Synoptic and remote sensing analysis of dust events in southwestern Iran

2012 ◽  
Vol 64 (2) ◽  
pp. 1625-1638 ◽  
Author(s):  
Azizi Ghasem ◽  
AliAkbar Shamsipour ◽  
Morteza Miri ◽  
Taher Safarrad
Keyword(s):  
Remote Sensing ◽  
Dust Events ◽  
Southwestern Iran

scholarly journals Asian Dust properties investigated by multi-instruments

2019 ◽  
Vol 99 ◽  
pp. 02003
Author(s):  
Janbai Nee
Keyword(s):  
Remote Sensing ◽  
Dust Cloud ◽  
Asian Dust ◽  
Dust Storms ◽  
Dust Particles ◽  
Atmospheric Processes ◽  
Aerosol Sources ◽  
Dust Events ◽  
Aerosol Cloud Interactions ◽  
Lidar Observations

Dust and many types of aerosols are major pollutants significantly affecting the environment in the East Asia. To identify and classify various types of aerosols is a challenge. In Taiwan and nearby areas, Asian Dust mainly arrive in spring with an average of about 5 dust storms each year. They usually come with some other aerosol sources, therefore it is important to identify these aerosols and their properties. In this paper, we report studying of dust aerosols by using several ground-based and remote sensing measurements. The AERONET data is used to find optical properties of aerosols in 2008-2012. The lidar observations can investigate further properties and atmospheric processes for specific dust events, including observations of aerosol-cloud interactions. These combined with model or space observations can help us to understand long range dust particles transported to distant areas and their interaction with weather systems. A real time case of observation of dust-cloud interaction is provided.

scholarly journals Long-Term Variability of Dust Events in Southwestern Iran and Its Relationship with the Drought

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1350
Author(s):  
Nasim Hossein Hamzeh ◽  
Dimitris G. Kaskaoutis ◽  
Alireza Rashki ◽  
Kaveh Mohammadpour
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Distribution ◽  
Dust Storms ◽  
Modis Aod ◽  
Spatio Temporal ◽  
Dust Events ◽  
Southwestern Iran ◽  
Local Dust ◽  
Southwest Iran

Dust storms represent a major environmental challenge in the Middle East. The southwest part of Iran is highly affected by dust events transported from neighboring desert regions, mostly from the Iraqi plains and Saudi Arabia, as well as from local dust storms. This study analyzes the spatio-temporal distribution of dust days at five meteorological stations located in southwestern Iran covering a period of 22 years (from 1997 to 2018). Dust codes (06, 07, 30 to 35) from meteorological observations are analyzed at each station, indicating that 84% of the dust events are not of local origin. The average number of dust days maximizes in June and July (188 and 193, respectively), while the dust activity weakens after August. The dust events exhibit large inter-annual variability, with statistically significant increasing trends in all of five stations. Spatial distributions of the aerosol optical depth (AOD), dust loading, and surface dust concentrations from a moderate resolution imaging spectroradiometer (MODIS) and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) retrievals reveal high dust accumulation over southwest Iran and surrounding regions. Furthermore, the spatial distribution of the (MODIS)-AOD trend (%) over southwest Iran indicates a large spatial heterogeneity during 2000–2018 with trends ranging mostly between −9% and 9% (not statistically significant). 2009 was the most active dust year, followed by 2011 and 2008, due to prolonged drought conditions in the fertile crescent and the enhanced dust emissions in the Iraqi plains during this period. In these years, the AOD was much higher than the 19-year average (2000 to 2018), while July 2009 was the dustiest month with about 25–30 dust days in each station. The years with highest dust activity were associated with less precipitation, negative anomalies of the vegetation health index (VHI) and normalized difference vegetation index (NDVI) over the Iraqi plains and southwest Iran, and favorable meteorological dynamics triggering stronger winds.

scholarly journals Numerical simulation of "An American Haboob"

2013 ◽  
Vol 13 (10) ◽  
pp. 26175-26215 ◽  
Author(s):  
A. Vukovic ◽  
M. Vujadinovic ◽  
G. Pejanovic ◽  
J. Andric ◽  
M. R. Kumjian ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Dust Storm ◽  
Sonoran Desert ◽  
Vegetation Index ◽  
Model Simulation ◽  
Numerical Models ◽  
Horizontal Resolution ◽  
Dust Concentration ◽  
Dust Events

Abstract. A dust storm of fearful proportions hit Phoenix in the early evening hours of 5 July 2011. This storm, an American haboob, was predicted hours in advance because numerical, land-atmosphere modeling, computing power and remote sensing of dust events have improved greatly over the past decade. High resolution numerical models are required for accurate simulation of the small-scales of the haboob process, with high velocity surface winds produced by strong convection and severe downbursts. Dust productive areas in this region consist mainly of agricultural fields, with soil surfaces disturbed by plowing and tracks of land in the high Sonoran desert laid barren by ongoing draught. Model simulation of the 5 July 2011 dust storm uses the coupled atmospheric-dust model NMME-DREAM with 3.5 km horizontal resolution. A mask of the potentially dust productive regions is obtained from the land cover and the Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Model results are compared with radar and other satellite-based images and surface meteorological and PM10 observations. The atmospheric model successfully hindcasted the position of the front in space and time, with about 1 h late arrival in Phoenix. The dust model predicted the rapid uptake of dust and high values of dust concentration in the ensuing storm. South of Phoenix, over the closest source regions (~ 25 km), the model PM10 surface dust concentration reached ~ 2500 μg m−3, but underestimated the values measured by the PM10stations within the city. Model results are also validated by the MODIS aerosol optical depth (AOD), employing deep blue (DB) algorithms for aerosol loadings. Model validation included Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), equipped with the lidar instrument, to disclose the vertical structure of dust aerosols as well as aerosol subtypes. Promising results encourage further research and application of high-resolution modeling and satellite-based remote sensing to warn of approaching severe dust events and reduce risks for safety and health.

scholarly journals Investigation of Aeolian Dust Deposition Rates in Different Climate Zones of Southwestern Iran

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 229
Author(s):  
Mansour Ahmadi Foroushani ◽  
Christian Opp ◽  
Michael Groll
Keyword(s):  
Deposition Rate ◽  
Dust Deposition ◽  
Deposition Rates ◽  
Climate Zones ◽  
Long Run ◽  
Seasonal Deposition ◽  
Dust Events ◽  
Southwestern Iran ◽  
Major Factors ◽  
Modern Era

Dust and atmospheric particles have been described in southwestern Iran primarily in terms of load, concentration and transport. The passive deposition, however, has been discussed inadequately. Therefore, the relationships between different climate zones in southwestern Iran and dust deposition rates were quantified between 2014 and 2017 using both space- (second modern-era retrospective analysis for research and applications, version 2 reanalysis model) and ground-based (eolian ground deposition rate) tools. In addition, the surface meteorological records, including the wind patterns favoring the occurrence of dust events, were examined. A hot desert climate (BWh), hot semi-arid climate (BSh), and temperate hot and dry summer climate (Csa) were identified as the three dominant climate regions in the study area, exhibiting the highest average dust deposition rates. In this study, correlations between the most relevant climate patterns and deposition rate weather parameters were found to describe a region’s deposition rate when a dust event occurred. Based on these results, the BSh and Csa regions were found to be associated with the seasonal cycle of dust events in March, April, and May, revealing that in the long run meteorological conditions were responsible for the varying dust deposition rates. Relatively, precipitation and temperature were the two major factors influencing dust deposition rates, not wind speed. Moreover, the peak seasonal deposition rates in the spring and summer were 8.40 t km−2 month−1, 6.06 t km−2 month−1, and 3.30 t km−2 month−1 for the BWh, BSh, and Csa climate regions, respectively. However, each of these climate types was directly related to the specific quantity of the dust deposition rates. Overall, the highest dust deposition rates were detected over the years studied were 100.80 t km−2 year−1, 79.27 t km−2 year−1, and 39.60 t km−2 year−1 for BWh, BSh, and Csa, respectively.

scholarly journals Numerical simulation of "an American haboob"

2014 ◽  
Vol 14 (7) ◽  
pp. 3211-3230 ◽  
Author(s):  
A. Vukovic ◽  
M. Vujadinovic ◽  
G. Pejanovic ◽  
J. Andric ◽  
M. R. Kumjian ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Dust Storm ◽  
Sonoran Desert ◽  
Mesoscale Model ◽  
Model Simulation ◽  
Numerical Models ◽  
Atmospheric Model ◽  
Dust Concentration ◽  
Dust Events

Abstract. A dust storm of fearful proportions hit Phoenix in the early evening hours of 5 July 2011. This storm, an American haboob, was predicted hours in advance because numerical, land–atmosphere modeling, computing power and remote sensing of dust events have improved greatly over the past decade. High-resolution numerical models are required for accurate simulation of the small scales of the haboob process, with high velocity surface winds produced by strong convection and severe downbursts. Dust productive areas in this region consist mainly of agricultural fields, with soil surfaces disturbed by plowing and tracks of land in the high Sonoran Desert laid barren by ongoing draught. Model simulation of the 5 July 2011 dust storm uses the coupled atmospheric-dust model NMME–DREAM (Non-hydrostatic Mesoscale Model on E grid, Janjic et al., 2001; Dust REgional Atmospheric Model, Nickovic et al., 2001; Pérez et al., 2006) with 4 km horizontal resolution. A mask of the potentially dust productive regions is obtained from the land cover and the normalized difference vegetation index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The scope of this paper is validation of the dust model performance, and not use of the model as a tool to investigate mechanisms related to the storm. Results demonstrate the potential technical capacity and availability of the relevant data to build an operational system for dust storm forecasting as a part of a warning system. Model results are compared with radar and other satellite-based images and surface meteorological and PM10 observations. The atmospheric model successfully hindcasted the position of the front in space and time, with about 1 h late arrival in Phoenix. The dust model predicted the rapid uptake of dust and high values of dust concentration in the ensuing storm. South of Phoenix, over the closest source regions (~25 km), the model PM10 surface dust concentration reached ~2500 μg m−3, but underestimated the values measured by the PM10 stations within the city. Model results are also validated by the MODIS aerosol optical depth (AOD), employing deep blue (DB) algorithms for aerosol loadings. Model validation included Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), equipped with the lidar instrument, to disclose the vertical structure of dust aerosols as well as aerosol subtypes. Promising results encourage further research and application of high-resolution modeling and satellite-based remote sensing to warn of approaching severe dust events and reduce risks for safety and health.

scholarly journals Estimating atmospheric visibility using synergy of MODIS data and ground-based observations

2015 ◽  
Vol 368 ◽  
pp. 46-50
Author(s):  
H. Komeilian ◽  
S. Mohyeddin Bateni ◽  
T. Xu ◽  
J. Nielson
Keyword(s):  
Meteorological Data ◽  
Back Propagation ◽  
Mean Square ◽  
Atmospheric Visibility ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Dust Events ◽  
Southwestern Iran

Abstract. Dust events are intricate climatic processes, which can have adverse effects on human health, safety, and the environment. In this study, two data mining approaches, namely, back-propagation artificial neural network (BP ANN) and supporting vector regression (SVR), were used to estimate atmospheric visibility through the synergistic use of Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1B (L1B) data and ground-based observations at fourteen stations in the province of Khuzestan (southwestern Iran), during 2009–2010. Reflectance and brightness temperature in different bands (from MODIS) along with in situ meteorological data were input to the models to estimate atmospheric visibility. The results show that both models can accurately estimate atmospheric visibility. The visibility estimates from the BP ANN network had a root-mean-square error (RMSE) and Pearson’s correlation coefficient (R) of 0.67 and 0.69, respectively. The corresponding RMSE and R from the SVR model were 0.59 and 0.71, implying that the SVR approach outperforms the BP ANN.

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