Abstract
We investigated whether Top-of-Atmosphere Shortwave (TOA SW) anisotropy—essential to convert satellite-based instantaneous TOA SW radiance measurements into TOA SW fluxes—is sensitive to cloud-top effective radii and cloud-topped water vapor. Using several years of CERES SSF Edition 4 data—filtered for overcast, horizontally homogeneous, low-level and single-layer clouds of cloud optical thickness 10—as well as broadband radiative transfer simulations, we built refined empirical Angular Distribution Models (ADMs). The ADMs showed that anisotropy fluctuated particularly around the cloud bow and cloud glory (up to 2.9–8.0%) for various effective radii and at highest and lowest viewing zenith angles under varying amounts of cloud-topped moisture (up to 1.3–6.4%). As a result, flux estimates from refined ADMs differed from CERES estimates by up to 20 W m−2 at particular combinations of viewing and illumination geometry. Applied to CERES cross-track observation of January and July 2007—utilized to generate global radiation budget climatologies for benchmark comparisons with global climate models—we found that such differences between refined and CERES ADMs introduced large-scale biases of 1–2 W m−2 and on regional levels of up to 10 W m−2. Such biases could be attributed in part to low cloud-top effective radii (about 8 μm) and low cloud-topped water vapor (1.7 kg m−2) and in part to an inopportune correlation of viewing and illumination conditions with temporally varying effective radii and cloud-topped moisture, which failed to compensate towards vanishing flux bias. This work may help avoid sampling biases due to discrepancies between individual samples and the median cloud-top effective radii and cloud-top moisture conditions represented in current ADMs.
Highlights
Radiative fluxes—leaving the Earth–Atmosphere system through Top-of-Atmosphere (TOA) and inferred from satellite measurements—are a key variable in diagnosing the system’s current energy balance and—when observed repeatedly—to assess the radiative effects of clouds and aerosols (e.g., [1]).Clouds impact the energy balance through: (1) the emission of terrestrial radiation—largely regulated through their cloud-top temperature; and (2) the reflection of solar radiation—mainly driven by their cloud micro- and macrophysical properties
For θv of up to 69.5◦, all footprints were collocated with MODIS imagery as well as products derived from the CERES/MODIS cloud algorithms based on [17]
We examined whether Angular Distribution Models (ADMs) should be sensitive to the cloud micro-physical structure and amount of absorbing atmospheric gas above the cloud layer
Summary
Clouds impact the energy balance through: (1) the emission of terrestrial radiation—largely regulated through their cloud-top temperature; and (2) the reflection of solar radiation—mainly driven by their cloud micro- and macrophysical properties. Marine boundary layer clouds are predominantly found in regions of large-scale subsidence and reflect solar radiation—where a much darker ocean would otherwise absorb—while emitting terrestrial radiation similar to cloud-free conditions Atmosphere 2018, 9, 256 altitude leads to a near-surface temperature at cloud-top) (e.g., [2]) This radiative response affects the prediction of tropical clouds in a future climate [3], and large uncertainties in the radiative feedback of low-level clouds arise from inaccurately predicted properties in general circulation models [4]. The covariance of aerosol with meteorological conditions, such as humidity above clouds (hereafter referred to as cloud-topped moisture) complicates the assessment of cloud-aerosol interaction (e.g., [12])
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