Abstract. Modern-Era Retrospective analysis for Research and Applications v.2 (MERRA-2), Copernicus Atmosphere Monitoring Service Operational Analysis (CAMS-OA), and a high-resolution regional Weather Research and Forecasting model coupled with chemistry (WRF-Chem) were used to evaluate natural and anthropogenic particulate matter (PM) air pollution in the Middle East (ME) during 2015–2016. Two Moderate Resolution Imaging Spectrometer (MODIS) retrievals – combined product Deep Blue and Deep Target (MODIS-DB&amp;DT) and Multi-Angle Implementation of Atmospheric Correction (MAIAC) – and Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) observations as well as in situ PM measurements for 2016 were used for validation of the WRF-Chem output and both assimilation products. MERRA-2 and CAMS-OA assimilate AOD observations. WRF-Chem is a free-running model, but dust emission in WRF-Chem is tuned to fit AOD and aerosol volume size distributions obtained from AERONET. MERRA-2 was used to construct WRF-Chem initial and boundary conditions both for meteorology and chemical and aerosol species. SO2 emissions in WRF-Chem are based on the novel OMI-HTAP SO2 emission dataset. The correlation with the AERONET AOD is highest for MERRA-2 (0.72–0.91), MAIAC (0.63–0.96), and CAMS-OA (0.65–0.87), followed by MODIS-DB&amp;DT (0.56–0.84) and WRF-Chem (0.43–0.85). However, CAMS-OA has a relatively high positive mean bias with respect to AERONET AOD. The spatial distributions of seasonally averaged AODs from WRF-Chem, assimilation products, and MAIAC are well correlated with MODIS-DB&amp;DT AOD product. MAIAC has the highest correlation (R=0.8), followed by MERRA-2 (R=0.66), CAMS-OA (R=0.65), and WRF-Chem (R=0.61). WRF-Chem, MERRA-2, and MAIAC underestimate and CAMS-OA overestimates MODIS-DB&amp;DT AOD. The simulated and observed PM concentrations might differ by a factor of 2 because it is more challenging for the model and the assimilation products to reproduce PM concentration measured within the city. Although aerosol fields in WRF-Chem and assimilation products are entirely consistent, WRF-Chem is preferable for analysis of regional air quality over the ME due to its higher spatial resolution and better SO2 emissions. The WRF-Chem’s PM background concentrations exceed the World Health Organization (WHO) guidelines over the entire ME. Mineral dust is the major contributor to PM (≈75 %–95 %) compared to other aerosol types. Near and downwind from the SO2 emission sources, nondust aerosols (primarily sulfate) contribute up to 30 % to PM2.5. The contribution of sea salt to PM in coastal regions can reach 5 %. The contributions of organic matter, black carbon and organic carbon to PM over the Middle East are insignificant. In the major cities over the Arabian Peninsula, the 90th percentile of PM10 and PM2.5 (particles with diameters less than 10 and 2.5 µm, respectively) daily mean surface concentrations exceed the corresponding Kingdom of Saudi Arabia air quality limits. The contribution of the nondust component to PM2.5 is <25 %, which limits the emission control effect on air quality. The mitigation of the dust effect on air quality requires the development of environment-based approaches like growing tree belts around the cities and enhancing in-city vegetation cover. The WRF-Chem configuration presented in this study could be a prototype of a future air quality forecast system that warns the population against air pollution hazards.

Abstract. With advances in modeling approaches and the application of satellite and ground-based data in dust-related research, our understanding of the dust cycle has significantly improved in recent decades. However, two aspects of the dust cycle, namely the vertical profiles and diurnal cycles, are not yet adequately understood, mainly due to the sparsity of direct observations. Measurements of backscattering caused by atmospheric aerosols have been ongoing since 2014 at the King Abdullah University of Science and Technology (KAUST) campus using a micro-pulse lidar (MPL) with a high temporal resolution. KAUST is located on the eastern coast of the Red Sea and currently hosts the only operating lidar system in the Arabian Peninsula. We use the data from the MPL together with other collocated observations and high-resolution simulations (with 1.33 km grid spacing) from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to study the following three aspects of dust over the Red Sea coastal plains. Firstly, we compare the model-simulated surface winds, aerosol optical depth (AOD), and aerosol size distributions with observations and evaluate the model performance in representing a typical large-scale dust event over the study site. Secondly, we investigate the vertical profiles of aerosol extinction and concentration in terms of their seasonal and diurnal variability. Thirdly, we explore the interactions between dust aerosols and land/sea breezes, which are the most influential components of the local diurnal circulation in the region. The WRF-Chem model successfully reproduced the diurnal profile of surface wind speed, AOD, and dust size distributions over the study area compared to observations. The model also captured the onset, demise, and height of a large-scale dust event that occurred in 2015, as compared to the lidar data. The vertical profiles of aerosol extinction in different seasons were largely consistent between the MPL data and WRF-Chem simulations along with key observations and reanalyses used in this study. We found a substantial variation in the vertical profile of aerosols in different seasons and between daytime and nighttime, as revealed by the MPL data. The MPL data also identified a prominent dust layer at ∼5–7 km during the nighttime, which likely represents the long-range transported dust brought to the site by the easterly flow from remote inland deserts. The sea breeze circulation was much deeper (∼2 km) than the land breeze circulation (∼1 km), but both breeze systems prominently affected the distribution of dust aerosols over the study site. We observed that sea breezes push the dust aerosols upwards along the western slope of the Sarawat Mountains. These sea breezes eventually collide with the dust-laden northeasterly trade winds coming from nearby inland deserts, thus causing elevated dust maxima at a height of ∼1.5 km above sea level over the mountains. Moreover, the sea and land breezes intensify dust emissions from the coastal region during the daytime and nighttime, respectively. Our study, although focused on a particular region, has broader environmental implications as it highlights how aerosols and dust emissions from the coastal plains can affect the Red Sea climate and marine habitats.

Air-borne dust affects all aspects of human life. The sources of dust have high spatial variation and a better quantification of dust emission helps to identify remediation measures. Orographic and statistical source functions allow a better estimation of dust emission fluxes in coarse-scale modeling, but a high-resolution source function is necessary to represent the highly heterogeneous nature of dust sources at the finer scale. Here we use a newly developed high-resolution (~500 m) source function in Weather Research and Forecasting model, coupled with chemistry (WRF-Chem) to simulate dust emission over the Middle East and North Africa and evaluate our simulated results against observations. Using a 4-km grid spacing, we also simulate the emission and transport of dust originating from the Tigris-Euphrates basin, one of the most important regional dust sources, and quantify the effects of this source on the air quality of the entire Arabian Peninsula. Results show that the use of new source function effectively represents the key dust sources and provides reasonable estimates of dust optical depth and concentrations. We find that the atmospheric dust originating from the Tigris-Euphrates basin alone exceeds the particulate matter 10 air quality standards in several downwind cities. Our results have broader environmental implications and indicate that the mobilization of depleted uranium deposited in Kuwait and Southern Iraq during the Gulf War (1991) could potentially affect the urban centers over the peninsula, albeit in low concentrations. Our results suggest that an integrated and coordinated management of the Tigris-Euphrates basin is necessary to maintain good air quality across the Arabian Peninsula.

The balance between vertical ascent and gravitational settling stabilizes the long-lived stratospheric aerosols at the level of neutral buoyancy within the Junge layer (Junge & Manson, 1961). Integrated over time volcanic contributions to the Junge layer prevail over those of anthropogenic emissions and meteoric processes (

Abstract. Water is the single most important element of life. Rainfall plays an important role in the spatial and temporal distribution of this precious natural resource, and it has a direct impact on agricultural production, daily life activities, and human health. One of the important elements that govern rainfall formation and distribution is atmospheric aerosol, which also affects the Earth's radiation balance and climate. Therefore, understanding how dust compositions and distributions affect the regional rainfall pattern is crucial, particularly in regions with high atmospheric dust loads such as the Middle East. Although aerosol and rainfall research has garnered increasing attention as both an independent and interdisciplinary topic in the last few decades, the details of various direct and indirect pathways by which dust affects rainfall are not yet fully understood. Here, we explored the effects of dust on rainfall formation and distribution as well as the physical mechanisms that govern these phenomena, using high-resolution WRF-Chem simulations (∼ 1.5 km × 1.5 km) configured with an advanced double-moment cloud microphysics scheme coupled with a sectional eight-bin aerosol scheme. Our model-simulated results were realistic, as evaluated from multiple perspectives including vertical profiles of aerosol concentrations, aerosol size distributions, vertical profiles of air temperature, diurnal wind cycles, and spatio-temporal rainfall patterns. Rainfall over the Red Sea coast is mainly caused by warm rain processes, which are typically confined within a height of ∼ 6 km over the Sarawat mountains and exhibit a strong diurnal cycle that peaks in the evening at approximately 18:00 local time under the influence of sea breezes. Numerical experiments indicated that dust could both suppress or enhance rainfall. The effect of dust on rainfall was calculated as total, indirect, and direct effects, based on 10-year August-average daily-accumulated rainfall over the study domain covering the eastern Red Sea coast. For extreme rainfall events (domain-average daily-accumulated rainfall of ≥ 1.33 mm), the net effect of dust on rainfall was positive or enhancement (6.05 %), with the indirect effect (4.54 %) and direct effect (1.51 %) both causing rainfall increase. At a 5 % significance level, the total and indirect effects were statistically significant whereas the direct effect was not. For normal rainfall events (domain-average daily-accumulated rainfall < 1.33 mm), the indirect effect enhanced rainfall (4.76 %) whereas the direct effect suppressed rainfall (−5.78 %), resulting in a negative net suppressing effect (−1.02 %), all of which were statistically significant. We investigated the possible physical mechanisms of the effects and found that the rainfall suppression by dust direct effects was mainly caused by the scattering of solar radiation by dust. The surface cooling induced by dust weakens the sea breeze circulation, which decreases the associated landward moisture transport, ultimately suppressing rainfall. For extreme rainfall events, dust causes net rainfall enhancement through indirect effects as the high dust concentration facilitates raindrops to grow when the water vapor is sufficiently available. Our results have broader scientific and environmental implications. Specifically, although dust is considered a problem from an air quality perspective, our results highlight the important role of dust on sea breeze circulation and associated rainfall over the Red Sea coastal regions. Our results also have implications for cloud seeding and water resource management.

&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; Modern-Era Retrospective analysis for Research and Applications v.2 (MERRA-2), Copernicus Atmosphere Monitoring Service Operational Analysis (CAMS-OA) data assimilation products, and a regional Weather Research and Forecasting model (10&amp;#8201;km resolution) coupled with Chemistry (WRF-Chem) were used to evaluate natural and anthropogenic aerosol air pollution in the ME during 2015&amp;#8211;2016. Satellite and ground-based AOD observations, as well as in-situ Particulate Matter (PM) measurements for 2016, were used for validation.&lt;/p&gt; &lt;p&gt;WRF-Chem code was modified to correct the calculation of dust gravitational settling and aerosol optical properties. The dust emission in WRF-Chem is calibrated to fit Aerosol Optical Depth (AOD) and aerosol volume size distributions obtained from Aerosol Robotic Network (AERONET) observations. MERRA-2 was used to construct WRF-Chem initial and boundary conditions both for meteorology and chemical/aerosol species. SO&lt;sub&gt;2&lt;/sub&gt; emissions in WRF-Chem are based on the novel NASA SO&lt;sub&gt;2&lt;/sub&gt; emission dataset that reveals unaccounted sources over the ME.&lt;/p&gt; &lt;p&gt;Although aerosol fields in WRF-Chem and assimilation products are quite consistent, WRF-Chem, due to its higher spatial resolution and better SO&lt;sub&gt;2&lt;/sub&gt; emissions, is preferable for analysis of regional air-quality over the ME. The WRF-Chem's PM background concentrations exceed the World Health Organization (WHO) guidelines over the entire ME. The major contributor to PM (~&amp;#8201;75&amp;#8211;95&amp;#8201;%) is mineral dust. In the ME urban centers and near oil recovery fields, non-dust aerosols (primarily sulfate) contribute up to 26&amp;#8201;% into PM&lt;sub&gt;2.5&lt;/sub&gt;. The contribution of sea salt into PM can rich up to 5&amp;#8201;%. The contribution of organic matter into PM prevails over black carbon.&lt;/p&gt;

Abstract. In this paper, we rectify inconsistencies that emerge in the Weather Research and Forecasting model with chemistry (WRF-Chem) v3.2 code when using the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol module. These inconsistencies have been reported, and corrections have been implemented in WRF-Chem v4.1.3. Here, we use a WRF-Chem experimental setup configured over the Middle East (ME) to estimate the effects of these inconsistencies. Firstly, we show that the old version underestimates the PM2.5 diagnostic output by 7 % and overestimates PM10 by 5 % in comparison with the corrected one. Secondly, we demonstrate that submicron dust particles' contribution was incorrectly accounted for in the calculation of optical properties. Therefore, aerosol optical depth (AOD) in the old version was 25 %–30 % less than in the corrected one. Thirdly, we show that the gravitational settling procedure, in comparison with the corrected version, caused higher dust column loadings by 4 %–6 %, PM10 surface concentrations by 2 %–4 %, and mass of the gravitationally settled dust by 5 %–10 %. The cumulative effect of the found inconsistencies led to the significantly higher dust content in the atmosphere in comparison with the corrected WRF-Chem version. Our results explain why in many WRF-Chem simulations PM10 concentrations were exaggerated. We present the methodology for calculating diagnostics we used to estimate the impacts of introduced code modifications. We share the developed Merra2BC interpolator, which allows processing Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) output for constructing initial and boundary conditions for chemical species and aerosols.

Abstract. In this paper, we rectify inconsistencies that emerge in the WRF-Chem code when using the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol module. These inconsistencies have been reported and corrections have been implemented in WRF-Chem v4.1.3. Here, we use a WRF-Chem experimental setup configured over the Middle East (ME) to estimate the effects of these inconsistencies. Firstly, we show that the diagnostic output of PM2.5 surface concentration was underestimated by 7% and PM10 was overestimated by 5 %. Secondly, we demonstrate that the contribution of sub-micron dust particles was underestimated in the calculation of optical properties and thus, Aerosol Optical Depth (AOD) was consequently underestimated by 25–30 %. Thirdly, we show that an inconsistency in the process of gravitational settling led to the overestimation of the dust column loadings by 4–6 %, PM10 surface concentrations by 2–4 %, and the rate of dust gravitational settling by 5–10 %. We present a methodology to calculate diagnostics that can be used to estimate the effects of these applied changes. Our corrections also help to explain the overestimation of PM10 surface concentrations encountered in many WRF-Chem simulations. We also share the developed Merra2BC interpolator, which allows constructing initial and boundary conditions for chemical species and aerosols based on MERRA-2 reanalysis. The results of this work can be useful for those who simulate the dust cycle using the WRF-Chem model coupled with the GOCART aerosol module.