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Biomass burning is a worldwide practice applied to deforestation that can have disastrous consequences for local and regional environments. This paper describes a case study of an extreme event of biomass burning smoke transport toward the São Paulo metropolitan area (MASP), on 19 August 2019, when the city experienced an uncommon completely dark sky around 15:00 UTC−3. A synergy between air mass back trajectories, satellite-retrieved aerosol fields and surface radiometric measurements was used to find the origin of the smoke plume affecting the city and to analyse the radiative impact of the transport of the smoke toward the city. Results showed that the MASP atmosphere was affected by the transport of a dense smoke plume with aerosol optical depth at 550 nm above 1. Air mass back trajectories and auxiliary data indicated that most of the smoke was emitted 2 d before arrival. The smoke plume in combination with clouds, associated with a frontal system, produced a strong radiative impact, as observed by a regional network of pyranometers. During the day of darkness, the diurnal clearness index was below 0.1 in all five MASP stations, and a maximum of the cloud optical depth higher than 300 was retrieved, producing irradiances at surface that dropped to 0 for approximately 40 min. The strong radiative efficiency (cloud radiative effect per cloud optical depth unit) of this extreme event was 7 % higher than other overcast days observed in a 2-year period.

Fossil-fuel combustion related winter heating has become a major air quality and public health concern in northern China recently. We analyzed the impact of winter heating on aerosol loadings over China using the MODIS-Aqua Collection 6 aerosol product from 2004-2012. Absolute humidity (AH) and planetary boundary layer height (PBL) -adjusted aerosol optical depth (AOD*) was constructed to reflect ground-level PM2.5 concentrations. GIS analysis, standard statistical tests, and statistical modeling indicate that winter heating is an important factor causing increased PM2.5 levels in more than three-quarters of central and eastern China. The heating season AOD* was more than five times higher as the non-heating season AOD*, and the increase in AOD* in the heating areas was greater than in the non-heating areas. Finally, central heating tend to contribute less to air pollution relative to other means of household heating.

Stratospheric Aerosol Geoengineering (SAG) is one of the solar geoengineering approaches that have been proposed to offset some of the impacts of anthropogenic climate change. Past studies have shown that SAG may have adverse impacts on the global hydrological cycle. Using a climate model, we quantify the sensitivity of the tropical monsoon precipitation to the meridional distribution of volcanic sulfate aerosols prescribed in the stratosphere in terms of the changes in aerosol optical depth (AOD). In our experiments, large changes in summer monsoon precipitation in the tropical monsoon regions are simulated, especially over the Indian region, in association with meridional shifts in the location of the intertropical convergence zone (ITCZ) caused by changes in interhemispheric AOD differences. Based on our simulations, we estimate a sensitivity of − 1.8° ± 0.0° meridional shift in global mean ITCZ and a 6.9 ± 0.4% reduction in northern hemisphere (NH) monsoon index (NHMI; summer monsoon precipitation over NH monsoon regions) per 0.1 interhemispheric AOD difference (NH minus southern hemisphere). We also quantify this sensitivity in terms of interhemispheric differences in effective radiative forcing and interhemispheric temperature differences: 3.5 ± 0.3% change in NHMI per unit (Wm −2 ) interhemispheric radiative forcing difference and 5.9 ± 0.4% change per unit (°C) interhemispheric temperature difference. Similar sensitivity estimates are also made for the Indian monsoon precipitation. The establishment of the relationship between interhemispheric AOD (or radiative forcing) differences and ITCZ shift as discussed in this paper will further facilitate and simplify our understanding of the effects of SAG on tropical monsoon rainfall.

The Southern Ocean is covered by a large amount of clouds with high cloud albedo. However, as reported by previous climate model intercomparison projects, underestimated cloudiness and overestimated absorption of solar radiation (ASR) over the Southern Ocean lead to substantial biases in climate sensitivity. The present study revisits this long-standing issue and explores the uncertainty sources in the latest CMIP6 models. We employ 10-year satellite observations to evaluate cloud radiative effect (CRE) and cloud physical properties in five CMIP6 models that provide comprehensive output of cloud, radiation, and aerosol. The simulated longwave, shortwave, and net CRE at the top of atmosphere in CMIP6 are comparable with the CERES satellite observations. Total cloud fraction (CF) is also reasonably simulated in CMIP6, but the comparison of liquid cloud fraction (LCF) reveals marked biases in spatial pattern and seasonal variations. The discrepancies between the CMIP6 models and the MODIS satellite observations become even larger in other cloud macro- and micro-physical properties, including liquid water path (LWP), cloud optical depth (COD), and cloud effective radius, as well as aerosol optical depth (AOD). However, the large underestimation of both LWP and cloud effective radius (regional means ∼20% and 11%, respectively) results in relatively smaller bias in COD, and the impacts of the biases in COD and LCF also cancel out with each other, leaving CRE and ASR reasonably predicted in CMIP6. An error estimation framework is employed, and the different signs of the sensitivity errors and biases from CF and LWP corroborate the notions that there are compensating errors in the modeled shortwave CRE. Further correlation analyses of the geospatial patterns reveal that CF is the most relevant factor in determining CRE in observations, while the modeled CRE is too sensitive to LWP and COD. The relationships between cloud effective radius, LWP, and COD are also analyzed to explore the possible uncertainty sources in different models. Our study calls for more rigorous calibration of detailed cloud physical properties for future climate model development and climate projection.

The evaluation of modelling diagnostics with appropriate observations is an important task that establishes the capabilities and reliability of models. In this study we compare aerosol and cloud properties obtained from three different climate models (ECHAM-HAM, ECHAM-HAM-SALSA, and NorESM) with satellite observations using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The simulator MODIS-COSP version 1.4 was implemented into the climate models to obtain MODIS-like cloud diagnostics, thus enabling model-to-model and model-to-satellite comparisons. Cloud droplet number concentrations (CDNCs) are derived identically from MODIS-COSP-simulated and MODIS-retrieved values of cloud optical depth and effective radius. For CDNC, the models capture the observed spatial distribution of higher values typically found near the coasts, downwind of the major continents, and lower values over the remote ocean and land areas. However, the COSP-simulated CDNC values are higher than those observed, whilst the direct model CDNC output is significantly lower than the MODIS-COSP diagnostics. NorESM produces large spatial biases for ice cloud properties and thick clouds over land. Despite having identical cloud modules, ECHAM-HAM and ECHAM-HAM-SALSA diverge in their representation of spatial and vertical distributions of clouds. From the spatial distributions of aerosol optical depth (AOD) and aerosol index (AI), we find that NorESM shows large biases for AOD over bright land surfaces, while discrepancies between ECHAM-HAM and ECHAM-HAM-SALSA can be observed mainly over oceans. Overall, the AIs from the different models are in good agreement globally, with higher negative biases in the Northern Hemisphere. We evaluate the aerosol–cloud interactions by computing the sensitivity parameter ACICDNC=dln⁡(CDNC)/dln⁡(AI) on a global scale. However, 1 year of data may be considered not enough to assess the similarity or dissimilarities of the models due to large temporal variability in cloud properties. This study shows how simulators facilitate the evaluation of cloud properties and expose model deficiencies, which are necessary steps to further improve the parameterisation in climate models.

Black carbon (BC) aerosol is a significant, short-lived climate forcing agent. To further understand the effects of BCs on the regional climate, the warming effects of BCs from residential, industrial, power and transportation emissions are investigated in Asian regions during summer using the state-of-the-art regional climate model RegCM4. BC emissions from these four sectors have very different rates and variations. Residential and industrial BCs account for approximately 85% of total BC emissions, while power BCs account for only approximately 0.19% in Asian regions during summer. An investigation suggests that both the BC aerosol optical depth (AOD) and direct radiative forcing (DRF) are highly dependent on emissions, while the climate effects show substantial nonlinearity to emissions. The total BCs AOD and clear-sky top of the atmosphere DRF averaged over East Asia (100–130°E, 20–50°N) are 0.02 and + 1.34 W/m 2 , respectively, during summer. Each sector’s BC emissions may result in a warming effect over the region, leading to an enhanced summer monsoon circulation and a subsequent local decrease (e.g., northeast China) or increase (e.g., south China) in rainfall in China and its surrounding regions. The near surface air temperature increased by 0.2 K, and the precipitation decreased by approximately 0.01 mm/day in east China due to the total BC emissions. The regional responses to the BC warming effects are highly nonlinear to the emissions, which may be linked to the influences of the perturbed atmospheric circulations and climate feedback. The nonuniformity of the spatial distribution of BC emissions may also have significant influences on climate responses, especially in south and east China. The results of this study could aid us in better understanding BC effects under different emission conditions and provide a scientific reference for developing a better BC reduction strategy over Asian regions.

The sub-micron (SM) aerosol optical depth (AOD) is an optical separation based on the fraction of particles below a specified cutoff radius of the particle size distribution (PSD) at a given particle radius. It is fundamentally different from spectrally separated FM (fine-mode) AOD. We present a simple (AOD-normalized) SM fraction versus FM fraction (SMF vs. FMF) linear equation that explains the well-recognized empirical result of SMF generally being greater than the FMF. The AERONET inversion (AERinv) products (combined inputs of spectral AOD and sky radiance) and the spectral deconvolution algorithm (SDA) products (input of AOD spectra) enable, respectively, an empirical SMF vs. FMF comparison at similar (columnar) remote sensing scales across a variety of aerosol types. SMF (AERinv-derived) vs. FMF (SDA-derived) behavior is primarily dependent on the relative truncated portion (εc) of the coarse-mode (CM) AOD associated with the cutoff portion of the CM PSD and, to a second order, the cutoff FM PSD and FM AOD (εf). The SMF vs. FMF equation largely explains the SMF vs. FMF behavior of the AERinv vs. SDA products as a function of PSD cutoff radius (“inflection point”) across an ensemble of AERONET sites and aerosol types (urban-industrial, biomass burning, dust, maritime and a mixed class of Arctic aerosols). The overarching dynamic was that the linear SMF vs. FMF relation pivots clockwise about the approximate (SMF, FMF) singularity of (1, 1) in a “linearly inverse” fashion (slope and intercept of approximately 1−εc and εc) with increasing cutoff radius. SMF vs. FMF slopes and intercepts derived from AERinv and SDA retrievals confirmed the general domination of εc over εf in controlling that dynamic. A more general conclusion is the apparent confirmation that the optical impact of truncating modal (whole) PSD features can be detected by an SMF vs. FMF analysis.

Aerosol optical depth (AOD), fine-mode fraction (FMF), and absorption aerosol optical depth (AAOD) are essential for quantifying aerosol extinction and related climate and air-quality effects. Yet, most satellite retrievals target a single wavelength or parameter. In this study, a deep neural network (DNN) framework was developed to synergistically retrieve AOD, FMF, and AAOD from Sentinel-5P/TROPOMI at seven wavelengths across 380–772 nm. Parameter-specific feature engineering was designed by incorporating physical linkages among aerosol optical properties. Bayesian optimization was employed to tune hyperparameters, and SHAP (Shapley additive explanations) was used to interpret feature contributions. The proposed model demonstrated high accuracy and robustness on an independent test set. The retrieved AOD showed excellent agreement with AERONET (R = 0.960, MAE = 0.034, RMSE = 0.070), and similarly strong performance was achieved for FMF (R = 0.955, MAE = 0.027, RMSE = 0.039). For AAOD, an overall correlation of 0.86 was obtained (MAE = 0.005, RMSE = 0.008). Comparisons with existing satellite products indicated globally consistent spatial patterns and improved spatial continuity under high aerosol loading. Overall, the proposed data-driven approach enhances the efficiency and coverage of multi-parameter aerosol retrieval while maintaining high accuracy, supporting absorbing aerosol monitoring, aerosol-type discrimination, and climate-effect assessment.

The current study investigates the relationship among Aerosol Optical Depth (AOD), rain rate in aerosol types (fine-mode and coarse-mode), and meteorological conditions (such as relative humidity and vertical velocity) during Indian Summer Monsoon (ISM) over regions of the Gangetic plain (GP) and the Modified Core Monsoon Region (MCMR) of India. The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products, including AOD and Angstrom Exponent (AE), the observed rainfall gridded data of India Meteorological Department (IMD) and reanalyzed data of relative humidity (RH), vertical velocity (VV) and wind speed and direction as meteorological variables from European Center for Medium Range Weather Forecasting (ECMWF) Reanalysis v5 (ERA5) are used for the period of 2003–2021. It is noticed that regions of GP and MCMR experienced significant rainfall suppression with increasing aerosol loading in moderately polluted condition and beyond moderately polluted condition, the different rain rate responses to aerosol loading is observed. Different aerosol types and meteorological conditions may have different influences on the AOD-rain rate relationship. It is found that an increase in AOD may suppress or enhance the rain rate in a region like GP where high RH condition prevails, as well as the presence of fine-mode aerosol can enhance the rain rate in a highly polluted condition (AOD ≥ 0.4). An increase in AOD may enhance the rain rate in conditions of high and low RH over the regions. In high and low updraft conditions, an increase in AOD suppresses the rain rate. Additionally, high (low) RH and high (low) updraft promote high (low) rain rate over the regions.

This study investigates, through regional climate modelling, the surface mass concentration and AOD (aerosol optical depth) evolution of the various (anthropogenic and natural) aerosols over the Euro-Mediterranean region between the end of the 20th century and the mid-21st century. The direct aerosol radiative forcing (DRF) as well as the future Euro-Mediterranean climate sensitivity to aerosols have also been analysed. Different regional climate simulations were carried out with the CNRM-ALADIN63 regional climate model, driven by the global CNRM-ESM2-1 Earth system model (used in CMIP6) and coupled to the TACTIC (Tropospheric Aerosols for ClimaTe In CNRM) interactive aerosol scheme. These simulations follow several future scenarios called shared socioeconomic pathways (SSP 1-1.9, SSP 3-7.0 and SSP 5-8.5), which have been chosen to analyse a wide range of possible future scenarios in terms of aerosol or particle precursor emissions. Between the historical and the future period, results show a total AOD decrease between 30 % and 40 % over Europe for the three scenarios, mainly due to the sulfate AOD decrease (between −85 and −93 %), that is partly offset by the nitrate and ammonium particles AOD increase (between +90 and +120 %). According to these three scenarios, nitrate aerosols become the largest contributor to the total AOD during the future period over Europe, with a contribution between 43.5 % and 47.5 %. It is important to note that one of the precursors of nitrate and ammonium aerosols, nitric acid, has been implemented in the model as a constant climatology over time. Concerning natural aerosols, their contribution to the total AOD increases slightly between the two periods. The different evolution of aerosols therefore impacts their DRF, with a significant sulfate DRF decrease between 2.4 and 2.8 W m−2 and a moderate nitrate and ammonium DRF increase between 1.3 and 1.5 W m−2, depending on the three scenarios over Europe. These changes, which are similar under the different scenarios, explain about 65 % of the annual shortwave radiation change but also about 6 % (in annual average) of the warming expected over Europe by the middle of the century. This study shows, with SSP 5-8.5, that the extra warming attributable to the anthropogenic aerosol evolution over Central Europe and the Iberian Peninsula during the summer period is due to “aerosol–radiation” as well as “aerosol–cloud” interaction processes. The extra warming of about 0.2 ∘C over Central Europe is explained by a surface radiation increase of 5.8 W m−2 over this region, due to both a surface aerosol DRF decrease of 4.4 W m−2 associated with a positive effective radiative forcing due to aerosol–radiation interactions (ERFari) of 2.7 W m−2 at the top of the atmosphere (TOA) and a cloud optical depth (COD) decrease of 1.3. In parallel, the simulated extra warming of 0.2∘C observed over the Iberian Peninsula is due to a COD decrease of 1.3, leading to a positive effective radiative forcing due to aerosol–cloud interactions (ERFaci) of 2.6 W m−2 at the TOA but also to an atmospheric dynamics change leading to a cloud cover decrease of about 1.7 % and drier air in the lower layers, which is a signature of the semi-direct forcing. This study thus highlights the necessity of taking into account the evolution of aerosols in future regional climate simulations.