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.

On-Orbit Calibration of Terra MODIS VIS Bands Using Polarization-Corrected Desert Observations

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra spacecraft is completing two decades of successful Earth observations, providing the scientific community with numerous products and supporting applications, such as land surface cover, sea surface temperature, aerosol properties, and vegetation. The 20 reflective solar bands (RSBs) cover a wavelength range from 0.41 to 2.1 $\mu \text{m}$ and are calibrated primarily using a solar diffuser (SD), with lunar measurements and Earth-view (EV) response trends from desert sites used for the response versus scan-angle (RVS) characterization. Prelaunch analysis showed that a few short-wavelength RSBs of Terra MODIS are particularly sensitive to the polarization of the incident light, with on-orbit results further indicating that the polarization sensitivity has experienced changes that are wavelength, mirror side (MS), and scan-angle dependent. Although the primary calibrator, the SD, should provide an unpolarized light, supplemental inputs from the EV response trends used in the RVS characterization are impacted by the Earth scene polarization. The EV trends, uncorrected for polarization, pose a significant challenge in the RVS characterization for the short wavelength bands (3, 8, 9, and 10), therefore impacting the long-term trends and uncertainty characterization. Previous studies from the MODIS Characterization Support Team (MCST) and the National Aeronautics and Space Administration (NASA) Ocean Biology Processing Group (OBPG) have independently estimated the polarization correction to be applied on the calibrated products to mitigate the impacts to some extent. In this article, the RVS is characterized using the EV response trends after correcting for the polarization effects. Results indicate a significant improvement in the long-term trending, reduced uncertainties in the forward prediction, and a more accurate per-pixel uncertainty provided by the uncertainty index (UI) in the MODIS L1B. This enhanced approach will, therefore, be considered for implementation in the future L1B reprocessing efforts. The enhanced approach also vastly simplifies the process of adding long-term trend corrections on top of the MODIS L1B, which should streamline the science data production in the future.

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.

MENGENAL SUHU PERMUKAAN LAUT DARI PENGINDERAAN JAUH

IDENTIFYING SEA SURFACE TEMPERATURE THROUGH REMOTE SENSING. Sea surface temperature is one of the physical parameters of oceanography that is useful to determine the water quality. Sea surface temperature can be observed using remote sensing technology. Remote sensing sensors must have a thermal infrared or a passive microwave to identify sea surface temperature. NASA's Ocean Color Web has provided sea surface temperature data processed by NASA's Ocean Biology Processing Group (OBPG) team. MODIS and VIIRS are remote sensing instruments used for sea surface temperature data on NASA's Ocean Color Web. The SST data provided in the form of data level 2 and level 3 are processed in daily, weekly, monthly and even yearly.

Using Synergy between Water Limnology and Satellite Imagery to Identify Algal Blooms Extent in a Brazilian Amazonian Reservoir

Monitoring algal blooms from space is a very challenging task, which becomes particularly difficult when dealing with cyanobacteria blooms. Cyanobacteria are strategic organisms adapted to a wide variety of environmental conditions. In high concentrations, they form scum on the water surface, which is a concern for public health due to the production of toxins, as well as being a nuisance. Knowledge of the ecological role of these organisms is, therefore, essential when trying to estimate their extent from satellite-based data. We present a multidisciplinary approach, based on both the ecological and the optical perspective. This approach is applied in a Brazilian Amazonian reservoir using spatial and temporal scales. The ACOLITE processor is employed to perform atmospheric correction. Extent of the algal bloom is mapped with outputs such as Rayleigh reflectance atmospheric corrected images. Chlorophyll-a estimation is accomplished using a blue-green edge algorithm from the Ocean Biology Processing Group (OBPG), and shows reasonable results (R2 = 0.95; RMSE = 0.40). The SAred-NIR slope algorithm identifies the extent of the algal bloom at both the spatial and temporal scale. Unfortunately, the performance of these algorithms is most likely affected by weather conditions and glint effects. Therefore, this study recommends that cyanobacteria or phytoplankton studies in this area ensure that their ecological functioning is carefully considered when attempting to map occurrence using limited satellite imagery.

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.

Evaluation of satellite-based algorithms to estimate photosynthetically available radiation (PAR) reaching the ocean surface at high northern latitudes

Abstract Two satellite-based methods to estimate daily averaged photosynthetically available radiation (PAR) at the ocean surface are evaluated at high northern latitudes. The first method employs a precomputed Look-Up-Table (LUT) generated from radiative transfer simulations. The LUT associates spectral irradiance reaching the surface to a given set of input parameters, namely solar zenith angle, cloud optical thickness, cloud fraction, ozone concentration, and surface albedo. The second method, as implemented by NASA's Ocean Biology Processing Group (OBPG) in the standard Ocean Color data processing chain, expresses the energy budget of the atmosphere-surface-ocean system via a simple radiative transfer model. The performance of these methods is evaluated using an extensive in situ PAR dataset collected in the Arctic Ocean between 1998 and 2014, with daily values ranging from 0.08 to 61.07 Em − 2 d − 1 . A methodology is developed to compare in situ measurements and satellite products of different spatial and temporal resolution. Agreement is generally good between satellite-derived estimates and ship-based data and between methods. Specifically, both methods yield a small positive bias of 6% and 2% and a relative uncertainty larger than that observed at low latitude, with a root mean squared error (RMSE) of 33% and 20% for the LUT and OPBG methods, respectively. This is attributed to the peculiar environmental conditions encountered in the Arctic, namely low solar elevation, changing surface albedo due to sea ice, and persistent cloudiness. The RMSE difference among methods is due to the high temporal resolution (3 h) of the International Satellite Cloud Climatology Project (ISCCP) LUT input not fully compensating for its low spatial resolution (280 km grid cells). The LUT method has the major advantage of providing PAR estimates in all conditions, including ice-covered regions, while the OBPG method is currently limited to open waters and a solar zenith angle lower than 83°. Consequently, the OBPG method may not account for as much as 38% of PAR reaching the Arctic ocean surface annually. Both methods have the potential to provide useful PAR estimates just below the ice, by including information about ice transmittance.

Improved Quality of MODIS Sea Surface Temperature Retrieval and Data Coverage Using Physical Deterministic Methods

Sea surface temperature (SST) retrievals from satellite imager measurements are often performed using only two or three channels, and employ a regression methodology. As there are 16 thermal infrared (IR) channels available for MODIS, we demonstrate a new SST retrieval methodology using more channels and a physically deterministic method, the modified total least squares (MTLS), to improve the quality of SST. Since cloud detection is always a part of any parameter estimation from IR satellite measurements, we hereby extend our recently-published novel cloud detection technique, which is based on both functional spectral differences and radiative transfer modeling for GOES-13. We demonstrate that the cloud detection coefficients derived for GOES-13 are working well for MODIS, while further improvements are made possible by the extra channels replacing some of the previous tests. The results are compared with available operational MODIS SST through the Group for High Resolution SST website–the data themselves are originally processed by the NASA Goddard Ocean Biology Processing Group. It is observed the data coverage can be more than doubled compared to the currently-available operational product, and at the same time the quality can be improved significantly. Two other SST retrieval methods, offline-calculated coefficients using the same form of the operational regression equation, and radiative transfer based optimal estimation, are included for comparison purposes.

Effect of MODIS Terra radiometric calibration improvements on Collection 6 Deep Blue aerosol products: Validation and Terra/Aqua consistency

AbstractThe Deep Blue (DB) algorithm's primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid‐2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terra's gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be applied to the whole Terra record. Through validation with Aerosol Robotic Network (AERONET) data, it is shown that the C6 DB Terra AOD quality is stable throughout the mission to date. Compared to the C5 calibration, in recent years the RMS error compared to AERONET is smaller by ∼0.04 over bright (e.g., desert) and ∼0.01–0.02 over darker (e.g., vegetated) land surfaces, and the fraction of points in agreement with AERONET within expected retrieval uncertainty higher by ∼10% and ∼5%, respectively. Comparisons to the Aqua C6 time series reveal a high level of correspondence between the two MODIS DB data records, with a small positive (Terra‐Aqua) average AOD offset <0.01. The analysis demonstrates both the efficacy of the new radiometric calibration efforts and that the C6 MODIS Terra DB AOD data remain stable (to better than 0.01 AOD) throughout the mission to date, suitable for quantitative scientific analyses.

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.

Scientific impact of MODIS C5 calibration degradation and C6+ improvements

Abstract. The Collection 6 (C6) MODIS (Moderate Resolution Imaging Spectroradiometer) land and atmosphere data sets are scheduled for release in 2014. C6 contains significant revisions of the calibration approach to account for sensor aging. This analysis documents the presence of systematic temporal trends in the visible and near-infrared (500 m) bands of the Collection 5 (C5) MODIS Terra and, to lesser extent, in MODIS Aqua geophysical data sets. Sensor degradation is largest in the blue band (B3) of the MODIS sensor on Terra and decreases with wavelength. Calibration degradation causes negative global trends in multiple MODIS C5 products including the dark target algorithm's aerosol optical depth over land and Ångström exponent over the ocean, global liquid water and ice cloud optical thickness, as well as surface reflectance and vegetation indices, including the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). As the C5 production will be maintained for another year in parallel with C6, one objective of this paper is to raise awareness of the calibration-related trends for the broad MODIS user community. The new C6 calibration approach removes major calibrations trends in the Level 1B (L1B) data. This paper also introduces an enhanced C6+ calibration of the MODIS data set which includes an additional polarization correction (PC) to compensate for the increased polarization sensitivity of MODIS Terra since about 2007, as well as detrending and Terra–Aqua cross-calibration over quasi-stable desert calibration sites. The PC algorithm, developed by the MODIS ocean biology processing group (OBPG), removes residual scan angle, mirror side and seasonal biases from aerosol and surface reflectance (SR) records along with spectral distortions of SR. Using the multiangle implementation of atmospheric correction (MAIAC) algorithm over deserts, we have also developed a detrending and cross-calibration method which removes residual decadal trends on the order of several tenths of 1% of the top-of-atmosphere (TOA) reflectance in the visible and near-infrared MODIS bands B1–B4, and provides a good consistency between the two MODIS sensors. MAIAC analysis over the southern USA shows that the C6+ approach removed an additional negative decadal trend of Terra ΔNDVI ~ 0.01 as compared to Aqua data. This change is particularly important for analysis of vegetation dynamics and trends in the tropics, e.g., Amazon rainforest, where the morning orbit of Terra provides considerably more cloud-free observations compared to the afternoon Aqua measurements.

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.

Impacts of Cross-Platform Vicarious Calibration on the Deep Blue Aerosol Retrievals for Moderate Resolution Imaging Spectroradiometer Aboard Terra

The retrieval of aerosol properties from spaceborne sensors requires highly accurate and precise radiometric measurements, thus placing stringent requirements on sensor calibration and characterization. For the Terra/Moderate Resolution Imaging Spectroradiometer (MODIS), the characteristics of the detectors of certain bands, particularly band 8 [(B8); 412 nm], have changed significantly over time, leading to increased calibration uncertainty. In this paper, we explore a possibility of utilizing a cross calibration method developed for characterizing the Terra/ MODIS detectors in the ocean bands by the National Aeronautics and Space Administration Ocean Biology Processing Group to improve aerosol retrieval over bright land surfaces. We found that the Terra/MODIS B8 reflectance corrected using the cross calibration method resulted in significant improvements for the retrieved aerosol optical thickness when compared with that from the Multi-angle Imaging Spectroradiometer, Aqua/MODIS, and the Aerosol Robotic Network. The method reported in this paper is implemented for the operational processing of the Terra/MODIS Deep Blue aerosol products.

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.

New aerosol models for the retrieval of aerosol optical thickness and normalized water-leaving radiances from the SeaWiFS and MODIS sensors over coastal regions and open oceans

We describe the development of a new suite of aerosol models for the retrieval of atmospheric and oceanic optical properties from the SeaWiFS and MODIS sensors, including aerosol optical thickness (τ), angstrom coefficient (α), and water-leaving radiance (L(w)). The new aerosol models are derived from Aerosol Robotic Network (AERONET) observations and have bimodal lognormal distributions that are narrower than previous models used by the Ocean Biology Processing Group. We analyzed AERONET data over open ocean and coastal regions and found that the seasonal variability in the modal radii, particularly in the coastal region, was related to the relative humidity. These findings were incorporated into the models by making the modal radii, as well as the refractive indices, explicitly dependent on relative humidity. From these findings, we constructed a new suite of aerosol models. We considered eight relative humidity values (30%, 50%, 70%, 75%, 80%, 85%, 90%, and 95%) and, for each relative humidity value, we constructed ten distributions by varying the fine-mode fraction from zero to 1. In all, 80 distributions (8 Rh×10 fine-mode fractions) were created to process the satellite data. We also assumed that the coarse-mode particles were nonabsorbing (sea salt) and that all observed absorptions were entirely due to fine-mode particles. The composition of the fine mode was varied to ensure that the new models exhibited the same spectral dependence of single scattering albedo as observed in the AERONET data. The reprocessing of the SeaWiFS data show that, over deep ocean, the average τ(865) values retrieved from the new aerosol models was 0.100±0.004, which was closer to the average AERONET value of 0.086±0.066 for τ(870) for the eight open-ocean sites used in this study. The average τ(865) value from the old models was 0.131±0.005. The comparison of monthly mean aerosol optical thickness retrieved from the SeaWiFS sensor with AERONET data over Bermuda and Wallops Island show very good agreement with one another. In fact, 81% of the data points over Bermuda and 78% of the data points over Wallops Island fall within an uncertainty of ±0.02 in optical thickness. As a part of the reprocessing effort of the SeaWiFS data, we also revised the vicarious calibration gain factors, which resulted in significant improvement in angstrom coefficient (α) retrievals. The average value of α from the new models over Bermuda is 0.841±0.171, which is in good agreement with the AERONET value of 0.891±0.211. The average value of α retrieved using old models is 0.394±0.087, which is significantly lower than the AERONET value.

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.

Moderate Resolution Imaging Spectroradiometer on Terra: limitations for ocean color applications

The Moderate Resolution Imaging Spectroradiometer (MODIS) is currently flying on both the Terra and Aqua satellite platforms. The Ocean Biology Processing Group (OBPG) at NASA Goddard Space Flight Center is producing operational ocean color products from the MODIS-Aqua sensor; however, documented uncertainties and instabilities in the prelaunch and on-orbit characterization have inhibited the production of similar products from MODIS-Terra. In particular, the radiometric response of the 412-nm band has degraded by more than 40% over the 7-year mission lifespan, with similar though less extreme changes in the longer wavelengths. While such variability may be fully correctable through the on-board calibration system, it suggests that the optical properties of the scan mirror have changed significantly since launch. Furthermore, the degradation trends are substantially different between the two mirror sides, which is likely a result of asymmetric damage done to the mirror during prelaunch testing. These effects contribute to uncertainty in our knowledge of instrument response versus incidence angle on the mirror and sensitivity with respect to polarization of the observed radiance. In this paper, we examine the impact of apparent MODIS-Terra instrument characterization errors on the derived ocean color products and show that residual errors in the current operational calibration give rise to significant cross-scan artifacts, mirror-side differences, and detector-to-detector striping in the retrieved water-leaving radiances. In addition, we describe OBPG efforts to reduce these artifacts through statistical and vicarious instrument characterization, and show the quality of the resulting water-leaving radiance retrievals relative to those derived from MODIS-Aqua.

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%.