Changes of Permanent Lake Surfaces, and Their Consequences for Dust Aerosols and Air Quality: The Hamoun Lakes of the Sistan Area, Iran

Rashki, Alireza; Kaskaoutis, Dimitris G.; Rautenbach, C.J.deW.; Eriksson, P.G.

doi:10.5772/48776

Cited by 5 publications

(2 citation statements)

References 85 publications

(100 reference statements)

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“…9a), show a clear annual cycle with peak winds in June correlated to low visibility. Conversely, lower average winter wind speeds result in better visibility conditions (see Rashki et al 2012). While summer conditions may be optimal for frequent and intense dust storms, interannual variability modulates the peak storm months.…”

Section: ) Synoptic Mappingmentioning

confidence: 99%

XMET—An Unattended Meteorological Sensing System for Austere Environments

Rogowski

Otero

Hazard

et al. 2021

Journal of Atmospheric and Oceanic Technology

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Accurate surface meteorological (MET) observations reported reliably and in near-real time remain a critical component of on-scene environmental observation systems. Presented is a system developed by Scripps Institution of Oceanography that allows for rapid, global deployment of ground-based weather observations to support both timely decision making and collection of high-quality weather time series for science or military applications in austere environments. Named the eXpeditionary METeorological (XMET), these weather stations have been deployed in extreme conditions devoid of infrastructure ranging from tropical, polar, maritime, and desert environments where near continuous observations were reported. To date, over 1 million weather observations have been collected during 225 deployments around the world with a data report success rate of 99.5%. XMET had its genesis during Operation Iraqi Freedom (OIF), when the United States Marine Corps 3rd Marine Aircraft Wing identified an immediate capability gap in environmental monitoring of their operation area due to high spatiotemporal variability of dust storms in the region. To address the sensing gap, XMET was developed to be a portable, expendable, ruggedized, self-contained, bi-directional, weather observation station that can be quickly deployed anywhere in the world to autonomously sample and report aviation weather observations. This paper provides an overview of the XMETs design, reliability in different environments, and examples of unique meteorological events that highlight both the unit’s reliability and ability to provide quality time series. The overview shows expeditionary MET sensing systems, such as the XMET, are able to provide long-term continuous observational records in remote and austere locations essential for regional spatiotemporal MET characterization.

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Section: ) Synoptic Mappingmentioning

confidence: 99%

XMET—An Unattended Meteorological Sensing System for Austere Environments

Rogowski

Otero

Hazard

et al. 2021

Journal of Atmospheric and Oceanic Technology

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“…Assessments of the effects of aerosols on the climate and environment still feature large uncertainties, and a better understanding of the spatiotemporal variation in these effects is needed [2]. Dust particles can range in size from a few nanometers to 100 microns [3]. They can rise to the top of the troposphere and for a long distance laterally (4000 km from the source of emission) and may remain in the atmosphere for several weeks due to their small size [4,5].…”

Section: Introductionmentioning

confidence: 99%

Regional Analysis of Dust Day Duration in Central Iran

et al. 2022

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The duration of dust days (DDD) is one of the most important parameters that may worsen the effects of the presence of dust in the affected areas. Persistent pollution over consecutive dusty days can have particularly negative effects on the human respiratory system. The present analysis was conducted in Central Iran, where the phenomenon of dust is one of the most important problems. In this study, using dust codes recorded at 35 synoptic stations, the homogeneity of DDD across the region was investigated using the L-moments method. Then, characteristics of DDD over the period 1999–2018 were calculated. The results showed that the region is statistically homogeneous. Furthermore, Zabol and Zahdan are the stations worst affected, with the longest durations of 22 and 21 days in 2014. Additionally, the values of DDD with return periods of 5, 10, 25, and 50 years were calculated using fitted statistical distributions and kriging and mapped. Finally, using the K nearest neighbor method the most important factor affecting DDD of the spatial characteristics, including longitude, latitude, elevation, average daily temperature (tm), dew point (td), wind altitude (u), maximum wind speed (ffmax), and direction of the fastest wind (ddmax), was determined. It was found that the southeastern parts of the study area are affected by the longest dust storm duration in all return periods; over longer return periods, long dust storms are also found in the central parts, especially the central desert of Iran. Therefore, these areas should be given priority in fighting and controlling wind erosion. Furthermore, the results showed that the maximum wind speed has the greatest effect on DDD.

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Numerical simulation of extreme dust storms in east of Iran by the WRF-Chem model

et al. 2019

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Iran, located in the desert belt, is characterized by frequently increasing sand and dust storms, especially in the eastern and southern areas and creating adverse environmental effects. Efficient management of these devastating events requires an understanding of their features. One way to understand the dust phenomenon is to simulate and predict. The general purpose of the article is to simulate severe storms in the southeast of the country (120-day-old winds) due to the weather conditions of the region and the display of their source and range inside Iran. Aim of this study: Weather Research and Forecasting-Chemistry coupled model (WRF-Chem.3.6.1) is used to simulate, forecast, and design an alert system for sand and dust storm events (east of Iran). Dust concentration data were collected by Environmental Protection Organization, wind speed and direction data were gathered from the Meteorological Organization, MODIS images, and HYSPLIT model forecast was also used to investigate the path of storms and more accurately forecast and time alerting. Results showed that the main dust emission source in Sistan is the dry bed of the Hamoon wetland. Also during the storms that investigated in this study, transport of dust clouds were observed in the southern part of Iran up to Oman sea because of converging currents (north-south winds in the eastern part of Iran, especially in spring and summer) that create strong winds in lower levels of the atmosphere. The WRF-Chem model had reasonable estimations related to spatial and temporal scales in the study area. Using the global forecasted data as model input data, it was expected to observe bias in concentration estimation versus reality. The model was run for 10 and 30 km spatial resolutions, and results revealed storm formation in Sistan was affected by local geographical properties especially topography features. Based on the results obtained and the experience gained, it can be concluded that most dust storms in the Sistan region began in the late spring and will continue until early autumn season. KeywordsNumerical simulation • Sand and dust storms • Sensor MODIS • WRF-Chem • Sistan climate Javad Bodagh Jamali: Deceased.

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Changes of Permanent Lake Surfaces, and Their Consequences for Dust Aerosols and Air Quality: The Hamoun Lakes of the Sistan Area, Iran

Cited by 5 publications

References 85 publications

XMET—An Unattended Meteorological Sensing System for Austere Environments

XMET—An Unattended Meteorological Sensing System for Austere Environments

Regional Analysis of Dust Day Duration in Central Iran

Numerical simulation of extreme dust storms in east of Iran by the WRF-Chem model

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