Preprints
https://doi.org/10.5194/egusphere-2024-1964
https://doi.org/10.5194/egusphere-2024-1964
11 Jul 2024
 | 11 Jul 2024
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Model analysis of biases in satellite diagnosed aerosol effect on cloud liquid water path

Harri Kokkola, Juha Tonttila, Silvia Calderón, Sami Romakkaniemi, Antti Lipponen, Aapo Peräkorpi, Tero Mielonen, Edward Gryspeerdt, Timo H. Virtanen, Pekka Kolmonen, and Antti Arola

Abstract. The response in cloud water content to changes in cloud condensation nuclei remains one of the major uncertainties in determining how aerosols can perturb cloud properties. In this study, we used an ensemble of large eddy simulations of marine stratocumulus clouds to investigate the correlation between cloud liquid water path and the amount of cloud condensation nuclei. We compare this correlation directly from the model to the correlation derived using equations which are used to retrieve liquid water path from satellite observations. Our comparison shows that spatial variability in cloud properties and instrumental noise in satellite retrievals of cloud optical depth and cloud effective radii result in bias in satellite-derived liquid water path. In depth investigation of high-resolution model data shows that in large part of a cloud, the assumption of adiabaticity does not hold which results in a similar bias in LWP-CDNC relationship as seen in satellite data. In addition, our analysis shows a significant positive bias of between 18 % and 40 % in satellite-derived cloud droplet number concentration. However, for the individual ensemble members, the correlation between the cloud condensation nuclei and the mean of the liquid water path was very similar between the methods. This suggests that if cloud cases are carefully chosen for similar meteorological conditions and it is ensured that cloud condensation nuclei concentrations are well-defined, changes in liquid water can be confidently determined using satellite data.

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Harri Kokkola, Juha Tonttila, Silvia Calderón, Sami Romakkaniemi, Antti Lipponen, Aapo Peräkorpi, Tero Mielonen, Edward Gryspeerdt, Timo H. Virtanen, Pekka Kolmonen, and Antti Arola

Status: open (until 22 Aug 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Harri Kokkola, Juha Tonttila, Silvia Calderón, Sami Romakkaniemi, Antti Lipponen, Aapo Peräkorpi, Tero Mielonen, Edward Gryspeerdt, Timo H. Virtanen, Pekka Kolmonen, and Antti Arola

Data sets

Datasets used in Kokkola et al. (2024) "Model analysis of biases in satellite diagnosed aerosol effect on cloud liquid water path" Harri Kokkola et al. https://doi.org/10.57707/fmi-b2share.8fc77f2c6a8a4deab3de2efd46683010

Model code and software

UCLALES-SALSA Juha Tonttila et al. https://github.com/UCLALES-SALSA/UCLALES-SALSA/tree/DEV

Harri Kokkola, Juha Tonttila, Silvia Calderón, Sami Romakkaniemi, Antti Lipponen, Aapo Peräkorpi, Tero Mielonen, Edward Gryspeerdt, Timo H. Virtanen, Pekka Kolmonen, and Antti Arola

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Short summary
Understanding how atmospheric aerosols affect clouds is a scientific challenge. One question is how aerosols affects the amount cloud water. We used a cloud-scale model to study these effects on marine clouds. The study showed that variations in cloud properties and instrument noise can cause bias in satellite derived cloud water content. However, our results suggest that for similar weather conditions with well-defined aerosol concentrations, satellite data can reliably track these effects.