Journal of Spatial Analysis

Heavy snowfall in the cold period will cause a lot of damages and troubles for society such as collapse of building installations, and confusions in road network and fuel distributions.  Freezing event will also make worse the intensity of damages. Therefore, identifying the mechanisms of Atmospheric Circulation Pattern (ACP) which form the heavy snowfall and freezing events will certainly help to manage the risk and mitigate the impacts of the crisis.  The main objective of this research was identification of Circulations Patterns (CP) related to snowy days in the basins located in the west and southwest parts of Iran.  In this study, the geographical location of the study area is  West of Iran in 30- 37degree  North latitude and 45 57  - 51 40  East longitude. The region consists of provinces of Kurdistan, Kermanshah, Hamedan, Lorestan, Ilam, Zanjan, Markazi, Chahar Mahal Bakhtiari, Kohgiloye Boyer and parts of West Azerbaijan. In this study, the days which have at least 15 cm of snow in 24 hours, are known as days with heavy snowfall.To choose widespread snowy days, the days that were reported in three stations at least, 3 adjacent provinces and the amounts of the snow were more than 15 cm, are known as heavy snow days. In this research, to analyze the synoptic patterns of heavy snowfall days, daily data of 500 hp level and sea level pressure in 2/5 degree from reanalysis data of NCEP were extracted. All effective systems covered the studied region. The region consisted of 408 point of (20-60) degree in north and (20-80 ) degree  in east altitude .To classify and analysis the synoptic patterns of heavy snowfall days Cluster  Methods  Analysis and Principal Component Analysis were used. To draw average maps of air circulation patterns, pressure data and daily resulted geopotential height of factor analysis and cluster analysis were used. Then four circulation patterns were obtained. Frequency of days with heavy snow – in fourth patterns - showed patterns of CP1 (13 days), CP2 (17 days), CP3 (39 days), and CP4 (12 days). During the under study period, the most frequency belonged to CP3 pattern – 39 day- and the least is belonged to CP4 pattern -12 days. The results obtained of researching synoptic patterns of heavy snowfall in west and south-west of Iran: On days with heavy snowfall in the South West and West of Iran usually Siberian  high pressure system extended widely and one toungue towerd east of Aral lake and other toungue developed to south till Tibetan also some times its toungue extend on the Caspian sea and north part of Iran to Europa. Azores high pressure center is usually reinforced and its tongue extends to the Mediterranean Sea, central europa and africa and other tongue semi- west Iran and Mesopotamia. Extension of Siberian high pressure in north part of Iran with cold high pressure in east Europe created Azore high pressure belt.the system turning clockwise will cause falling the cold air. While it is snowing heaviling,the blocking system create  between  azore  - Siberian high pressure in the east europa and its tongue covers western north and west of Iran. Sudan tongue of low pressure is active.this low pressure with orient east northern or north extened to north of Iran and create a partly strong tongue. Low pressure and high pressure tongues, to other hand warm air and cold air, hit together in west of Iran. Most strong ridge in east Europe was located .this ridge mostly extened tiltly from east north of Moscow to south of Red sea. -subtropical High height center in west Mediterranean and  Tibetan Plateau reinforced then moved to upper latitudes and caused strong ridges in Asia and europe with axis northern-southern These ridges and low height centers in west of Iran and region of Mesopotamia reinforce ridge in east of Mediterranean and extend to lower latitudes. The ridge cause cold advection the region. In these situation,Polar wandering  with axis of northern- southern or eastern north- western south extended to lower  such as nourth of caspean sea and west of Iran and in the rigon  caused falling cold weather. Ridges of Mediterranean (western-east) in europe and Tibet (northen-southern) in Asia is leaded to tilt in axis of ridge towerd lower latitudes. In such days, studied stations have intense tempreture lapse rate.

Global changes in extremes of the climatic variables that have been observed in recent decades can only be accounted anthropogenic, as well as natural changes. Factors are considered, and under enhanced greenhouse gas forcing the frequency of some of these extreme events is likely to change (IPCC, 2007 Alexander et al., 2007). Folland et al. (2001) showed that in some regions both temperature and precipitation extremes have already shown amplified responses to changes in mean values. Extreme climatic events, such as heat waves, floods and droughts, can have strong impact on society and ecosystems and are thus important to study (Moberg and Jones, 2005). Climate change is characterized by variations of climatic variables both in mean and extremes values, as well as in the shape of their statistical distribution (Toreti and Desiato, 2008) and knowledge of climate extremes is important for everyday life and plays a critical role in the development and in the management of emergency situations. Studying climate change using climate extremes is rather complex, and can be tackled using a set of suitable indices describing the extremes of the climatic variables.    The Expert Team on climate change detection, monitoring and indices, sponsored by WMO (World Meteorological Organization) Commission for Climatology (CCL) and the Climate Variability and Predictability project (CLIVAR), an international research program started in 1995 in the framework of the World Climate Research Programme, has developed a set of indices (Peterson et al., 2001) that represents a common guideline for regional analysis of climate.    It is widely conceived that with the increase of temperature, the water cycling process will be accelerated, which will possibly result in the increase of precipitation amount and intensity. Wang et al. (2008), show that many outputs from Global Climate Models (GCMs) indicate the possibility of substantial increases in the frequency and magnitude of extreme daily precipitation.     eneral circulation models (GCMs) are three-dimensional mathematical models based on principles of fluid dynamics, thermodynamics and radiative heat transfer. These are easily capable of simulating or forecasting present-future values of various climatic parameters. Output of GCMs can be used to analyze Extreme climate. For this study high quality time series data of key climate variables (daily rainfall totals and Maximum and minimum temperature) of 27 Synoptic stations were used across Iran from a network of meteorological stations in the country. In order to get a downscaled time series using a weather generator (LARS-WG), the daily precipitation output of HadCM3 GCM, SRES A2 and A1B scenario for 2011-2040 are estimated.     The Nine selected precipitation indices of ETCCDMI[1] core climate indices are used to assess changes in precipitation extremes and monitor their trends in Iran in the standard-normal period 1961–1990 and future (2011-2030).    Due to the purpose of this study, at first changes in extreme precipitation indices in the standard-normal period is evaluated and its results show annual maximum 1-day precipitation increased in many regions in the East of Iran. Simple measure of daily rainfall intensity (SDII), annual maximum consecutive 5-day precipitation, annual count of days with daily precipitation greater than 10mm (R10mm), annual count of days when rainfall is equal to or greater than 20 mm (R20mm) have increased in the central areas, regions in the north , north east and southern parts of Iran. Similar results are obtained for the R25mm index.    The consecutive dry days (CDD) index has generally increased across the west areas, southwest, north, northwest and southeast of Iran and indices of consecutive wet days (CWD) decreased in these areas.    Trends of extreme precipitation indices simulated by HadCM3 SRES A2 showing increases RX1Day in North West expect west Azerbaijan Province, central, southwest, north east and coasts of Caspian Sea. Similar results are obtained for the R5mm index expects northeast. There are mixed changes in R10mm across Iran, increasing in west, southwest, coasts of Caspian Sea, Hormozgan and Ardebil provinces, East Azerbaijan, Zanjan and Qazvin  provinces. Similar results are obtained for the R20, 25 mm index in northeast, south of Caspian Sea, and some parts in western and central areas. Same as HadCM3 SRES A2 pattern there are mixed changes in R10mm across the region. Positive trends are seen in part of the Isfahan, Markazi, Kuhkilue , Lorestan, Ilam, Chaharmahaland Khozestan provinces and some part of Hormozgan and Kerman and some areas in north west. Similar results are obtained for the R20mm and R25mm index and in west of Yazd to north of Khozestan provinces have increased.    Consecutive wet days (CWD) have increased over most of the west of Iran, Khorasn Razavi and Southern Khorasn provinces, In contrast consecutive dry days (CDD) index has generally increased in many parts of the region.  
[1]. Expert Team on Climate Change Detection and Monitoring Indices

Dust particles consist of important aerosols and resulting in blowing strong winds on the surface of desert areas. These particles enter the atmosphere under the influence of different factors including: weather condition (wind, precipitation and temperature), land surface (topography, humidity level, roughness and vegetation), soil features (texture, density, composition and land use (agriculture).

Today powerful dust storm destroys people lives and causes severe damages to their life and also causes financial problems in most regions of the world especially in west and southwest of Asia. Dust storm is one of the most important natural phenomena and also a kind of severe natural disaster that influence Iran and its west and southwest part. The location of Iran on the desert belt is accompanied by frequent increasing of sand and dust storm. Integral prediction of dust storm phenomena can be useful in decreasing damages caused by these storms. So synoptic-dynamic analysis of dust storms and their simulation play an important role in achieving to this goal.

In this research, we investigate severe dust storm in August 2005 that affected a large area of our country. Select of dusty days were based on minimum visibility and maximum durability of that dust storm. At first, we show the minimum of daily visibility table. These data has been provided by Meteorological Organization in 5 western cities. The synoptic maps were related to these phenomena derived from NOAA website and synoptic and dynamic interpretation has been done. We have got the data with resolution of 2.5 degree from NOAA website.

Then 700 hpa relative vorticity maps were drawn. We investigate MODIS images instrument on Aqua satellite and evaluate the amount of mass concentration of dust particles. Then the Lagrangian Integrated Trajectory Model has been used to determine the backward trajectory of dust particles. We run HYSPLIT model by GDAS data with a resolution of 0.5 degrees. At last we investigate the output of the WRE-CHEM model. This model was run to simulate dust storms in 7-10 August and FNL data with a resolution 1 degree use for initial and boundary conditions. WRF-CHEM is used to simulate dust condition and transmission. As a part of WRF model, its main application is the study of atmosphere chemistry.

At 500 hpa a very strong ridge entered Iran from the southwest. It covered all areas of our country which prevents the transference of dust to high levels of atmosphere. In 700 hpa relative vorticity maps show one day before dust storm reach to Iran a Positive voriticity is located in Iraq and Syria. So dust comes up to higher levels of the atmosphere and in dusty days in our country. There is a negative voriticity located in our country and because of downside movement of the air, dust storm happen in Iran.

Dust loading and friction velocity of outputs of the model has been drawn in dusty days. The time series of dust concentration of output models for Tabriz are compared with the concentration data of Environmental Organization of visibility data. Result show that a low pressure system is located over the Oman sea that its blaze has been extended to the northwest of Iran. On the other hand a high pressure center is located in the Europe that extended to the east of Mediterranean. So strong pressure gradient were in Iraq and Syria and they caused the creation of strong winds in their deserts which caused dust emission.

Friction velocity related to the model outputs show that the velocity of wind is high in dusty days in Iraq and Syria. So conditions are suitable for dust raining. Satellite images showed that WRF/CHEM model is simulated very well in emission, source, diffusion and the extent of the areas covered with dust. Comparing MP10 concentration of the model output with and Environment Organization data of Tabriz city show that WRF/CHEM model forecast daily changes well. But model underestimate significantly in quantity of concentration. This error may be due to a model considering only dust quantity but other pollutants affected on visibility. In general it can be said that in this event, dust concentration has been underestimated by WRF/CHEM model especially in maximum amount of PM10 concentration.

Due to the growth of industries and factories, deforestation and other environmental degradation as well as greenhouse gases have been increasing on the Earth's surface in recent decades. This increase disturbs the climate of the Earth and is called climate change. An Increase in greenhouse gases in the future could exacerbate the climate change phenomenon and have several negative consequences on different systems, including water resources, agriculture, environment, health and industry. On the other hand to evaluate the destructive effects of climate change on different systems, it is necessary to initially study the area affected by climate change phenomena. One of the most important effects of climate change on water resource is Drought.  On the other hand, one of the most serious consequences of climate change is how it will affect droughts and water resources.

Drought along with warmer temperature and less precipitation will threaten the water supplies for the crop irrigation, which will directly reduce the production of crops.The climate of the 21st century will very likely be quite different from the climate we observed in the past. The changes will continue to be large in the future period with increasing carbon dioxide emissions. Analyzing and quantifying the signal of climate change will be much in demand considering the above sectors, which are highly relating to the sustainability and human living.

In the past several decades, global climate models have been used to estimate future projections of precipitation [Intergovernmental Panel on Climate Change (IPCC), 2007], and have led to future estimation of drought, to quantify the impact of climate change and comparing the duration  and intensity of droughts under future climate conditions with current climate by using Atmospheric-Ocean General Circulation Models AOGCMs to predict future Precipitation. Global circulation models namely, coupled Atmosphere-Ocean Global Climate Models (AOGCMs) are current state of the art in climate change research. in This study aims at investigating the impact of climate change on droughts conditions in Iran using the Standard Precipitation Index (SPI).

The precipitation time series have been used for the estimation of Standardized Precipitation Index

(SPI) for three timescales, 3, 12 and 24 months, for the region. The outputs of HadCM3-A2 and A1B were applied for the assessment of climate change impact on droughts. One of the major problems in using the output of AOGCMs , is their low degree of resolution compared to the study area so to make them appropriate for use, downscaling methods are required. In this study we have used lars WG for downscaling monthly average of rainfall of AOGCM-HadCM3, and The HadCM3 outputs were downscaled statistically to the study area for a future period 2011-2040.then, was evaluated by the coefficient of determination (R2) between observed and downscaled data.  A method has been used for the estimation of annual cumulative drought severity-time scale-frequency curves. According to the rainfall results, in the 2011- 2040 period rainfall would decrease  to compared to baseline period in the study area.

The SPI time series were estimated (2011-2040) and compared with the respective time series of the historical period 1961-1990. Results revealed that there are decreases in the frequency of severe and mild droughts for the three examined SPI time series while there are increases in the duration of moderate droughts. This implies that droughts will be a concern in the future during the growing season (for the dominant crop) which should be considered in water resources management. specially in the west station of Iran.

Also, these frequency ratios were mapped by GIS on study area. Results showed that generally in the future periods, frequency of droughts ratio of three months drought time- scale will be increase in the North, North West and some parts of the south Alborz mountains and, The Ratio of long ( 24 months) drought for scenario A2 compare to the current climate shows increasing drought in the parts of the North khorasn, sistan and baluchestan and kerman provinces and parts of South West of Iran. scenario A1B shows increasing drought in the parts of the East of Mazandaran , Tehran , Horozgan and parts of Fars and Yazd  provinces.

Finally ,further  more analysis of drought, AWCDS-Timescale-Return Periods computed. These curves integrate the drought severity and frequency for various types of drought. The AWCDS time series were estimated

for basic period and 2011-2040 under scenarios A2 and A1B. The comparison indicated the three types of drought intensity increases for the three examined SPI time series in the South East of Iran.