Abstract

Recent studies suggest that resonant absorption of sunlight by cloud droplets may constitute a significant and unaccounted-for solar energy sink in the atmosphere. We spectrally resolve, for the first time, all solar absorption, including sharp resonances, in typical liquid water clouds. Resolving all sharp resonances requires a resolution in size parameter χ = 2 π r / λ ( r —droplet radius, λ —incident wavelength) of about 10 - 7 . The canonical integration resolution Δ χ ≈ 10 - 1 produces absorption biases up to 70% over 10 nm spectral bands. Hence, neglecting Mie resonances may cause substantial biases in radiance-based retrievals from sensor channels where atmospheric absorption is particle dominated. The canonical resolution produces broadband solar mean and RMS absorption coefficient biases of about 0.02% and 4%, respectively. Self-cancellation of the pseudo-randomly distributed biases explains why the mean bias is much smaller than the RMS bias. Exceeding 1% RMS accuracy in solar absorption requires Δ χ < 10 - 5 . Increased cloud heating due to resolving all resonant absorption is less than 0.1%, equivalent to about 0.01 W m - 2 global annual mean heating. Overlap of droplet and water vapor absorption within clouds helps diminish the net enhanced absorption by sharp resonances. Hence, the heretofore unrepresented absorption is negligible for global climate, though very important for narrow spectral regions. These results apply to homogeneous liquid water clouds and aerosols.

Highlights

  • Atmospheric solar absorption is not directly observable on global scales

  • Global models estimate that clouds, aerosols, and trace gases absorb at least 20% of the solar radiation annually received by Earth [1,2]

  • Atmospheric models base their predictions of solar absorption within liquid water clouds on parameterizations (e.g., [3,4,5]) of Mie theory

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Summary

Introduction

Atmospheric solar absorption is not directly observable on global scales. the partitioning of known column solar heating between the atmosphere and the surface is poorly constrained and is model based. Global models estimate that clouds, aerosols, and trace gases absorb at least 20% of the solar radiation annually received by Earth [1,2]. Atmospheric models base their predictions of solar absorption within liquid water clouds on parameterizations (e.g., [3,4,5]) of Mie theory. These parameterizations are based on spectral or size resolution [6] insufficient to fully resolve the resonant absorption structure [7,8] that accounts for about 20% of solar absorption by cloud droplets [4,9]. To document the tradeoff between accuracy and computational expense of increasing the canonical resolution in typical atmospheric applications such as cloud and aerosol radiative transfer

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