300
H.R. Gordon
aerosol optical thickness, the figure suggests that the aerosol concentration varies
by a factor of 1.5 along the track. Using Equation (17.3) to form S(λ i ,λ j ), the graph
on the right in Fig. 17.6 (upper curve) shows the resulting variation of S(520,670)
along the track as a function of the aerosol radiance (concentration).
The result seems to show that S(520,670) varies with aerosol concentration;
however, there are two items in this estimate that carry significant uncertainties:
the values of F 0 (λ i ) and the sensor calibration leading to the values of L t (λ i ).
Error in either of these could lead to significant variations in S(520,670) with
aerosol concentration (Equations (17.2) and (17.6)). As an example, I decreased
the value of F 0 (670) by about 6% and this simple change led to the lower curves
in Fig. 17.6 (right), i.e., rendered S(520,670) nearly constant along the track. This
exercise, which was the subject of my paper at Oceans from Space, Venice 1980
(Gordon, 1981), convinced me (1) that it was probably reasonable to assume
the S (and ε) is independent of aerosol concentration, and (2) that the sensor
calibration (relative to whatever version of the extraterrestrial solar irradiance is
being used) is of paramount importance, and we needed to address the CZCS
calibration.
At approximately the same time, at the urging of Charlie Yentsch and Ros Austin,
the NET agreed to devote a significant portion of the 2 h/day that CZCS operated
to acquiring a global data set. Although the computer resources to analyze such a
data set did not exist at the time, they would in a few years. This turned out to be an
key decision and the results demonstrated the importance of ocean color to global
marine ecology.
17.5 Calibration
Understanding the calibration (or at least the relative calibration) of CZCS was a difficult problem (and, without several assumptions, impossible). Calibration as used
here refers to the conversion from the digital counts (DC) recorded by the sensor
to top-of-atmosphere radiance L t , i.e., L t (λ i ) = k(λ i ) × DC(λ i ), where k(λ i ) is the
“calibration constant.” The onboard calibration system did not work well and did
not include the entire optical train, so its use was abandoned. The only calibration
scheme that seemed possible was what is now referred to as vicarious calibration,
estimating the sensor radiance based on theoretical considerations and measurements of L w (λ i ) made at the surface, or equivalently, ensuring that the application
of the algorithms to (re)calibrated sensor radiances yielded the observed L w (λ i )’s
within their expected uncertainties. For CZCS, we had only the measurements of
L w (λ i ) carried out on the validation cruises. We made the leap-of-faith assumption
that the atmospheric correction algorithm was valid (and L w (Red) ≈ 0). Thus, combining Equations (17.1), (17.2), (17.3), (17.4) and (17.5), the L w (λ i )’s are given by
t(λ i )L w (λ i ) = L t (λ i ) − L r (λ i ) − [L t (Red) − L r (Red)] ×
F 0 (λ i )
F 0 (Red)
ε(λ i ,Red),
H.R. Gordon
aerosol optical thickness, the figure suggests that the aerosol concentration varies
by a factor of 1.5 along the track. Using Equation (17.3) to form S(λ i ,λ j ), the graph
on the right in Fig. 17.6 (upper curve) shows the resulting variation of S(520,670)
along the track as a function of the aerosol radiance (concentration).
The result seems to show that S(520,670) varies with aerosol concentration;
however, there are two items in this estimate that carry significant uncertainties:
the values of F 0 (λ i ) and the sensor calibration leading to the values of L t (λ i ).
Error in either of these could lead to significant variations in S(520,670) with
aerosol concentration (Equations (17.2) and (17.6)). As an example, I decreased
the value of F 0 (670) by about 6% and this simple change led to the lower curves
in Fig. 17.6 (right), i.e., rendered S(520,670) nearly constant along the track. This
exercise, which was the subject of my paper at Oceans from Space, Venice 1980
(Gordon, 1981), convinced me (1) that it was probably reasonable to assume
the S (and ε) is independent of aerosol concentration, and (2) that the sensor
calibration (relative to whatever version of the extraterrestrial solar irradiance is
being used) is of paramount importance, and we needed to address the CZCS
calibration.
At approximately the same time, at the urging of Charlie Yentsch and Ros Austin,
the NET agreed to devote a significant portion of the 2 h/day that CZCS operated
to acquiring a global data set. Although the computer resources to analyze such a
data set did not exist at the time, they would in a few years. This turned out to be an
key decision and the results demonstrated the importance of ocean color to global
marine ecology.
17.5 Calibration
Understanding the calibration (or at least the relative calibration) of CZCS was a difficult problem (and, without several assumptions, impossible). Calibration as used
here refers to the conversion from the digital counts (DC) recorded by the sensor
to top-of-atmosphere radiance L t , i.e., L t (λ i ) = k(λ i ) × DC(λ i ), where k(λ i ) is the
“calibration constant.” The onboard calibration system did not work well and did
not include the entire optical train, so its use was abandoned. The only calibration
scheme that seemed possible was what is now referred to as vicarious calibration,
estimating the sensor radiance based on theoretical considerations and measurements of L w (λ i ) made at the surface, or equivalently, ensuring that the application
of the algorithms to (re)calibrated sensor radiances yielded the observed L w (λ i )’s
within their expected uncertainties. For CZCS, we had only the measurements of
L w (λ i ) carried out on the validation cruises. We made the leap-of-faith assumption
that the atmospheric correction algorithm was valid (and L w (Red) ≈ 0). Thus, combining Equations (17.1), (17.2), (17.3), (17.4) and (17.5), the L w (λ i )’s are given by
t(λ i )L w (λ i ) = L t (λ i ) − L r (λ i ) − [L t (Red) − L r (Red)] ×
F 0 (λ i )
F 0 (Red)
ε(λ i ,Red),