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

A new approach has been proposed to determine ocean subsurface particulate backscattering coefficient b_bp from CALIOP 30° off-nadir lidar measurements. The new method also provides estimates of the particle volume scattering function at the 180° scattering angle. The CALIOP based layer-integrated lidar backscatter and particulate backscattering coefficients are compared with the results obtained from MODIS ocean color measurements. The comparison analysis shows that ocean subsurface lidar backscatter and particulate backscattering coefficient b_bp can be accurately obtained from CALIOP lidar measurements, thereby supporting the use of space-borne lidar measurements for ocean subsurface studies.

NIR- and SWIR-based on-orbit vicarious calibrations for satellite ocean color sensors

The near-infrared (NIR) and shortwave infrared (SWIR)-based atmospheric correction algorithms are used in satellite ocean color data processing, with the SWIR-based algorithm particularly useful for turbid coastal and inland waters. In this study, we describe the NIR- and two SWIR-based on-orbit vicarious calibration approaches for satellite ocean color sensors, and compare results from these three on-orbit vicarious calibrations using satellite measurements from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP). Vicarious calibration gains for VIIRS spectral bands are derived using the in situ normalized water-leaving radiance nLw(λ) spectra from the Marine Optical Buoy (MOBY) in waters off Hawaii. The SWIR vicarious gains are determined using VIIRS measurements from the South Pacific Gyre region, where waters are the clearest and generally stable. Specifically, vicarious gain sets for VIIRS spectral bands of 410, 443, 486, 551, and 671 nm derived from the NIR method using the NIR 745 and 862 nm bands, the SWIR method using the SWIR 1238 and 1601 nm bands, and the SWIR method using the SWIR 1238 and 2257 nm bands are (0.979954, 0.974892, 0.974685, 0.965832, 0.979042), (0.980344, 0.975344, 0.975357, 0.965531, 0.979518), and (0.980820, 0.975609, 0.975761, 0.965888, 0.978576), respectively. Thus, the NIR-based vicarious calibration gains are consistent with those from the two SWIR-based approaches with discrepancies mostly within ~0.05% from three data processing methods. In addition, the NIR vicarious gains (745 and 862 nm) derived from the two SWIR methods are (0.982065, 1.00001) and (0.981811, 1.00000), respectively, with the difference ~0.03% at the NIR 745 nm band. This is the fundamental basis for the NIR-SWIR combined atmospheric correction algorithm, which has been used to derive improved satellite ocean color products over open oceans and turbid coastal/inland waters. Therefore, a unified vicarious gain set for VIIRS bands M1-M8 and M10-M11 has been implemented in the VIIRS ocean color data processing. Using the unified vicarious gain set, VIIRS mission-long ocean color data have been successfully reprocessed using the NIR-, SWIR-, and NIR-SWIR-based atmospheric correction algorithms.

Implementation of an analytical Raman scattering correction for satellite ocean-color processing

Raman scattering of photons by seawater molecules is an inelastic scattering process. This effect can contribute significantly to the water-leaving radiance signal observed by space-borne ocean-color spectroradiometers. If not accounted for during ocean-color processing, Raman scattering can cause biases in derived inherent optical properties (IOPs). Here we describe a Raman scattering correction (RSC) algorithm that has been integrated within NASA's standard ocean-color processing software. We tested the RSC with NASA's Generalized Inherent Optical Properties algorithm (GIOP). A comparison between derived IOPs and in situ data revealed that the magnitude of the derived backscattering coefficient and the phytoplankton absorption coefficient were reduced when the RSC was applied, whilst the absorption coefficient of colored dissolved and detrital matter remained unchanged. Importantly, our results show that the RSC did not degrade the retrieval skill of the GIOP. In addition, a time-series study of oligotrophic waters near Bermuda showed that the RSC did not introduce unwanted temporal trends or artifacts into derived IOPs.

Out-of-band effects of satellite ocean color sensors

We analyze the sensor out-of-band (OOB) effects for satellite ocean color sensors of the sea-viewing wild field-of-view sensor (SeaWiFS), the moderate resolution imaging spectroradiometer (MODIS), and the visible infrared imaging radiometer suite (VIIRS) for phytoplankton-dominated open oceans and turbid coastal and inland waters, following the approach of Wang et al. [Appl. Opt.40, 343 (2001)APOPAI0003-693510.1364/AO.40.000343]. The applicability of the open ocean water reflectance model of Morel and Maritorena [J. Geophys. Res.106, 7163 (2001)JGREA20148-022710.1029/2000JC000319] (MM01) for the sensor OOB effects is analyzed for oligotrophic waters in Hawaii. The MM01 model predicted OOB contributions for oligotrophic waters are consistent with the result from in situ measurements. The OOB effects cause an apparent shift in sensor band center wavelengths in radiometric response, which depends on the sensor spectral response function and the target radiance being measured. Effective band center wavelength is introduced and calculated for three satellite sensors and for various water types. Using the effective band center wavelengths, satellite and in situ measured water optical property data can be more meaningfully and accurately compared. It is found that, for oligotrophic waters, the OOB effect is significant for the SeaWiFS 555 nm band (and somewhat 510 nm band), MODIS 412 nm band, and VIIRS 551 nm band. VIIRS and SeaWiFS have similar sensor OOB performance. For coastal and inland waters, however, the OOB effect is generally not significant for all three sensors, even though some small OOB effects do exist. This study highlights the importance of understanding the sensor OOB effect and the necessity of a complete prelaunch sensor characterization on the quality of ocean color products. Furthermore, it shows that hyperspectral in situ optics measurements are preferred for the purpose of accurately validating satellite-measured normalized water-leaving radiance spectra data.

Using a multiwavelength LiDAR for improved remote sensing of natural waters

This paper describes research to characterize the benefits of a multiwavelength oceanographic LiDAR for various water types. Field measurements were conducted to establish endmembers representative of both typical and extremely challenging natural conditions. Laboratory tests were performed using a prototype multiwavelength LiDAR in water tanks with optical conditions simulating both sediment-laden and biologically rich water types. LiDAR models were used to simulate the LiDAR signal from both field and laboratory experiments. Our measurements and models show that using a laser wavelength of 470-490 nm in the open ocean leads to an improvement factor of 1.50-1.75 compared to a 532 nm system. In more turbid areas using a laser wavelength of 560-580 nm leads to an improvement factor of 1.25. We conclude by demonstrating how using multiple LiDAR wavelengths can help detect and characterize constituents in the water column.

Inherent optical properties of Jerlov water types

The diffuse attenuation coefficient K_d(λ) was first expressed in terms of the inherent optical properties (IOPs) of water according to well-established empirical bio-optical models. Boltzmann simulated annealing was then used to find the best sets of IOPs to fit K_d(λ) spectra to the reference spectra Kd0(λ) that define the Jerlov water types. Absorption a(λ) and scattering b(λ) coefficients were thus obtained for all Jerlov water types over the wavelength range 300-700 nm. The chlorophyll concentrations corresponding to the Jerlov water types were also obtained via bio-optical models. The result is a self-consistent set of spectral IOPs, chlorophyll concentrations, and Jerlov water types useful for a variety of underwater optical communications and remote sensing applications.

Technique for monitoring performance of VIIRS reflective solar bands for ocean color data processing

A technique for monitoring and evaluating the performance of on-orbit calibration for satellite ocean color sensors has been developed. The method is based on the sensor on-orbit vicarious calibration approach using in situ ocean optics measurements and radiative transfer simulations to predict (calculate) sensor-measured top-of-atmosphere spectral radiances. Using this monitoring method with in situ normalized water-leaving radiance nLw(λ) data from the Marine Optical Buoy (MOBY) in waters off Hawaii, we show that the root-cause for an abnormal inter-annual difference of chlorophyll-a data over global oligotrophic waters between 2012 and 2013 from the Visible Infrared Imaging Radiometer Suite (VIIRS) is primarily due to the VIIRS on-orbit calibration performance. In particular, VIIRS-produced Sensor Data Records (SDR) (or Level-1B data) are biased low by ~1% at the wavelength of 551 nm in 2013 compared with those in 2012. The VIIRS calibration uncertainty led to biased low chlorophyll-a data in 2013 by ~30-40% over global oligotrophic waters. The methodology developed in this study can be implemented for the routine monitoring of on-orbit satellite sensor performance (such as VIIRS). Particularly, long-term Chl-a data over open oceans can also be used as an additional source to evaluate ocean color satellite sensor performance. We show that accurate long-term and consistent MOBY in situ measurements can be used not only for the required system vicarious calibration for satellite ocean color data processing, but also can be used to characterize and monitor both the short-term and long-term sensor on-orbit performances.

Destriping algorithm for improved satellite-derived ocean color product imagery

While modern multi-detector sensors offer a much improved image resolution and signal-to-noise ratio among other performance benefits, the multi-detector arrangement gives rise to striping in satellite imagery due to various sources, which cannot be perfectly corrected by sensor calibration. Recently, Bouali and Ignatov (2014) [J. Atmos. Oceanic Technol., 31, 150-163 (2014)] introduced a new approach to remove relatively small detector performance-related striping from thermal infrared bands for improved sea surface temperature data. We show that this methodology, with appropriately chosen parameters and adjustments, can also be applied to remove striping of a much larger variance from the solar reflective band data. Specifically, we modify and apply this new approach to remove striping from satellite-derived normalized water-leaving radiance spectra nLw(λ) obtained from solar reflective bands. It is important that the destriping approach not be applied to the top-of-atmosphere radiances. The results show a significant improvement in image quality for both nLw(λ) spectra and nLw(λ)-derived ocean biological and biogeochemical products such as chlorophyll-a concentration, and the water diffuse attenuation coefficient at the wavelength of 490 nm Kd(490).

Lidar extinction-to-backscatter ratio of the ocean

Bio-optical models are used to develop a model of the lidar extinction-to-backscatter ratio applicable to oceanographic lidar. The model is based on chlorophyll concentration, and is expected to be valid for Case 1 waters. The limiting cases of narrow- and wide-beam lidars are presented and compared with estimates based on in situ optical measurements. Lidar measurements are also compared with the model using in situ or satellite estimates of chlorophyll concentration. A modified lidar ratio is defined, in which the properties of pure sea water are removed. This modified ratio is shown to be nearly constant for wide-beam lidar operating in low-chlorophyll waters, so accurate inversion to derive extinction and backscattering is possible under these conditions. This ratio can also be used for lidar calibration.

Assessment of the colored dissolved organic matter in coastal waters from ocean color remote sensing

Knowledge on absorption by colored dissolved organic matter, a(cdom), spatio-temporal variability in coastal areas is of fundamental importance in many field of researches related to biogeochemical cycles studies, coastal areas management, as well as land and water interactions in the coastal domain. A new method, based on the theoretical link between the vertical attenuation coefficient, K(d), and the absorption coefficient, has been developed to assess a(cdom). This method, confirmed from radiative transfer simulations and in situ measurements, and tested on an independent in situ data set (N = 126), allows a(cdom) to be assessed with a Mean Relative Absolute Difference, MRAD, of 33% over two order of magnitude (from 0.01 to 1.16 m(-1)). In the frame of ocean color observation, K(d) is not directly measured but estimated from the remote sensing reflectance, R(rs). Based on 109 satellite (SeaWiFS) and in situ coincident (i.e. match-up) data points a(cdom) is retrieved with a MRAD value of 37%. This simple model generally presents slightly better performances than recently developed empirical or semi-analytical algorithms.

Atmospheric correction of HJ-1 CCD imagery over turbid lake waters

We have presented an atmospheric correction algorithm for HJ-1 CCD imagery over Lakes Taihu and Chaohu with highly turbid waters. The Rayleigh scattering radiance (Lr) is calculated using the hyperspectral Lr with a wavelength interval 1nm. The hyperspectral Lr is interpolated from Lr in the central wavelengths of MODIS bands, which are converted from the band response-averaged Lr calculated using the Rayleigh look up tables (LUTs) in SeaDAS6.1. The scattering radiance due to aerosol (La) is interpolated from La at MODIS band 869nm, which is derived from MODIS imagery using a shortwave infrared atmospheric correction scheme. The accuracy of the atmospheric correction algorithm is firstly evaluated by comparing the CCD measured remote sensing reflectance (Rrs) with MODIS measurements, which are validated by the in situ data. The CCD measured Rrs is further validated by the in situ data for a total of 30 observation stations within ± 1h time window of satellite overpass and field measurements. The validation shows the mean relative errors about 0.341, 0.259, 0.293 and 0.803 at blue, green, red and near infrared bands.

A new model for the vertical spectral diffuse attenuation coefficient of downwelling irradiance in turbid coastal waters: validation with in situ measurements

The vertical spectral diffuse attenuation coefficient of Kd is an important optical property related to the penetration and availability of light underwater, which is of fundamental interest in studies of ocean physics and biology. Models developed in the recent decades were mainly based on theoretical analyses and numerical (radiative transfer) simulations to estimate this property in optically deep waters, thus leaving inadequate knowledge of its variability at multiple depths and wavelengths, covering a wide range of solar incident geometry, in turbid coastal waters. In the present study, a new model is developed to quantify the vertical, spatial and temporal variability of K(d) at multiple wavelengths and to quantify its dependence with respect to solar incident geometry under differing sky conditions. Thus, the new model is derived as a function of inherent optical properties (IOPs - absorption a and backscattering b(b)), solar zenith angle and depth parameters. The model results are rigorously evaluated using time-series and discrete in situ data from clear and turbid coastal waters. The K(d) values derived from the new model are found to agree with measured data within the mean relative error 0.02~6.24% and R² 0.94~0.99. By contrast, the existing models have large errors when applied to the same data sets. Statistical results of the new model for the vertical spectral distribution of K(d) in clear oceanic waters (for different solar zenith and in-water conditions) are also good when compared to those of the existing models. These results suggest that the new model can provide an improved interpretation about the variation of the vertical spectral diffuse attenuation coefficient of downwelling irradiance, which will have important implications for ocean physics, biogeochemical cycles and underwater applications in both relatively clear and turbid coastal waters.

An inherent-optical-property-centered approach to correct the angular effects in water-leaving radiance

Remote-sensing reflectance (R(rs)), which is defined as the ratio of water-leaving radiance (L(w)) to downwelling irradiance just above the surface (E(d)(0⁺)), varies with both water constituents (including bottom properties of optically-shallow waters) and angular geometry. L(w) is commonly measured in the field or by satellite sensors at convenient angles, while E(d)(0⁺) can be measured in the field or estimated based on atmospheric properties. To isolate the variations of R(rs) (or L(w)) resulting from a change of water constituents, the angular effects of R(rs) (or L(w)) need to be removed. This is also a necessity for the calibration and validation of satellite ocean color measurements. To reach this objective, for optically-deep waters where bottom contribution is negligible, we present a system centered on water's inherent optical properties (IOPs). It can be used to derive IOPs from angular R_rs and offers an alternative to the system centered on the concentration of chlorophyll. This system is applicable to oceanic and coastal waters as well as to multiband and hyperspectral sensors. This IOP-centered system is applied to both numerically simulated data and in situ measurements to test and evaluate its performance. The good results obtained suggest that the system can be applied to angular R(rs) to retrieve IOPs and to remove the angular variation of R(rs).

Relationships between water attenuation coefficients derived from active and passive remote sensing: a case study from two coastal environments

Relationships between the satellite-derived diffuse attenuation coefficient of downwelling irradiance (K(d)) and airborne-based vertical attenuation of lidar volume backscattering (α) were examined in two coastal environments. At 1.1 km resolution and a wavelength of 532 nm, we found a greater connection between α and K(d) when α was computed below 2 m depth (Spearman rank correlation coefficient up to 0.96), and a larger contribution of K(d) to α with respect to the beam attenuation coefficient as estimated from lidar measurements and K(d) models. Our results suggest that concurrent passive and active optical measurements can be used to estimate total scattering coefficient and backscattering efficiency in waters without optical vertical structure.

Uncertainties of optical parameters and their propagations in an analytical ocean color inversion algorithm

Following the theory of error propagation, we developed analytical functions to illustrate and evaluate the uncertainties of inherent optical properties (IOPs) derived by the quasi-analytical algorithm (QAA). In particular, we evaluated the effects of uncertainties of these optical parameters on the inverted IOPs: the absorption coefficient at the reference wavelength, the extrapolation of particle backscattering coefficient, and the spectral ratios of absorption coefficients of phytoplankton and detritus/gelbstoff, respectively. With a systematically simulated data set (46,200 points), we found that the relative uncertainty of QAA-derived total absorption coefficients in the blue-green wavelengths is generally within +/-10% for oceanic waters. The results of this study not only establish theoretical bases to evaluate and understand the effects of the various variables on IOPs derived from remote-sensing reflectance, but also lay the groundwork to analytically estimate uncertainties of these IOPs for each pixel. These are required and important steps for the generation of quality maps of IOP products derived from satellite ocean color remote sensing.