Tong Ying

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.

Current climate models struggle to capture the mean state and variability of dust emissions. This is partially due to their inability to resolve convection, a consequence of their relatively coarse spatial resolution. Via analysis of output from an offline dust emission scheme forced with output from a global storm‐resolving model, we show that resolving convection doubles the contribution of the Sahel, an important dust source region sensitive to environmental change, to global dust emissions from 6.1% to 12.3% during its late monsoon season. Resolving convection induces an increase in friction velocity and a decrease in soil moisture, and thus enhances Sahelian dust emissions. These changes are due to improved representation of mesoscale convective systems associated with African Easterly Waves. These results demonstrate that high‐resolution modeling with resolved convection can improve understanding of the global dust cycle and how dust emissions are affected by a changing climate.

Aerosol forcing remains highly uncertain in climate change assessment. Observation‐based forcing estimates have been typically given more weight as they do not rely on assumptions and parameterizations in models. Traditional estimation of direct aerosol radiative forcing (DARF) based on observation is realized by regressing the observed radiative fluxes against aerosol optical depth (AOD). Here we improve this procedure by considering more aerosol parameters such as single scattering albedo (SSA) and adopting a machine learning‐based method (eXtreme Gradient Boosting (XGBoost)) to establish the relationship between top‐of‐atmosphere (TOA) radiative fluxes and aerosol properties. Our approach gives a global mean DARF of −0.80 ± 0.73 W/m² under clear sky, which largely agrees with previously reported results. The DARF uncertainty includes the impact of measurement errors and the XGBoost model, in which AOD and SSA uncertainties cause ∼0.66 and ∼0.14 W/m² changes in the DARF respectively.

Over the past 2 decades, remarkable changes in aerosol concentrations and compositions have been observed worldwide, especially over developing countries, potentially resulting in considerable changes in aerosol properties. The Aerosol Robotic Network (AERONET) offers high-precision measurements of aerosol optical parameters over about 1700 stations globally, many of which have long-term measurements for 1 or more decades. Here we use AERONET Level 2.0 quality-assured measurements to investigate long-term aerosol optical depth (AOD) and Ångström exponent (AE) trends and quality-controlled Level 1.5 inversion products to analyse trends in absorption aerosol optical depth (AAOD) and single scattering albedo (SSA) at stations with long-term records. We also classify the aerosol properties in these sites into six types and analyse the trends in each type. Results reveal decreases in AOD over the majority of the stations, except for northern India and the Arabian Peninsula, where AOD increased. AE (computed from the AOD within the range of 440–870 nm) decreased in Europe, eastern North America, and the Middle East but increased over South Asia and western North America. The decreased AE over Europe and eastern North America is likely due to decreased fine-mode anthropogenic aerosols, whereas that over the Arabian Peninsula is attributed to increased dust activity. Conversely, increased AE over northern India is probably attributed to increased anthropogenic emissions and decreased dust loading. Most stations in Europe, North America, East Asia, and South Asia exhibit negative trends in AAOD, whereas Solar_Village in the Arabian Peninsula has positive trends. SSA at most stations increases and exhibits opposite trends to AAOD but with several stations in North America and central Europe showing decreased SSA values. Trend analysis of different aerosol types further reveals the changes in different aerosol components that are related to AOD, AE, AAOD, and SSA trends. The reductions in aerosols in eastern North America mainly result from non-absorbing species. Reductions in both fine-mode absorbing species and non-absorbing aerosols are found over Europe and East Asia, but the reduction in absorbing species is stronger than that of non-absorbing species. Increased aerosols in Kanpur over northern India should be mainly comprised of fine-mode scattering species, whereas those in Solar_Village over the Arabian Peninsula are mainly dust. The majority of stations exhibit consistent monotonic trends across different seasons for these parameters.

The relative amount of scattering and absorbing aerosols is essential in determining the aerosol radiative and climate effects. Using reanalysis datasets and climate simulations, here, we show that changes in the relative amount of scattering and absorbing aerosols in the Northern Hemisphere (NH) high latitudes, manifested as long-term decreasing trends in aerosol single-scattering albedo (SSA), have played an important role in driving the widening and weakening trends of the NH Hadley circulation (HC) since the early 1980s. Decreasing SSA in the NH middle and high latitudes can notably warm the troposphere there, thus reducing the equator-to-pole temperature gradient, increasing static stability in mid-latitude regions, and leading to the widening and weakening trends of NH HC. Further analysis of the Coupled Model Intercomparison Project Phase 6 (CMIP6) aerosol forcing–only simulations also supports the importance of SSA trends in perturbing NH HC through the above mechanism.

Satellite observations are widely used in large-scale aerosol monitoring. In the past 20 years, aerosol compositions have changed substantially worldwide, especially over developing regions such as East and South Asia, which leads to long-term trends in aerosol single scattering albedo (SSA). However, major satellite aerosol retrieval algorithms, such as the widely used Dark Target (DT) algorithm by the MODerate resolution Imaging Spectroradiometer (MODIS), apply a same set of aerosol models over time with almost a constant SSA, which may have defects in capturing the actual aerosol optical depth (AOD) trend. In this work, we use MODIS-Aqua observations as an example to investigate the impact of SSA trends on the satellite-retrieved AOD trend. A series of sensitivity experiments using radiative transfer simulations with different surface conditions and aerosol loadings indicate that ± 0.06 SSA change may lead to 30% AOD retrieval uncertainties, and increased surface albedo and aerosol loading would enhance this error. Analysis at four representative sites in the Aerosol Robotic Network (AERONET) where significant long-term SSA trends are observed, namely Beijing, Kanpur, Barcelona and Carpentras, shows that the operational MODIS products at all four sites suffer from distinct biases in the AOD trends. By replacing the prescribed SSAs with those observed by AERONET in the MODIS algorithm, the retrieved AOD trend biases are largely corrected. This study points out the importance of aerosol scattering and absorption properties in MODIS-like AOD retrieval algorithms. It is therefore urgent to establish long-term monitoring of SSA globally.

The El Niño–Southern Oscillation (ENSO) is a crucial driver of fire weather in Australia, with the correlation between ENSO and Australian fire weather having intensified over the past 2 decades. However, the underlying causes for this change have not been thoroughly investigated. In this study, we utilize reanalysis datasets and numerical model simulations to demonstrate that the Atlantic Multidecadal Oscillation (AMO) could potentially modulate the ENSO–Australian fire weather relationship. The correlation between ENSO and the Australian Fire Weather Index (FWI) increases from 0.17 to 0.70 as the AMO transitions from its negative to positive phase. This strengthening effect can be attributed to atmospheric teleconnection mechanisms. Specifically, the positive AMO phase, characterized by warming in the northern and tropical Atlantic, generates Rossby wave trains, leading to high-pressure systems over Australia. Consequently, local temperature and wind speed increase, while precipitation decreases. This signal, superimposed on ENSO, serves to amplify the ENSO effect on Australian fire weather.

The climate effects of atmospheric aerosols remain uncertain. Part of the uncertainty arises from the fact that scattering and absorbing aerosols have distinct or even opposite effects, and thus their relative fraction is critical in determining the overall aerosol climate effect. Here, combining observations and global model simulations, we demonstrate that changes in the fraction of scattering and absorbing aerosols play the major role in driving the monsoon precipitation decrease over northern India, especially the Gangetic Basin, since the 1980s. Increased aerosol scattering, or decreased aerosol absorption, manifested as a significant increase of aerosol single scattering albedo (SSA), causes strong cooling in the lower atmosphere, suppressing vertical convection and thus reducing precipitation. Further analysis of the Couple Model Intercomparison Project Phase 6 multi-model-mean historical simulation shows that failing to capture the SSA increase over northern India is likely an important source of the simulated precipitation trend bias in this area.