Ocean Backscatter Profiling Using High-Spectral-Resolution Lidar and a Perturbation Retrieval

Churnside, James; Hair, Johnathan; Hostetler, Chris; Scarino, Amy

doi:10.3390/rs10122003

i

Ocean Backscatter Profiling Using High-Spectral-Resolution Lidar and a Perturbation Retrieval

2018
By Churnside, James ; Hair, Johnathan ; Hostetler, Chris ; ...

Details

Journal Title:

Remote Sensing
Personal Author:

Churnside, James ; Hair, Johnathan ; Hostetler, Chris ; Scarino, Amy
NOAA Program & Office:

CIRES (Cooperative Institute for Research in Environmental Sciences) ; OAR (Oceanic and Atmospheric Research) ; ESRL (Earth System Research Laboratory) ; CSL (Chemical Sciences Laboratory)
Description:

Ocean lidar attenuation and scattering parameters were derived from a high-spectral-resolution lidar (HSRL) using two different retrieval techniques. The first used the standard HSRL retrieval, and the second used only the total backscatter channel and a perturbation retrieval (PR). The motivation is to evaluate differences between the two techniques that would affect the decision of whether to use a simple backscatter lidar or a more complex HSRL in future applications. For the data set investigated, the attenuation coefficient from the PR was an average of 11% lower than that from the HSRL. The PR estimate of the scattering parameter decreased with depth relative to the HSRL estimate, although the overall bias was zero as a result of the calibration procedure. Near the surface, the coefficient of variability in both estimates of attenuation and in HSRL estimates of scattering were around 5%, but that in the PR estimate of scattering was over 10%. At greater depths, the variability increases for all of the profile parameters. The correlation between the two estimates of attenuation coefficient was 0.7. The correlation between scattering parameters was > 0.8 near the surface, but decreased to 0.4 at a depth of around 20 m. Overall, the PR performed better relative to the HSRL in offshore waters than in nearshore waters.
Keywords:

Oceanography Remote Sensing Remote Sensing
Source:

Remote Sens. 2018, 10(12), 2003
DOI:

https://doi.org/10.3390/rs10122003
Document Type:

Journal Article
Rights Information:

CC BY
Compliance:

Submitted
Main Document Checksum:

urn:sha-512:ffc8349fbfb3dde77d8283963bda090090ee24ab5587479d1e000358d90fa21a1259fa415a918e5968911d51efb3c47cd7c43840ab45458d1f605ba48fb76509
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https://repository.library.noaa.gov/view/noaa/26420/noaa_26420_DS1.pdf
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[PDF - 7.41 MB ]

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