Polarized lidar and ocean particles: insights from a mesoscale coccolithophore bloom.
Appl Opt
; 59(15): 4650-4662, 2020 May 20.
Article
in En
| MEDLINE
| ID: mdl-32543574
Oceanographic lidar can provide remote estimates of the vertical distribution of suspended particles in natural waters, potentially revolutionizing our ability to characterize marine ecosystems and properly represent them in models of upper ocean biogeochemistry. However, lidar signals exhibit complex dependencies on water column inherent optical properties (IOPs) and instrument characteristics, which complicate efforts to derive meaningful biogeochemical properties from lidar return signals. In this study, we used a ship-based system to measure the lidar attenuation coefficient (α) and linear depolarization ratio (δ) across a variety of optically and biogeochemically distinct water masses, including turbid coastal waters, clear oligotrophic waters, and calcite rich waters associated with a mesoscale coccolithophore bloom. Sea surface IOPs were measured continuously while underway to characterize the response of α and δ to changes in particle abundance and composition. The magnitude of α was consistent with the diffuse attenuation coefficient (Kd), though the α versus Kd relationship was nonlinear. δ was positively related to the scattering optical depth and the calcite fraction of backscattering. A statistical fit to these data suggests that the polarized scattering properties of calcified particles are distinct and contribute to measurable differences in the lidar depolarization ratio. A better understanding of the polarized scattering properties of coccolithophores and other marine particles will further our ability to interpret polarized oceanographic lidar measurements and may lead to new techniques for measuring the material properties of marine particles remotely.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Phytoplankton
/
Scattering, Radiation
/
Light
Type of study:
Prognostic_studies
Language:
En
Journal:
Appl Opt
Year:
2020
Document type:
Article
Country of publication:
United States