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Abstract. Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, the relative contributions of the world’s major dust source regions to the global dust cycle remain poorly constrained. This problem hinders accounting for the potentially large impact of regional differences in dust properties on clouds, the Earth's energy balance, and terrestrial and marine biogeochemical cycles. Here, we constrain the contribution of each of the world’s main dust source regions to the global dust cycle. We use an analytical framework that integrates an ensemble of global model simulations with observationally informed constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We obtain a data set that constrains the relative contribution of each of nine major source regions to size-resolved dust emission, atmospheric loading, optical depth, concentration, and deposition flux. We find that the 22–29 Tg (one standard error range) global loading of dust with geometric diameter up to 20 μm is partitioned as follows: North African source regions contribute ~50 % (11–15 Tg), Asian source regions contribute ~40 % (8–13 Tg), and North American and Southern Hemisphere regions contribute ~10 % (1.8–3.2 Tg). Current models might on average be overestimating the contribution of North African sources to atmospheric dust loading at ~65 %, while underestimating the contribution of Asian dust at ~30 %. However, both our results and current models could be affected by unquantified biases, such as due to errors in separating dust aerosol optical depth from that produced by other aerosol species in remote sensing retrievals in poorly observed desert regions. Our results further show that each source region's dust loading peaks in local spring and summer, which is partially driven by increased dust lifetime in those seasons. We also quantify the dust deposition flux to the Amazon rainforest to be ~10 Tg/year, which is a factor of 2–3 less than inferred from satellite data by previous work that likely overestimated dust deposition by underestimating the dust mass extinction efficiency. The data obtained in this paper can be used to obtain improved constraints on dust impacts on clouds, climate, biogeochemical cycles, and other parts of the Earth system.

Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with geometric diameter up to 20 μm (PM20) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

Large volcanic eruptions are known to influence the climate through a variety of mechanisms including aerosol‐forced cooling and warming via emitted CO2. The January 2022 Hunga shallow underwater eruption caused an increase in stratospheric water vapor, and demonstrated how the associated positive radiative forcing can be an important component of an eruption's climate forcing. We present interactive stratospheric aerosol model simulations of super‐volcanic eruptions with a range of SO2 emissions that can produce climate warming through feedback effects produced by a large igneous province (or "flood basalt") mid‐latitude super‐eruption using Goddard Earth Observing System Chemistry Climate Model climate model simulations. The model experiments suggest total SO2 emissions ≳4,000 Tg/4 Gt generate a multi‐year period of sustained aerosol absorptive local‐heating of the upper troposphere and lower stratosphere and hence produce net climate warming after strong initial cooling. The eruptions produce stratospheric water vapor increases of factors of 8–600. The initiation of these feedbacks within the simulations suggest they could occur for individual stratovolcano eruptions of the scale of the Toba or Tambora eruptions. We note the sensitivity of our results to volcanic sulfate aerosol microphysics and model chemistry. Plain Language Summary: Volcanic eruptions are important drivers of climate change throughout Earth's history. Using climate model experiments, we examine how massive volcanic eruptions can produce warmer climate conditions through an increase in stratospheric water vapor. We find that there is a range of volcanic sulfur dioxide emissions that can produce climate warming, but that the stratospheric water vapor increase occurs in all of our model experiments. Key Points: Stratospheric water vapor increases by a factor of 8–600 for volcanic SO2 emissions of 1,875–60,000 TgVolcanic SO2 emissions ≳4,000 Tg can produce net climate warming through feedbacksAbsorptive‐heating driven increases to stratospheric water vapor likely becomes the dominant forcing for volcanic super‐eruptions [ABSTRACT FROM AUTHOR]

The emergence of aerosol reanalyses in recent years has facilitated a comprehensive and systematic evaluation of aerosol optical depth (AOD) trends and attribution over multi-decadal timescales. Notable multi-year aerosol reanalyses currently available include NAAPS-RA from the US Naval Research Laboratory, the NASA MERRA-2, JRAero from the Japan Meteorological Agency (JMA), and CAMSRA from Copernicus/ECMWF. These aerosol reanalyses are based on differing underlying meteorology models, representations of aerosol processes, as well as data assimilation methods and treatment of AOD observations. This study presents the basic verification characteristics of these four reanalyses versus both AERONET and MODIS retrievals in monthly AOD properties and identifies the strength of each reanalysis and the regions where divergence and challenges are prominent. Regions with high pollution and often mixed fine-mode and coarse-mode aerosol environments, such as South Asia, East Asia, Southeast Asia, and the Maritime Continent, pose significant challenges, as indicated by higher monthly AOD root mean square error. Moreover, regions that are distant from major aerosol source areas, including the polar regions and remote oceans, exhibit large relative differences in speciated AODs and fine-mode versus coarse-mode AODs among the four reanalyses. To ensure consistency across the globe, a multi-reanalysis consensus (MRC, i.e., ensemble mean) approach was developed similarly to the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME). Like the ICAP-MME, while the MRC does not consistently rank first among the reanalyses for individual regions, it performs well by ranking first or second globally in AOD correlation and RMSE, making it a suitable candidate for climate studies that require robust and consistent assessments. [ABSTRACT FROM AUTHOR]

Satellite observations and ground-based measurements have indicated a high variability in the aerosol optical depth (AOD) in the Middle East region in recent decades. In the period that extends from 2003 to 2012, observations show a positive AOD trend of 0.01–0.04 per year or a total increase of 0.1–0.4 per decade. This study aimed to investigate if the observed trend was also captured by the NASA Goddard Earth Observing System (GEOS) model. To this end, we examined changes in the simulated dust emissions and dust AOD during this period. To understand the factors driving the increase in AOD in this region we also examined meteorological and surface parameters important for dust emissions, such as wind fields and soil moisture. Two GEOS model simulations were used in this study: the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis (with meteorological and aerosol AOD data assimilated) and MERRA-2 Global Modeling Initiative (GMI) Replay (with meteorology constrained by the MERRA-2 reanalysis but without aerosol assimilation). We did not find notable changes in the modeled 10 m wind speed and soil moisture. However, analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data did show an average decrease of 8 % per year in the region encompassing Syria and Iraq, which prompted us to quantify the effects of vegetation on dust emissions and AOD in the Middle East region. This was done by performing a sensitivity experiment in which we enhanced dust emissions in grid cells where the NDVI decreased. The simulation results supported our hypothesis that the loss of vegetation cover and the associated increase in dust emissions over Syria and Iraq can partially explain the increase in AOD downwind. The model simulations indicated dust emissions need to be 10-fold larger in those grid cells in order to reproduce the observed AOD and trend in the model. [ABSTRACT FROM AUTHOR]

The Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which controls the sources, sinks, and chemistry of aerosols within the Goddard Earth Observing System (GEOS), recently underwent a major refactoring and update, including a revision of the emissions datasets and the addition of brown carbon. A 4-year benchmark simulation utilizing the new version of the model code, termed GOCART Second Generation (GOCART-2G) and coupled to the Goddard Earth Observing System (GEOS) model, was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development. A comparison of simulated aerosol optical depth between GOCART-2G and MODIS retrievals indicates the model captures the overall spatial pattern and seasonal cycle of aerosol optical depth but overestimates aerosol extinction over dusty regions and underestimates aerosol extinction over Northern Hemisphere boreal forests, requiring further investigation and tuning of emissions. This MODIS-based analysis is corroborated by comparisons to MISR and selected AERONET stations; however, discrepancies between the Aqua and Terra satellites indicate there is a diurnal component to biases in aerosol optical depth over southern Asia and northern Africa. Despite the underestimate of aerosol optical depth in biomass burning regions in GEOS, there is an overestimate in the surface mass of organic carbon in the United States, especially during the summer months. Over Europe, GOCART-2G is unable to match the summertime peak in aerosol optical depth, opposing the observed late fall and early spring peaks in surface mass concentration. A comparison of the vertical profile of attenuated backscatter to observations from CALIPSO indicates the GEOS model is capable of capturing the vertical profile of aerosol; however, the mid-troposphere plumes of dust in the North Atlantic and smoke in the southeastern Atlantic are perhaps too low in altitude. The results presented highlight priorities for future development with GOCART-2G, including improvements for dust, biomass burning aerosols, and anthropogenic aerosols. [ABSTRACT FROM AUTHOR]

The emergence of aerosol reanalyses in recent years has facilitated a comprehensive and systematic evaluation of Aerosol Optical Depth (AOD) trends and attribution over multi-decadal timescales. Notable aerosol reanalyses currently available include NAAPS-RA from the U.S. Naval Research Laboratory; the NASA MERRA-2; JRAero from the Japan Meteorological Agency (JMA); and CAMSRA from Copernicus/ECMWF. These aerosol reanalyses are based on differing underlying meteorology models, representations of aerosol processes, and data assimilation methods and treatment of AOD observations. This study presents the basic verification characteristics of these four reanalyses versus both AERONET and MODIS retrievals in monthly AOD properties and identifies the strength of each reanalysis and the regions where diversity and challenges are prominent. Regions with high pollution and often mixed fine-coarse mode aerosol environments such as South Asia, East Asia, Southeast Asia, and the Maritime Continent pose significant challenges, as indicated by higher monthly AOD root mean square error. Moreover, regions that are distant from major aerosol source areas, including the polar regions, and remote oceans exhibit large relative differences in speciated AODs and fine-mode vs coarse-mode AODs among the four reanalyses. To ensure consistency across the globe, a multi-reanalysis-consensus (MRC) approach was developed similar to the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME). Like the ICAP-MME, while the MRC does not consistently rank first among the reanalyses for individual regions, it performs well by ranking first or second globally in AOD correlation and RMSE, making it a suitable candidate for climate studies that require robust and consistent assessments.   [ABSTRACT FROM AUTHOR]

The emergence of aerosol reanalyses in recent years has facilitated a comprehensive and systematic evaluation of Aerosol Optical Depth (AOD) trends and attribution over multi-decadal timescales. Notable aerosol reanalyses currently available include NAAPS-RA from the U.S. Naval Research Laboratory; the NASA MERRA-2; JRAero from the Japan Meteorological Agency (JMA); and CAMSRA from Copernicus/ECMWF. These aerosol reanalyses are based on differing underlying meteorology models, representations of aerosol processes, and data assimilation methods and treatment of AOD observations. This study presents the basic verification characteristics of these four reanalyses versus both AERONET and MODIS retrievals in monthly AOD properties and identifies the strength of each reanalysis and the regions where diversity and challenges are prominent. Regions with high pollution and often mixed fine-coarse mode aerosol environments such as South Asia, East Asia, Southeast Asia, and the Maritime Continent pose significant challenges, as indicated by higher monthly AOD root mean square error. Moreover, regions that are distant from major aerosol source areas, including the polar regions, and remote oceans exhibit large relative differences in speciated AODs and fine-mode vs coarse-mode AODs among the four reanalyses. To ensure consistency across the globe, a multi-reanalysis-consensus (MRC) approach was developed similar to the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME). Like the ICAP-MME, while the MRC does not consistently rank first among the reanalyses for individual regions, it performs well by ranking first or second globally in AOD correlation and RMSE, making it a suitable candidate for climate studies that require robust and consistent assessments. [ABSTRACT FROM AUTHOR]

The sulfur cycle plays a key role in atmospheric air quality, climate, and ecosystems. In this study, we compare the spatial and temporal distribution of four sulfur-containing species, dimethyl sulfide (DMS), sulfur dioxide (SO2), particulate methanesulfonate (MSA), and particulate sulfate (SO4), that were measured during the airborne NASA Atmospheric Tomography (ATom) mission and simulated by five AeroCom-III models to analyze the budget of sulfur cycle from the models. This study focuses on remote regions over the Pacific, Atlantic, and Southern Oceans from near the ocean surface to ~12-km altitude range, and covers all four seasons. These regions provide us with highly heterogeneous natural and anthropogenic source environments, which is not usually the case for traditional continental studies. We examine the vertical and seasonal variations of these sulfur species over tropical, mid-, and high-latitude regions in both hemispheres. We identify their origins from land versus ocean and from anthropogenic versus natural sources with sensitivity studies by applying tagged tracers linking to emission types and regions. In general, the differences among model results can be greater than one-order of magnitude. Comparing with observations, simulated SO2 is generally low while SO4 is high, and the model-observation agreement is much better in ATom-4 (April-May, 2018). There are much larger DMS concentrations simulated close to the sea surface than observed, indicating that the DMS emissions may be too high from all models. Anthropogenic emissions are the dominant source (40-60% of the total amount) for atmospheric sulfate simulated at locations and times along the ATom flight tracks at almost every altitude, followed by volcanic emissions (18-32%) and oceanic sources (16-32%). Similar source contributions can also be derived at broad ocean basin and monthly scales, indicating that any reductions of anthropogenic sulfur emissions would have global impacts in modern times. [ABSTRACT FROM AUTHOR]

The sulfur cycle plays a key role in atmospheric air quality, climate, and ecosystems. In this study, we compare the spatial and temporal distribution of four sulfur-containing species, dimethyl sulfide (DMS), sulfur dioxide (SO2), particulate methanesulfonate (MSA), and particulate sulfate (SO4), that were measured during the airborne NASA Atmospheric Tomography (ATom) mission and simulated by five AeroCom-III models to analyze the budget of sulfur cycle from the models. This study focuses on remote regions over the Pacific, Atlantic, and Southern Oceans from near the ocean surface to ~12-km altitude range, and covers all four seasons. These regions provide us with highly heterogeneous natural and anthropogenic source environments, which is not usually the case for traditional continental studies. We examine the vertical and seasonal variations of these sulfur species over tropical, mid-, and high-latitude regions in both hemispheres. We identify their origins from land versus ocean and from anthropogenic versus natural sources with sensitivity studies by applying tagged tracers linking to emission types and regions. In general, the differences among model results can be greater than one-order of magnitude. Comparing with observations, simulated SO2 is generally low while SO4 is high, and the model-observation agreement is much better in ATom-4 (April–May, 2018). There are much larger DMS concentrations simulated close to the sea surface than observed, indicating that the DMS emissions may be too high from all models. Anthropogenic emissions are the dominant source (40–60 % of the total amount) for atmospheric sulfate simulated at locations and times along the ATom flight tracks at almost every altitude, followed by volcanic emissions (18–32 %) and oceanic sources (16–32 %). Similar source contributions can also be derived at broad ocean basin and monthly scales, indicating that any reductions of anthropogenic sulfur emissions would have global impacts in modern times. [ABSTRACT FROM AUTHOR]

Satellite observations and ground-based measurements have indicated a high variability in the Aerosol Optical Depth (AOD) in the Middle East region in recent decades. In the period that extends from 2003 to 2012, observations show a positive trend of 0.01-0.04 AOD per year or a total increase of 0.1-0.4 per decade. This study aimed to investigate if the observed trend was also captured by the NASA Goddard Earth Observing System (GEOS) Earth system model. To this end, we examined changes in the simulated dust emissions and dust AOD during this period. To understand the factors driving the increase of AOD in this region we also examined meteorological and surface parameters important for dust emissions, such as wind fields and soil moisture. Two GEOS model simulations were used in this study: the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) Reanalysis (with meteorological and aerosol AOD data assimilated) and MERRA-2 GMI Replay (with meteorology constrained by MERRA-2 Reanalysis, but without aerosol assimilation). We did not find notable changes in the modeled 10-meter wind speed and soil moisture. However, analysis of MODIS Normalized Difference Vegetation Index (NDVI) data, did show an average decrease of 8% per year in the region encompassing Syria and Iraq, which prompted us to quantify the effects of vegetation on dust emissions and AOD in the Middle East region. This was done by performing a sensitivity experiment in which we enhanced dust emissions in grid cells where NDVI decreased. The simulation results supported our hypothesis that the loss of vegetation cover and the associated increase of dust emissions over Syria and Iraq can partially explain the increase of AOD downwind. The model simulations indicated dust emissions need to be tenfold larger in those grid cells in order to reproduce the observed AOD and trend in the model. [ABSTRACT FROM AUTHOR]

The Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which controls the sources sinks and chemistry within the Goddard Earth Observing System, recently underwent a major refactoring and update to the representation of physical processes. This paper serves to document code changes that were included in GOCART 2nd Generation (GOCART-2G) and establishes a benchmark simulation that is to be used for future development of the system. The code refactoring increases flexibility such multiple instances of an aerosol species can be run and interact with radiation and cloud microphysics, in addition to the output of multiple wavelength aerosol optical properties in support of data assimilation. From a science perspective, a new radiatively active tracer, brown carbon, was added to distinguish smoke from other sources of organic aerosol thereby improving optical properties entering the radiative calculations. A four-year benchmark simulation was evaluated using in situ and space borne measurements to develop a baseline and prioritize future development. A comparison of simulated aerosol optical depth between GOCART-2G and MODIS retrievals indicates the model captures the overall spatial pattern and seasonal cycle of aerosol optical depth but overestimates aerosol extinction over dusty regions and underestimates aerosol extinction over northern hemisphere boreal forests, requiring further tuning of emissions. This MODIS-based analysis is corroborated by comparisons to MISR and selected AERONET stations. Despite the underestimate of aerosol optical depth in biomass burning regions in GEOS, there is an overestimate in the surface mass of organic carbon in the United States, especially during the summer months. [ABSTRACT FROM AUTHOR]

In order to improve aerosol representation in the NASA Goddard Earth Observing System (GEOS) model, we evaluated simulations of the aerosol properties and transport over the southern African biomass burning source and outflow region using observations made during the first deployment of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign in September 2016. An example case study of September 24 was analyzed in detail, during which aircraft-based in-situ and remote sensing observations showed the presence of a multi-layered smoke plume structure with significant vertical variation in single scattering albedo (SSA). Our baseline GEOS simulations were not able to represent the observed SSA variation, nor the observed organic aerosol-to-black carbon ratio (OA:BC). Analyzing the simulated smoke age suggests that the higher altitude, less absorbing smoke plume was younger (~4 days), while the lower altitude and more absorbing smoke plume was older (~7 days). We hypothesize a chemical or microphysical loss process exists to explain the change in aerosol absorption as the smoke plume ages, and we apply a simple 6-day e-folding loss rate to the model hydrophilic biomass burning OA to mimic this process. Adding this loss process required some adjustment to the model assumed scaling factors of aerosol emissions to conserve the regional aerosol loading and further improve the simulated OA:BC ratio. Accordingly, we have increased our biomass burning emissions of OA by 60% and biomass burning BC by 15%. We also utilized the ORACLES airborne observations to better constrain the simulation of aerosol optical properties, adjusting the assumed particle size, hygroscopic growth, and absorption. Our final GEOS model simulation with additional OA loss and updated optics showed a better performance in simulating AOD and SSA compared to independent ground and space based retrievals for the entire month of September 2016, including the OMI Aerosol Index. In terms of radiative implications of our model adjustments, the final GEOS simulation suggested a decreased atmospheric warming of about 10% (~2 W m-2) over the south-east Atlantic region and above the stratocumulus cloud decks compared to the model baseline simulations. These results improve the representation of the smoke age, transport, and optical properties in Earth system models. [ABSTRACT FROM AUTHOR]