Dust Regional Atmospheric Model Research Articles

Effect of major dust storm on optical, physical, and radiative properties of aerosols over coastal and urban environments in Western India

The present study deals with a major summertime dust storm event that occurred over the Arabian Desert, Saudi Arabia (SA), and the United Arab Emirates (UAE) and spread to Pakistan, the Arabian Sea, and Western India (in particular over Alibaug and Pune), using multi-satellite- and ground-based measurements. Analysis of the aerosol parameters retrieved over Alibaug and Pune from the ground-based MICROTOPS-II Sunphotometer, seven Aeronet Robotic Network (AERONET) stations, including Pune, and satellite (Moderate-resolution Imaging Spectroradiometer (MODIS)) and Ozone Monitoring Instrument ((OMI-Aura)) measurements shows significant changes on dusty days as compared with non-dusty days prior to and after the dust storm event. A large increase in aerosol optical depths (AODs) and decrease in Angstrom exponent (AE, α440-870 nm), showing the presence of a larger fraction of coarser particles comparable to those of other intense dust outbreak episodes worldwide, have been found at all these sites during the dust storm event. Higher observed AODs are considered to be the combined effect of desert dust and burning biomass/biofuel-induced aerosols. AERONET-retrieved mean aerosol volume size distributions (AVSDs) on non-dusty and dusty days are bimodal in nature at the stations of Pune, Kanpur, Jaipur, Karachi, and Lahore, while at the stations of KAUST_Campus (SA) and Mezaira (UAE), AVSDs are monomodal. This indicates that at the first five stations, the aerosol system is a complex mixture of fine- and coarse-mode aerosols with coarse mode exerting a strong influence on the system. Dust-induced turbid conditions triggered significant extinction of 30–40%, in shortwave (SW) global solar irradiance, resulting in an increase of 57% and 74% in aerosol direct radiative forcing (ADRF) at Alibaug and Pune, respectively, causing perturbation in the radiation budget. The space-borne Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-retrieved aerosol vertical profiles reveal the presence of polluted dust (a mixture of fine- and coarse-mode aerosols), corroborating well with the aerosol behaviour captured by the MICROTOPS/AERONET measurements and MODIS retrievals over the study areas. The Dust Regional Atmospheric Model (BSC-DREAM8b) predictions are also found to be consistent with satellite retrievals, implying the ability of the model to monitor dust transport over the study region.

Assessment of aerosol's mass concentrations from measured linear particle depolarization ratio (vertically resolved) and simulations

Abstract. Multi-wavelength depolarization Raman lidar measurements from Magurele, Romania are used in this study along with simulated mass-extinction efficiencies to calculate the mass concentration profiles of different atmospheric components, due to their different depolarization contribution to the 532 nm backscatter coefficient. Linear particle depolarization ratio (δpart) was computed using the relative amplification factor and the system-dependent molecular depolarization. The low depolarizing component was considered as urban/smoke, with a mean δpart of 3%, while for the high depolarizing component (mineral dust) a mean δpart of 35% was assumed. For this study 11 months of lidar measurements were analysed. Two study cases are presented in details: one for a typical Saharan dust aerosol intrusion, 10 June 2012 and one for 12 July 2012 when a lofted layer consisting of biomass burning smoke extended from 3 to 4.5 km height. Optical Properties of Aerosols and Clouds software package (OPAC) classification and conversion factors were used to calculate mass concentrations. We found that calibrated depolarization measurements are critical in distinguishing between smoke-reach aerosol during the winter and dust-reach aerosol during the summer, as well as between elevated aerosol layers having different origins. Good agreement was found between lidar retrievals and DREAM- Dust REgional Atmospheric Model forecasts in cases of Saharan dust. Our method was also compared against LIRIC (The Lidar/Radiometer Inversion Code) and very small differences were observed.

Application of a Synergetic Lidar and Sunphotometer Algorithm for the Characterization of a Dust Event Over Athens, Greece

We present first retrievals of the Lidar-Radiometer Inversion Code (LIRIC), applied on combined lidar and sunphotometer data during a Saharan dust episode over Athens, Greece, on July 20, 2011. A full lidar dataset in terms of backscatter signals at 355, 532 and 1064 nm, as well as depolarization at 532 nm was acquired from the European Aerosol Research Network (EARLINET) station of Athens and combined with Aerosol Robotic Network (AERONET) data, in order to retrieve the concentration and extinction coefficient profiles of dust. The lidar measurements showed a free tropospheric layer between 1-5 km above Athens, with low Angstrom exponent of ~0.5 and high particle depolarization ratio, ~25-30%, both values characteristic of dust particles. The application of LIRIC revealed high concentration profiles of non-spherical coarse particles in the layer, in the range of 0.04-0.07 ppb and a smaller fine particle component with concentrations of ~0.01 ppb. The extinction coefficients at 532 nm ranged between 50 and 90 Mm-1 for coarse non-spherical particles and between 25 and 50Mm-1 for fine particles. The retrievals were compared with modeled dust concentration and extinction coefficient profiles from the Dust Regional Atmospheric Modeling (BSC-DREAM8b), showing good agreement, especially for the coarse mode

Application of a synergetic lidar and sunphotometer algorithm for the characterization of a dust event over Athens, Greece

We present first retrievals of the Lidar-Radiometer Inversion Code (LIRIC), applied on combined lidar and sunphotometer data during a Saharan dust episode over Athens, Greece, on July 20, 2011. A full lidar dataset in terms of backscatter signals at 355, 532 and 1064 nm, as well as depolarization at 532 nm was acquired from the European Aerosol Research Network (EARLINET) station of Athens and combined with Aerosol Robotic Network (AERONET) data, in order to retrieve the concentration and extinction coefficient profiles of dust. The lidar measurements showed a free tropospheric layer between 1-5 km above Athens, with low Angstrom exponent of ~0.5 and high particle depolarization ratio, ~25-30%, both values characteristic of dust particles. The application of LIRIC revealed high concentration profiles of non-spherical coarse particles in the layer, in the range of 0.04-0.07 ppb and a smaller fine particle component with concentrations of ~0.01 ppb. The extinction coefficients at 532 nm ranged between 50 and 90 Mm-1 for coarse non-spherical particles and between 25 and 50Mm-1 for fine particles. The retrievals were compared with modeled dust concentration and extinction coefficient profiles from the Dust Regional Atmospheric Modeling (BSC-DREAM8b), showing good agreement, especially for the coarse mode

Analysis of long-range transport of aerosols for Portugal using 3D chemical transport model and satellite measurements

The objective of this work is to assess the contribution of long-range transport of mineral dust from North Africa to the air pollution levels in Portugal based on a combination of a modelling approach and satellite observations. The Comprehensive Air Quality Model (CAMx) was applied together with the updated Dust REgional Atmospheric Model (BSC-DREAM8b) to characterise anthropogenic and natural sources of primary aerosols as well as secondary aerosols formation. The modelling results, after their validation and bias removing process, have been used in combination with aerosol measurements provided by Ozone Monitoring Instrument (OMI), using OMAERUV Level-2 v003 product, aiming to better understand the advantages and shortcomings of both, satellite and modelling aerosol data.The data analysis is presented for Portugal for July 2006 focusing on aerosol optical depth (AOD) at 500 nm and aerosol type. Based on the modelling results, the importance of the long-range transport of mineral dust was demonstrated for the simulation days, achieving a 60% contribution to AOD levels. The mineral dust is affecting atmospheric layers up to 6 km but peak concentrations are presented at layers below 2 km. The model predicts a complex mixture of different types of aerosol for the pixels classified by OMI as “mineral dust” and “sulphates”. Although a good agreement between the model outputs and OMI observations has been found in terms of the spatial pattern and AOD correlation is about 0.48 for mineral dust, several problems were identified. The model is systematically underestimating the aerosol concentration at near ground level in comparison with the air quality monitoring stations, while OMI is in general overestimating AOD for the analysed period based on the comparison with AERONET data. Additionally, misclassification of mineral dust for some geographical locations and discontinuity in AOD values along the coastal line at water/land interface in the OMI data are discussed.

Saharan dust and heterogeneous ice formation: Eleven years of cloud observations at a central European EARLINET site

More than 2300 observed cloud layers were analyzed to investigate the impact of aged Saharan dust on heterogeneous ice formation. The observations were performed with a polarization/Raman lidar at the European Aerosol Research Lidar Network site of Leipzig, Germany (51.3°N, 12.4°E) from February 1997 to June 2008. The statistical analysis is based on lidar‐derived information on cloud phase (liquid water, mixed phase, ice cloud) and cloud top height, cloud top temperature, and vertical profiles of dust mass concentration calculated with the Dust Regional Atmospheric Modeling system. Compared to dust‐free air masses, a significantly higher amount of ice‐containing clouds (25%–30% more) was observed for cloud top temperatures from −10°C to −20°C in air masses that contained mineral dust. The midlatitude lidar study is compared with our SAMUM lidar study of tropical stratiform clouds at Cape Verde in the winter of 2008. The comparison reveals that heterogeneous ice formation is much stronger over central Europe and starts at higher temperatures than over the tropical station. Possible reasons for the large difference are discussed.

The combined use of satellite data, air-mass trajectories and model applications for monitoring dust transport over Athens, Greece

This study focused on Saharan dust (SD) events over Athens, Greece, based on measurements of the daily aerosol optical depth at 550 nm (AOD550) and the fine-mode fraction (FM) derived from Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations. Back-trajectories ending at Athens at altitudes of 500, 1000 and 4000 m were calculated by means of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Several criteria were taken into account to identify the SD events. According to these criteria and the altitudes of the air masses, three dust transport mechanisms were identified: (1) vertical transport (VT), including the whole atmospheric column, (2) upper atmosphere transport (UAT), above the atmospheric boundary layer, and (3) boundary layer transport (BLT), only within the lower atmospheric levels. The Aerosol Index (AI) derived from Total Ozone Mapping Spectrometer (TOMS) data was found to be adequate for characterization of the dust load over Athens, while higher values of the AI were found in cases where the dust was transported in the upper atmosphere. The predictions of the Dust Regional Atmospheric Model (DREAM) were consistent with the satellite observations and back trajectories, indicating the suitability of the model for monitoring dust transport over the Mediterranean. The analysis presents three case studies, one for each transport mechanism, where the aerosol field deduced from satellites and models is presented over the Eastern Mediterranean. In conclusion, this study shows that the combination of remote sensing measurements and back-trajectory calculations constitutes a powerful tool for the identification of SD events over Athens, while modelling can monitor the spread of the dust.

An Assessment of the Efficiency of Dust Regional Modelling to Predict Saharan Dust Transport Episodes

Aerosol levels at Mediterranean Basin are significantly affected by desert dust that is eroded in North Africa and is transported northwards. This study aims to assess the performance of the Dust REgional Atmospheric Model (BSC‐DREAM8b) in the prediction of dust outbreaks near the surface in Eastern Mediterranean. For this purpose, model PM10 predictions covering a 7‐year period and PM10 observations at five surface monitoring sites in Greece are used. A quantitative criterion is set to select the significant dust outbreaks defined as those when the predicted PM10 surface concentration exceeds 12 μg/m3. The analysis reveals that significant dust transport is usually observed for 1–3 consecutive days. Dust outbreak seasons are spring and summer, while some events are also forecasted in autumn. The seasonal variability of dust transport events is different at Finokalia, where the majority of events are observed in spring and winter. Dust contributes by 19–25% to the near surface observed PM10 levels, which can be increased to more than 50 μg/m3 during dust outbreaks, inducing violations of the air quality standards. Dust regional modeling can be regarded as a useful tool for air quality managers when assessing compliance with air quality limit values.

High-performance computing for the simulation of dust storms

Dust storm is a primary natural hazard that impact human activities. Previous work has simulated dust events with Eta model. This paper reports our effort to migrate a Dust Regional Atmospheric Model (DREAM) to the Nonhydrostatic Mesoscale Model (NMM), core of the Weather Research and Forecasting (WRF) system’s (WRF–NMM)-based dust model. The process is as follows: (1) the DREAM model is modified to fit into a high-performance computing environment by parallelizing the dust model based on the WRF–NMM weather forecasting model. We couple a dust module to the WRF–NMM model and parallelize the serial program using Message Passing Interface (MPI). (2) The performance of the parallel dust simulation model is tested using the southwestern United States as the experiment area and a dust event during 7 January 2008 for the case study. (3) The new dust model based on WRF–NMM is implemented and tested on a Linux cluster with 28 computing nodes and over 200 CPU cores. The new model can leverage high-performance computing clusters to reduce the execution time while at the same time enhancing the simulation resolution. As tested, when simulating a 72 h period, the WRF–NMM dust model took 1.8 h when using a resolution of 1/9 of a degree grid space, when 36 CPU cores were used for high-performance computing. The results show that the parallelized version of the dust simulation model can get a maximum speedup about 13.3. We also built a transformation component to export the model output to geographic information system (GIS) software through a Web Map Service (WMS).

The potential of the synergistic use of passive and active remote sensing measurements for the validation of a regional dust model

Abstract. A long-lasting Saharan dust event affected Europe on 18–23 May 2008. Dust was present in the free troposphere over Greece, in height ranges between the surface and approximately 4–5 km above sea level. The event was monitored by ground-based CIMEL sunphotometric and multi-wavelength combined backscatter/Raman lidar measurements over Athens, Greece. The dust event had the maximum of its intensity on 20 May. Three-dimensional dust spatial distribution over Greece on that day is presented through satellite synergy of passive and active remote sensing using MODIS and CALIPSO data, respectively. For the period under study, the ground-based measurements are used to characterize the dust event and evaluate the latest version of the BSC Dust Regional Atmospheric Modeling (BSC-DREAM) system. Comparisons of modeled and measured aerosol optical depths over Athens show that the Saharan dust outbreak is fairly well captured by BSC-DREAM simulations. Evaluation of BSC-DREAM using Raman lidar measurements on 20 May shows that the model consistently reproduces the dust vertical distribution over Athens.

Risques de fièvre catarrhale ovine liés à la propagation éolienne

The introduction of bluetongue virus (BTV) infected Culicoides carried by the wind is an important way of disease introduction into BTV-free areas. The aim of this study was to estimate the amount of Culicoides that could potentially be carried by the wind into Europe from disease-prevalent surrounding countries. Firstly, we focused on the estimation of the potential introduc­tion of Culicoides by using a climatic model called the Dust Regional Atmospheric Model (DREAM). It is used to estimate dust particle transportation and final deposition in Europe by measuring the surface concentration (μg/m3/day). We hypoth­esised that there is a significant association between dust intro­duction into Europe and Culicoides introduction by wind. Data of the surface concentration per day were collected for each of the centroids of a 0.5x0.5 degree grid, and a temporal and spa­tial analysis was performed. Preliminary results of the spatial and temporal variation of dust deposition were presented for Spain. The correlation between outbreak occurrence in North Africa, dust introduction and outbreak occurrence in Spain was also evaluated. Preliminary results revealed that Culicoides introduc­tion was most likely to occur in the south-eastern part of Spain and the Canary Islands, and sporadically in the Balearic Islands. The period from April to July was found to be at highest risk for Culicoides introduction. The combination of outbreak occur­rence in Algeria or Tunisia and dust entrance was found to be correlated with the risk of outbreak occurrence in the Balearic Islands. Similarly, the combination of outbreaks in Morocco and dust introduction was correlated with the risk of outbreak occur­rence in Andalucía. Results of this study will be useful to help European countries to develop policies and to allocate resources in areas and periods of time at highest risk for BTV introduction, helping ultimately to mitigate the consequences of BTV incur­sion into the countries.

Public-health applications in remote sensing

Remote sensing of the environment is critical to warn of imminent, life-threatening dust storms and to reduce risk of exposure to desert dust and hitchhiking bacteria, molds, heavy metals, and other human-health concerns. Desert dust affects cardiovascular and respiratory illness. Respirable particulates result in health-care costs exceeding $11.5 billion annually, with an additional $4.6 billion for lost productivity.1 As part of the NASA-sponsored Public Health Applications in Remote Sensing (PHAiRS) project, data from NASA’s Terra satellite are assimilated into a numerical-dynamical model of dust generation and entrainment, DREAM (Dust Regional Atmospheric Model). Originally developed for the Mediterranean region2 and modified in PHAiRS for the southwestern United States,3 DREAM is driven by operational weather-forecast models of the US National Weather Service (the Nonhydrostatic Mesoscale Model, NMM, and the operational model it replaces, eta). The DREAM system simulates and predicts—up to three days in advance—the onset of dust storms and the 3D size-concentration characteristics of the resulting airborne-dust clouds. Current barren-ground input to the model consists of MOD12 classification (an International Geosphere-Biosphere Programme ecosystem descriptor of land-cover type and dynamics) condensed to a two-class product: bare ground=1 and all other classes=0. Using Moderate Resolution Imaging Spectroradiometer (MODIS) products to replace the bare-ground class from the Olson World Ecosystem Land Cover map—the model’s original design parameter (see Figure 1)—improved DREAM’s performance significantly (see Figure 2).4, 5 Working with New Mexico’s Environmental Public Health Tracking System, we developed a Web-based client server (see Figure 3) to assist asthma andmyocardial-infarction surveillance Figure 1. (left) Olson World Ecosystem ‘barren’ category. (right) MOD12 (land-cover type and dynamics)-classified ‘barren’ category.

Application of aerosol speciation data as an in situ dust proxy for validation of the Dust Regional Atmospheric Model (DREAM)

The Dust REgional Atmospheric Model (DREAM) predicts concentrations of mineral dust aerosols in time and space, but validation is challenging with current in situ particulate matter (PM) concentration measurements. Measured levels of ambient PM often contain anthropogenic components as well as windblown mineral dust. In this study, two approaches to model validation were performed with data from preexisting air quality monitoring networks: using hourly concentrations of total PM with aerodynamic diameter less than 2.5 μm (PM 2.5); and using a daily averaged speciation-derived soil component. Validation analyses were performed for point locations within the cities of El Paso (TX), Austin (TX), Phoenix (AZ), Salt Lake City (UT) and Bakersfield (CA) for most of 2006. Hourly modeled PM 2.5 did not validate at all with hourly observations among the sites (combined R < 0.00, N = 24,302 hourly values). Aerosol chemical speciation data distinguished between mineral (soil) dust from anthropogenic ambient PM. As expected, statistically significant improvements in correlation among all stations (combined R = 0.16, N = 343 daily values) were found when the soil component alone was used to validate DREAM. The validation biases that result from anthropogenic aerosols were also reduced using the soil component. This is seen in the reduction of the root mean square error between hourly in situ versus hourly modeled (RMSE hourly = 18.6 μg m −3) and 24-h in situ speciation values versus daily averaged observed (RMSE soil = 12.0 μg m −3). However, the lack of a total reduction in RMSE indicates there is still room for improvement in the model. While the soil component is the theoretical proxy of choice for a dust transport model, the current sparse and infrequent sampling is not ideal for routine hourly air quality forecast validation.

Origin of observed high 7Be and mineral dust concentrations in ambient air on the Island of Tenerife

Temporal series of atmospheric PM1 and PM10 matter (particulate matter with aerodynamic diameter below 1 and 10μm) as well as 40K and 7Be concentrations in aerosol filters, collected in the Island of Tenerife from 30 June 2003 until 17 January 2005, were analysed here to: (1) study the variability of 7Be in the atmosphere at this site and (2) to identify the origin of high 7Be events and check their possible connection with the transport of Saharan dust to Tenerife.A complex relationship was observed between PM10 matter and 7Be concentrations in the measured aerosol filters. Due to this fact, the analysed atmospheric events had to be grouped in: (I) high 7Be and high PM10 matter events; (II) low 7Be and high PM10 matter events; and (III) high 7Be and low PM10 matter events. The low 7Be and low PM10 matter events were not considered in this study. The results indicated that four times during the study period significant concentrations of 7Be were observed with the arrival of suspended material from the African continent. An enhanced scavenging effect of the 7Be available in the aerosol transport zone by the re-suspended material is believed to have caused these detected increments in local atmospheric concentrations. Seventy-two hours forecasts created with the Dust Regional Atmospheric model (DREAM model) for these events, also, seem to support this hypothesis.

Forecast errors in dust vertical distributions over Rome (Italy): Multiple particle size representation and cloud contributions

In this study, forecast errors in dust vertical distributions were analyzed. This was carried out by using quantitative comparisons between dust vertical profiles retrieved from lidar measurements over Rome, Italy, performed from 2001 to 2003, and those predicted by models. Three models were used: the four‐particle‐size Dust Regional Atmospheric Model (DREAM), the older one‐particle‐size version of the SKIRON model from the University of Athens (UOA), and the pre‐2006 one‐particle‐size Tel Aviv University (TAU) model. SKIRON and DREAM are initialized on a daily basis using the dust concentration from the previous forecast cycle, while the TAU model initialization is based on the Total Ozone Mapping Spectrometer aerosol index (TOMS AI). The quantitative comparison shows that (1) the use of four‐particle‐size bins in the dust modeling instead of only one‐particle‐size bins improves dust forecasts; (2) cloud presence could contribute to noticeable dust forecast errors in SKIRON and DREAM; and (3) as far as the TAU model is concerned, its forecast errors were mainly caused by technical problems with TOMS measurements from the Earth Probe satellite. As a result, dust forecast errors in the TAU model could be significant even under cloudless conditions. The DREAM versus lidar quantitative comparisons at different altitudes show that the model predictions are more accurate in the middle part of dust layers than in the top and bottom parts of dust layers.

A long Saharan dust event over the western Mediterranean: Lidar, Sun photometer observations, and regional dust modeling

A long Saharan dust event affected the western Mediterranean in the period 12–28 June 2002. Dust was present mainly between 1‐ and 5‐km height affecting most parts of the Iberian Peninsula and reaching western/central Europe. Intensive backscatter lidar observations over Barcelona (Spain) and Sun photometer data from two stations (El Arenosillo, Spain, and Avignon, France) are used to evaluate different configurations the Dust Regional Atmospheric Modeling (DREAM) system. DREAM currently operates dust forecasts over the Mediterranean region (http://www.bsc.es/projects/earthscience/DREAM/) considering four particle size bins while only the first two are relevant for long‐range transport analysis since their life time is larger than 12 hours. A more detailed bin method is implemented, and two different dust distributions at sources are compared to the operational version. Evaluations are performed at two wavelengths (532 and 1064 nm). The dust horizontal and vertical structure simulated by DREAM shows very good qualitative agreement when compared to SeaWIFS satellite images and lidar height‐time displays over Barcelona. When evaluating the modeled aerosol optical depth (AOD) against Sun photometer data, significant improvements are achieved with the use of the new detailed bin method. In general, the model underpredicts the AOD for increasing Ångström exponents because of the influence of anthropogenic pollution in the boundary layer. In fact, the modeled AOD is highly anticorrelated with the observed Ångström exponents. Avignon shows higher influence of small anthropogenic aerosols which explains the better results of the model at the wavelength of 1064 nm over this location. The uncertainties of backscatter lidar inversions (20–30%) are in the same order of magnitude as the differences between the model experiments. Better model results are obtained when comparing to lidar because most of the anthropogenic effect is removed.