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Abstract Desert dust accounts for a large fraction of shortwave radiation absorbed by aerosols, which adds to the climate warming produced by greenhouse gases. However, it remains uncertain exactly how much shortwave radiation dust absorbs. Here, we leverage in-situ measurements of dust single-scattering albedo to constrain absorption at mid-visible wavelength by North African dust, which accounts for approximately half of the global dust. We find that climate and chemical transport models overestimate North African dust absorption aerosol optical depth (AAOD) by up to a factor of two. This occurs primarily because models overestimate the dust imaginary refractive index, the effect of which is partially masked by an underestimation of large dust particles. Similar factors might contribute to an overestimation of AAOD retrieved by the Aerosol Robotic Network, which is commonly used to evaluate climate and chemical transport models. The overestimation of dust absorption by models could lead to substantial biases in simulated dust impacts on the Earth system, including warm biases in dust radiative effects.
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A Method to Account for the Impact of Water Vapor on Observation‐Based Estimates of the Clear‐Sky Shortwave Direct Radiative Effect of Mineral Dust
Abstract 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.
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- Award ID(s):
- 1833173
- PAR ID:
- 10371894
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Atmospheres
- Volume:
- 127
- Issue:
- 17
- ISSN:
- 2169-897X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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