recognized and led to the Marine Optical Buoy (MOBY) system.
Conclusion: During the CZCS era, scientists learned about the importance of continuous sampling to achieve global coverage, of making in situ measurements throughout a mission’s lifetime to assess changes in the sensor’s gain over time and to validate the data products, and of atmospheric corrections. In particular, the need for near-infrared (NIR) measurements to improve atmospheric correction was recognized during the CZCS experience and led to the SeaWiFS band-set.
SeaWiFS and MODIS-Aqua have been highly successful, global-scale U.S. ocean color missions that contributed to major advances in the ocean sciences (Siegel et al., 2004; NRC, 2008a; McClain, 2009). SeaWiFS launched in September 1997 with a design life of five years and operated for 13 years, until December 14, 2010 (Hooker et al., 1992; McClain, 2009). SeaWiFS provided almost daily global Earth coverage from a polar orbit. Six visible bands detected changes in ocean properties with high signal-to-noise ratio (SNR) to allow discrimination of low ocean reflectance against a very high atmospheric background signal. Two near-infrared (NIR) bands were used to estimate aerosol properties for atmospheric correction (although reduction in digitization of the NIR channels was an important source of noise in open ocean retrievals [Hu et al., 2004]). Key design features minimized polarization sensitivity and far-field stray light and enabled the measurement of low signal ocean radiances, and land and cloud reflectance at very high signals, without saturation. A solar diffuser assisted with the on-orbit sensor performance evaluation (Eplee et al., 2007). The sensor tilt capability minimized sun glint. Most importantly, the lunar calibration capability (Barnes et al., 2004) helped SeaWiFS achieve superb long-term stability.
The overall uncertainty level for SeaWiFS calibration gains can be estimated to be ~0.3 percent (assuming independence among the three sources of uncertainty). Reducing the system calibration uncertainty to such a low number was a major accomplishment of the SeaWiFS mission and resulted from a commitment to minimizing the sources of uncertainty from three primary independent sources: (1) uncertainty in the calibration trends in time, (2) uncertainty in the MOBY calibration and its determinations of water-leaving radiance, and (3) uncertainty in the estimation of SeaWiFS calibration gain corrections. The details of the three sources of uncertainty are presented below; however, their contribution to estimation of the overall uncertainty levels are briefly discussed here. First, uncertainty in the estimation of SeaWiFS calibration over time, i.e., sensor sensitivity degradation, has been determined for SeaWiFS using its monthly lunar viewing of the moon at the same phase (Eplee et al., 2004, 2011). Relative calibration coefficients for some bands had decreased by as much as nearly 20 percent (Figure 3.4); however, uncertainty about the fit trend lines for the lunar views were quite small (~0.1 percent for all bands). Second, uncertainties in the MOBY water-leaving radiances (Lw(λ)) involve both the MOBY spectrometer calibration and the propagation of the subsurface radiances through the water column and the air-sea interface. Brown et al. (2007) provide the contribution of each to the Lw(λ) error budget, with the total uncertainty in Lw(λ) ranging from 2.1 to 3.3 percent depending on the spectral band. The Lw(λ) contribution to the top of the atmosphere radiance is typically 10 percent for oligotrophic waters and clear atmospheres, which are typically found where MOBY has been deployed. Thus the Lw(λ) uncertainty is equivalent to 0.21 to 0.33 percent at the top of the atmosphere. Third, uncertainties in the vicarious calibration of gain factors for individual time points were often large (~1 percent; Franz et al., 2007) and are primarily due to uncertainty in the atmospheric corrections (Gordon, 1997; Ahmad et al., 2010). After evaluating many (>50) independent estimates, the uncertainty in the mean gains (standard errors about the mean) are ~0.1 percent (Table 1 in Franz et al., 2007). It is interesting to note that the largest source of uncertainty to the SeaWiFS calibration budget is from the vicarious calibration source used.
In December 1999, MODIS followed SeaWiFS on the Earth Observing System (EOS) Terra spacecraft and in May 2002, on EOS Aqua. Each had a design life of five years (Esaias et al., 1998). Both remain operational after 11 and 8 years on-orbit, respectively. MODIS addresses atmosphere, land, and ocean research requirements; the Aqua sensor continues SeaWiFS ocean color capability.
Unfortunately, the Terra MODIS sensor has major limitations in its application of ocean color products because of poor radiometric and polarization stability (Franz et al., 2008). The recent reprocessing of Terra MODIS (January 2011) was only possible because the entire dataset was vicariously calibrated using SeaWiFS observations. These difficulties with Terra MODIS highlight the need for a stable and well-characterized ocean color sensor.
Nine of 36 MODIS spectral bands are within the visible range matching SeaWiFS, with the exception of slight changes in bandpass (see below). The MODIS sensor includes for the first time spectral bands that detect the chlorophyll fluorescence line height from satellite orbit (Letelier and Abbott, 1996; Behrenfeld et al., 2009). Like SeaWiFS, MODIS is able to measure the low-signal radiance from the ocean as well as the high-signal reflectance from land and clouds throughout the visible and near-infrared. Therefore, MODIS provides full atmosphere, land, and ocean spectral and radiometric coverage for a broad range of applications, including ocean color. Moreover, MODIS improves SeaWiFS calibration with a better solar diffuser, a solar diffuser stability monitor to compensate for solar diffuser changes over time, and a spectroradiometric calibration assembly that