Vicarious calibration of satellite ocean color sensors at two coastal sites

Evaluation of regions suitable for vicarious calibration of ocean color satellite sensors in the South China Sea

Accurate retrieval of biogeochemical components of the ocean at a global scale from space requires accurately calibrated top-of-atmosphere (TOA) radiance, which is usually achieved by deriving a vicarious gain coefficient (g-factor) through a process called system vicarious calibration (SVC). Currently, only two SVC sites, Marine Optical Buoy (MOBY) and BOUée pour l'acquiSition d'une Série Optique à Long termE (BOUSSOLE), are routinely operated to support the SVC process for all on-orbit ocean color satellite payloads. However, high-quality matchups between satellite observations and in situ measurements are rare because of the strict requirements of the SVC process. Meanwhile, a stable g-factor is usually computed by averaging sufficient gain measurements. Therefore, more SVC sites are required to derive a stable g-factor in a short duration, particularly for the initial calibration of newly launched satellite sensors. In this study, nearly twenty years of well-calibrated ocean color satellite data were used to calculate the mean and standard deviation of physical and optical properties of waters and the atmosphere in the South China Sea (SCS) to evaluate the feasibility of establishing a SVC site. A region was identified that meets all requirements that were used to evaluate the MOBY and BOUSSOLE sites. Two in situ measurements within this region were used to derive a g-factor for MODIS-Terra and MODIS-Aqua and were compared with the g-factor derived using MOBY data. The consistence of the two g-factors indicates that the identified region in the SCS could be a potential area for establishing a long-term moored SVC site.

Vicarious Radiometric Calibration of Ocean Color Bands for FY-3D/MERSI-II at Lake Qinghai, China

To calibrate the low signal response of the ocean color (OC) bands and test the stability of the Fengyun-3D (FY-3D)/Medium Resolution Spectral Imager II (MERSI-II), an absolute radiometric calibration field test of FY-3D/MERSI-II at the Lake Qinghai Radiometric Calibration Site (RCS) was carried out in August 2018. The lake surface and atmospheric parameters were mainly measured by advanced observation instruments, and the MODerate spectral resolution atmospheric TRANsmittance algorithm and computer model (MODTRAN4.0) was used to simulate the multiple scattering radiance value at the altitude of the sensor. The results showed that the relative deviations between bands 9 and 12 are within 5.0%, while the relative deviations of bands 8, and 13 are 17.1%, and 12.0%, respectively. The precision of the calibration method was verified by calibrating the Aqua/Moderate-resolution Imaging Spectroradiometer (MODIS) and National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer (VIIRS), and the deviation of the calibration results was evaluated with the results of the Dunhuang RCS calibration and lunar calibration. The results showed that the relative deviations of NPP/VIIRS were within 7.0%, and the relative deviations of Aqua/MODIS were within 4.1% from 400 nm to 600 nm. The comparisons of three on-orbit calibration methods indicated that band 8 exhibited a large attenuation after launch and the calibration results had good consistency at the other bands except for band 13. The uncertainty value of the whole calibration system was approximately 6.3%, and the uncertainty brought by the field surface measurement reached 5.4%, which might be the main reason for the relatively large deviation of band 13. This study verifies the feasibility of the vicarious calibration method at the Lake Qinghai RCS and provides the basis and reference for the subsequent on-orbit calibration of FY-3D/MERSI-II.

An evaluation of marine regions relevant for ocean color system vicarious calibration

System Vicarious Calibration (SVC) is the fundamental process commonly implemented to meet uncertainty requirements in satellite ocean color data. It is performed by applying gain factors, g-factors, to the pre-launch calibration coefficients of the space sensor already corrected for sensitivity decay with time. Mission specific g-factors are determined from top-of-the-atmosphere data computed by propagating highly accurate in situ values of the water-leaving radiance, L_w, to the satellite sensor. Values of L_w from marine regions characterized by oligotrophic/mesotrophic waters and maritime aerosols, high environmental stability and spatial homogeneity, low cloudiness and absence of any source of land contamination, are essential to determine g-factors applicable to the creation of Climate Data Records (CDRs) from multiple ocean color missions. Accounting for the location of existing and potential new SVC fixed sites, marine regions satisfying SVC requirements for the generation of CDRs have been identified through the analysis of satellite data from recent ocean color missions.

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

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

Tracking radiometric responsivity of optical sensors without on-board calibration systems-case of the Chinese HJ-1A/1B CCD sensors

The radiometric stability of satellite sensors is crucial for generating highly consistent remote sensing measurements and products. We have presented a radiometric responsivity tracking method designed especially for optical sensors without on-board calibration systems. Using a temporally stable desert site with high reflectance, the sensor responsivity was simulated using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model (RTM) with information from validated MODIS atmospheric data. Next, radiometric responsivity drifting was identified using a linear regression of the time series bidirectional reflectance distribution function (BRDF) normalized coefficients. The proposed method was applied to Chinese HJ-1A/1B charge-coupled device (CCD) sensors, which have been on-orbit operations for more than 5 years without continuous assessment of their radiometric performance. Results from the Dunhuang desert site between 2008 and 2013 indicated that the CCD sensors degraded at various rates, with the most significant degradation occurring in the blue bands, ranging from 2.8% to 4.2% yr^-1. The red bands were more stable, with a degradation rate of 0.7-3.1% yr^-1. A cross-sensor comparison revealed the least degradation for the HJ-1A CCD1 (blue: 2.8%; green: 2.8%; red: 0.7%; and NIR: 0.9% yr^-1), whereas the degradation of HJ-1B CCD1 was most pronounced (blue: 3.5%; green: 4.1%; red: 2.3%; and NIR: 3.4% yr^-1). The uncertainties of the method were evaluated theoretically based on the propagation of uncertainties from all possible sources of the RT simulations. In addition, a cross comparison with matchup ground-based absolute calibration results was conducted. The comparison demonstrated that the method was useful for continuously monitoring the radiometric performance of remote sensors, such as HJ-1A/1B CCD and GaoFen (GF) series (China's latest high-definition Earth observation satellite), and indicated the potential use of the method for high-precision absolute calibration.

Radiometric calibration of ocean color satellite sensors using AERONET-OC data

Radiometric vicarious calibration of ocean color (OC) satellite sensors is carried out through the full sunlight path radiative transfer (RT) simulations of the coupled ocean-atmosphere system based on the aerosol and water-leaving radiance data from AERONET-OC sites for the visible and near-infrared (NIR) bands. Quantitative evaluation of the potential of such approach for achieving the radiometric accuracies of OC satellite sensors is made by means of direct comparisons between simulated and satellite measured top of atmosphere (TOA) radiances. Very high correlations (R ≥ 0.96 for all visible channels) are achieved for the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor when this approach is applied with the data from the LISCO and WaveCIS AERONET-OC sites. Vicarious calibration gain factors derived with this approach are highly consistent, with comparisons between the two sites exhibiting around 0.5% discrepancy in the blue and green parts of the spectrum, while their average temporal variability is also within 0.28% - 1.23% permitting the approach to be used, at this stage, for verification of sensor calibration performance.

Simulation and analysis of adjacency effects in coastal waters: a case study

A methodology has been developed and applied to accurately quantify and analyze adjacency effects in satellite ocean color data for a set of realistic and representative observation conditions in the northern Adriatic Sea. The procedure properly accounts for sea surface reflectance anisotropy, off-nadir views, coastal morphology, and atmospheric multiple scattering. The study further includes a sensitivity analysis on commonly applied approximations. Results indicate that, within the accuracy limits defined by the radiometric resolution of ocean color sensors, adjacency effects in coastal waters might be significant at both visible and near-infrared wavelengths up to several kilometers off the coast. These results additionally highlight a significant dependence on the angle of observation, on the directional reflectance properties of the sea surface, and on the atmospheric multiple scattering.

Assessment of MERIS reflectance data as processed with SeaDAS over the European seas

The uncertainties associated with MERIS remote sensing reflectance (RRS) data derived from the SeaWiFS Data Analysis System (SeaDAS) are assessed with field observations. In agreement with the strategy applied for other sensors, a vicarious calibration is conducted using in situ data from the Marine Optical BuoY offshore Hawaii, and leads to vicarious adjustment factors departing from 1 by 0.2% to 1.6%. The three field data sets used for validation have been collected at fixed stations in the northern Adriatic Sea and the Baltic Sea, and in a variety of European waters in the Baltic, Black, Mediterranean and North Seas. Excluding Baltic waters, the mean absolute relative difference |ψ| between satellite and field data is 10-14% for the spectral interval 490-560 nm, 16-18% at 443 nm, and 24-26% at 413 nm. In the Baltic Sea, the |ψ| values are much higher for the blue bands characterized by low RRS amplitudes, but similar or lower at 560 and 665 nm. For the three validation sets, the root-mean-square differences decrease from approximately 0.0013 sr-1 at 413 nm to 0.0002 sr-1 at 665 nm, and are found similar or lower than those obtained for SeaWiFS or MODIS-Aqua. As derived from SeaDAS, the RRS records associated with these three missions thus provide a multi-mission data stream of consistent accuracy.

Influence of polarimetric satellite data measured in the visible region on aerosol detection and on the performance of atmospheric correction procedure over open ocean waters

An original atmospheric correction algorithm, so-called multi-directionality and POLarization-based Atmospheric Correction (POLAC), is described. This algorithm is based on the characteristics of the multidirectional and polarimetric data of the satellite PARASOL (CNES). POLAC algorithm is used to assess the influence of the polarimetric information in the visible bands on the retrieval of the aerosol properties and the water-leaving radiance over open ocean waters. This study points out that the use of the polarized signal significantly improves the aerosol type determination. The use of the polarized information at one visible wavelength only, namely 490 nm, allows providing estimates of the Angstrom exponent of aerosol optical depth with an uncertainty lower than 4%. Based on PARASOL observations, it is shown that the detection of the fine aerosols is improved when exploiting polarization data. The atmospheric component of the satellite signal is then better modeled, thus improving de facto the water-leaving radiance estimation.