Retrieving instantaneous extinction of aerosol undetected by the CALIPSO layer detection algorithm

Aerosols significantly affect the Earth-atmosphere energy balance and climate change by acting as cloud condensation nuclei. Specifically, the susceptibility of cloud and precipitation to aerosols is stronger when aerosols are faint but tends to be saturated in polluted conditions. However, previous methodologies generally miss these faint aerosols based on instantaneous observations because they are too optically thin to be detected and are therefore usually unretrieved. This result in a large underestimation when quantifying aerosol climate impacts. Here, we focus on retrieving and verifying the instantaneous extinction of undetected faint aerosol by the CALIPSO layer detection algorithm on a global scale. Using the observations during the Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) as constraints, the lidar ratios of undetected faint aerosol are estimated with a global median of 42.2 and 24.5 sr at the stratosphere and the troposphere, respectively. The retrieved extinction of undetected aerosol during night-time shows good agreement with the independent 12-month SAGE III/ISS product on a 1 degrees average. The corresponding correlation coefficient and averaged normalized root-mean-square error are 0.66 % and 100.6 %, respectively. The minimum retrieved extinction coefficients can be extended to 10(-3) and 10(-4) km(-1) with an uncertainty of 35 % and 125 % during night-time, respectively. The CALIPSO retrieval during daytime has a positive bias and relatively low agreement with SAGE III/ISS due to the low signal-to-noise ratio caused by sunlight. This study has great potential for improving the understanding of aerosol variations and the quantification of aerosol impacts on global climate change.

Automated summary

This study focuses on retrieving and verifying the extinction of undetected faint aerosol on a global scale using the CALIPSO layer detection algorithm. The results show good agreement with independent observations during night-time, but a positive bias and low agreement during daytime. This research is important for improving our understanding of aerosol variations and quantifying their impacts on global climate change.