Jasper F. Kok

Mineral dust interacts with Earth’s radiation across a broad spectral range, from near UV to the thermal Infrared (TIR). While global distributions of dust optical depth at mid-visible wavelength (at 0.55 μm, DOD_0.55) are well characterized by remote sensing and models, corresponding TIR products (at 10 μm, DOD₁₀) remain limited to a few satellite retrievals and are rarely simulated by models. This coordinated AeroCom–AeroSat study addresses these gaps by presenting the current state of DOD₁₀ using four satellite TIR products, six AeroCom model simulations, a model-based, observation-constrained climatological database, and laboratory measurements of dust properties. The analysis reveals substantial differences in DOD₁₀ across satellite products and models, sometimes exceeding a factor of ten. Discrepancies among satellite products may link to retrieval algorithms and assumptions, while model differences arise from dust emission, removal processes, and mass extinction efficiencies determined by dust optical properties and size distributions. Multi-model mean results indicate that coarse-mode dust (diameter > 2.5 μm) accounts for nearly 80 % of dust mass loading and DOD₁₀ but only about 40 % for DOD_0.55. The absence of a reference dataset for DOD₁₀ poses a major challenge, limiting validation to indirect comparisons with proxies such as AERONET coarse-mode AOD_0.55, which is informative but insufficient for DOD₁₀ validation. Laboratory measurements of spectral-dependent optical properties highlight the potential of combining shortwave and longwave remote sensing to advance dust compositions analysis through their distinct spectral sensitivities.

Mineral dust interacts with Earth’s radiation across a broad spectral range, from near UV to the thermal Infrared (TIR). While global distributions of dust optical depth at mid-visible wavelength (at 0.55 μm, DOD_0.55) are well characterized by remote sensing and models, corresponding TIR products (at 10 μm, DOD₁₀) remain limited to a few satellite retrievals and are rarely simulated by models. This coordinated AeroCom–AeroSat study addresses these gaps by presenting the current state of DOD₁₀ using four satellite TIR products, six AeroCom model simulations, a model-based, observation-constrained climatological database, and laboratory measurements of dust properties. The analysis reveals substantial differences in DOD₁₀ across satellite products and models, sometimes exceeding a factor of ten. Discrepancies among satellite products may link to retrieval algorithms and assumptions, while model differences arise from dust emission, removal processes, and mass extinction efficiencies determined by dust optical properties and size distributions. Multi-model mean results indicate that coarse-mode dust (diameter > 2.5 μm) accounts for nearly 80 % of dust mass loading and DOD₁₀ but only about 40 % for DOD_0.55. The absence of a reference dataset for DOD₁₀ poses a major challenge, limiting validation to indirect comparisons with proxies such as AERONET coarse-mode AOD_0.55, which is informative but insufficient for DOD₁₀ validation. Laboratory measurements of spectral-dependent optical properties highlight the potential of combining shortwave and longwave remote sensing to advance dust compositions analysis through their distinct spectral sensitivities.

Dust particles larger than 10 μm are increasingly recognized as important to the climate system, yet models tend to underestimate their atmospheric abundance. Although recent work has improved representations of dust emission processes, dry deposition remains comparatively unexplored. Here we derive a mass-conserving parameterization of the dust deposition velocity that is physically consistent from submicron through giant particle sizes. We calibrate the parameterization using laboratory measurements and compare it to commonly used formulations. We find that assuming spherical particles overestimates the deposition velocity for supermicron dust, while assuming Stokes-regime settling increasingly overestimates the deposition velocity for particles larger than 10 μm. Furthermore, the commonly used electric analogue formulation produces substantially larger deposition velocities than the mass-conserving formulation, particularly for particles larger than 10 μm, although the magnitude and, in some cases, sign of this discrepancy depend on atmospheric stability, friction velocity, reference height, and treatment of particle rebound. Taken together, commonly used assumptions can produce deposition velocities and fluxes up to a factor of 1.6 larger than more physically consistent formulations. A survey of dust schemes used in climate models participating in the Sixth Climate Model Intercomparison Project found that all used non-mass-conserving dry deposition formulations and Stokes theory for spherical-particle settling. These results suggest that commonly used model parameterizations tend to overestimate dust dry deposition, which may contribute to an underestimation of the abundance and lifetime of large dust particles.

Aerosol radiative forcing represents the largest source of uncertainty for calculating present-day climate sensitivity. This uncertainty has been underestimated in climate models, as they have not adequately accounted for uncertainties in the emissions of aerosols prior to the satellite era. This is especially the case for natural aerosols, such as mineral dust and aerosols from biomass burning. In this paper, we take a step towards reducing this uncertainty by providing a roadmap for improved integration of proxy-based observational constraints on past aerosol variability with model simulations. We first review existing literature on the importance of natural aerosol radiative forcing during historical and paleo-time periods, with a focus on the Last Glacial Maximum and the preindustrial era (ca. 1850) to the present. We then compile existing paleo-data archives and describe their ability to constrain emissions of aerosols, highlighting existing gaps. Model-data combinations are available to estimate radiative effects for dust and volcanoes in several time periods, and for biomass burning for preindustrial to present day, but are not available for other aerosols. Modeled feedbacks of aerosols to climate (W/m²/°C) are 10–100⨉ lower than model-data derived estimates for dust, casting doubt on our ability to successfully model feedbacks in the current generation of Earth system models. Finally, we propose a framework for integrating paleo-archives with models through harmonized datasets, proxy–model translation metrics, and regularized inversion approaches, and identify priority measurements needed to reduce uncertainty in both aerosol loading and radiative-effect efficiency across climate states.

Mineral dust interacts with Earth’s radiation across a broad spectral range, from near UV to the thermal Infrared (TIR). While global distributions of dust optical depth at mid-visible wavelength (at 0.55 μm, DOD0.55) are well characterized by remote sensing and models, corresponding TIR products (at 10 μm, DOD10) remain limited to a few satellite retrievals and are rarely simulated by models. This coordinated AeroCom–AeroSat study addresses these gaps by presenting the current state of DOD10 using four satellite TIR products, six AeroCom model simulations, a model-based, observation-constrained climatological database, and laboratory measurements of dust properties. The analysis reveals substantial differences in DOD10 across satellite products and models, sometimes exceeding a factor of ten. Discrepancies among satellite products may link to retrieval algorithms and assumptions, while model differences arise from dust emission, removal processes, and mass extinction efficiencies determined by dust optical properties and size distributions. Multi-model mean results indicate that coarse-mode dust (diameter > 2.5 μm) accounts for nearly 80 % of dust mass loading and DOD10 but only about 40 % for DOD0.55. The absence of a reference dataset for DOD10 poses a major challenge, limiting validation to indirect comparisons with proxies such as AERONET coarse-mode AOD0.55, which is informative but insufficient for DOD10 validation. Laboratory measurements of spectral-dependent optical properties highlight the potential of combining shortwave and longwave remote sensing to advance dust compositions analysis through their distinct spectral sensitivities.

Aerosol radiative forcing represents the largest source of uncertainty for calculating present-day climate sensitivity. This uncertainty has been underestimated in climate models, as they have not adequately accounted for uncertainties in the emissions of aerosols prior to the satellite era. This is especially the case for natural aerosols, such as mineral dust and aerosols from biomass burning. In this paper, we take a step towards reducing this uncertainty by providing a roadmap for improved integration of proxy-based observational constraints on past aerosol variability with model simulations. We first review existing literature on the importance of natural aerosol radiative forcing during historical and paleo-time periods, with a focus on the Last Glacial Maximum and the preindustrial era (ca. 1850) to the present. We then compile existing paleo-data archives and describe their ability to constrain emissions of aerosols, highlighting existing gaps. Model-data combinations are available to estimate radiative effects for dust and volcanoes in several time periods, and for biomass burning for preindustrial to present day, but are not available for other aerosols. Modeled feedbacks of aerosols to climate (W/m²/°C) are 10–100⨉ lower than model-data derived estimates for dust, casting doubt on our ability to successfully model feedbacks in the current generation of Earth system models. Finally, we propose a framework for integrating paleo-archives with models through harmonized datasets, proxy–model translation metrics, and regularized inversion approaches, and identify priority measurements needed to reduce uncertainty in both aerosol loading and radiative-effect efficiency across climate states.

Transatlantic dust from North Africa is the largest intercontinental aerosol flux on Earth, affecting radiative forcing, cloud processes, and biogeochemical cycling, yet the inter-model spread of dust transport remains large in previous AeroCom experiments. With the progress in 17 AeroCom Phase III (P3) models, this study evaluates the transatlantic dust cycle for 2010 against AERONET inversions, satellite products (MODIS, CALIOP, MISR, IASI, POLDER, and MODIS-TIR), DustCOMM, CAMS, MERRA-2, in-situ records, and GPCP precipitation across subregions from North Africa to the Caribbean. We found that AeroCom P3 narrows mid-visible dust optical depth (DOD) diversity to 30–45 % across the transport domain relative to AeroCom P2 (38–59 %), yet this convergence masks compensatory biases, as models with lower (or higher) mass loading may have higher (or lower) mass extinction efficiency (MEE), yielding similar DOD despite a large spread of mass representations. Compared with observational estimates, model biases intensify with transport distance, with median DOD underestimated by ~50 % and ~70 % over mid- and long-range regions, and loss frequencies exceed satellite estimates by a factor of 2–3. Such biases remain unresolved even with super-coarse extensions, indicating that constraining mid-visible DOD alone is inadequate for the dust cycle. The excess removal implicates deficiencies in gravitational settling, wet scavenging, and vertical transport parameterizations. This systematic underestimation could propagate into dust radiative forcing, cloud-dust interactions, and nutrient delivery to Atlantic and Amazonian ecosystems. Progress requires size-resolved benchmarking (DOD at 550 nm and 10 µm with size-segregated mass), non-spherical settling treatments, and mechanisms sustaining coarse particles aloft.

Mineral dust affects Earth’s energy budget, clouds, and biochemistry, yet the evolution of the global dust cycle in recent decades remains shrouded in uncertainty. Here we reconstruct the global dust cycle during the early 21st century by integrating a suite of global dust aerosol optical depth (DAOD) products from satellite-borne lidar, infrared sounders, and multispectral imagers; three aerosol reanalyses; and a compilation of dust-dominated AERONET sites into a large-ensemble inverse modeling framework. We show that North Africa has remained the dominant global dust source, yet it has experienced a decline in DAOD of −10 ± 8% between 2003 and 2023. A comparable reduction is observed across Asia (−10 ± 12%), together driving a global decrease of −10 ± 8%. Similar declines in dust loading, emissions, and deposition indicate a coherent reduction of the global dust cycle. Individual satellite products converge on overall similar trends, providing the strongest evidence to date that the planet has become less dusty in the early 21st century. This decline in atmospheric dust has exerted a positive effective radiative forcing of +0.02 ± 0.05 watts per square meter over 2003–2023, implying that declining atmospheric dust might have modestly contributed to the rapid warming of the past two decades.

Transatlantic dust from North Africa is the largest intercontinental aerosol flux on Earth, affecting radiative forcing, cloud processes, and biogeochemical cycling, yet the inter-model spread of dust transport remains large in previous AeroCom experiments. With the progress in 17 AeroCom Phase III (P3) models, this study evaluates the transatlantic dust cycle for 2010 against AERONET inversions, satellite products (MODIS, CALIOP, MISR, IASI, POLDER, and MODIS-TIR), DustCOMM, CAMS, MERRA-2, in-situ records, and GPCP precipitation across subregions from North Africa to the Caribbean. We found that AeroCom P3 narrows mid-visible dust optical depth (DOD) diversity to 30–45 % across the transport domain relative to AeroCom P2 (38–59 %), yet this convergence masks compensatory biases, as models with lower (or higher) mass loading may have higher (or lower) mass extinction efficiency (MEE), yielding similar DOD despite a large spread of mass representations. Compared with observational estimates, model biases intensify with transport distance, with median DOD underestimated by ~50 % and ~70 % over mid- and long-range regions, and loss frequencies exceed satellite estimates by a factor of 2–3. Such biases remain unresolved even with super-coarse extensions, indicating that constraining mid-visible DOD alone is inadequate for the dust cycle. The excess removal implicates deficiencies in gravitational settling, wet scavenging, and vertical transport parameterizations. This systematic underestimation could propagate into dust radiative forcing, cloud-dust interactions, and nutrient delivery to Atlantic and Amazonian ecosystems. Progress requires size-resolved benchmarking (DOD at 550 nm and 10 µm with size-segregated mass), non-spherical settling treatments, and mechanisms sustaining coarse particles aloft.