Abstract. Shortwave (SW) fluxes estimated from broadband radiometry rely on
empirically gathered and hemispherically resolved fields of outgoing
top-of-atmosphere (TOA) radiances. This study aims to provide more
accurate and precise fields of TOA SW radiances reflected from clouds
over ocean by introducing a novel semiphysical model predicting
radiances per narrow sun-observer geometry. This model was
statistically trained using CERES-measured radiances paired with
MODIS-retrieved cloud parameters as well as reanalysis-based
geophysical parameters. By using radiative transfer approximations as
a framework to ingest the above parameters, the new approach incorporates
cloud-top effective radius and above-cloud water vapor in addition to
traditionally used cloud optical depth, cloud fraction, cloud phase,
and surface wind speed. A two-stream cloud albedo – serving to
statistically incorporate cloud optical thickness and cloud-top
effective radius – and Cox–Munk ocean reflectance were used to
describe an albedo over each CERES footprint. Effective-radius-dependent asymmetry parameters were obtained empirically and
separately for each viewing-illumination geometry. A simple equation
of radiative transfer, with this albedo and attenuating above-cloud
water vapor as inputs, was used in its log-linear form to allow for
statistical optimization. We identified the two-stream functional
form that minimized radiance residuals calculated against CERES
observations and outperformed the state-of-the-art approach for most
observer geometries outside the sun-glint and solar zenith angles
between 20 and 70∘, reducing the median SD
of radiance residuals per solar geometry by up to 13.2 % for
liquid clouds, 1.9 % for ice clouds, and 35.8 % for
footprints containing both cloud phases. Geometries affected by
sun glint (constituting between 10 % and 1 % of the
discretized upward hemisphere for solar zenith angles of 20 and
70∘, respectively), however, often showed weaker
performance when handled with the new approach and had increased
residuals by as much as 60 % compared to the state-of-the-art
approach. Overall, uncertainties were reduced for liquid-phase and
mixed-phase footprints by 5.76 % and 10.81 %,
respectively, while uncertainties for ice-phase footprints increased
by 0.34 %. Tested for a variety of scenes, we further
demonstrated the plausibility of scene-wise predicted radiance
fields. This new approach may prove useful when employed in angular
distribution models and may result in improved flux estimates, in
particular dealing with clouds characterized by small or large
droplet/crystal sizes.
Skeptical Reasoning with Preferred Semantics in Abstract Argumentation without Computing Preferred Extensions
