Ocean Lidar Measurements of Beam Attenuation and a Roadmap to Accurate Phytoplankton Biomass Estimates

Abstract

Beam attenuation coefficient, c, provides an important optical index of plankton standing stocks, such as phytoplankton biomass and total particulate carbon concentration. Unfortunately, c has proven difficult to quantify through remote sensing. Here, we introduce an innovative approach for estimating c using lidar depolarization measurements and diffuse attenuation coefficients from ocean color products or lidar measurements of Brillouin scattering. The new approach is based on a theoretical formula established from Monte Carlo simulations that links the depolarization ratio of sea water to the ratio of diffuse attenuation Kd and beam attenuation C (i.e., a multiple scattering factor).On July 17, 2014, the CALIPSO satellite was tilted 30° off-nadir for one nighttime orbit in order to minimize ocean surface backscatter and demonstrate the lidar ocean subsurface measurement concept from space. Depolarization ratios of ocean subsurface backscatter are measured accurately. Beam attenuation coefficients computed from the depolarization ratio measurements compare well with empirical estimates from ocean color measurements. We further verify the beam attenuation coefficient retrievals using aircraftbased high spectral resolution lidar (HSRL) data that are collocated with in-water optical measurements.

Retrieval of ocean subsurface particulate backscattering coefficient from space-borne CALIOP lidar measurements

“…(2) stands for the surface contribution to the 532 nm subsurface backscatter, which was estimated using 1064 nm observations as its subsurface signals are near zero due to strong absorption by water at 1064 nm. Observations suggest that ocean surface backscatter at 532 nm is about 30% less than ocean surface backscatter at 1064 nm due to more atmospheric attenuation and ozone absorption at 532 nm [8].…”

“…For the CALIOP near nadir (0.3° or 3° off nadir angles) measurements, the ocean surface attenuated backscatter is about 30 times stronger than the subsurface backscatter [8,9], which makes it difficult to separate the subsurface backscatter from ocean surface backscatter [6,10]. Behrenfeld et al quantified the global ocean phytoplankton biomass and total particulate organic carbon stocks using CALIOP near nadir measurements, where the ocean surface backscatter was estimated from co-located Advanced Microwave Scanning Radiometer-EOS (AMSR-E) ocean surface wind speed and CloudSat microwave measurements, and particulate depolarization ratio in water was evaluated using MODerate-resolution Imaging Spectroradiometer (MODIS) monthly diffuse attenuation coefficients [4].…”

“…The CALIOP lidar was designed to provide the observations necessary for an improved understanding of the impact of clouds and aerosols on the Earth's radiation budget and climate [1][2][3]. Current analyses indicate a potential of CALIOP lidar for quantifying global ocean carbon stocks [4,5] and ocean subsurface backscatter [6][7][8] as well.…”

Estimation of Size-Fractionated Primary Production from Satellite Ocean Colour in UK Shelf Seas

“…Due to the difficulty in modelling variable sub-surface physical features from satellite, using simpler, generalised models of sub-surface biomass distribution tuned to the hydrography of specific regions may be a reasonable approach. The advent of combined passive ocean colour and BioArgo float arrays, offer the potential to improve the modelling of the vertical distribution of phytoplankton to increase the accuracy of satellite estimates of PP [98][99][100][101][102][103][104][105][106][107].…”

An interpretation of underwater LiDAR waveforms based on a modified Weibull probability distribution function

“…However, these techniques often require more than one LiDAR system configuration (e.g., 3 FOVs) [6], the a priori knowledge of bathymetry [8] or additional apparent optical properties [7,9] , or assumptions regarding the volume scattering function [5] . In all cases, these inversions were developed for data collected by airborne LiDARs.…”