The Suomi National Polar-orbiting Partnership (SNPP) was successfully launched on October 28, 2011. The Visible
Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP, which has 22 spectral bands (from visible to
infrared) similar to the NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS), is a multi-disciplinary
sensor providing observations for the Earth’s atmosphere, land, and ocean properties. In this paper, we provide some
evaluations and assessments of VIIRS ocean color data products, or ocean color Environmental Data Records (EDR),
including normalized water-leaving radiance spectra nLw(λ) at VIIRS five spectral bands, chlorophyll-a (Chl-a)
concentration, and water diffuse attenuation coefficient at the wavelength of 490 nm Kd(490). Specifically, VIIRS ocean
color products derived from the NOAA Multi-Sensor Level-1 to Level-2 (NOAA-MSL12) ocean color data processing
system are evaluated and compared with MODIS ocean color products and in situ measurements. MSL12 is now
NOAA’s official ocean color data processing system for VIIRS. In addition, VIIRS Sensor Data Records (SDR or Level-
1B data) have been evaluated. In particular, VIIRS SDR and ocean color EDR have been compared with a series of in
situ data from the Marine Optical Buoy (MOBY) in the waters off Hawaii. A notable discrepancy of global deep water
Chl-a derived from MODIS and VIIRS between 2012 and 2013 is observed. This discrepancy is attributed to the SDR
(or Level-1B data) calibration issue and particularly related to VIIRS green band at 551 nm. To resolve this calibration
issue, we have worked on our own sensor calibration by combining the lunar calibration effect into the current
calibration method. The ocean color products derived from our new calibrated SDR in the South Pacific Gyre show that
the Chl-a differences between 2012 and 2013 are significantly reduced. Although there are still some issues, our results
show that VIIRS is capable of providing high-quality global ocean color products in support of science research and
operational applications. The VIIRS evaluation and monitoring results can be found at the website:
http://www.star.nesdis.noaa.gov/sod/mecb/color/index.html.
In situ data are essential for calibration, validation, and bio-optical algorithm development of ocean color remote sensing, as well as for studying and understanding of ocean optical, biological, and biogeochemical properties. Especially, calibration and validation of ocean color satellite data relies on high quality in situ data. In addition, objective evaluation of satellite ocean color products need well quality controlled in situ data from various bio-optical environments covering diverse aquatic waters. The goal of ocean color satellite sensors is to remotely derive accurate normalized water-leaving radiance spectra (nLw(λ)), therefore other water biological and biogeochemical property data can be obtained using satellite-measured nLw(λ) spectra. In this paper, we show results from analyzing in situ data processing procedure from the Marine Optical Buoy (MOBY) and NASA SeaWiFS Bio-optical Archive and Storage System (SeaBASS) used for satellite ocean color calibration and validation purposes. Various issues in determining final product of in situ radiometric data processing such as convolving nLw(λ) with respect to satellite sensor spectral response functions, sensor effective band center wavelengths, and effects of Bi-directional Reflectance Distribution Function (BRDF) are analyzed and discussed. Performance of satellite-derived nLw(λ) taking into consideration of various issues in the in situ data processing is also assessed.
Particulate absorption (aP()) including phytoplankton (aPHY()) and non-algal particles (NAP) (aNAP()) were measured in southeastern Bering Sea during a cruise in July 2008. This study analyzes the aP() properties through in-situ and quasi analytical algorithm (QAA) derived ocean color satellite Medium Resolution Imaging spectrometer (MERIS) and Moderate resolution Imaging Spectroradiometer (MODIS) observations. We found that the aP() and aPHY() correlated well with chlorophyll-a and were lower as a function of chlorophyll-a as compared to low latitudes. The specific phytoplankton absorption (a*PHY()) showed more variability in the blue as compared to the red part of the spectrum indicating pigment packaging and/or change in pigment composition. The remote sensing reflectance (Rrs()) showed significant variability in spectral shape and magnitude which was consistent with the variable total absorption minus pure water absorption (aT-W()) spectra observed in the study area. Simple satellite retrieved Rrs() ratios were related to in-situ aPHY() and aDG() by applying an inverse power fit; Rrs(490)/Rrs(510) gave the best results for aPHY(443) and aDG(443) (R2 - 0.80 and 0.75) respectively. The match-ups of in-situ and MERIS retrieved aPHY() and NAP plus colored dissolved organic matter (aDG()) using QAA after log-transformation showed reasonable agreement with R2 of 0.71 and 0.61 and RMSE of 0.316 and 0.391 at 443 nm, respectively. Although the QAA derived aPHY() and aDG() from MERIS overestimated and underestimated, respectively the in-situ measurements at all wavelengths, the match-up analysis was encouraging.
°Empirical orthogonal function (EOF) analysis was used to study spatio-temporal variability of the Moderate Resolution
Imaging Spectroradiometer (MODIS) imagery of sea surface temperature (SST (C)) and chlorophyll (mg m-3) for the
eastern Bering Sea for May, June, July, August, September (MJJAS) for a period of 7 years (2003 - 2009). The EOF
analysis was conducted on SST and chlorophyll monthly composites that were normalized by subtracting the spatial and
temporal means with cloud, ice and land cover masked out. The SST in eastern Bering Sea showed a transition from a
warm period (2003-2005) to cooler period (2006-2009). The first 3 EOF modes of SST were retained as they explained
76.7% of the spatio-temporal variability, with the first SST EOF mode explaining 59.5% of the total variation of SST in
the study area during the study period. For the chlorophyll dataset, the first 3 EOF modes explained greater than 58.5%
of the spatio-temporal variability, with the first chlorophyll EOF explaining 28.14% of total variance in chlorophyll. The
decreasing amplitude of first SST EOF and switching from mostly positive to negative amplitude of the third chlorophyll
EOF mode in 2006 was consistent with the May SST Index, Ice Cover Index and Bering Sea Pressure Index (BSPI).
Measurements of particulate absorption, namely absorption by phytoplankton and non-algal particles (NAP) are
important components in bio-optical models; only a few studies have been reported for the southeastern Bering Sea. This
study analyzes variability in spectral particulate absorption (aP(λ)) including phytoplankton (aPHY(λ)) and NAP
absorption (aNAP(λ)) from in-situ data in conjunction with ocean color satellite data (MODIS - Moderate Resolution
Imaging Spectroradiometer) along four transects in the southeastern Bering Sea shelf during a cruise in July 2008.
Results obtained indicate that surface aPHY(λ) at 443 nm is higher in middle shelf near the Pribilof Islands with aNAP(λ)
decreasing from north to south across the shelf. Greater than 90% of variability in aP(λ) could be explained by aPHY(λ)
indicating biogenic matter dominates changes in particulate absorption. Good correlations were found between aP(λ),
aPHY(λ) at 443 nm and chlorophyll-a (R2 = 0.65 and 0.80, respectively). aPHY(λ) spectra were highly variable, with larger
variability in blue than red part of the spectrum, indicating change in pigment composition or package effect. MODIS
satellite derived aPHY(λ) using quasi-analytical algorithms (QAA) revealed patterns similar to in-situ absorption data for a
major part of the study area. Inconsistencies seen between in-situ absorption and QAA retrieved satellite absorption
could probably be attributed to temporal differences between in-situ data collection and satellite overpass.
We present here the cross calibration of ocean color satellite sensor, IRS-P4 OCM using the radiative transfer code, with
SeaWiFS as a reference. Since the bands of IRS-P4 OCM are identical to those of SeaWiFS and SeaWiFS has been
continuously and rigorously calibrated, SeaWiFS is used as a reference for the cross calibration of IRS-P4 OCM.
Calibrations coefficients for each band of IRS-P4 OCM are derived by comparing the actual radiances detected by the
satellites at top of the atmosphere and those obtained from the radiative transfer simulations of IRS-P4 OCM and
SeaWiFS. The chlorophyll a values derived using the calibrated IRS-P4 OCM are found to be comparable with those
derived from SeaWiFS and in close agreement with the measured values. The relative root mean square error (RRMSE)
between measured chlorophyll a and those derived from the satellites are found to be 0.28 and 0.26 for SeaWiFS and
IRS-P4 OCM respectively.
We present here algorithms to determine the inherent optical properties of water, backscattering probability and single scattering albedo at 490 and 676 nm from the apparent optical property, remote sensing reflectance. We have used the measured scattering and backscattering coefficients and the remote sensing reflectance to obtain a relationship for the backscattering ratio, which is defined as the ratio of the total backscattering to the total scattering in terms of the remote sensing reflectance of two bands. Using the empirical relationship for the total backscattering ratios, we have also computed single scattering albedo, which is defined as the ratio of the scattering to the beam attenuation coefficient. The values of single scattering albedo obtained from measured values and those obtained from the empirical method are found to be comparable. The values of single scattering albedo derived using the algorithm are found to be comparable to the measured values obtained from the eastern Arabian Sea, with the root mean squared error of 0.078 and the mean percentage error of 9.5% for the 490 nm and root mean squared error of 0.043 and the mean percentage error of 7.5% for the 676 nm.
An empirical method is presented here to estimates bulk particulate refractive index using the measured inherent and apparent optical properties from the various waters types of the Arabian Sea. We have used the empirical model, where the bulk refractive index is modeled in terms of the backscattering ratio and the hyperbolic slope of the particle size1. Empirical models are obtained to determine the slope of the particle size and backscattering ratio as a function of the remote sensing reflectance. We have used these algorithms with the IRS-P4 OCM satellite data and derived the refractive index image. The values of indexes are found to be lower for the open ocean and relatively higher for the coastal waters. Distinct features are observed even in the in the waters with similar chlorophyll concentrations. This algorithm provides scope for the classification of water types and detection of blooms.
Secchi depth provides the oceanographer with the first hand information about transparency and penetration of light in the water. Here we present results of the Secchi depth and the optical properties measured in the Arabian Sea. Our analyses show spatial and temporal variability of Secchi depth and their dependence on the optical properties beam attenuation and diffuse attenuation the biological parameter of Chlorophyll. The in-situ measured inherent and apparent optical properties have been used to understand the underwater light properties and their relations to the Secchi depth in various water types. The Secchi depth model is validated using the measured optical properties. We also present an empirical method to determine Secchi depth from the satellite ocean color sensor, and the application of the same to the IRS-P4 OCM is found to provide comparable results to the measured values.
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