The NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission launched from Kennedy Space Center in the early morning of February 8, 2024. Just 63 days later, data from NASA’s newest Earth-observing satellite became available to the public. These data will extend and improve upon NASA’s 20+ years of global satellite observation of our living oceans, atmospheric aerosols, and cloud and initiate an advanced set of climate-relevant data records. Ultimately, PACE is the first mission to provide daily, global measurements that will enable prediction of the “boom-bust” cycle of fisheries, the appearance of harmful algae, and other factors that affect commercial and recreational industries. PACE also observes clouds and tiny airborne particles known as aerosols that influence air quality and absorb and reflect sunlight, thus warming and cooling the atmosphere. In the months since launch and initial data release, the PACE Project pursued instrument temporal and system vicarious calibrations, executed cross-instrument comparisons, conducted performance assessments, explored synergies with other missions, and released advanced science data products. In parallel, the PACE Validation Science Team left for the field and the Post-launch Airborne eXperiment (PACE-PAX) prepared for its mission. And, most importantly, preliminary science results were realized. Here, we present a snapshot of these activities and their impacts and outcomes, encompassing the first half year of the PACE mission.
The NASA Ocean Biology Processing Group (OBPG) has continued monitoring the SNPP VIIRS on-orbit calibration for bands M1-M11 over its mission to optimize the calibration for ocean color applications. The OBPG has recently implemented several changes to the calibration scheme: using solar-derived f-factors to detrend the lunar observations; using long-term exponentials of time as basis vectors (along with libration angles) for radiometric fits to any resulting lunar temporal drifts; deriving gain adjustments to the solar f-factors from these exponentials; and deriving gain adjustments due to modulated RSRs outside of the solar/lunar calibration using TOA reference spectra. These calibration changes minimize the impact of uncertainties in any one component of the calibration on the derived f-factors. The final f-factors incorporate VIIRS solar diffuser measurements, h-factor BRDF corrections, lunar-derived gains, and modulated RSR gains. The combined BRDF corrections, lunar gain adjustments, and mRSR gain adjustments define effective h-factors for each band. The improvements in the on-orbit calibration are validated by evaluation of globally-derived anomaly plots of remote sensing reflectance for the ocean color bands. The ultimate goal of the OBPG calibration effort is incorporation of a consistent SNPP VIIRS ocean color data set into the NASA multi-mission ocean color climate data record.
The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) in Lagrange-1 (L1) orbit provides observations of the Earth’s surface lit by the Sun at a cadence of 13 to 22 images/day and optical resolution of 16 km in 10 spectral bands from 317 to 780 nm. The EPIC data collected in the bands centered on 443, 551, and 680 nm are used to estimate daily mean photosynthetically available radiation (PAR) reaching the surface of the global, ice-free oceans. The solar irradiance reaching the surface is obtained by subtracting from the extraterrestrial irradiance (known), the irradiance reflected to space (estimated from the EPIC measurements), while taking into account atmospheric transmission (modeled). Clear and cloudy regions within a pixel do not need to be distinguished, i.e., the methodology is adapted to the relatively large EPIC pixels. A first daily mean EPIC PAR imagery is generated. Comparison with estimates from sensors in polar and geostationary orbits, namely MODIS and AHI, shows good agreement, with coefficients of determination of 0.79 and 0.92 and RMS differences of 8.2 and 5.7 E/m2/d, respectively, but overestimation by 1.08 E/m2/d (MODIS) and 3.44 E/m2/d (AHI). The advantages of using observations from L1 orbit are: 1) the daily cycle of cloudiness is well described (unlike from polar orbit) and 2) spatial resolution is not significantly degraded at high latitudes (unlike from geostationary orbit). The methodology can be easily extended to estimate ultraviolet (UV) surface irradiance using the spectral bands centered on 317, 325, 340, and 388 nm, all the more as ozone content, a key variable controlling atmospheric transmittance, is retrieved from the measurements.
The NASA Ocean Color calibration team continued to reanalyze and improve on their approach to the on-orbit calibration of the Visible Infrared Imaging Radiometer Suite (VIIRS), aboard the Suomi National Polar-orbiting Partnership (NPP) satellite, now five years into its Earth Observation mission. As the calibration was adjusted for changes in ocean band responsitivity with time, the team also observed the variance and autocorrelation properties of calibration trend fit residuals, which appeared to have a standard deviation within a few tenths of a percent. Autocorrelation was observed to be different between bands at the blue end of the spectrum and bands at the red/NIR end, which are affected by significant changes in responsitivity stemming from mirror contamination. This residual information offered insight into the effect of small calibration biases, which can cause significant trend uncertainties in regional time series of surface reflectance and derived products. This work involves modeling spurious trends that are inherent to the calibration over time and that also arise between reprocessing efforts because of extrapolation of the time-dependent calibration table. Uncertainty in calibration trends was estimated using models of instrument and calibration system trend artifacts and correlated noise models using Monte Carlo techniques. Combined table reprocessing and extrapolation biases are presented for the first time. Calibration trend uncertainty is then propagated through to ocean color remote sensing reflectance and chlorophyll-a concentration time series. The results quantify the smallest trend observable in these oceanic parameters. This quantification furthers our understanding of uncertainty in measuring regional and global biospheric trends in the ocean using VIIRS, and better defines the roles of records in climate research.
The NASA Ocean Biology Processing Group (OBPG) has continued monitoring the SNPP VIIRS on-orbit calibration since the derivation of the calibration for Reprocessing 2014.0 of the VIIRS ocean color data set. This paper examines four changes to the on-orbit calibration data processing scheme: the prelaunch counts-toradiance conversion; residual solar beta-angle effects in the solar calibration time series; the impact of additional lunar observations on the solar/lunar time series comparisons; and the necessity of putting calibration epochs into fits of the radiometric time series. Updating the prelaunch counts-to-radiance conversion from a linear function of instrument counts to a temperature-dependent, quadratic function of counts had the primary effect of reducing the observational scatter in the lunar calibration time series. The RMS errors due to residual solar beta angle effects are 0.1% for bands M1 (412 nm), M2 (445 nm), and M5 (672 nm) and less for the other bands. The additional lunar observations show that the slopes of the differences in the lunar and solar radiometric trends change nonlinearly over time. VIIRS bands M1–M11 all show changes in radiometric response trends between late 2014 and early 2015, which can be mitigated with an epoch boundary in the fits to the radiometric response on 1 January 2015. The updated solar calibration time series show RMS residuals per band of 0.05–0.22%. The updated lunar calibration time series shows RMS residuals per band of 0.08–0.27%. The solar and lunar time series show RMS differences of 0.10–0.20%.
The NASA Ocean Biology Processing Group (OBPG) has continued monitoring the SNPP VIIRS on-orbit calibration since the derivation of the calibration for Reprocessing 2014.0 of the VIIRS ocean color data set. That calibration was based on solar and lunar observations through July 2014. Updates to the R2014.0 calibration include: 1) the addition of solar and lunar observations through May 2015; 2) the extension of the lunar libration corrections to incorporate sub-solar point corrections in addition to sub-spacecraft point corrections; 3) the implementation of a shortwave infrared (SWIR) band lunar and solar calibration; and 4) the absolute calibration of the solar observations using solar diffuser measurements. The SWIR band lunar calibration shows residual libration effects. Comparison of the lunar and solar time series yields lunar-derived adjustments to the solar calibration. The solar calibration time series show RMS residuals per band of 0.066–0.17%. The lunar calibration time series show RMS residuals per band of 0.072–0.23%. The solar and lunar time series show RMS differences per band of 0.10–0.23%. The VIIRS on-orbit calibration stability is comparable to that achieved for heritage instruments (SeaWiFS, Aqua MODIS). The quality of the resulting ocean color products is sufficient for incorporation of the VIIRS data into the long-term NASA ocean color data record.
The Operational Land Imager (OLI) is a multispectral radiometer hosted on the recently launched Landsat8 satellite. OLI includes a suite of relatively narrow spectral bands at 30 m spatial resolution in the visible to shortwave infrared, which makes it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that carries information on the biogeochemical constituents of the upper ocean euphotic zone. To evaluate the potential of OLI to measure ocean color, processing support was implemented in Sea-viewing Wide Field-of-View Sensor (SeaWiFS) Data Analysis System (SeaDAS), which is an open-source software package distributed by NASA for processing, analysis, and display of ocean remote sensing measurements from a variety of spaceborne multispectral radiometers. Here we describe the implementation of OLI processing capabilities within SeaDAS, including support for various methods of atmospheric correction to remove the effects of atmospheric scattering and absorption and retrieve the spectral remote sensing reflectance (Rrs; sr−1). The quality of the retrieved Rrs imagery will be assessed, as will the derived water column constituents, such as the concentration of the phytoplankton pigment chlorophyll a.
Remotely sensed ocean color products require highly accurate top-of-atmosphere (TOA) radiances, on the order of 0.5% or better. Due to incidents both prelaunch and on-orbit, meeting this requirement has been a consistent problem for the MODIS instrument on the Terra satellite, especially in the later part of the mission. The NASA Ocean Biology Processing Group (OBPG) has developed an approach to correct the TOA radiances of MODIS Terra using spatially and temporally averaged ocean color products from other ocean color sensors (such as the SeaWiFS instrument on Orbview-2 or the MODIS instrument on the Aqua satellite). The latest results suggest that for MODIS Terra, both linear polarization parameters of the Mueller matrix are temporally evolving. A change to the functional form of the scan angle dependence improved the quality of the derived coefficients. Additionally, this paper demonstrates that simultaneously retrieving polarization and gain parameters improves the gain retrieval (versus retrieving the gain parameter only).
KEYWORDS: Calibration, MODIS, Near infrared, Satellites, Sensors, Environmental sensing, Data modeling, Climatology, Infrared sensors, Monte Carlo methods
Launched in late 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft is being evaluated by NASA to determine whether this sensor can continue the ocean color data record established through the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the MODerate resolution Imaging Spectroradiometer (MODIS). To this end, Goddard Space Flight Center generated evaluation ocean color data products using calibration techniques and algorithms established by NASA during the SeaWiFS and MODIS missions. The calibration trending was subjected to some initial sensitivity and uncertainty analyses. Here we present an introductory assessment of how the NASA-produced time series of ocean color is influenced by uncertainty in trending instrument response over time. The results help quantify the uncertainty in measuring regional and global biospheric trends in the ocean using satellite remote sensing, which better define the roles of such records in climate research.
The NASA VIIRS Ocean Science Team (VOST) has developed two independent calibrations of the SNPP VIIRS moderate resolution reflective solar bands using solar diffuser and lunar observations through June 2013. Fits to the solar calibration time series show mean residuals per band of 0.078–0.10%. There are apparent residual lunar libration correlations in the lunar calibration time series that are not accounted for by the ROLO photometric model of the Moon. Fits to the lunar time series that account for residual librations show mean residuals per band of 0.071–0.17%. Comparison of the solar and lunar time series shows that the relative differences in the two calibrations are 0.12–0.31%. Relative uncertainties in the VIIRS solar and lunar calibration time series are comparable to those achieved for SeaWiFS, Aqua MODIS, and Terra MODIS. Intercomparison of the VIIRS lunar time series with those from SeaWiFS, Aqua MODIS, and Terra MODIS shows that the scatter in the VIIRS lunar observations is consistent with that observed for the heritage instruments. Based on these analyses, the VOST has derived a calibration lookup table for VIIRS ocean color data based on fits to the solar calibration time series.
A global, 13-year record of photo-synthetically available radiation (PAR) at the ocean surface (9-km resolution) has
been generated from SeaWiFS, MODIS-Aqua, and MODIS-Terra data. The PAR values are essentially obtained by
subtracting from the solar irradiance at the top of the atmosphere (known) the solar energy reflected by the oceanatmosphere
system (satellite-derived) and absorbed by the atmosphere (modeled). Observations by individual
instruments, combinations of two instruments, and three instruments are considered in the calculations. Spatial and
temporal biases between estimates from one, two, or three instruments are determined and corrected, resulting in a
consistent time series for variability studies. Uncertainties are quantified on daily, weekly, and monthly time scales
for the various instrument combinations from comparisons with in situ measurements. The correlative behavior of
PAR, sea surface temperature, and chlorophyll concentration in the Equatorial Pacific is examined. PAR monitoring
will continue with current and future satellite ocean-color sensors, in particular VIIRS, and the methodology will be
extended to generating UV-A and UV-B irradiance.
Following the launch of the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polarorbiting
Partnership (NPP) spacecraft, the NASA NPP VIIRS Ocean Science Team (VOST) began an evaluation of
ocean color data products to determine whether they could continue the existing NASA ocean color climate data record
(CDR). The VOST developed an independent evaluation product based on NASA algorithms with a reprocessing
capability. Here we present a preliminary assessment of both the operational ocean color data products and the NASA
evaluation data products regarding their applicability to NASA science objectives.
The NASA VIIRS Ocean Science Team (VOST) has the task of evaluating Suomi NPP VIIRS ocean color data
for the continuity of the NASA ocean color climate data records. The generation of science quality ocean color
data products requires an instrument calibration that is stable over time. Since the VIIRS NIR Degradation
Anomaly directly impacts the bands used for atmospheric correction of the ocean color data (Bands M6 and
M7), the VOST has adapted the VIIRS on-orbit calibration approach to meet the ocean science requirements.
The solar diffuser calibration time series and the solar diffuser stability monitor time series have been used to
derive changes in the instrument response and diffuser reflectance over time for bands M1–M11. The lunar
calibration observations have been used, in cooperation with the USGS ROLO Program, to derive changes in
the instrument response over time for these same bands. In addition, the solar diffuser data have been used to
develop detector-dependent striping and mirror side-dependent banding corrections for the ocean color data. An
ocean surface reflectance model has been used to perform a preliminary vicarious calibration of the VIIRS ocean
color data products. These on-orbit calibration techniques have allowed the VOST to produce an optimum timedependent
radiometric calibration that is currently being used by the NASA Ocean PEATE for its VIIRS ocean
color data quality evaluations. This paper provides an assessment of the current VIIRS radiometric calibration
for the ocean color data products and discusses the path forward for improving the quality of the calibration.
KEYWORDS: Global system for mobile communications, Remote sensing, Absorption, Data modeling, Ocean optics, Reflectivity, Backscatter, Optimization (mathematics), Water, Spectral models
Over the past few decades, various algorithms have been developed for the retrieval of water constituents from the
measurement of ocean color radiometry, and one of those approaches is spectral optimization. This approach defines an
error function (or cost function) between the observed spectral remote sensing reflectance and an estimated spectral
remote sensing reflectance over the range of observed wavelengths, with the latter modeled using a few variables that
represent the optically active properties (such as the absorption coefficient of phytoplankton and the backscattering
coefficient of particles). The values of the variables when the error function reaches a minimum are the optimized
properties. The applications of this approach implicitly assume that there is only one global minimum condition, and that
any local minimum (if exist) can be avoided through the numerical optimization scheme. Here, with data from numerical
simulations, we show the shape of the error surface as a mechanism to visualize the solution space for the model
variables. Further, using two established models as examples, we demonstrate how the solution space changes under
different model assumptions as well as the impacts on the quality of the retrieved water properties.
Ocean color climate data records 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-theatmosphere
radiances. The rigorous on-orbit calibration program developed and implemented for SeaWiFS by
the NASA Ocean Biology Processing Group (OBPG) Calibration and Validation Team (CVT) has allowed the
CVT to maintain the stability of the radiometric calibration of SeaWiFS at 0.13% or better over the mission.
The uncertainties in the resulting calibrated top-of-the-atmosphere (TOA) radiances can be addressed in terms of
accuracy (biases in the measurements), precision (scatter in the measurements), and stability (repeatability of the
measurements). The calibration biases of lunar observations relative to the USGS RObotic Lunar Observatory
(ROLO) photometric model of the Moon are 2-3%. The biases from the vicarious calibration against the Marine
Optical Buoy (MOBY) are 1-2%. The precision of the calibration derived from the solar calibration signal-tonoise
ratios are 0.16%, from the lunar residuals are 0.13%, and from the vicarious gains are 0.10%. The long-term
stability of the TOA radiances, derived from the lunar time series, is 0.13%. The stability of the vicariouslycalibrated
TOA radiances, incorporating the uncertainties in the MOBY measurements and the atmospheric
correction, is 0.30%. These results allow the OBPG to produce climate data records from the SeaWiFS ocean
color data.
The VIIRS Ocean Science Team (VOST) has been developing an Ocean Data Simulator to create realistic
VIIRS SDR datasets based on MODIS water-leaving radiances. The simulator is helping to assess instrument
performance and scientific processing algorithms. Several changes were made in the last two years
to complete the simulator and broaden its usefulness. The simulator is now fully functional and includes
all sensor characteristics measured during prelaunch testing, including electronic and optical crosstalk influences,
polarization sensitivity, and relative spectral response. Also included is the simulation of cloud and
land radiances to make more realistic data sets and to understand their important influence on nearby ocean
color data. The atmospheric tables used in the processing, including aerosol and Rayleigh reflectance coefficients,
have been modeled using VIIRS relative spectral responses. The capabilities of the simulator were
expanded to work in an unaggregated sample mode and to produce scans with additional samples beyond the
standard scan. These features improve the capability to realistically add artifacts which act upon individual
instrument samples prior to aggregation and which may originate from beyond the actual scan boundaries.
The simulator was expanded to simulate all 16 M-bands and the EDR processing was improved to use these
bands to make an SST product. The simulator is being used to generate global VIIRS data from and in
parallel with the MODIS Aqua data stream. Studies have been conducted using the simulator to investigate
the impact of instrument artifacts. This paper discusses the simulator improvements and results from the
artifact impact studies.
The MODIS instruments on Terra and Aqua were designed to allow the measurement of chlorophyll fluorescence
effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at
667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the topof-
atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to
a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design
choice and provides justification for the use of only one set of gains for global processing of ocean color products.
Noise characteristics of the two bands and their related products are compared to other products of bands from
412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray
light on the two bands is compared to other MODIS bands.
The Moderate-Resolution Imaging Spectroradiometer (MODIS) on NASA's Earth Observing System (EOS)
satellite Terra provides global coverage of top-of-atmosphere (TOA) radiances that have been successfully used
for terrestrial and atmospheric research. The MODIS Terra ocean color products, however, have been compromised
by an inadequate radiometric calibration at the short wavelengths. The Ocean Biology Processing Group
(OBPG) at NASA has derived radiometric corrections using ocean color products from the SeaWiFS sensor as
truth fields. In the R2010.0 reprocessing, these corrections have been applied to the whole mission life span
of 10 years. This paper presents the corrections to the radiometric gains and to the instrument polarization
sensitivity, demonstrates the improvement to the Terra ocean color products, and discusses issues that need
further investigation. Although the global averages of MODIS Terra ocean color products are now in excellent
agreement with those of SeaWiFS and MODIS Aqua, and image quality has been significantly improved, the
large corrections applied to the radiometric calibration and polarization sensitivity require additional caution
when using the data.
For several years, the NASA/Goddard Space Flight Center (GSFC) NPP VIIRS Ocean Science Team (VOST) provided
substantial scientific input to the NPP project regarding the use of Visible Infrared Imaging Radiometer Suite (VIIRS) to
create science quality ocean color data products. This work has culminated into an assessment of the NPP project and
the VIIRS instrument's capability to produce science quality Ocean Color data products. The VOST concluded that
many characteristics were similar to earlier instruments, including SeaWiFS or MODIS Aqua. Though instrument
performance and calibration risks do exist, it was concluded that programmatic and algorithm issues dominate concerns.
One of the roles of the VIIRS Ocean Science Team (VOST) is to assess the performance of the instrument and scientific processing software that generates ocean color parameters such as normalized water-leaving radiances and chlorophyll. A VIIRS data simulator is being developed to help aid in this work. The simulator will create a sufficient set of simulated Sensor Data Records (SDR) so that the ocean component of the VIIRS processing system can be tested. It will also have the ability to study the impact of instrument artifacts on the derived parameter quality. The simulator will use existing resources available to generate the geolocation information and to transform calibrated radiances to geophysical parameters and visa-versa. In addition, the simulator will be able to introduce land features, cloud fields, and expected VIIRS instrument artifacts. The design of the simulator and its progress will be presented.
Scanning radiometers on earth-orbiting satellites are used to measure the chlorophyll content of the oceans
via analysis of the water-leaving radiances. These radiances are very sensitive to the atmospheric correction
process, which in turn is polarization dependent. The image created by a scanning radiometer is usually composed
of successive scans by two mirror sides and one or several detectors. The Moderate Resolution Imaging
Spectroradiometer (MODIS) has 10 detectors for each ocean color band. If the polarization sensitivities are
different among detectors and this is not taken account of in the atmospheric correction process, striping will
occur in different parts of the images. MODIS polarization parameters were derived using ground truth data
from another earth-orbiting sensor (Sea-viewing Wide Field-of-view Sensor, SeaWiFS), allowing a comparison
of the on-orbit characterization and the prelaunch characterization. This paper presents these comparisons for
the MODIS instruments on the Aqua and Terra satellites. The detector dependency is clearly different in the
prelaunch characterization. This paper also describes the detector dependency of the vicarious corrections to
the radiometric calibration coefficients. During the first four years of each mission, the only correction needed
to minimize striping in the ocean color products is a constant offset, there is indication of a temporal trend or a
view angle dependency for these offsets. The offsets are similar for both instruments, but larger in Terra.
Scanning radiometers on earth-orbiting satellites are used to measure the chlorophyll content of the oceans
via analysis of the water-leaving radiances. These radiances are very sensitive to the atmospheric correction
process. In the standard atmospheric correction algorithms, two bands in the NIR wavelength region are used to
determine the radiance contributions of aerosols to the top-of-atmosphere radiance. In the standard algorithms,
thin cirrus clouds are treated as aerosols. The MODIS instruments on the Terra and Aqua satellites have a band
at 1380nm that allows the detection of thin cirrus clouds. This paper shows that the presence of thin cirrus
clouds causes a small bias in the water-leaving radiances derived with the traditional algorithms for the MODIS
Aqua instrument. The bias is insignificant when averaging over large areas.
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.
The MODIS (Moderate Resolution Imaging Spectroradiometer) scanner makes subframe measurements in some
of its bands to increase the spatial resolution from its standard 1km resolution to 500m or 250m. This is achieved
by sampling a detector of a high resolution band at twice (or four times) the sampling rate of the 1km bands.
This paper shows that a calibration equation nonlinear with radiance and specific to the individual subframes will
reduce striping in the images. The effects are significant for low radiance levels like those encountered over ocean
scenes. A preliminary calibration correction is derived with two approaches: first from prelaunch measurements,
then from on-orbit data. The results of the two methods are qualitatively similar.
KEYWORDS: Satellites, Algorithm development, Global system for mobile communications, Ocean optics, Sensors, Atmospheric corrections, MODIS, Remote sensing, Water, Magnesium
Ocean color satellites provide a mechanism for studying the marine biosphere on temporal and spatial scales
otherwise unattainable via conventional in situ sampling methods. These satellites measure visible and infrared
radiances, which are used to estimate additional geophysical data products, such as the concentration of the
phytoplankton pigment chlorophyll a, Ca, via the application of secondary bio-optical algorithms. The operational
Ca algorithms for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution
Imaging Spectroradiometer (MODIS), for example, perform well in the global open ocean, but often degrade
in more optically complex coastal environments where global parameterizations are less applicable. Organizations
such as the Chesapeake Bay Program, which have interest in using SeaWiFS and MODIS data products
to facilitate regional monitoring activities, must rely on locally parameterized algorithms to achieve requisite
accuracies. To facilitate algorithm selection, the NASA Ocean Biology Processing Group recently developed the
infrastructure to spatially and temporally evaluate a long-term regional time-series of satellite observations using
in situ measurements as ground-truth. Here, we present this approach using a case study in the Chesapeake Bay,
where a series of Ca algorithms and atmospheric correction schemes were evaluated for the full SeaWiFS and
MODIS-Aqua time-series. We demonstrate how the selection of the best algorithms and processing approaches
is driven by trade-offs in coverage needs and relative accuracy requirements. While our case study highlights Ca
in the Chesapeake Bay, our methodology is applicable to any geophysical data product and region of interest.
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. Furthermore,
the degradation trends are significantly 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.
The NASA Ocean Biology Processing Group's Calibration and Validation (Cal/Val) Team has used SeaWiFS onorbit
lunar and gain calibration data, in conjunction with mission-long trends of global ocean color data products,
to diagnose and correct recently emergent residual drifts in the radiometric response of the instrument.
An anomaly analysis of the time series of global mean normalized water-leaving radiances, the atmospheric
correction parameter ∈, and chlorophyll show significant departures from the mission-long trends beginning in
January 2006. The lunar time series trends for the near infrared (NIR) bands (765 nm and 865 nm) show
significant periodic departures from mission-long trends beginning at the same time. ∈ is dependent on the ratio
of these two bands; trends in this parameter would propagate through the atmospheric correction algorithm to
the retrieved water-leaving radiances. An analysis of fit residuals from the lunar time series shows that the focal
plane temperature dependencies of the radiometric response of the detectors for these two bands have changed
over the 9+ year mission. The Cal/Val Team has used these residuals to compute a revised set of temperature
corrections for data collected starting 1 January 2006. The lunar calibration data and a mission-long ocean color
test data set have been reprocessed with the revised temperature corrections. The reprocessed data show that
the trends in the NIR bands have been minimized and that the departures of the water-leaving radiances, ∈, and
chlorophyll from the mission-long trends have been greatly reduced.
The anomaly analysis of the water-leaving radiances in the 510 nm band still shows a residual drift of -2.9%
over the mission. The anomaly analysis of the ∈ time series shows a residual drift of +2.8% over the mission. A
corresponding drift is not observed in the lunar calibration time series for the NIR bands. The lunar calibration
data are obtained at a different set of instrument gains than are the ocean data. An analysis of the mission-long
time series of on-orbit gain calibration data shows that the gain ratios for the NIR bands change -0.76% (765 nm)
and +0.56% (865 nm) over the mission, corresponding to a -1.3% drift in the band ratio. The lunar calibration
time series for the NIR bands have been corrected for this gain drift, and the change in radiometric response over
time has been recomputed for each band. The mission-long ocean color test data set has been reprocessed with
these revised corrections for the NIR bands. The anomaly analysis of the reprocessed water-leaving radiances
at 510 nm shows the drift to have been essentially eliminated, while the anomaly analysis of epsilon shows a
reduced drift of +2.0%.
These analyses show the sensitivity of ocean color data to small drifts in instrument calibration and demonstrate
the use of time series of global mean geophysical parameters to monitor the long-term stability of the
instrument calibration on orbit. The two updates to SeaWiFS radiometric calibration have been incorporated
into the recent reprocessing of the SeaWiFS mission-long ocean data set.
The Ocean Biology Processing Group (OBPG) at NASA's Goddard Space Flight Center is responsible for the processing and validation of oceanic optical property retrievals from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). A major goal of this activity is the production of a continuous ocean color time-series spanning the mission life of these sensors from September 1997 to the present time. This paper presents an overview of the calibration and validation strategy employed to optimize and verify sensor performance for retrieval of upwelling radiances just above the sea surface. Substantial focus is given to the comparison of results over the common mission lifespan of SeaWiFS and the MODIS flying on the Aqua platform, covering the period from July 2002 through December 2004. It will be shown that, through consistent application of calibration and processing methodologies, a continuous ocean color time-series can be produced from two different spaceborne sensors.
The NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Program had a worldwide, ongoing ocean color data collection program, as well as an operational data processing and analysis capability. SIMBIOS data collection takes place via the SIMBIOS Science Team. In addition, SIMBIOS had a calibration and product validation component (Project Office). The primary purpose of these calibration and product validation activities were to (1) reduce measurement error by identifying and characterizing true error sources, such as real changes in the satellite sensor or problems in the atmospheric correction algorithm, in order to differentiate these errors from natural variability in the marine light field; and (2) evaluate the various bio-optical and atmospheric correction algorithms being used by different ocean color missions. For each sensor, the SIMBIOS Project reviews the sensor design and processing algorithms being used by the particular ocean color project, compares the algorithms with alternate methods when possible, and provides the results to the appropriate project office.
The success of the Modular Optoelectronic Scanner MOS on the Indian Remote Sensing Satellite IRS-P3 during the 6 years mission time has been based on its sophisticated in-orbit calibration concept to a large extent. When the internal lamp and the sun calibration failed in September 2000 we tested the possibility of ground target based (or vicarious) calibration of the MOS instruments to continue the high data quality. This is essential for future watching of global changes of the ocean coastal zones (phytoplancton, sediments, pollution, etc.) using spectral measurements of the VIS/NIR MOS spectral channels.
The investigations have shown the suitability of a part of the Great Eastern Erg in the Sahara desert for this purpose. The satellite crosses this very homogeneous area every 24 days. Because of the good cloudfree conditions we can use 6 - 8 overflys a year for calibration. The seasonal variability of the surface reflectance is very small so that we obtain relative calibration data of sufficient accuracy even without ground truth measurements for most of the channels.
The trend of this "vicarious" calibration corresponds very well with the previous trend of the failed lamp and sun calibration. Dfferences between the three methods will be discussed.
In the paper we will also present the results of a comparison between SeaWiFS and MOS data of comparable spectral channels from the Great Eastern Erg area. They confirm the suitability of this area for calibration purposes too.
The Diffuse Infrared Background Experiment (DIRBE) on board NASA's Cosmic Background Explorer (COBE) satellite has surveyed the entire sky in 10 broad photometric bands covering the wavelength region from 1 to 240 micrometers , at an angular resolution of 0.7 degree(s) (Boggess et al. 1992). the extensive spectral coverage of the DIRBE observations offers an unprecedented opportunity to undertake comprehensive large-scale studies of the content, structure, and energetics of the stellar and interstellar components of the Galaxy. Understanding the Galactic emission is not only a task of scientific value in its own right, but also a necessary step in the accurate extraction of faint cosmological emission from the DIRBE data.
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