Aerosol Direct Radiative Forcing Research Articles

Research on simulation and validation methods of aerosol radiative forcing on the Tibetan Plateau based on satellite and ground-based remote sensing observations over the past 20 years

Atmospheric radiative changes induced by aerosol radiative forcing are the most uncertain factors in climate change, affecting a comprehensive understanding of aerosol's role in the climate system and ecosystem, with current research mainly focused on densely populated and heavily polluted regions. This study utilizes satellite and ground-based remote sensing data to establish a multi-source data processing and analysis workflow suitable for the Qinghai-Tibet Plateau region, and based on atmospheric radiative transfer models, constructs methods for simulating and validating regional aerosol radiative forcing, optimizing the long-term observational, simulation, and variation studies of aerosol radiative forcing at regional scales. The results indicate: (1) Key input parameters for simulating aerosol radiative forcing regions were determined through sensitivity tests of radiative transfer model parameters to be AOD, surface albedo, atmospheric column water vapor content, and total atmospheric ozone. A method for simulating aerosol direct radiative forcing regions was constructed. Comparison and validation against aerosol radiative forcing site simulations based on ground-based remote sensing observations at the Yangbajing station in Tibet showed R2 values above 0.8 and NRMSE values between 0.25 and 0.39, indicating high accuracy of the method, suitable for the Qinghai-Tibet Plateau. (2) Utilizing satellite remote sensing data, aerosol direct radiative forcing simulations for the Qinghai-Tibet Plateau region over the past 20 years were conducted based on the constructed method. Results showed: ① The annual mean aerosol radiative forcing at the top of the atmosphere was −3.03 W/m2, gradually increasing from west to east; monthly means were negative, decreasing by an average of 0.0025 W/m2 per year, with decreases mainly in February to May. ② The annual mean surface aerosol radiative forcing was −13.56 W/m2, gradually increasing from west to east; monthly means were negative, decreasing by an average of 0.015 W/m2 per year, with decreases mainly in February, June to July, and October to December. ③ The annual mean atmospheric aerosol radiative forcing was 10.6 W/m2, gradually increasing from southwest to northeast; monthly means were positive, increasing by 0.007 W/m2 per year, with increases mainly in October to December. Overall, the annual and monthly mean aerosol direct radiative forcing values at the top of the atmosphere and surface were negative, indicating a cooling effect, while those in the atmosphere were positive, indicating a heating effect; the strongest aerosol radiative forcing occurred in summer at the top of the atmosphere, and in spring for both surface and atmosphere; April showed the fastest variation.

Comparative Analysis of Aerosol Direct Radiative Forcing During COVID-19 Lockdown Period in Peninsular India

AbstractThe load of aerosols in the atmosphere has been increasing gradually due to industrialization and urbanization. This increase has contributed to change in the Earth’s radiation budget through the absorption or scattering of radiation. The aerosol direct radiative forcing (ADRF) is a measurement utilized to comprehend the impact of cooling or warming up of the atmosphere directly by aerosols. Our study examined the impact of aerosols during the COVID-19 pandemic by comparing them to the average from the preceding 5-year period (2015–2019) in peninsular India. The measure of aerosols deployed in this study is the Aerosol Optical Depth (AOD), and the study was carried out on three distinct time frames: prior to lockdown, during lockdown, and post lockdown. The study revealed that the ADRF increased during all the three time frames of 2020 compared to the average of 2015–2019, and the other time scales experienced an increase in ADRF as well. The most notable rise in ADRF and decrease in temperature occurred in the tropical savanna and warm semi-arid climate regions during the pre-lockdown period. During lockdown, the increase in ADRF was seen throughout the study area, and a decrease in temperature was observed only in the tropical monsoon region. In the post-lockdown period, the decline in ADRF was accompanied by a fall in temperature in the tropical savanna region. This study provides insights into the effect of aerosols on ADRF in peninsular India and highlights the importance of monitoring and regulating aerosol emissions to mitigate the changes in temperature.

LUCC-induced dust aerosol change increase surface and reduce atmospheric direct radiative forcing in Northern China

Land use and land cover change (LUCC) can alter surface properties, such as albedo, roughness, and vegetation coverage, directly affecting dust emissions and aerosol concentrations, leading to variations in direct radiative forcing (DRF) of dust aerosols and consequently impacting the climate. This study utilized the Weather Research and Forecasting model with Chemistry (WRF-Chem) to quantify the impact of LUCC in northern China from 2000 to 2020 on dust aerosol DRF. Results indicated that LUCC's influence on shortwave radiative forcing of dust was significantly greater than its influence on longwave radiative forcing and exhibited obvious seasonal variations. Overall, LUCC can cause net direct radiative forcing to increase by 5.3 W m−2 at the surface and decrease by 7.8 W m−2 in the atmosphere. Different types of LUCC transformation showed distinct impacts on dust aerosol DRF, with the conversion from sparse vegetation to barren land had the most significant effect on net radiative intensity, resulting in a decrease of 8.1 W m−2 at the surface, an increase of 12.2 W m−2 in the atmosphere, and an increase of 4.1 W m−2 at the top of the atmosphere. Conversely, the conversion from barren land to sparse vegetation led to surface cooling and atmospheric warming. These findings are of great significance for enhancing our knowledge of the effects of LUCC on the radiative balance of dust aerosols.

Changes in aerosol properties at the El Arenosillo site in Southern Europe as a result of the 2023 Canadian forest fires

From the beginning of May 2023 to the end of August 2023, the Northern Hemisphere experienced significant wildfire activity with the most widespread fires occurring in Canada. Forest fires in Canada destroyed more than 15.6 million hectares of forests. These wildfires worsened air quality across the region and other parts of the world. The smoke reached southern Europe by the end of June 2023. To better understand the consequences of such forest fires far from the site of origin, aerosol optical, microphysical and radiative properties were analyzed during this event for southern Europe using data from the Visible Infrared Imaging Radiometer Suite (VIIRS), TROPOspheric Monitoring Instrument (TROPOMI), and Aerosol Robotic Network (AERONET). TROPOMI aerosol index (AI) and the carbon monoxide (CO) product confirm that the smoke originated directly from these forest fires. AERONET data from the El Arenosillo site in southern Spain showed maximum aerosol optical depth (AOD) values on June 27 reached 2.36. Data on Angstrom Exponent (AE), aerosol volume size distribution (VSD), single scattering albedo (SSA), fine mode fraction (FMF), volume particle concentration, effective radius (REff), absorption AOD (AAOD), extinction AE (EAE) and absorption AE (AAE) showed that fine-mode particles with carbonaceous aerosols contribution predominated in the atmosphere above the El Arenosillo site. Direct aerosol radiative forcing (DARF) at the top (DARFTOA) and bottom of atmosphere (DARFBOA) were −103.1 and −198.93 Wm−2, respectively. The atmospheric aerosol radiative forcing (DARFATM) was found to be 95.83 Wm−2 and with a heating rate 2.69 K day−1, which indicates the resulting warming of the atmosphere.

More Accurate Quantification of Direct Aerosol Radiative Effects Using Vertical Profiles of Single‐Scattering Albedo Derived From Tethered Balloon Observations

AbstractAerosol single‐scattering albedo (SSA) is the most critical factor for the accurately calculating of aerosol radiative effects, however, the observation of vertical profiles of SSA is difficult to realize. Current assessments of aerosol radiative effects remain uncertain because of the lack of long‐term, high‐resolution vertical profiles of SSA observations. High‐resolution SSA vertical profiles were observed in a semi‐arid region of Northwest China during winter using a tethered balloon. The observed SSA vertical profiles were used to calculate the aerosol direct radiative forcing and radiative heating rates. Significant differences in the calculated radiative forcing were found (e.g., a 48.3% relative difference for the heating effect in the atmosphere at 14:00) between the observed SSA profiles and the constant assumption with SSA = 0.90. Diurnal variations in the vertical distribution of SSA decisively influenced direct radiative forcing of aerosols. Furthermore, high‐resolution vertical profiles of absorbing aerosols and meteorological parameters provide robust observational evidence of the heating effect of an elevated absorbing aerosol layer. This study provides a more accurate calculation of aerosol radiative forcing using observed aerosol SSA profiles.

Sensitivity of global direct aerosol shortwave radiative forcing to uncertainties in aerosol optical properties

Abstract. New satellite missions promise global reductions in the uncertainties in aerosol optical properties, but it is unclear how those reductions will propagate to uncertainties in the shortwave (SW) direct aerosol radiative effect (DARE) and direct aerosol radiative forcing (DARF), which are currently large, on the order of at least 20 %. In this work, we build a Monte Carlo framework to calculate the impact of uncertainties in aerosol optical depth (AOD), single scattering albedo (SSA), and the asymmetry parameter on the uncertainty in shortwave DARE and DARF. This framework uses the results of over 2.3 million radiative transfer simulations to calculate global clear-sky DARE and DARF based on a range of uncertainties in present-day and pre-industrial aerosol optical properties, representative of existing and future global observing systems. We find the 1σ uncertainty varies between ±0.23 and ±1.91 W m−2 (5 % and 42 %) for the top-of-atmosphere (TOA) clear-sky DARE and between ±0.08 and ±0.47 W m−2 (9 % and 52 %) for the TOA DARF. At the TOA, AOD uncertainty is the main contributor to overall uncertainty except over bright surfaces where SSA uncertainty contributes most. We apply regionally varying uncertainties to represent current measurement uncertainties and find that aerosol optical property uncertainties represent 24 % of TOA DARE and DARF. Reducing regionally varying optical property uncertainties by a factor of 2 would reduce their contributions to TOA DARE and DARF uncertainty proportionally. Applying a simple scaling to all-sky conditions, aerosol optical property uncertainty contributes to about 25 % total uncertainty in TOA, all-sky SW DARE, and DARF. Compared to previous studies which considered uncertainties in non-aerosol variables, our results suggest that the aerosol optical property uncertainty accounts for one-third to half of the total direct SW uncertainty. Recent and future progress in constraining aerosol optical properties using ground-based or satellite retrievals could be translated into DARE and DARF uncertainty using our freely available framework.

MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm

Abstract. For over 40 years, the Geostationary Operational Environmental Satellite (GOES) system has provided frequent snapshots of the Western Hemisphere. The advanced baseline imagers (ABIs) on the GOES-16, GOES-17, and GOES-18 platforms are the first GOES-series imagers that meet the precision requirements for high-quality, aerosol-related research. We present MAGARA, a Multi-Angle Geostationary Aerosol Retrieval Algorithm, that leverages multi-angle ABI imagery to exploit the differences in autocorrelation timescales between surface reflectance, aerosol type, and aerosol loading. MAGARA retrieves pixel-level (up to 1 km) aerosol loading and fine-mode fraction at up to the cadence of the measurements (10 min), fine- and coarse-mode aerosol particle properties at a daily cadence, and surface properties by combining the multi-angle radiances with robust surface characterization inherent to temporally tiled algorithms. We present three case studies, and because GOES-17 was not making observations for one case, we present this as a unique demonstration of the multi-angle algorithm using only a single ABI sensor. We also compare MAGARA retrievals of fine-mode (FM) aerosol optical depth (AOD), coarse-mode (CM) AOD, and single-scattering albedo (SSA) statistically, with coincident AErosol RObotic NETwork (AERONET) spectral deconvolution algorithm (SDA) and inversion retrievals for the same period, and against bias-corrected NOAA GOES-16 and GOES-17 retrieved 550 nm AOD. For MAGARA vs. coincident AERONET over-land 500 nm fine-mode fraction and AOD>0.3, MAE=0.031, RMSE=0.100, and r=0.902, indicating good sensitivity to fine-mode fraction over land, especially for smoky regions. For bias-corrected MAGARA vs. coincident AERONET spectral single-scattering albedo with MAGARA AOD>0.5 (n=116), MAE=0.010, RMSE=0.015, and the correlation is 0.87. MAGARA performs best in regions where surface reflectance varies over long timescales with minimal clouds. This represents a large portion of the western half of the United States, much of north-central Africa and the Middle East, some of central Asia, and much of Australia. For these regions, aerosol type and aerosol loading on timescales as short as 10 min could allow for novel research into aerosol–cloud interactions, improvements to air-quality modeling and forecasting, and tighter constraints on direct aerosol radiative forcing.

A method to obtain scattering phase function based on particle size distribution and refractive index retrieved from Aurora 4000 multi-angle scattering measurements: A numerical study

Scattering phase function of aerosol particles is crucial to the accurate estimation of aerosol direct radiative forcing, and is also of great interest in the field of remote sensing. One feasible and promising way to obtain scattering phase function on a long-term scale with satisfying temporal resolution is based upon the particle size distribution (PSD) and the refractive index (m = n + ik) simultaneously retrieved from multi-wavelength multi-angle scattering detected by Aurora 4000, a commercially available and easily operated, as well as lab- and field-deployable instrument. In this study, a retrieval algorithm was specifically developed according to the characteristics of Aurora 4000 measurements, using the regularization method. The algorithm was systematically evaluated for its applicability, capability and limitation by a series of designed numerical experiments, considering both monomodal and bimodal log-normal distributions with various settings of parameters and different m, in order to be prepared for its application in field studies. The retrieval algorithm has exhibited a successful performance in deriving the PSDs and the real part of the refractive index (n) without a priori assumptions about the shape of the PSDs and the value of n, and consequently in obtaining scattering phase function, for aerosol particles from purely scattering to slightly absorbing (the imaginary part of the refractive index k ≤ 0.01) both without and with assumed measurement errors (when ±ψs≤±3%). Under such circumstances, relative errors in retrieved effective diameter (De), total surface area concentration (Sa), total volume concentration (Va) are almost within ±20%, relative errors in retrieved total number concentration (Na) stay roughly within ±50%, and absolute errors of n are well within ±0.02. Moreover, relative errors in backscattering ratio (BSR) and the defined parameter to describe relative errors in scattering phase function (δP), as good indicators for demonstrating how well scattering phase function can be captured, averagely locate within ±20% and ±10%, respectively. In contrast, relative errors in the widely used parameters of the asymmetry parameter (g) and hemispheric backscattering ratio (HBSR) remain still quite small even when considerable deviations can be observed in the forward and backward scattering regimes. Hopefully, when applied in field studies in the next step, the retrieval algorithm established in this study will improve our knowledge and understanding on angular scattering properties of ambient aerosol particles, as well as the associated impacts on aerosol direct radiative forcing.

Progress of aerosol direct radiative forcing

Progress of aerosol direct radiative forcing

Broadband spectrum characteristics and radiative effects of primary brown carbon from wood pyrolysis

Brown carbon (BrC), known as light-absorbing organic aerosol in the near-ultraviolet (UV) and short visible region, plays a significant role in the global and regional climate change. A detailed understanding of the spectral optical properties of BrC is beneficial for reducing the uncertainty in radiative forcing calculation. In this work, the spectral properties of primary BrC were investigated by using a four-wavelength broadband cavity-enhanced albedometer with central wavelengths at 365, 405, 532 and 660 nm. The BrC samples were generated by the pyrolysis of three types of wood. During the pyrolysis process, the measured average single scattering albedo (SSA) at 365 nm was about 0.66 to 0.86, where the average absorption Ångström exponent (AAE) was between 5.8 and 7.8, and the average extinction Ångström exponent (EAE) was within 2.1 to 3.5. The full spectral measurement of SSA (300–700 nm) was realized by an optical retrieval method and the retrieved SSA spectrum was directly applied to evaluate aerosol direct radiative forcing (DRF) efficiency. The DRF efficiency over ground of various primary BrC emissions increased from 5.3 % to 68 % as compared to the non-absorbing organic aerosol assumption. A decrease of about 35 % in SSA would cause the DRF efficiency over ground to change from cooling effect to warming effect (from −0.33 W/m2 to +0.15 W/m2) in the near-UV band (365–405 nm). The DRF efficiency over ground of strongly absorptive primary BrC (lower SSA) contributed 66 % more than weakly absorptive primary BrC (higher SSA). These findings proved the importance of broadband spectral properties of BrC, which are substantial for radiative forcing evaluation of BrC and should be considered in global climate models.

Small and large particle limits of the asymmetry parameter for homogeneous, spherical particles

The aerosol single scattering asymmetry parameter g is an important intensive particle parameter in determining aerosol direct radiative forcing and radiation pressure. For homogeneous spherical particles and a complex refractive index that is independent of wavelength, g is solely dependent on the size parameter x, the ratio of the particle circumference to the wavelength, and the complex refractive index m of the particle. Here, we explore this dependency for the small and large particle limits with size parameters much smaller and much larger than one. We show that in the small particle (Rayleigh) regime, g is proportional to x2, and give the proportionality factor as a function of the complex m. In addition, we separate regions in the complex refractive index space where the asymmetry parameter is negative (dominantly backscattering) and where it is positive (dominantly forward scattering). In the large particle limit, the geometric optics regime, g converges to a constant value that is a function of m.

Aerosol direct radiative forcing over China: A 40-year MERRA-2-based evaluation

Aerosol direct radiative forcing (ADRF) has substantial impacts on regional and global climate changes, whereas it remains one of the largest uncertainties among various climate forcing factors. The 40-year detailed clear-sky ADRFs over China from 1981 to 2020 are systematically studied based on the MERRA-2 satellite reanalysis data, which hopefully benefit for the evaluation of the performances of aerosol-climate models. The clear-sky shortwave ADRFs show diverse spatial distributions with strong top of atmosphere (TOA) and surface cooling and atmospheric heating over the Taklamakan desert, eastern China, and southern China. A high clear-sky longwave surface ADRF reaching ∼6.5 W/m2 over dust source regions is found, and continuous increase of ADRFs over the Taklamakan desert during the past four decades may indicate that dust episodes therein are becoming severe. The mean clear-sky shortwave surface, TOA and atmospheric ADRFs, and longwave surface ADRF over China during 1981–2020 are found to be −12.3, −5.1, 7.2, and 1.0 W/m2, respectively. The seasonality of clear-sky ADRFs shows strongest mean values in spring, moderate forcings in summer and fall, and weakest levels in winter. The monthly average clear-sky surface and TOA ADRFs over China vary by approximately twofold, ranging the weakest values of −7.8 and −3.9 W/m2 in December to the strongest −17.6 and −7.1 W/m2 in April, respectively. Distinctive seasonal and monthly patterns of clear-sky ADRFs are generally seen among the Beijing-Tianjin-Hebei region, Yangtze River Delta, Pearl River Delta and Tarim Basin in China, while the monthly ADRF patterns over a typical area of these four regions are similar during four different decades. The clear-sky ADRFs over China are highly correlated with aerosol optical thickness, and dust has strong influences on clear-sky shortwave aerosol direct radiative forcing among column aerosol compositions. Our study indicates general underestimations of clear-sky atmospheric ADRF over China by aerosol-climate models and stronger impacts of aerosol scattering than absorption on the TOA radiation budgets in China.

Observations on the decadal variability of aerosol in eastern Himalayan foothills: Evidence of an anthropologically induced positive shift

The decadal variability of direct radiative effects of aerosols is investigated at Dibrugarh, a site in northeast India (NEI) at the eastern Himalayan foothills, primarily using multi-wavelength solar radiometer measurements spanning from October 2001 to February 2020. The ground-based aerosol observations are combined with satellite remote sensing, reanalysis data, and model simulations to study the change in atmospheric particle loading over the region. Observations indicate a statistically significant increase (∼0.015 yr−1) in Aerosol Optical Depth (AOD) during the last two decades in line with an increase in human activity. As compared to 2001–2007 (we call it as Stage I), the aerosol burden has grown rapidly during 2008 until 2020 (Stage II). AOD at 500 nm is found to increase by ∼40% from Stage I to Stage II, resulting in an increase in the aerosol direct radiative forcing (DRF) at the top of the atmosphere (TOA) by ∼43% during stage II (∼−16.0 W m-2), from the base value of −11.2 W m−2 in Stage I. Decreasing biomass burning activities, black carbon aerosol mass concentration, and high sulfate and organic aerosols are the primary factors responsible for the trend in TOA cooling by −0.46 W m−2 yr−1. This is further aided by the decrease in rainfall over NEI. MERRA-2 data analysis shows a similar enhancements in aerosol load over the entire NEI and the adjacent highly polluted Indo-Gangetic Plains (IGP). A similar feature is seen over the IGP, primarily driven by anthropogenic emissions, but precedes that in NEI by about a year. A simulation of the regional climate model (RegCM) over the south Asian domain quantifies the contribution of aerosol loading over NEI due to the aerosols carried from the IGP. In the highest aerosol loading period, about 12–30% of the aerosols, equivalent to 15–30% of atmospheric warming, are transported from the IGP to the NEI.

Investigation of aerosol direct radiative forcing during a dust storm using a regional climate model over Turkiye

Dust particles originating from arid zones can be transported long distances and change the radiation budget. Understanding atmospheric aerosols and their radiative forcing is important to determine their global and regional climate effects. The aim of this study is to simulate the dust transport event that occurred on March 22, 2018, using RegCM-4.5 and investigate the radiative forcing effect of Saharan dust particles. The model was run with the 4 dust bin chemistry option and the direct effect of aerosols on the regional radiation balance was investigated. Validation of the model was made by a comparison between simulated aerosol optical depth (AOD) and MODIS satellite data. The radiative forcing at the top and surface was calculated at all sky conditions. During the dust episode, the shortwave radiative forcing was ranging between -3 and -50 W/m2 at surface and -2 and -22 W/m2 at top of atmosphere while the longwave radiative forcing was between 0.5 and 8 W/m2 at surface and 0.2 and 2 W/m2 at top of atmosphere over Turkiye. In Istanbul it produced a cooling up to -18 W/m2 at surface and -9 W/m2 at top of atmosphere, a warming up to 3.5 W/m2 at surface and 0.6 W/m2 at top of atmosphere.

Spatiotemporal analysis of absorbing aerosols and radiative forcing over environmentally distinct stations in East Africa during 2001–2018

East Africa (EA) suffers from the inadequate characterization of atmospheric aerosols, with far-reaching consequences of its inability to quantify precisely the impacts of these particles on regional climate. The current study aimed at characterizing absorption and radiative properties of aerosols using the long-term (2001–2018) AErosol RObotic NETwork (AERONET) and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data over three environmentally specific sites in EA. The annual mean absorption aerosol optical depth (AAOD440 nm), absorption Angstrom Exponent (AAE440−870 nm), total effective radius (REff), and total volume concentration (μm3/μm2) revealed significant spatial heterogeneity over the domain. The study domain exhibited a significant contribution of fine-mode aerosols compared to the coarse-mode particles. The monthly variation in SSA440 nm over EA explains the strength in absorption aerosols that range from moderate to strong absorbing aerosols. The aerosols exhibited significant variability over the study domain, with the dominance of absorbing fine-mode aerosols over Mbita accounting for ∼40 to ∼50 %, while weakly absorbing coarse-mode particles accounted for ∼8.2 % over Malindi. The study conclusively determined that Mbita was dominated by AAOD mainly from biomass burning in most of the months, whereas Malindi was coated with black carbon. The direct aerosol radiative forcing (DARF) retrieved from both the AERONET and MERRA-2 models showed strong cooling at the top of the atmosphere (TOA; −6 to −27 Wm−2) and the bottom of the atmosphere (BOA, −7 to −66 Wm−2). However, significant warming was noticed within the atmosphere (ATM; +14 to +76 Wm−2), an indication of the role of aerosols in regional climate change. The study contributed to understanding aerosol absorption and radiative characteristics over EA and can form the basis of other related studies over the domain and beyond.

Changes in Aerosols, Meteorology, and Radiation in the Southeastern U.S. Warming Hole Region during 2000 to 2019

Abstract Surface air temperatures in the southeastern United States that did not change from the climatological mean from 1900 to 2000 have increased since the year 2000. Analyzed herein are factors modulating the surface air temperatures in the region for a 20-yr period (2000–19) using space- and surface-based observations, and output from a reanalysis model. The 20-yr period is segregated into two decades, 2000–09 and 2010–19, corresponding to different tropospheric chemical regimes. Changes in seasonal and decadal averages are examined. The later decade experienced higher average surface air temperatures with significant warming during summer and fall seasons. Decadal and seasonal averages of cloud properties, column water vapor, rain rates, and top-of-atmosphere outgoing longwave radiation did not exhibit statistically significant differences between the two decades. The region experienced strong warm and moist advection during the winter months and very weak advection during the summer months. The later decade exhibited higher low-level moisture advection during the winter months than the earlier decade with insignificant changes in the temperature advection between the two decades. The later decade had significantly lower aerosol dry and liquid water mass during all seasons, along with lower aerosol optical depth, higher single scattering albedo, and lower top-of-the-atmosphere outgoing shortwave radiation during cloud-free conditions in the summer season. Collectively, these results suggest that changes in the aerosol direct radiative forcing are responsible for warming during summer months that experience weak advection and highlight seasonal differences in the temperature controlling mechanisms in the region.

Sensitivity and uncertainties assessment in radiative forcing due to aerosol optical properties in diverse locations in China

Aerosol optical properties play an important role in affecting direct aerosol radiative forcing (DARF). However, DARF estimation is still uncertain due to the complexity of aerosol optical properties. Therefore, in this study, the spatiotemporal distributions of aerosol properties and their effects on DARF in China from 2004 to 2020 are investigated using the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. The results show that the aerosol optical parameters vary greatly and change with seasonal regularity, which is greatly affected by human activities. The control variable method was employed on aerosol optical properties for better estimation of DARF. Single scattering albedo (SSA) has the greatest effect on DARF, followed by aerosol optical depth (AOD) and the asymmetric factor (ASY) among the seven examined stations in China. The average DARF decreases by 4.2 % when the SSA increases by 0.3 % but increases by 34.7 % when the SSA decreases by 3 % in mainland China. When the AOD changes from −60 to +60 %, DARF changes from −54.7 % to +58.4 %. The variation in DARF is between −3 % and +3 % when the ASY varies from −30 % to +30 %. The instability in DARF resulted from the complicated and volatile nature of aerosol optical properties in the region; the aerosol optical properties are greatly affected by the aerosol types and relative humidity. The results of this study have important reference significance for understanding the variation of DARF and formulating pollution prevention and control policies in the region.

Correcting for filter-based aerosol light absorption biases at the Atmospheric Radiation Measurement program's Southern Great Plains site using photoacoustic measurements and machine learning

Abstract. Measurement of light absorption of solar radiation by aerosols is vital for assessing direct aerosol radiative forcing, which affects local and global climate. Low-cost and easy-to-operate filter-based instruments, such as the Particle Soot Absorption Photometer (PSAP), that collect aerosols on a filter and measure light attenuation through the filter are widely used to infer aerosol light absorption. However, filter-based absorption measurements are subject to artifacts that are difficult to quantify. These artifacts are associated with the presence of the filter medium and the complex interactions between the filter fibers and accumulated aerosols. Various correction algorithms have been introduced to correct for the filter-based absorption coefficient measurements toward predicting the particle-phase absorption coefficient (Babs). However, the inability of these algorithms to incorporate into their formulations the complex matrix of influencing parameters such as particle asymmetry parameter, particle size, and particle penetration depth results in prediction of particle-phase absorption coefficients with relatively low accuracy. The analytical forms of corrections also suffer from a lack of universal applicability: different corrections are required for rural and urban sites across the world. In this study, we analyzed and compared 3 months of high-time-resolution ambient aerosol absorption data collected synchronously using a three-wavelength photoacoustic absorption spectrometer (PASS) and PSAP. Both instruments were operated on the same sampling inlet at the Department of Energy's Atmospheric Radiation Measurement program's Southern Great Plains (SGP) user facility in Oklahoma. We implemented the two most commonly used analytical correction algorithms, namely, Virkkula (2010) and the average of Virkkula (2010) and Ogren (2010)–Bond et al. (1999) as well as a random forest regression (RFR) machine learning algorithm to predict Babs values from the PSAP's filter-based measurements. The predicted Babs was compared against the reference Babs measured by the PASS. The RFR algorithm performed the best by yielding the lowest root mean square error of prediction. The algorithm was trained using input datasets from the PSAP (transmission and uncorrected absorption coefficient), a co-located nephelometer (scattering coefficients), and the Aerosol Chemical Speciation Monitor (mass concentration of non-refractory aerosol particles). A revised form of the Virkkula (2010) algorithm suitable for the SGP site has been proposed; however, its performance yields approximately 2-fold errors when compared to the RFR algorithm. To generalize the accuracy and applicability of our proposed RFR algorithm, we trained and tested it on a dataset of laboratory measurements of combustion aerosols. Input variables to the algorithm included the aerosol number size distribution from the Scanning Mobility Particle Sizer, absorption coefficients from the filter-based Tricolor Absorption Photometer, and scattering coefficients from a multiwavelength nephelometer. The RFR algorithm predicted Babs values within 5 % of the reference Babs measured by the multiwavelength PASS during the laboratory experiments. Thus, we show that machine learning approaches offer a promising path to correct for biases in long-term filter-based absorption datasets and accurately quantify their variability and trends needed for robust radiative forcing determination.

Retrieving aerosols single scattering albedo from MODIS reflectances

Single scattering albedo (SSA) is a key parameter to estimate aerosol direct radiative forcing. However, retrieving SSA from satellite observations is still challenging. In this study, a new method optimizing the aerosol optical model based on four basic aerosol components is developed for retrieving SSA from Moderate Resolution Imaging Spectroradiometer (MODIS) data. The new method takes advantage of the relationship between aerosol composition and reflectance at multiple wavelengths to derive SSA, which considers the variation of aerosol species with time and location. A sensitivity study considering the uncertainties from the top of the atmosphere (TOA) apparent reflectance, aerosol optical depth (AOD) at 550 nm and land surface bidirectional reflectance distribution function (BRDF) parameters is performed to test the stability of the proposed method. The results demonstrate the high accuracy and robustness of the new method. The root mean square error (RMSE) is within 0.03 at 470 and 550 nm based on the sensitivity study. The aerosol components used in our method show better representativeness of real aerosol components than that used in the Second Simulation of a Satellite Signal in the Solar Spectrum - Vector (6SV) model. The aerosols SSA values are retrieved from real MODIS observations with the new method and compared with the AERONET SSA product at two polluted AERONET sites in Asia. A better consistency with the correlation coefficient (R) of 0.27– 0.55 and the RMSE within 0.04 at 470 and 550 nm wavelengths between MODIS SSA retrievals and the AERONET SSA product is obtained with the new method compared with that of deep blue (DB) SSA. The new method can help to better understand aerosol radiative forcing regionally and globally.

Columnar aerosol optical depth, water vapor and ozone over a semi-arid urban location of western India: Potential sources and direct radiative effects

Continuous measurements of Aerosol Optical Depth (AOD), columnar water vapor (WV) and Ozone (O3) concentrations were made over a semi-arid urban location Rajkot (22.29°N, 70.74°E, and 142 m AMSL) in the western India. The annual mean values of AOD, WV and O3 were 0.37 ± 0.15, 1.44 ± 0.6 gm cm−2 and 243 ± 18 DU during 2016–2019. AOD showed large seasonal variability mostly dominated by abundant coarse mode aerosols (Angstrom Exponent, AE < 0.65 and AOD ∼ 0.37) during pre-monsoon and monsoon, mainly caused by wind-blown and transported dust from nearby Thar and Kutch desert. Mixture of fine and coarse mode aerosols were abundant (AE = 1.13 ± 0.26) during post-monsoon influenced by both anthropogenic and natural sources. Columnar WV were also higher in pre-monsoon and monsoon seasons. The O3 concentrations is higher during pre-monsoon (247 DU) and lower during monsoon (230 DU). The vertical distribution of aerosol extinction coefficient derived from satellite (CALIPSO) based observations revealed the dominance of dust aerosols (∼74 %) in pre-monsoon; smoke and polluted dust in winter and post monsoon period. The trajectory clusters and concentration weighted trajectory maps also indicated the combined effect of anthropogenic (especially from the northern part of India) and natural aerosol sources during the post-monsoon period. Associated with the higher anthropogenic components during post-monsoon season, aerosol direct radiative forcing depicted surface dimming as high as − 48.7 ± 12.6 Wm−2, resulting in atmospheric forcing of 42.6 ± 12.5 Wm−2.