NASA Ocean Biology Processing Group Research Articles

Evaluation of the NASA OBPG MERIS ocean surface PAR product in clear sky conditions.

The operational MEdium Resolution Imaging Spectrometer (MERIS) daily mean photosynthetically available radiation (PAR) product generated by the NASA Ocean Biology Processing Group (OBPG) was evaluated in clear sky conditions against in-situ measurements at various sites in the northwestern Mediterranean Sea (BOUSSOLE buoy), the northwestern Pacific (CCE-1 and -2 moorings), and the northeastern Atlantic (COVE platform). The measurements were first checked and corrected for calibration errors and uncertainties in data processing by comparing daily means for clear days (i.e., no clouds from sunrise to sunset and low aerosol abundance) with theoretical values from an accurate Monte Carlo radiative transfer code. The OBPG algorithm performed well when sky was completely cloudless during daytime, with a bias of 0.26 E/m2/d (0.6%) and a RMS difference of 1.7 E/m2/d (4.0%). Using satellite-derived aerosol optical thickness (AOT) and Angström coefficient instead of climatology slightly degraded the results, which was likely due to uncertainties in the aerosol retrievals. A sensitivity study to aerosol properties indicated that climatology may not work in some situations (e.g., episodic dust, pollution, or biomass burning events), suggesting that it is best to use actual aerosol estimates in clear sky conditions. The analysis also revealed that specifying aerosol properties, therefore atmospheric transmittance, from AOT and Angström coefficient, even retrieved from the satellite imagery, may not be sufficient in the presence of absorbing aerosols, especially when loadings are important. Performance was degraded when including situations of clear sky at the time of the MERIS observation but cloudy sky before and/or after overpass, resulting in a bias (overestimation) of 2.8 E/m2/d (7.3%) and a RMS difference of 6.0 E/m2/d (15.8%). The relatively large overestimation was due to the inability of the OBPG PAR algorithm to detect cloudiness at times other than the time of satellite overpass. The key to improving the daily mean PAR estimates in such situations does not reside so much in improving the radiative transfer treatment or specifying more accurately aerosol properties, but rather in accounting properly for the diurnal variability of cloudiness. To this end, a methodology that utilized Modern Era Retrospective Reanalysis for Research and Applications, Version 2 (MERRA-2) hourly cloud data (fractional coverage, optical thickness) was proposed and tested, reducing the bias to 1.6 E/m2/d (4.2%). Improvement was not sufficient in some situations, due to the coarse resolution and uncertainties of the MERRA-2 products, which could not describe properly the cloud properties at the local scale (MERIS pixel). The treatment is applicable to any cloud situation and should be considered in a future version of the of OBPG PAR algorithm. This would require, however, refreshing the standard OBPG PAR products generated as part of the ocean-color processing line according to MERRA-2 data availability.

MODIS Aqua Reflective Solar Band Calibration for NASA’s R2018 Ocean Color Products

Remote-sensing ocean color products have stringent requirements on radiometric calibration stability. To address a calibration deficiency in Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua in recent years, the NASA Ocean Biology Processing Group (OBPG) developed a new calibration for reflective solar bands. Prior to the reprocessing of NASA’s ocean color products for 2018 (R2018), the OBPG MODIS products had been based on calibration provided by the MODIS Calibration Support Team (MCST). Several modifications were made to the MCST calibration approach to improve the calibration accuracy for ocean color products. These include 1) applying 936-nm detector normalization to solar diffuser stability monitor (SDSM) data to reduce coherent noise; 2) modeling solar diffuser (SD) degradation wavelength dependency to determine SD degradation in near-infrared and shortwave infrared wavelengths; 3) computing detector gains using SD screen-closed data to better match ocean radiance levels in all bands; 4) performing a simple atmospheric correction to reduce bidirectional reflectance distribution function (BRDF) effects in desert trends; 5) estimating and using modulated relative spectral response (RSR) impact on ocean data to adjust the calibration coefficients; 6) using smoothing to characterize the temporal change in calibration; and characterizing response versus scan angle (RVS) changes using 2nd-order polynomials to improve spatial/temporal calibration stability. Relative to the previous R2014 ocean color products, the R2018 calibration removed the suspect late-mission global trends in blue-band water-leaving reflectance and some anomalously large short-term variability (spikes) in the temporal trend of chlorophyll concentration. This paper will describe the OBPG calibration with a focus on the differences between the MCST and OBPG approaches.

Evaluation of sea-surface photosynthetically available radiation algorithms under various sky conditions and solar elevations.

In this study, we report on the performance of satellite-based photosynthetically available radiation (PAR) algorithms used in published oceanic primary production models. The performance of these algorithms was evaluated using buoy observations under clear and cloudy skies, and for the particular case of low sun angles typically encountered at high latitudes or at moderate latitudes in winter. The PAR models consisted of (i) the standard one from the NASA-Ocean Biology Processing Group (OBPG), (ii) the Gregg and Carder (GC) semi-analytical clear-sky model, and (iii) look-up-tables based on the Santa Barbara DISORT atmospheric radiative transfer (SBDART) model. Various combinations of atmospheric inputs, empirical cloud corrections, and semi-analytical irradiance models yielded a total of 13 (11 + 2 developed in this study) different PAR products, which were compared with in situ measurements collected at high frequency (15min) at a buoy site in the Mediterranean Sea (the "BOUée pour l'acquiSition d'une Série Optique à Long termE," or, "BOUSSOLE" site). An objective ranking method applied to the algorithm results indicated that seven PAR products out of 13 were well in agreement with the in situ measurements. Specifically, the OBPG method showed the best overall performance with a root mean square difference (RMSD) (bias) of 19.7% (6.6%) and 10% (6.3%) followed by the look-up-table method with a RMSD (bias) of 25.5% (6.8%) and 9.6% (2.6%) at daily and monthly scales, respectively. Among the four methods based on clear-sky PAR empirically corrected for cloud cover, the Dobson and Smith method consistently underestimated daily PAR while the Budyko formulation overestimated daily PAR. Empirically cloud-corrected methods using cloud fraction (CF) performed better under quasi-clear skies (CF<0.3) with an RMSD (bias) of 9.7%-14.8% (3.6%-11.3%) than under partially clear to cloudy skies (0.3<CF<0.7) with 16.1%-21.2% (-2.2%-8.8%). Under complete overcast conditions (CF>0.7), however, all methods showed larger RMSD differences (biases) ranging between 32% and 80.6% (-54.5%-8.7%). Finally, three methods tested for low sun elevations revealed systematic overestimation, and one method showed a systematic underestimation of daily PAR, with relative RMSDs as large as 50% under all sky conditions. Under partially clear to overcast conditions all the methods underestimated PAR. Model uncertainties predominantly depend on which cloud products were used.

Assessment of Terra MODIS On-Orbit Polarization Sensitivity Using Pseudoinvariant Desert Sites

The Moderate Resolution Imaging Spectroradiometer (MODIS) is currently flying on NASA’s Earth Observing System Terra and Aqua satellites, launched in 1999 and 2002, respectively. MODIS reflective solar bands in the visible wavelength range are known to be sensitive to polarized light based on prelaunch polarization sensitivity tests. After about five years of on-orbit operations, it was discovered that the polarization sensitivity at short wavelengths had shown a noticeable increase. In this paper, we examine the impact of polarization on measured top-of-atmosphere (TOA) reflectances based on MODIS Collection-6 L1B over pseudoinvariant desert sites. The standard polarization correction equation is used in combination with simulated at-sensor radiances using the second simulation of a satellite signal in the Solar Spectrum, Vector Radiative Transfer Code (6SV). We ignore the polarization contribution from the surface and a ratio approach is used for both 6SV-derived input parameters and observed TOA reflectances. Results indicate that significant gain corrections up to 25% are required near the end of scan for the 412 and 443 nm bands. The polarization correction reduces the seasonal fluctuations in reflectance trends and mirror side ratios from 30% and 12% to 10% and 5%, respectively, for the two bands. Comparison of the effectiveness of the polarization correction with the results from the NASA Ocean Biology Processing Group shows a good agreement in the corrected reflectance trending results and their seasonal fluctuations.

On-orbit calibration of the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite for ocean color applications.

The NASA Ocean Biology Processing Group (OBPG) developed two independent calibrations of the Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) moderate resolution reflective solar bands using solar diffuser measurements and lunar observations, and implemented a combined solar- and lunar-based calibration to track temporal changes in radiometric response of the instrument. Differences between the solar and lunar data sets have been used to identify issues and verify improvements in each. Linearization of the counts-to-radiance conversion yields a more consistent calibration at low radiance levels. Correction of a recently identified error in the VIIRS solar unit vector coordinate frame has been incorporated into the solar data and diffuser screen transmission functions. Temporal trends in the solar diffuser stability monitor data have been evaluated and addressed. Fits to the solar calibration time series show mean residuals per band of 0.067%-0.17%. Periodic residuals in the VIIRS lunar data are confirmed to arise from a wavelength-dependent libration effect for the sub-spacecraft point in the output of the U.S. Geological Survey Robotic Lunar Observatory photometric model of the Moon. Temporal variations in the relative spectral responses for each band have been assessed, and significant impact on band M1 (412 nm) lunar data has been identified and rectified. Fits to the lunar calibration time series, incorporating sub-spacecraft point libration corrections, show mean residuals per band of 0.069%-0.20%. Lunar calibrations have been used to adjust the solar-derived radiometric corrections for bands M1, M3, and M4. After all corrections, the relative differences in the solar and lunar calibrations for bands M1-M7 are 0.093%-0.22%. The OBPG has achieved a radiometric stability for the VIIRS on-orbit calibration that is commensurate with those achieved for SeaWiFS and Aqua MODIS, supporting the incorporation of VIIRS data into the long-term NASA ocean color data record.

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

AbstractA semianalytical ocean color inversion algorithm was developed for improving retrievals of inherent optical properties (IOPs) in optically shallow waters. In clear, geometrically shallow waters, light reflected off the seafloor can contribute to the water‐leaving radiance signal. This can have a confounding effect on ocean color algorithms developed for optically deep waters, leading to an overestimation of IOPs. The algorithm described here, the Shallow Water Inversion Model (SWIM), uses pre‐existing knowledge of bathymetry and benthic substrate brightness to account for optically shallow effects. SWIM was incorporated into the NASA Ocean Biology Processing Group's L2GEN code and tested in waters of the Great Barrier Reef, Australia, using the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua time series (2002–2013). SWIM‐derived values of the total non‐water absorption coefficient at 443 nm, at(443), the particulate backscattering coefficient at 443 nm, bbp(443), and the diffuse attenuation coefficient at 488 nm, Kd(488), were compared with values derived using the Generalized Inherent Optical Properties algorithm (GIOP) and the Quasi‐Analytical Algorithm (QAA). The results indicated that in clear, optically shallow waters SWIM‐derived values of at(443), bbp(443), and Kd(443) were realistically lower than values derived using GIOP and QAA, in agreement with radiative transfer modeling. This signified that the benthic reflectance correction was performing as expected. However, in more optically complex waters, SWIM had difficulty converging to a solution, a likely consequence of internal IOP parameterizations. Whilst a comprehensive study of the SWIM algorithm's behavior was conducted, further work is needed to validate the algorithm using in situ data.

Underway sampling of marine inherent optical properties on the Tara Oceans expedition as a novel resource for ocean color satellite data product validation

Developing and validating data records from operational ocean color satellite instruments requires substantial volumes of high quality in situ data. In the absence of broad, institutionally supported field programs, organizations such as the NASA Ocean Biology Processing Group seek opportunistic datasets for use in their operational satellite calibration and validation activities. The publicly available, global biogeochemical dataset collected as part of the two and a half year Tara Oceans expedition provides one such opportunity. We showed how the inline measurements of hyperspectral absorption and attenuation coefficients collected onboard the R/V Tara can be used to evaluate near-surface estimates of chlorophyll-a, spectral particulate backscattering coefficients, particulate organic carbon, and particle size classes derived from the NASA Moderate Resolution Imaging Spectroradiometer onboard Aqua (MODISA). The predominant strength of such flow-through measurements is their sampling rate—the 375 days of measurements resulted in 165 viable MODISA-to-in situ match-ups, compared to 13 from discrete water sampling. While the need to apply bio-optical models to estimate biogeochemical quantities of interest from spectroscopy remains a weakness, we demonstrated how discrete samples can be used in combination with flow-through measurements to create data records of sufficient quality to conduct first order evaluations of satellite-derived data products. Given an emerging agency desire to rapidly evaluate new satellite missions, our results have significant implications on how calibration and validation teams for these missions will be constructed.

On-orbit calibration of SeaWiFS

Ocean color climate data records (CDRs) require water-leaving radiances with 5% absolute and 1% relative accuracies as input. Because of the amplification of any sensor calibration errors by the atmospheric correction, the 1% relative accuracy requirement translates into a 0.1% long-term radiometric stability requirement for top-of-the-atmosphere (TOA) radiances. The rigorous prelaunch and on-orbit calibration program developed and implemented for Sea-viewing Wide Field-of-view Sensor (SeaWiFS) by the NASA Ocean Biology Processing Group (OBPG) has led to the incorporation of significant changes into the on-orbit calibration methodology over the 13-year lifetime of the instrument. Evolving instrument performance and ongoing algorithm refinement have resulted in updates to approaches for the lunar, solar, and vicarious calibration of SeaWiFS. The uncertainties in the calibrated TOA radiances are addressed in terms of accuracy (biases in the measurements), precision (scatter in the measurements), and stability (repeatability of the measurements). The biases are 2%-3% from lunar calibration and 1%-2% from vicarious calibration. The precision is 0.16% from solar signal-to-noise ratios, 0.13% from lunar residuals, and 0.10% from vicarious gains. The long-term stability of the TOA radiances, derived from the lunar time series, is 0.13%. The stability of the vicariously calibrated TOA radiances, incorporating the uncertainties of the in situ measurements and the atmospheric correction, is 0.30%. This stability of the radiometric calibration of SeaWiFS over its 13-year on-orbit lifetime has allowed the OBPG to produce CDRs from the ocean color data set.

Cross calibration of SeaWiFS and MODIS using on-orbit observations of the Moon

Observations of the Moon provide a primary technique for the on-orbit cross calibration of Earth remote sensing instruments. Monthly lunar observations are major components of the on-orbit calibration strategies of SeaWiFS and MODIS. SeaWiFS has collected more than 132 low phase angle and 59 high phase angle lunar observations over 12 years, Terra MODIS has collected more than 82 scheduled and 297 unscheduled lunar observations over nine years, and Aqua MODIS has collected more than 61 scheduled and 171 unscheduled lunar observations over seven years. The NASA Ocean Biology Processing Group Calibration and Validation Team and the NASA MODIS Characterization Support Team use the USGS RObotic Lunar Observatory (ROLO) photometric model of the Moon to compare these time series of lunar observations over time and varying observing geometries. The cross-calibration results show that Terra MODIS and Aqua MODIS agree, band to band, at the 1%-3% level, while SeaWiFS and either MODIS instrument agree at the 3%-8% level. The combined uncertainties of these comparisons are 1.3% for Terra and Aqua MODIS, 1.4% for SeaWiFS and Terra MODIS, and 1.3% for SeaWiFS and Aqua MODIS. Any residual phase dependence in the ROLO model, based on these observations, is less than 1.7% over the phase angle range of -80° to -6° and +5° to +82°. The lunar cross calibration of SeaWiFS, Terra MODIS, and Aqua MODIS is consistent with the vicarious calibration of ocean color products for these instruments, with the vicarious gains mitigating the calibration biases for the ocean color bands.

Estimation of near-infrared water-leaving reflectance for satellite ocean color data processing

The atmospheric correction algorithm employed by the NASA Ocean Biology Processing Group requires an assumption of negligible water-leaving reflectance in the near-infrared region of the spectrum. For waters where this assumption is not valid, an optical model is used to estimate near-infrared water-leaving reflectance. We describe this optical model as implemented for the sixth reprocessing of the SeaWiFS mission-long time-series (September 2009). Application of the optical model resulted in significant reductions in the number of negative water-leaving reflectance retrievals in turbid and optically complex waters, and improved agreement with in situ chlorophyll-a observations. The incidence of negative water-leaving reflectance retrievals at 412 nm was reduced by 40%, while negative reflectance at 490 nm was nearly eliminated.

SeaWiFS on-orbit gain and detector calibrations: effect on ocean products

The NASA Ocean Biology Processing Group's Calibration and Validation Team has analyzed the mission-long Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) on-orbit gain and detector calibration time series to verify that lunar calibrations, obtained at nonstandard gains and radiance ranges, are valid for Earth data collected at standard gains and typical ocean, cloud, and land radiances. For gain calibrations, a constant voltage injected into the postdetector electronics allows gain ratios to be computed for all four detectors in each band. The on-orbit lunar gain ratio time series show small drifts for the near infrared bands. These drifts are propagated into the ocean color data through the atmospheric correction parameter epsilon, which uses the 765/865 nm band ratio. An anomaly analysis of global mean normalized water-leaving radiances at 510 nm shows a small decrease over the mission, while an analysis of epsilon shows a corresponding increase. The drifts in the lunar time series for the 765 and 865 nm bands were corrected. An analysis of the revised water-leaving radiances at 510 nm shows the drift has been eliminated, while an analysis of epsilon shows a reduced drift. For detector calibrations, solar diffuser observations made by the individual detectors in each band allows the response of the detectors to be monitored separately. The mission-long time series of detector calibration data show that the variations in the response of the individual detectors are less than 0.5% over the mission for all bands except the 865 nm band, where the variations are less than 1%.

Sensor-independent approach to the vicarious calibration of satellite ocean color radiometry

The retrieval of ocean color radiometry from space-based sensors requires on-orbit vicarious calibration to achieve the level of accuracy desired for quantitative oceanographic applications. The approach developed by the NASA Ocean Biology Processing Group (OBPG) adjusts the integrated instrument and atmospheric correction system to retrieve normalized water-leaving radiances that are in agreement with ground truth measurements. The method is independent of the satellite sensor or the source of the ground truth data, but it is specific to the atmospheric correction algorithm. The OBPG vicarious calibration approach is described in detail, and results are presented for the operational calibration of SeaWiFS using data from the Marine Optical Buoy (MOBY) and observations of clear-water sites in the South Pacific and southern Indian Ocean. It is shown that the vicarious calibration allows SeaWiFS to reproduce the MOBY radiances and achieve good agreement with radiometric and chlorophyll a measurements from independent in situ sources. We also find that the derived vicarious gains show no significant temporal or geometric dependencies, and that the mission-average calibration reaches stability after approximately 20-40 high-quality calibration samples. Finally, we demonstrate that the performance of the vicariously calibrated retrieval system is relatively insensitive to the assumptions inherent in our approach.

SeaWiFS long-term solar diffuser reflectance and sensor noise analyses

The NASA Ocean Biology Processing Group's Calibration and Validation (Cal/Val) team has undertaken an analysis of the mission-long Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) solar calibration time series to assess the long-term degradation of the solar diffuser reflectance over 9 years on orbit. The SeaWiFS diffuser is an aluminum plate coated with YB71 paint. The bidirectional reflectance distribution function of the diffuser was not fully characterized before launch, so the Cal/Val team has implemented a regression of the solar incidence angles and the drift in the node of the satellite's orbit against the diffuser time series to correct for solar incidence angle effects. An exponential function with a time constant of 200 days yields the best fit to the diffuser time series. The decrease in diffuser reflectance over the mission is wavelength dependent, ranging from 9% in the blue (412 nm) to 5% in the red and near infrared (670-865 nm). The Cal/Val team has developed a methodology for computing the signal-to-noise ratio (SNR) for SeaWiFS on orbit from the diffuser time series corrected for both the varying solar incidence angles and the diffuser reflectance degradation. A sensor noise model is used to compare on-orbit SNRs computed for radiances reflected from the diffuser with prelaunch SNRs measured at typical radiances specified for the instrument. To within the uncertainties in the measurements, the SNRs for SeaWiFS have not changed over the mission. The on-orbit performance of the SeaWiFS solar diffuser should offer insight into the long-term on-orbit performance of solar diffusers on other instruments, such as the Moderate-Resolution Imaging Spectrometer [currently flying on the Earth Observing System (EOS) Terra and Aqua satellites], the Visible and Infrared Radiometer Suite [scheduled to fly on the NASA National Polar-orbiting Operational Environmental Satellite System (NPOESS) and NPOESS Preparatory Project (NPP) satellites] and the Advanced Baseline Imager [scheduled to fly on the National Oceanic and Atmospheric Administration Geostationary Environmental Operational Satellite Series R (GOES-R) satellites].

A multi-sensor approach for the on-orbit validation of ocean color satellite data products

The validation of satellite ocean color data products is a critical component in establishing their measurement uncertainties, assessing their scientific utility, and identifying conditions for which their reliability is suspect. Such efforts require a considerable amount of high quality in situ data, preferably consistently processed and spanning the satellite mission lifetime. This paper outlines the NASA Ocean Biology Processing Group's (OBPG) method for validating satellite data products using in situ measurements as ground truth. Currently, the OBPG uses the described method for validating several historical and operational ocean color missions. By way of a case study, results for the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) are shown. These results indicate that for the majority of the global ocean, SeaWiFS data approach the target uncertainties of ± 5% for clear water radiances as defined prior to launch. Our results add confidence in the use of these data for global climate studies, where a consistent, high quality data set covering a multi-year time span is essential.

An improved in-situ bio-optical data set for ocean color algorithm development and satellite data product validation

Global satellite ocean color instruments provide the scientific community a high-resolution means of studying the marine biosphere. Satellite data product validation and algorithm development activities both require the substantial accumulation of high-quality in-situ observations. The NASA Ocean Biology Processing Group maintains a local repository of in-situ marine bio-optical data, the SeaWiFS Bio-optical Archive and Storage System (SeaBASS), to facilitate their ocean color satellite validation analyses. Data were acquired from SeaBASS and used to compile a large set of coincident radiometric observations and phytoplankton pigment concentrations for use in bio-optical algorithm development. This new data set, the NASA bio-Optical Marine Algorithm Data set (NOMAD), includes over 3400 stations of spectral water-leaving radiances, surface irradiances, and diffuse downwelling attenuation coefficients, encompassing chlorophyll a concentrations ranging from 0.012 to 72.12 mg m − 3 . Metadata, such as the date, time, and location of data collection, and ancillary data, including sea surface temperatures and water depths, accompany each record. This paper describes the assembly and evaluation of NOMAD, and further illustrates the broad geophysical range of stations incorporated into NOMAD.