The shortwave direct radiative effect of dust, the difference between net shortwave radiative flux in a cloud free and cloud and aerosol free atmosphere, is typically estimated using forward calculations made with a radiative transfer model. However, estimates of the direct radiative effect made via this initial method can be highly uncertain due to difficultly in accurately describing the relevant optical and physical properties of dust used in these calculations. An alternative approach to estimate this effect is to determine the forcing efficiency, or the direct radiative effect normalized by aerosol optical depth. While this approach avoids the uncertainties associated with the initial method for calculating the direct effect, random errors and biases associated with this approach have not been thoroughly examined in literature. Here we explore biases in this observation‐based approach that are related to atmospheric water vapor. We use observations to show that over the Sahara Desert dust optical depth and column‐integrated atmospheric water vapor are positively correlated. We use three idealized radiative models of varying complexity to demonstrate that a positive correlation between dust and water vapor produces a positive bias in the dust forcing efficiency estimated via the observation‐based method. We describe a simple modification to the observation‐based method that correctly accounts for the correlation between dust and water vapor when estimating the forcing efficiency and use this method to estimate the instantaneous forcing efficiency of dust over the Sahara Desert using satellite data, obtaining −12.3 ± 6.68 to 20.9 ± 11.9 W m−2per unit optical depth.
Clouds cover on average nearly 70% of Earth’s surface and regulate the global albedo. The magnitude of the shortwave reflection by clouds depends on their location, optical properties, and three-dimensional (3D) structure. Due to computational limitations, Earth system models are unable to perform 3D radiative transfer calculations. Instead they make assumptions, including the independent column approximation (ICA), that neglect effects of 3D cloud morphology on albedo. We show how the resulting radiative flux bias (ICA-3D) depends on cloud morphology and solar zenith angle. We use high-resolution (20–100-m horizontal resolution) large-eddy simulations to produce realistic 3D cloud fields covering three dominant regimes of low-latitude clouds: shallow cumulus, marine stratocumulus, and deep convective cumulonimbus. A Monte Carlo code is used to run 3D and ICA broadband radiative transfer calculations; we calculate the top-of-atmosphere (TOA) reflected flux and surface irradiance biases as functions of solar zenith angle for these three cloud regimes. Finally, we use satellite observations of cloud water path (CWP) climatology, and the robust correlation between CWP and TOA flux bias in our LES sample, to roughly estimate the impact of neglecting 3D cloud radiative effects on a global scale. We find that the flux bias is largest at small zenith angles and for deeper clouds, while the albedo bias is most prominent for large zenith angles. In the tropics, the annual-mean shortwave radiative flux bias is estimated to be 3.1 ± 1.6 W m−2, reaching as much as 6.5 W m−2locally.
more » « less- NSF-PAR ID:
- 10303140
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Journal of the Atmospheric Sciences
- Volume:
- 78
- Issue:
- 12
- ISSN:
- 0022-4928
- Page Range / eLocation ID:
- p. 4053-4069
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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