficient, scattering coefficient,

beam attenuation coefficient, volume scattering function

A four-component model of absorption

Chlorophyll-based approach

IOP() = IOPw() + f [ Chla ]

for example aph() = f [ Chla ]

ap() = f [ Chla ]

AOP() (e.g., ocean reflectance) = f [ Chla ]

Case 1 and Case 2 Waters

Morel and Prieur (1977); Gordon and Morel (1983)

(Bricaud et al. 1998)

Absorption vs.

chlorophyll-a

~ 4-fold variation

Beam attenuation vs. chlorophyll

(Loisel and Morel 1998)

> 10-fold variation

Chlorophyll Algorithm

OC4 Algorithm

(Clarke, Ewing & Lorenzen 1970) (O’Reilly et al. 2000)

Global distribution of phytoplankton chlorophyll in the

world’s oceans from Sea-viewing Wide Field-of-view Sensor

(SeaWiFS) based on Sep 1997 - Feb 2007 data

Courtesy of NASA

• Parameterization in terms of

chlorophyll-a concentration

alone

• Empirical regressions

(statistically-derived models)

• Provide average trends but no

information about variability

• Not valid for Case 2 waters

• Not necessarily satisfactory

for Case 1 waters

Chlorophyll-based approach: Summary

Reductionist approach

m

min m,IOP minerals)(

k

pla k,IOPIOP plankton )( )(p

n

det n,IOP detritus)(

To develop an understanding and assemble a

model of the whole, from the reductionist

study of its parts

Example criteria

• Manageable number of components

• The sum of components should account

for the total bulk particulate and optical

properties as accurately as possible

• The components should play specific

well-defined roles in ocean optics and

biogeochemistry

Example reductionist model

of particle functional types (PFTs)

Living Particles

Autotrophs

1. Picophytoplankton <2-3 m

(prokaryotes and eukaryotes)

2. Small nanophytoplankton ~2-8 m

3. Coccolithophores

4. Large nanophytoplankton ~8-20 m

5. Microphytoplankton 20-200 m

Heterotrophs

6. Bacteria ~0.5 m

7. Microzooplankton O(1-100) m

Non-Living Particles

Organic

8. Small colloids 0.02-0.2 m

9. Coarse colloids 0.2-1m

10. Detritus >1m

Inorganic

11. Colloidal/Clay minerals <2m

12. Larger (Silt and Sand-sized) minerals >2m

Challenge: Characterization of PFT properties

s i

) ( e.g., optical cross-sections

concentration in seawater Ni

Multi-component model of bulk IOPs

)()()(11

s i

j

i

i

j

i

i NIOPIOP

Ni

Example IOP

model with

detailed

description of

plankton

community


Size

distribution


Absorption Scattering


Reductionist IOP/radiative transfer/reflectance model

)()()(11

s i

j

i

i

j

i

i NIOPIOP

• In what ways does variability in detailed

seawater composition determine variability in

ocean reflectance?

• What information about water constituents and

optical properties can we hope to extract from

remotely sensed reflectance?

j

i

bi

j

i

ai NNfR1

,i

1

,i )],(,)([( ss

Input to radiative

transfer model

Output, e.g. ocean

reflectance

Multi-component IOP database → Radiative transfer model

(Stramski and Mobley 1997; Mobley and Stramski 1997)

• Optical measurements include b(, ); target specific water constituents

• Particle identification and characterization particle species composition, size distribution,

particle chemistry, biology, mineralogy, etc.

• Laboratory experiments (not just field experiments)

• New techniques and instrumentation

What do we need to do?

Reductionist approach:

“The reductionist worldview has to be

accepted as it is, not because we like it,

but because that is the way the world

works”

Steven Weinberg 1979 Nobel Prize in Physics

The complexity of seawater as an optical

medium should not deter us from pursuing the

proper course in future research

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Optics of Marine Particles - Home - IOCCG of Marine Particles... · Optics of Marine Particles ... Morel and Prieur (1977); Gordon and Morel (1983) (Bricaud et al. 1998) Absorption