Dust Events in the Western Parts of Iran and the Relationship with Drought Expansion over the Dust-Source Areas in Iraq and Syria

The most famous deserts exist in subtropical regions which is the direct outcome of insufficient precipitation and high temperatures. The Middle East deserts are subjected often to dust, which reduces horizontal visibility to 5 km, and sometimes even to less than 100 m. The severe and prolong drought recently afflicting the west Asia region has been suggested to be instrumental in producing an increased output of dust into the atmosphere from the region. Regarding the increasing of dust events over the west of Iran with the external origin in the recent decade (from 2000 to present), so the main dust-source areas over Iraq and Syria have been detected using the dust-source map of the southwest of Asia, satellite images and soil type maps. We considered the relationship between the increasing of dust events in the western of Iran and drought expansion over the main dust-production areas during the recent decade. Dust frequency data series, and drought variables which include the VHI (vegetation health index), precipitation and temperature data series in long-term and monthly scales have been monitored and compared. And then we used the correlation analysis that indicated the significant proximity between the dust events and droughts/dryness in a yearly scale and also during the warm season (May to Aug). Meantime the derived results from the T-student test for the aforementioned data series confirm the fact that the droughts are parallel to the increasing of dust events from 1996 to 2011 (especially in the recent decade). We found that the recent droughts in the external dust source areas had the remarkable potential to increase the dust events in the west of Iran.

Validation and Coupling of the SWAN Wave Prediction Model by WRF for the Persian Gulf

Generation of waves is affected by forces that exerted constantly in the oceans. The most obvious reason for the appearance of surface-waves is a process of interaction between atmosphere and sea surface that results in wind generation. Wave predictions are usually issued for a maximum of a few days for using in different fields such as shipping, fishing, oil industry, tourism, and to increase the safety of seafarers and beach habitants, maintaining economic assets and optimal utilization of natural resources. In this study, SWAN model has been run for this research over the Oman sea and the Persian Gulf. For implementation of SWAN, another dynamic model with prediction ability of 99-hours also has been used. In this example, wind field is obtained from the outputs of the WRF model converted to the required format for SWAN model. The computational network of SWAN model has been set to spatial grid points of 6 minutes with 1-hour temporal scale. Standard validation ways, including experimental verification, Multiplicative Bias, Mean Error and Root Mean Square Error are used in this study by comparing together for evaluation of accuracy of the model outputs. The results show that the prediction of wave heights by the model for 9 to 24-hour prediction could be the most accurate.

Evaluation of Spatial-Temporal Variability of Drought Events in Iran Using Palmer Drought Severity Index and Its Principal Factors (through 1951-2005)

Intensity and variability of droughts are considered inIranduring the period 1951 to 2005. Four variables are considered: the Palmer Drought Severity Index (PDSI), the soil moisture, the temperature and the precipitation (products used for the analysis are downloaded from the NCAR website). Link with the climatic indexLa Ninais also considered (NOAA downloadable products is used). The analysis is based on basic statistical approaches (correlation, linear regressions and Principal Component Analysis). The analysis shows that PDSI is highly correlated to the soil moisture and poorly correlated to the other variables—although the temperature in the warm season shows high correlation to the PDSI and that a severe drought was experienced during 1999-2002 inthe country.

Evaluation of cloud seeding project in Yazd Province of Iran using historical regression method(case study:Yazd 1 cloud seeding project,1999)

In this research, the result of the cloud seeding over Yazd province during three months of February, March and April in 1999 has been evaluated using the historical regression method. Hereupon, the rain-gages in Yazd province as the target stations and the rain-gages of the neighboring provinces as the control stations have been selected. The rainfall averages for the three aforementioned months through 25 years (1973-1997) in all control and target stations have been calculated. In the next step, the correlations between the rainfalls of control and target stations have been estimated about 75%, which indicates a good consistency in order to use the historical regression. Then, through the obtained liner correlation equation between the control and target stations the precipitation amount for February, March and April in 1999, over the target region (Yazd province) was estimated about 27.57 mm, whiles the observed amount was 34.23 mm. In fact the precipitation increasing around 19.5% over Yazd province confirmed the success of this cloud seeding project.

Application of the dust simulation models in the Middle East, and dust-dispersion toward the western/southwestern Iran (case study: 22-26 June 2010)

Many developed researches have confirmed the increasing of dust event and its dangerous impacts on the environment, health, economy, etc. in west and southwest ofIranduring the recent decade. This investigation aims to have a comparison between the derived outputs from the dust simulation models and satellite images analysis over 22-26 June 2010, as this spell is considered a typical case of the dust event over the western/southwestern parts of Iran. We found that the obtained results from the HYSPLIT and WRF/CHEM models respectively on dust dispersion trajectories and aerosol concentration rate were reliable to be used in dust prediction systems over the region.

Water-Level Fluctuations of Urmia Lake: Relationship with the Long-Term Changes of Meteorological Variables (Solutions for Water-Crisis Management in Urmia Lake Basin)

Urmia Lake in northwest of Iran, through the recent years has been extremely faced with the water crisis. Climate variations and anthropogenic impacts could be two main affiliated factors in this regard. We considered the long term data series of precipitation, temperature and evaporation in monthly and yearly scales in order to compare to water-level values of Urmia Lake. The statistics approaches such as: standard deviation, trend analysis, T test, Pearson and Spearman correlations, liner regression are used to analyze all variables. The results released that the water-level of Urmia Lake along with the precipitation and temperature of the lake’s basin have experienced the periodic changes through 1961 to 2010, as there are some gradual dryness trends on the study area according to precipitation and temperature variations. Urmia Lake periodic water-level fluctuations show more significant correlation to temperature than the precipitation. Whiles, the water-level’s decreasing behavior especially through 1998 to 2010 is more harsh and different than the rate that is considered for precipitation’s decrease and temperature’s increase. Thus, there could be some anthropogenic factors in the basin which produced some supplementary causes to shrink Urmia Lake. Extracting the double precipitation over the basin through introducing and categorizing of atmospheric synoptic systems in order to cloud seeding operation could be one of urgent and innovative solutions to mitigate water crisis in the basin.