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Closing the gap: an algorithmic approach to reconciling in-situ and remotely sensed aerosol properties
Closing the gap: an algorithmic approach to reconciling in-situ and remotely sensed aerosol properties
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Closing the gap: an algorithmic approach to reconciling in-situ and remotely sensed aerosol properties
Closing the gap: an algorithmic approach to reconciling in-situ and remotely sensed aerosol properties

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Closing the gap: an algorithmic approach to reconciling in-situ and remotely sensed aerosol properties
Closing the gap: an algorithmic approach to reconciling in-situ and remotely sensed aerosol properties
Journal Article

Closing the gap: an algorithmic approach to reconciling in-situ and remotely sensed aerosol properties

2025
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Overview
Remote sensing retrievals of atmospheric particle (i.e., aerosol) properties, such as those from lidars and polarimeters, are increasingly used to study aerosol effects on critical cloud and marine boundary layer processes. To ensure the reliability of these retrievals, it is important to validate them using aerosol measurements from in-situ instruments (i.e., external closure). However, achieving rigorous external closure is challenging because in-situ instruments often (1) provide dry (relative humidity (RH) < 40 %) aerosol measurements, while remote sensors typically retrieve properties in ambient conditions and (2) only sample a limited aerosol size-range due to sampling inlet cutoffs. To address these challenges, we introduce the In-Situ Aerosol Retrieval Algorithm (ISARA), a methodological framework designed to enable closure between in-situ and remote sensing aerosol data by converting dry in-situ aerosol optical and microphysical properties into their humidified equivalents in ambient air. We apply ISARA to aerosol measurements collected during the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) field campaign to test its ability to generate aerosol properties that are physically consistent across in-situ and remote sensing platforms. To assess this performance, we conduct consistency analyses comparing ISARA-calculated intensive and extensive aerosol properties with corresponding measurements from (1) ACTIVATE's in-situ instruments (internal consistency), (2) Monte Carlo in-situ data simulations (synthetic consistency), (3) ACTIVATE's Second Generation High Spectral Resolution Lidar (HSRL-2) and Research Scanning Polarimeter (RSP) instruments (external consistency). This study demonstrates that: (1) appropriate a priori assumptions for aerosol can lead to consistency between many in-situ measurements and remote sensing retrievals in the ACTIVATE campaign, (2) ambient aerosol properties retrieved from dry in-situ and the RSP polarimetric data are compared showing reasonable agreement for the first time in literature, (3) measurements are externally consistent even in the presence of moderately absorbing (imaginary refractive index (IRI) > 0.015) and coarse nonspherical particles, and (4) ISARA is likely limited by (i) under-sampling of low background concentrations (N < 1 cm−3) for aerosol sizes greater than 5 µm in diameter as well as (ii) by an under-determined measurement system. These results suggest that additional in-situ measurements under ambient conditions, at a wider range of wavelengths, of the real refractive index, and of the coarse aerosol size distribution, can reduce the uncertainties of the in-situ ambient aerosol products. Although this study focuses on fine spherical aerosol mixtures with a coarse mode that is spherical or nonspherical (spheroidal), its success demonstrates that ISARA could have the potential to support systematic and physically consistent closure of aerosol data sets in various field campaigns and aerosol regimes.