Mutual constraints on global aerosol composition from novel PACE data and ModelE

Abstract. Aerosol climate impacts remain uncertain, in part because global aerosol composition observations have been unavailable to constrain Earth System Models (ESMs). We present the first comparison of aerosol composition from the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite’s Spectropolarimeter for Planetary Exploration one (SPEXone) against an ESM, co-locating Remote sensing of Trace gas and Aerosol Products (RemoTAP) retrievals with NASA GISS ModelE simulations to within ±15 minutes over 2024–2025. In the fine mode, the two correlate well over land, capturing the same seasonal biomass burning and pollution cycles. The coarse mode, however, diverges: mineral dust agrees to within ∼10 % by volume over land, yet SPEXone exceeds ModelE eightfold over ocean, where it covaries with modeled sea salt and increases away from desert sources. Because SPEXone partitions the coarse mode on shape alone, we suggest this excess is nonspherical marine aerosol rather than mineral dust. Finally, ModelE carries a median 3.6 times the water per unit dry sea salt that SPEXone infers over ocean. Substituting reanalysis relative humidity (RH) and an observationally constrained hygroscopicity each move the model toward the retrieval, but neither alone nor together do they reproduce it. This factor amounts to only 0.027 in global median effective marine refractive index, amplified by the nonlinearity of the mixing rule used to infer water. Together, these results provide a first evaluation of modeled aerosol composition against PACE SPEXone retrievals.

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Publication Details

Published
2026-10-07
DOI
https://doi.org/10.5194/egusphere-2026-5135
Primary Topic
Atmospheric aerosols and clouds
Type
preprint

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preprint

Mutual constraints on global aerosol composition from novel PACE data and ModelE

Sylvain Foisy, Otto Hasekamp, Susanne Elizabeth Bauer, Kostas Tsigaridis et al.
Atmospheric aerosols and clouds
preprint

Mutual constraints on global aerosol composition from novel PACE data and ModelE

Sylvain Foisy, Otto Hasekamp, Susanne Elizabeth Bauer, Kostas Tsigaridis, Guangliang Fu
preprint en

Abstract

Abstract. Aerosol climate impacts remain uncertain, in part because global aerosol composition observations have been unavailable to constrain Earth System Models (ESMs). We present the first comparison of aerosol composition from the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite’s Spectropolarimeter for Planetary Exploration one (SPEXone) against an ESM, co-locating Remote sensing of Trace gas and Aerosol Products (RemoTAP) retrievals with NASA GISS ModelE simulations to within ±15 minutes over 2024–2025. In the fine mode, the two correlate well over land, capturing the same seasonal biomass burning and pollution cycles. The coarse mode, however, diverges: mineral dust agrees to within ∼10 % by volume over land, yet SPEXone exceeds ModelE eightfold over ocean, where it covaries with modeled sea salt and increases away from desert sources. Because SPEXone partitions the coarse mode on shape alone, we suggest this excess is nonspherical marine aerosol rather than mineral dust. Finally, ModelE carries a median 3.6 times the water per unit dry sea salt that SPEXone infers over ocean. Substituting reanalysis relative humidity (RH) and an observationally constrained hygroscopicity each move the model toward the retrieval, but neither alone nor together do they reproduce it. This factor amounts to only 0.027 in global median effective marine refractive index, amplified by the nonlinearity of the mixing rule used to infer water. Together, these results provide a first evaluation of modeled aerosol composition against PACE SPEXone retrievals.

Goddard Institute for Space Studies (US), Space Research Organisation Netherlands (NL), Columbia University (US)
National Aeronautics and Space Administration
Climate action
Atmospheric aerosols and clouds
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Mutual constraints on global aerosol composition from novel PACE data and ModelE — Sylvain Foisy, Otto Hasekamp, et al. · (2026) | TGRS Research Map | TGRS