Download D5.1: In-situ data quality control - AQUA

D5.1: IS data quality control
30/11/2014
Figure 17. The plot still has a and b in it and was not normalized. Still, same result for the one-parameter
model.
The model parameter varies roughly from 0 to 1. The 'perfect' fits, e.g. R>0.99, are mostly
represented by Rayleigh-scattering dominated skies (cloud free), whereas the spectra where the fit
didn't work out perfectly (0.95<R<0.99), tend to be Mie-dominated. Especially the 'bad' fits (R<0.95)
might result from obstacles in the FOV of the radiance measurements, e.g. trees or buildings, which
introduce spectral features. In any case, these measurements should be regarded with care and
flagged accordingly.
At this moment, both cloud radiance distribution methods are tested on the WISPweb database. In
the near future, the best methods will be implemented and the results will be integrated with the
reflected skylight correction discussed below.
Position of sun angle: Based on the UTM time registration during the measurement the position of
sun angle is calculated on WISPweb. A flag will raise if the sun angle is lower than 30 degree.
Repeated measurement accuracy: In one measurement, the WISP-3 takes the mean of five readings
minimising the noise and error due to instrument stablization. When the user uploads spectra with
repeated measurement (usually >=3 Spectra) then spectra of Ed , Ld , Lu will be flagged if their
values at 550 nm differ by more than 25% (Ruddick et al. 2006).
Correcting for the reflected skylight: Because of surface reflectance, Rrs or water-leaving radiance is
challenging to measure from above the surface. It usually is estimated by correcting for the reflected
skylight in the measured above-water upwelling radiance (Lu) using a theoretical Fresnel reflectance
value. WISPweb uses the “Fingerprint algorthim” developed by Simis and Olsson (2013) to estimate
the correct Fresnel value. It is based on the assumption that features in Rrs of water are spectrally
smooth, whereas downwelling and reflected upward (ir)radiance contain a multitude of narrow
features caused by gas absorption in the outer layers of the sun and the Earth atmosphere. In field
measurements, when an unsuitable value for r is applied, these features can be recognized in
resulting erroneous Rrs spectra. Reciprocally, the value of r can be optimized to minimize the
presence of these features in Rrs, which is adapted in this approch. Because the atmospheric
absorption features are both numerous and spectrally narrow, the optimization of r can be based on
a series of these features without risk that the underlying absorption, scattering, or fluorescence
features in Rrs influence the estimate of r (Simis and Olsson 2013). The optimization technique
converges on a value of r labeled high, low, suspect and empty (table 10).
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