A novel concept for measuring seawater inherent optical properties in and out of the water

Alina Gainusa Bogdan and Emmanuel Boss School of Marine Sciences, University of Maine, Orono, ME, 04469, US

IOP change Effect on backscattering spot

Scattering Intensity

Lateral spread

AbsorptionIntensity

Lateral spread

Figure 3. Sketch of the proposed sensor, with typical modeled measurement. A collimated light beam is shone into the water and the backscattered light intensity is retrieved as a function of distance from the center of illumination by three concentric photodetector rings. The signal is described by the integrated detected photon count within each ring as a function of the distance from the center. The final signal descriptors are calculated on the basis of the cumulative photon count within each radius. The total detected photon count, D, is an indicator of the retrieved intensity; the geometry parameter, α, is a measure of the lateral spread of detected light.

Top view

R = 3.1 cm Δr = 1 cm

Typical signal

photon detected

Side view

photon emitted

photon scattered

photon absorbed

0 0.01 0.02 0.031.5

1.6

1.7

1.8 x 10-4

(Det

ecte

d/in

cide

nt)

phot

on c

ount

r [m]

D (Intensity)

α (Geometry)

Scattering

Absorption 0.005 0.01 0.015 0.02 0.025 0.031

2

3

4

5

6

7 x 10-4

Model outputlinear fit

r [m]

Cum

ulat

ive

phot

on c

ount

α

D

References: R F Cahalan, M McGill, J Kolasinski, T Várnai, and K Yetzer. THOR – Cloud thickness from off beam LIDAR returns. Journal of Atmospheric and Oceanic Technology, 22:605-627, 2005

G R Fournier and M Jonasz. Computer-based underwater imaging analysis. Airborne and In-Water Underwater Imaging, 3761(1):62-70, July 1999

Acknowledgements:

Aim: Test sensor concept inspired by atmospheric THOR instrument (Cahalan et al., 2005), to

simultaneously measure the absorption (a) and backscattering (bb) coefficients of seawater.

Applications: water quality assessment - turbidity measurements; oceanography and ecology -

characterization of algal blooms and biogeochemical processes; calibration of satellite ocean color.

a0b0

a1> a0b0

a2> a1b1

a1b1> b0

Figure 1. Photographs of the backscattering spot for a series of solutions with increasing concentrations of absorbing (green die) and scattering (Maalox) agents. The camera sensitivity and exposure time were held constant.

Idea Shine laser in water

samples with different

IOPs observe the

intensity and geometry

of the backscattering

spot.

Interpret in terms of

beam attenuation with

path length.

IFdIntensity/dScatteringdIntensity/dAbsorption

dGeometry/dScatteringdGeometry/dAbsorption

≠

THENIntensity

Geometry

Scattering

Absorption

Methodology Use Monte Carlo modeling of light propagation to simulate the instrument response to different IOP combinations

Identify robust mathematical relationships between the known, imposed IOPs and some descriptors of the modeled instrument signal

Invert relationships to obtain the algorithm that the actual instrument would use to convert a measured signal into estimates of the water IOPs

+Bp ≡bbp/bp= [0.5%,1%,1.5%,2%,2.5%]

Low Bp values are typical of organic particles (e.g., phytoplankton); high values are typical of inorganic particles (e.g., suspended sediments).

Particle scattering is modeled using the Fournier-Forand phase function (Fournier & Jonasz, 1999)

10-3 10-2 10-1 10010-2

100

102

ap [m-1]

b p [m-1

]

Figure 2. Particulate absorption and scattering values chosen to drive the optical simulations.

Results

10-4 10-2 10010-4

10-3

10-2

10-1

100

[m-1]

b b [m-1

]

data for Bp=2.5%data for Bp=2%data for Bp=1.5%data for Bp=1%data for Bp=0.5%fit

10-5 10-110-310-3

10-2

10-1

100

D

b b/a

data for Bp=2.5%data for Bp=2%data for Bp=1.5%data for Bp=1%data for Bp=0.5%fit

Figure 4. Water IOPs plotted against resulting signal descriptors. bb - backscattering coef.; a - absorption

coef.; α - geometry parameter.; D - intensity.

bb = 101.048log10(α)+0.341 (1)

bba = 10-0.074log10

2(D)+0.353log10(D)+0.656 (2) -0.2 -0.1 0 0.1 0.20

5

10

15

20

25

30

35

bb inversion relative errors

-1 -0.5 0 0.5 10

20

40

60

80

100

a inversion relative errorsFigure 5. Histograms of the relative errors in inverting

bb and a from the modeled instrument response to the full range of IOPs

These equations can be used to obtain a and bb from a given measurement described by D and α. The maximum relative errors when this inversion is applied to the original modeled data set are 13.4% for the inversion of bb and 56.9% for a. 90% of the errors fall below 6.9% for bb and below 29.7% for a.

The signal retrieved by the instrument is determined mainly by a and bb, with little or no added effect from the backscattering ratio, Bp.

Emerging ideasHand-held in-water instrument

3D profiling of a and bb

Long instrument mounted on AUVs

Plausible: Adaptations to optical model

Out-of-water instrument

Long-term deploymenton dry platforms

Discussion

1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 3 3.20.12

0.14

0.16

0.18

0.2

0.22

0.24

0.26

Scattering angle [rad]

VS

F/b b [s

r-1]

1.4 1.6 1.8 2 2.2 2.4 2.6 2.8 3 3.20.12

0.14

0.16

0.18

0.2

0.22

0.24

0.26

Scattering angle [rad]

parti

cula

te V

SF/

b bp

FF: Bp = 0.5%FF: Bp = 1%FF: Bp = 1.5%FF: Bp = 2%FF: Bp = 2.5%Petzold (Bp = 1.83%)

Figure 6. Range of VSF shapes (in the back direction) used in this study. ‘FF’ stands for ‘Fournier-Forand’.

• Test inversion on data obtained using the Petzold scattering phase function => inversion algorithm not sensitive to volume scattering function (VSF), at least within the rangeshown in Figure 6.

• Quality of bb inversion does not depend on the instrument size; larger instrument => better a inversion

• Increasing the detector resolution does NOT improve the quality of IOP inversions

• Radial symmetry of backscattering spot => other instrument shapes possible (keeping symmetry

with respect to the center of illumination)