Transcript Poster
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 Aim: Test sensor concept inspired by atmospheric THOR instrument (Cahalan et al., 2005), to Applications: water quality assessment - turbidity measurements; oceanography and ecology - simultaneously measure the absorption (a) and backscattering (bb) coefficients of seawater. characterization of algal blooms and biogeochemical processes; calibration of satellite ocean color. Emerging ideas Idea b0 b0 Top view Side view Hand-held in-water instrument Long instrument mounted on AUVs photon emitted photon detected IOPs observe the Typical signal 3D profiling of a and bb intensity and geometry Plausible: photon absorbed of the backscattering IOP change Scattering Absorption b1 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. R = 3.1 cm photon scattered Δr = 1 cm Discussion 0.26 IF D (Intensity) 7 α (Geometry) Effect on backscattering spot Intensity Lateral spread Intensity Lateral spread THEN ≠ Scattering Absorption dGeometry/ dScattering dGeometry/ dAbsorption Intensity Scattering Geometry Absorption x 10 6 D 5 4 3 α 2 0.01 Model output linear fit 0.015 0.02 0.025 0.03 Methodology b [m-1] 10 10 -2 10 -1 10 10 + -3 0 -2 10 [m-1] 10 0 using the Fournier-Forand phase function (Fournier & Jonasz, 1999) References: 1.6 10 1.8 2 2.2 2.4 2.6 2.8 3 3.2 0.14 0.12 1.4 1.5 0 1.6 0.01 0.02 0.03 1.6 1.8 2 2.2 2.4 2.6 Scattering angle [rad] 2.8 3 3.2 • 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) 35 30 -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 -2 -3 10 -5 10 20 (1) 15 10 5 (2) 0 -0.2 -0.1 0 0.1 bb inversion relative errors 0.2 100 b Invert relationships to obtain the Low Bp values are typical of algorithm that the actual instrument organic particles (e.g., phytoplankton); would use to convert a measured high values are typical of inorganic particles (e.g., suspended sediments). signal into estimates of the water Particle scattering is modeled IOPs 0.14 0.12 1.4 bb = bb 2 -0.074log (D)+0.353log (D)+0.656 10 10 = 10 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 b /a Bp ≡bbp/bp= [0.5%,1%,1.5%,2%,2.5%] 10 0.16 0.16 1.048log (α)+0.341 10 10 -2 -4 Identify robust mathematical Figure 2. Particulate absorption and scattering values chosen to drive the optical simulations. relationships between the known, imposed IOPs and some descriptors of the modeled instrument signal 0.18 25 10 -4 10 ap [m ] 0.2 -1 0 -1 0.22 0.18 Results -2 10 1.7 0.2 0 b 0 10 -3 10 0.24 0.22 r [m] 2 p b [m-1] 10 x 10 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. 10 Use Monte Carlo modeling of light propagation to simulate the instrument response to different IOP combinations 1.8 FF: Bp = 0.5% FF: Bp = 1% FF: Bp = 1.5% FF: Bp = 2% FF: Bp = 2.5% Petzold (Bp = 1.83%) • Test inversion on data obtained using the Petzold scattering phase function => inversion algorithm not sensitive to volume scattering function (VSF), Scattering angle [rad] at least within the range Figure 6. Range of VSF shapes (in the back direction) used in this study. shown in Figure 6. ‘FF’ stands for ‘Fournier-Forand’. -4 -4 1 0.005 10 10 0.26 0.24 r [m] dIntensity/ dScattering dIntensity/ dAbsorption Long-term deployment on dry platforms bp path length. b1> b0 particulate VSF/b beam attenuation with a2> a1 (Detected/incident) photon count Interpret in terms of a1 Out-of-water instrument Cumulative photon count spot. Adaptations to optical model b samples with different a1> a0 VSF/b [sr-1] Shine laser in water a0 -3 10 D 10 -1 Figure 4. Water IOPs plotted against resulting signal descriptors. bb - backscattering coef.; a - absorption coef.; α - geometry parameter.; D - intensity. These equations can be used to obtain a and bb from 80 a given measurement described by D and α. The maximum 60 relative errors when this inversion is applied to the original modeled data set are 13.4% for the inversion of bb and 40 56.9% for a. 90% of the errors fall below 6.9% for bb and 20 below 29.7% for a. The signal retrieved by the instrument is determined 0 -1 -0.5 0 0.5 1 a inversion relative errors mainly by a and bb, with little or no added effect from the Figure 5. Histograms of the relative errors in inverting backscattering ratio, Bp. bb and a from the modeled instrument response to 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 the full range of IOPs Acknowledgements: