Uncertainty assessment of the SeaWiFS on-orbit calibration

Abstract

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.

Global and regional evaluation of over-land spectral aerosol optical depth retrievals from SeaWiFS

“…The 0.3 % radiometric stability of SeaWiFS calibration (Eplee Jr. et al, 2011) should translate into potential artificial trends in retrieved AOD smaller than 0.01 across the mission. The retrieval stability may differ from this if nonradiometric factors (e.g., applicability of assumptions made about surface reflectance or aerosol microphysical properties) change through time.…”

“…The aerosol loading is linked with large-scale meteorology and seasonality differs between the Indian subcontinent and the eastern end of the region. In the Indian pre-monsoon (April-June), westerly winds blow dust across the Indo-Gangetic plain, where it is trapped by the Himalayas; the winter monsoon is associated with fog and thick haze from urban pollution and biomass burning aerosols (Prospero et al, 2002;Gautam et al, 2007Gautam et al, , 2011. Over the Indo-China peninsula, intense biomass burning during the pre-monsoon (February-April), in combination with urban emissions, leads to an optically-thick absorbing haze layer (Carmichael et al, 2003;See et al, 2006); monsoon rains during the summer washout much of the aerosol and cloud cover limits SeaWiFS's coverage.…”

“…The main focus of the SeaWiFS mission was determination of ocean colour parameters (McClain et al, 2004). Due to the small contribution of the ocean to the reflected solar radiance at top-of-atmosphere (TOA), this requires a highly accurate and stable calibration, which was maintained over the mission (Eplee Jr. et al, 2011; of order 1-3 % absolute calibration accuracy and temporal stability around 0.3 %). The long time series and quality of calibration make SeaWiFS a good candidate sensor for the creation of an AOD dataset.…”

Analysis of linear long-term trend of aerosol optical thickness derived from SeaWiFS using BAER over Europe and South China

“…From the perspective of on-board, lunar , and vicarious calibrations (Gordon, 1998;Eplee et al, 2001), SeaWiFS is one of the most accurate and stable sensors (0.5 % accuracy and 0.3 % stability (Li et al, 2009), 5 % absolute and 1 % relative radiometric accuracies (Eplee et al, 2007;Franz et al, 2007)). Especially, because the calibration errors of any sensor are usually amplified by the atmospheric correction, the 1 % relative accuracy of SeaW-IFS converted into a 0.1 % long-term radiometric stability for TOA radiances (Eplee et al, 2011). Therefore, we could assume that the sensor degradation of SeaWiFS might be a negligible effect in this study.…”

“…However, there is a lot of missing observations from 2008 to 2010 (Patt, 2010). In addition, it has a shift in the measurement time (caused by orbital drift), which started in around 2002 (Eplee et al, 2011). These could induce significant uncertainties in the trend analysis because AOT over the regions close to local aerosol sources (e.g.…”