نشریه جغرافیا و مخاطرات محیطی
پیاپی 9 (بهار 1393)

With regard to natural and human urban threats and risks which endanger security of the residents, ensuring urban safety and passive defense issues, especially before being hit by crisis and in peace situation such as natural disasters, war, etc., are the most significant duties of urban practitioners and planners. The main criterion of passive defense Viewpoint is to increase the defense factor in time of war and its related crises in a city. Due to aggregation of human, decision centers, and monetary and cultural capitals, the criterion has an active role in stability and cohesion of spatial regions of the country. These issues, along with report of human settlement released by United Nation in 2007 concerning safety and security reinforcement of cities, precisely defined the necessity of focusing on aspects of safety and passive defense enhancement in design system and urban planning (Mahmoudinejad, 2009, 53). On the other hand, components and indexes by which we can identify vulnerable urban areas and zones from passive defense Viewpoint are provided only through design system and planning framework. Accordingly, the major concern of the present article is failure in identification of urban areas and zones from passive defense Viewpoint in Shahid Bahonar district of Mashhad which cause vulnerability against probable damages of human and natural risks and disasters. The main objective of the study was to identify vulnerable zones of passive defense in Shahid Bahonar district of Mashhad city. In this regard, theoretical principles of the research were presented using analysis of the related literature, and then Shahid Bahonar district is evaluated. Since it was a qualitative analysis, analytic spatial maps were provided in accordance with extracted components and indexes of the literature. By weighting the data layers using the Delphi and AHP techniques, vulnerable points and zones of the desired area has been identified via evaluation and analysis of weighted overlay method and based on the obtained results the related strategies were drawn up
Shahid Bahonar district of Mashhad Metropolis, as a discrete urban zone, with 152 hectare area is located in sixth region of Mashhad municipality. In terms of pattern and tissue combination, the area is formed organically and is considered as a worthless worn-out tissue around Mashhad city holy shrine. The existence of a passing lane (Mashhad-Sarakhs road) tears the zone apart and brings about physical rupture of the tissue. Strategic location of metropolis of Mashhad in east of country have doubled the necessity of attention (Asas Shahr Shargh, 2010). Location of residence like Shahid Bahonar district in the vicinity of such a metropolis directs a special safety and security attention to this region. It is worth mentioning that Shahid Bahonar district, after being recognized as a part of Mashhad city in 2008, has went through renovation process. Therefore, paying attention to vulnerable zones of passive defense could have positive effect in development and renovation process of the district.

The project was conducted in mixed method. Various models and techniques have been employed to investigate and evaluate the urban vulnerable factors and elements of passive defense. Analytical models and techniques of this research included spatial link method, analytical model of weighted overlay, Delphi model, and hierarchical analysis model (AHP) which will be explained later.
Space syntax with spatial arrangement is one the useful techniques of urbanization for understanding complexity and spatial-functional relationships of a city. Based on existing spatial relationships and behavioral patterns (movement in spaces) and amount of integration of lines, this technique analyzes the structure of a city (Abbaszadegan, 2002) and investigates walking movement in the district.
Using Delphi, as a systematic method in research in accordance with extraction of experts or panellists opinions on a certain problem via questionnaire, will provide the areas of optimal decision making and improvement of effective strategies (Ahmadi, 2008, p. 177). Experts’ opinions determine the level of significance of vulnerable factors and elements of the city.
Analytical Hierarchy Process (AHP) is a flexible, powerful, and simple method for making decision in situations that decision making criteria make it hard to select among the alternatives (Zebardast, 2001, p. 13). AHP is initiated by identification and Prioritization of decision making elements. These elements include objectives, criteria or indexes and probable options being used in the prioritization (Zebardast, 2001). In this method, significance weight of criteria and sub-criteria in each vulnerable section of the district is calculated according to binary comparison and significant factor of each criterion is determined.
The method of Geographical information system (GIS) is by analytic function of weighted overlay (WO). This method has been applied for interpolation of weighted layers in environment with the aim of obtaining comprehensive analysis of various and heterogeneous inputs (ArcGIS, 2013). The method is used for determining urban vulnerable zones of passive defense based on information layers of vulnerable factors and elements of city.

In this section, after realization of corresponding significance of vulnerable factors and elements of Shahid Bahonar district by specialists and experts' opinion in a group judgment using Delphi method, AHP is used for weighting and prioritizing of existing criteria and sub-criteria. The final score of this analysis indicated the importance of each criterion and sub-criteria in weighted overlay process and concerning these scores the overlay of existing layers was evaluated in databank by weighted overlay analyzer. By applying this method, vulnerable areas and zones of passive defense is shown based on the amount of vulnerability in the form of final map. Regarding factors and elements and vulnerable zones of passive defense and high vulnerability range of the district (26 percent) in status quo, it can be said that:- Passive defense principles were not regulated in locating land uses and operational canons.
- Major and leading centers were located in areas with high population and traffic.
- If the case of damage to main access of the tissue, communication system is totally paralyzed.
- The existence of only one communicative access from passing stream at the east of district.
- Mono central structure increases the vulnerability degree in critical situation.
Generally, it can be said that spatial organization of the district cannot properly manage and tackle with crises and military and security risks.

Based on the obtained results of the previous section, following strategies could be formulated for enhancing safety and passive defence in Shahid Bahonar district of Mashhad:- Building new peripheral access to improve the link of existing tissue with the main access according to the map of vulnerability rating
- Improving distribution, combination, and placement of functions and urban spaces (urban spaces).
- Designing shelters and open spaces in the city concerning existing surrounding open spaces.
- Locating relief centers with regard to existing vulnerable zones in middle zones and around the district.
- Paying attention to modification of access and communicative network to enhance integration (regarding mono central structure that increases range of vulnerability in critical situations).
- Locating elements and major infrastructure of the city regarding passive defense criterion to change the mono-center pattern.
- Building capacity and prioritizing of access to services and critical facilities (water, food, etc.) in crisis regarding map of vulnerable zones.
- Forecasting and locating of alarm systems regarding map of vulnerable zones.
- Increasing urban accesses via existing stream of the city based on map of vulnerable zones.
- Informing and creating the culture to enhance public participation as central core of passive defense.
Geographic Information System (GIS) is dynamic, efficient, and powerful system in collecting, managing, and analyzing data. Using this system in relation to new analytic techniques like spatial arrangement analysis, facilitate the possibility of strategic planning in passive defense. In addition, by applying the employed methods and processes of this study, we could identify factors and elements of passive defense damage and prioritization regarding the existing criteria.
Identification of vulnerable zones of passive defense of the city, in the case that improve the existing damages and risks, is useful and operational and the prerequisite of that is pre-crisis management. By placing in an active and overall process, Pre-crisis management must engage all related urban institutions and organizations. It is only in this case that we have the possibility of formation of safe cities consistence with passive defense principles or in other words, resilient cities, against possible crises

The analysis of drainage networks is a powerful tool to detect recent tectonic activity and uplift, as river channels are very sensitive to changes in the parameters that control their shapes and. Climate changes, tectonics and lithology affect river equilibrium conditions and hence, river geometry. A river is in dynamic equilibrium when erosion keeps pace with sedimentation and under these conditions a river can be considered to be graded.
River channel profiles and various geomorphologic variables, including temporal variations of at-a-station hydraulic geometry (e.g., Park 1977)
The results have implications for the late-Cenozoic topographic and geomorphic evolution of the southern Rocky Mountains as being related to erosional exhumation and epeirogenic uplift (Frankle, 2002).
Geomorphological analyses allow the study of modifications that affect hydrographic basins, particularly modifications due to active tectonics, and the quantitative description of landforms. The evaluation of geomorphic indices may be used to appraise the influence of active faults on the hydrographic network. (Guarnieri, 2008).
Ratios of Valley floor width to valley height (Vf) values being one of the best morphometric parameter for tectonic studies were calculated along of Tista River and its tributaries especially in the vicinity of Thrusts (Tajbakhsh, 2009).
In the Sikkim area (northeast of India), longitudinal profiles of rivers are prepared and these profiles show six Knick points on Tista River and six Knick points on tributaries Rangpo and Rongli that indicates strong structural control in determining the course of the river located close to the major thrust zone (Tajbakhsh, 2009).
The aim of this study is to investigate the interactions and possible feedbacks between morphometric and tectonic processes especially along Khartut River.
Since any changes in the geometry of the river will affect to flood condition sand cause serious damages to the rivers. Analyze the temporal change of hydraulic geometry at individual cross-sections and its spatial changes along the river course as it flows from mountainous bedrock to alluvial floodplain valleys.

The study area is located between56° 54'- 57° 7' E longitudes and 37° 55'- 37° 59' N latitudes in the north Khorasan province covering an area of about 371.92 km2.The study area is characterized by deep gorges and rugged mountain. Topographical elevation varies between 973 m at outlet and 1747 m at Raz and Aqchil mountains and the average elevation is about 1349 m. Raz city and 7 villages are located around the main river channel.
The upper portion of the area is rocky and remains under snow during the winter months. The middle portion is mostly covered with Sanganeh and Atamir formations and the lower portion is covered by Quaternary sediments occur along the main river.

The physiographic factors of the study area have been extracted in detail on the basis of DEM generated from 10 m counter from topographic maps at 1:25000 scale and elevation points from surveying in 1:500 scale.
Natural conditions of cross sections in the river and each section of the coast were simulated with ArcGIS software and Hec-GeoRas extension.
The calculation of the water surface profile was performed byHecRassoftware.25 cross-sections had chosen that included 10pointsare intersection of faults and15points are subsidiary water course confluence with the main river. Also the hydraulic parameters have been calculated in Hec- Ras software.
Morphometric parameters have allowed us to comment about land form change in feature. For example Vf factor have direct relation to active tectonics and uplift. Morphometric calculations also conclude that the similar results according to tectonic activity, uplift, erosion and chances of flood. The ratio of valley floor width to valley height (Vf) may be expressed as
(Vf) = 2Vfw / (EId-Esc) + (Erd-Esc)-3
Where Vf is the valley floor width to height ratio; Vfw is the width of valley floor; EId and Erdare elevations of the left and right drainage/ valley divides respectively and Esc is the elevations of the valley floor (Bull and McFadden, 1977).
Then the river profile was preparedfor10 intersections of faults with a river to length of 400meters, with using ArcGIS software.

Investigation of the relationships between geometry and hydraulic of Khartut River, has led in a series of mathematics and empirical relations between the characteristics of the river and the other parameters. These relations are obtained the regression from geometrical and hydraulic parameters .Regression relationship is established between the dependent variable means discharge and independent variables means width, depth, slope, hydraulic radius of the stream. The equations are given follows that:D = 0.241Q0.36 r= 56 -3
W= 0.003Q 2- 0.152Q + 15.25 r= 79 -4
S = 0.174Q-0.56 r = 58 -5
R= -0.0001Q2 + 0.0179Q + 0.2932 r = 55 -6

Where, D: Flow Depth (m), W: Flow Width (m), S: slop (m/m), R: Hydraulic radius (m), Q: flow rate (m/s3).
Ratios of Valley floor width to valley height (Vf) values being one of the best morphometric parameter for tectonic studies were calculated along of Khartut river and its tributaries especially in the vicinity of faults.
The values obtained for majority locations show relatively low values of Vf indicating the high tectonics activity is dominant. Thus it is inversely related to tectonic activity i.e. high values of Vf are associated with low values of uplift rates in the study area. In the present study, majority of Vf values are significantly lower than 0.5 in most of the main tributaries of each sub-basin and on all the investigated faults. Based on the classification, the river is active. Also Vf value for sections 4 and 7 are close to 0.1 that are very active.
These sections are distinct for others hydraulic parameters. As the speed and shear stress increased in the two sections that could have an important role in the degradation of the bed river.
Investigation of the river profiles for 10 sections, were examined knick points and the impact of geological factors. For example, river profiles of numbers 1 and 6 indicate that faults caused knick points as iffault1 has created 8meterheight change in less than200meterslength.
Faults in sections2, 3, 5, and 10did not make any change in river profile but in sections 4, 7and 8,are causing changes in the river profile, that will impact on the water surface profile and then the rise up river flood zone. The uplift is significant in river profile of section 8(Fig 6).

Knick point’s behavior is a key to understanding to the landscape response. A knick point may also be a disequilibrium steeping in response to a relative fall in base level. Such disequilibrium in Knick points in bed Rock Rivers are commonly triggered by surface uplift.
The results show that tectonic activity during river is causing uplift and down lift of the bed river that has a significant impact on the changing status the river geometry and any change in the geometry of the river, increase flood zone, making river sand natural hazards.
The water surface width responded significantly to changes in discharge in along Main River

One of the most important conditions to have dusty weather beside of unstable weather is existence or non-existence of humidity. Unstable weather having enough humidity will produce rain and thunder storm, else if the result will be dust storm. Number of particles of dusty storm is depended to wind speed, sec of soil and its dimension. Furthermore, vegetation type has importance on dust storms. Vision reduction is one of the main causes of dust storm beside of inspiration problem, environmental pollution and airline traffic. In the recent years, a lot of flights especially in west and south-western part of Iran have been cancelled because of dusty storm. One of the criteria to measure dusty storm is vision ability. Recently, Kermanshah has a growth in industrial development, urbanization and transportation that cause increasing of pollutant elements in atmosphere. Pollutant density causes major problems for citizens of Kermanshah especially elderly, infant and sick people. Thus, studies and analyses of air pollution and its causes are necessary in Kermanshah. In this paper, the cause of air pollution from synoptic sight is carefully considered.

Kermanshah is the capital of Kermanshah province and is located in west of Iran. This city is one of the seventh biggest major cities in Iran and has population around one million. Longitude of this city is 47/3 and its latitude is 34/13 and the altitude from see is about 1300 meter. Irregular development of the city, increasing of transportation vehicles and industrial development beside of entrance of dusty in recent years becaus e intensifying of air pollution in this city.

In this paper we are focused on pollution and present of synoptic algorithms using by synoptic ground level maps and upper level of atmosphere data.
1. Air pollution data is depending on environmental protection organization of Kermanshah obtained from control center in Zibapark between 1385-1386 years.
2. Data of metrology is obtained from metrology organization of Iran.
3. Average of daily air pressure maps in 700 hpa level is obtained from NOAA organization site.
4. SkewTcharts for different hours are obtained from Wyoming University in USA.
The method in this paper is synoptic approach consist of the following steps:1. Suitable Station selection for this study is synoptic station in Kermanshah and air pollution station of environmental protection organization located in Ziba park of Kermanshah
2. Detection and study of weak and strong of pressure systems that affects the air pollution of Kermanshah
3. Determination of polluted days in period of hourly and daily basis for pollutants as NO, NO2, etc….Based on air pollution standard index (PSI).
Based on daily and hourly data of air pollution, air pollution period events in each month in statistic periods have been determined and the charts have been prepared. Following, based on sequence of days with pollution, air polluted periods has been determined. Then, based on synoptic map, ground level and upper atmosphere, the condition of pressure systems are considered. With detection of trajectory of pressure system and their impacts on weakness and strong of air pollution in Kermanshah, the dependent patterns have been presented.

In this study, retrieve of pressure centers beside of its origins and trajectory of pressure system that affect air pollution in periods of pollution based on pollutant have been studied. In this regards, affected pressure system from average pressure maps for 3 and 4 days waves from NOAA organization have been details studied. With study of pressure maps in ground level and adaptability with average pressure maps in altitude of geopotential levels of 850,700 and 500 hpa affective systems on air pollution have been detected. Regarding to similarity behavior of trajectory of air pollution in each pressure system, one the periods as sample and index have been selected. Then, more details of behavior of each system have been detected and finally the main affective system on air pollution has been identified. Regarding to, array of systems in ground level and upper levels of atmosphere and also synoptic and dynamics condition are placed in three main groups. They are called as A, B and C patterns.
In A pattern, a high pressure center, European dynamic high pressure with central pressure of 1035 hpa will be establishes in the region. Eastern movement of this system from north-western and south- western of Europe and north of black sea cause in western region govern of Iran and Kermanshah too.
This system, in following days moves towards eastern part. In critical days of air pollution with rotation of this high pressure cell, pole cold weather will be combined with cold weather of Caucasus. Thus, a cold weather will govern the region. This condition, cause stable weather and inversion of temperature and will increase the air pollution of Kermanshah.
The second pattern B shows in the critical days of air pollution, the different condition will govern in the ground level and upper levels of atmosphere in region. Maps and charts shows that in commence and pick of air pollution of Siberian high pressure will come to the region and intensify and stability and air pollution in Kermanshah. Ground cooling, losses of long wave radiation, shortage of cloud in sky, no mixture of in atmosphere and stability of air; establish an unpleasant condition in point of air pollution.
The C pattern of air pollution is completely different compare to two last patterns.In the last two patterns, air stability and high pressure system cause intensifying of air pollution in the city. While in the this pattern that can be called as low pressure, instability intensifying cause intensifying of air pollution in the city. Pollutant kind that can be called dust pollutant, are different in this pattern. Thus, we can conclude that their origin is based outside of Iran frontier.

Investigation of intensifying of air pollution in periods of study and temperature inversion shows that the second pattern has the maximum pollutant compare to others. The reason is in specification of air mass responsible for these systems. In the second pattern, weather dynamic subsidence cause strong temperature inversion in level of 850 hpa. Thus, an inversion layer will be established and intensify the air pollution. In the first pattern that will happen mostly in the winter, temperature is lower compared to the second pattern. The humidity of temperature is higher in A pattern compared to others.
In the most days of a pattern, humidity is high and in the most of times is combined with fog. While in the B pattern, for the reason of entrance of air mess from pole toward region, and also the cold weather from Siberian high pressure cause weather become dry.
In the C pattern, because of the strong instability in the different level of atmosphere cause reduction of continuity of air pollution and doesn’t last more than half day. The other point has to be considered is the direction of wind in the air pollution. The study of wind direction shows that wind direction is similar in all the patterns. In the most times, wind comes from west, North West and south western of Kermanshah. It is clear that topographical situation in Kermanshah has causes this situation .This point has to be considered in urbanization and industrial development considered by responsible organization and managers.

Tropical cyclones (TCs), all over the world, are recognized as the most common and most devastating of all the natural disasters. Nearly 80–90 TCs occur around the globe that about 40–50 attain intensity of 33 m/s (Frank and George, 2007). Approximately 7% of TCs originate in north of Indian Ocean and nearly 2% in Arabian Sea (WMO report, 2008).
The prediction of TC track has been on a clear path toward improvement for many years and nearly has been achieved (Elsberry, 2005). The global and regional simulations have proved that high resolution is not a requirement for improved track prediction (Goerss, 2006). The prediction of TC intensity is very complicated, because track prediction depends more on large-scale processes, and intensity depends on the inner-core dynamics and its relationship to the environment (Marks and Shay, 1998). It means that the intensity is a multiscale problem (Goerss, 2006). Only recently has the computational capability to address multiple scales of convection (cell scale, mesoscale, and synoptic scale) been achieved. The requirement to resolve the inner core, including the eyewall, the eye, and inner spiral rain bands near the eyewall, has led to the application of models with grid lengths of only a few kilometers (e.g., Krishnamurti, 2005; Braun et al., 2006; Chen, 2006; Davis et al., 2008).
Further the importance of resolution, other key issues for TCs prediction include the effect of mixing-induced ocean-surface cooling, treatment of momentum, heat and mixture fluxes at the air–sea interface, and improvement of the initial vortex structure through data assimilation. These Allegers will be each more important when we are moving toward finer spatial resolution in simulations.
In this study, sensitivity of Gonu simulations to air–sea fluxes parameterization and model resolution are studied as key issues for improving simulation accuracy. Herein, sensitivity to atmospheric physical parameterizations such as cloud physics and the boundary layer physics that affect Gonu intensity too, are not considered explicitly.

The Indian Ocean is the third largest of the world's oceanic divisions, covering approximately 20% of the water on the Earth's surface. It is bounded by Asia—including India, after which the ocean is named—on the north, on the west by Africa, on the east by Australia, and on the south by the Southern Ocean (or, depending on definition, by Antarctica).

Gonu was strong cyclone (categury 5) that was formed in the Arabian Sea during the periods of 1-7 June 2007 .At the peak intensity, cyclones Gonu was caused 3-min sustained wind about 240 km/h and minimum pressure about 920 mb. Financial losses of Gonu cyclone was reported around 4.2 billion USD and for human casualties at least 78 persons (IMD report, 2008). Herein, we have not planned to discuss about synoptical conditions of the Gonu cyclone formation, and only the effects of Air-Sea interactions on intensification is interpreted.
The performance of Advance Hurricane WRF (Advanced Research Weather Research and Forecasting) model (AHW model: Davis et al., 2008) is evaluated in explicit simulations of Guno super cyclone (2007). The data from National Centre of Environmental prediction (NCEP) global final analysis (FNL) on a 1.0°×1.0° grid is used to provide initial and boundary conditions for numerical simulations. Sea surface temperatures were derived from the high-resolution real-time global sea surface temperature (RTG_SST) at 1/12-degree resolution analyses from NCEP/MMAB. The information of reference track for Gonu cyclone has been received from Indian Meteorological Department (IMD). The mixed layer ocean model requires specification of an initial mixed layer depth h0, and a deep-layer lapse rate Γ. The ocean model was initialized with h0 and Γ equal to 50 m 0.14 in order to the NCEP Global Ocean Data Assimilation System (GODAS), when the negative feedback of wind-driven ocean mixing on hurricane intensity was planned to be considered (Davis et al., 2008).
In order to implement the Gonu simulations we considered two domain, the first domain was fixed with 27-km horizontal grid resolution (with 145×110 grid points) and second domain was nested movable domain with 9-km horizontal grid resolution (with 49×49 grid points) that was configured with a two-way nesting (fig. 1). All domains had 41 vertical layers with a terrain that followed sigma coordinates with the model top at 0.5 hPa.
The surface-flux parameterizations include of both momentum and enthalpy (heat and moisture) exchange. Two main schemes for momentum exchange are presented by Charnock and Donelan (Charnock, 1955; Donelan et al., 2005) that Charnock formulation is a default scheme in mesoscale meteorological models. In Charnock formulation, roughness length given as
(1)

Where and m and frictional velocity defined as
(2)

Where τ is Reynolds stress (shearing stress) and ρ is air density. The relation between roughness length and frictional velocity is recursive, but the model formulations use values from the previous time step and adjusted quickly.
In atmospheric boundary layer, drag coefficient is defined as
(3)

Where V10is the wind speed at 10-m height. The Charnock relation gives a 10-m drag coefficient that generally increases from about 0.001 to 0.003 at normal TC wind strengths, and it would recent to 0.005 for category 5 storms (wind >70 m s-1). However, this estimation for category 5 storms does not match with observational evidence (e.g., Black et al. 2007) that suggests drag coefficient remains near 0.003 for high wind speeds.
Donelan is introduced a drag formulation based on the high wind speed wind-tunnel experiments (Donelan et al. 2004) that results are showed Cdlower than those from the Charnock relation for low winds with a linear increase up to a maximum near 0.0024 at about 35 m s-1. In Donelan formulation, roughness length given as
(4)

With a lower and upper limit on z0 of 0.125×10-6 and 2.85 ×10-3 m, respectively. The Donelan formulation, with less drag than the Charnock formulation shows yourself effects with higher wind speeds but also higher central pressures and a larger eyewall radius in strong TCs simulations. This subject needs to validate with TCs observations over all the tropical.
The exchange coefficients of heat (Cɵ), moisture (Cq) and enthalpy (Ck) formulate by friction velocity, scaling temperature ɵ* and scaling moisture q*. These scaling parameters define the similarity theory profile. The available schemes for estimation of molecular viscosity sub-layer roughness length confirm an inverse relationship between roughness length and wind speed, and has the effect of a resistance to the eddy scalar transports that increases with wind speed. It means that the q* contribution to the surface moisture flux u*q* tends to oppose the effect of u* increasing with wind speed (similarly for heat and enthalpy). The coefficients of Cɵ, Cq and Ck formulate as
(5)

Where Δθ and Δq are difference in water vapor mixing ratio and potential temperature between the surface and 10-m. CP and Lv are heat capacity at constant pressure and specific latent heat of vaporization, respectively.
For example, estimated exchange coefficient of enthalpy (Ck)during the simulations are related to selected scheme for estimation of ɵ* and q*. The Ck will increase slowly in Carlson and Boland, stay steady in Large and Pond and decrease in Garratt parameterizations with increasing of wind speed (Carlson and Boland, 1978; Large and Pond, 1981; Garratt, 1992).
According above description, considering different schemes for different roughness lengths velocity, water vapor mixing ratio and potential temperature scaling in atmospheric surface layer over water would significantly affect estimated Ckand CD and also TC intensity. For example, the ratio of Ckto CDis introduced as an important factor in TC intensity (Emanuel, 1995; Braun and Tao, 2000; Davis et al. 2008).

In the first, the results of simulated intensity (minimum pressure and maximum wind speed) for coarse domain (Fig. 2) are analyzed. It is clearly showed that the sensitivity of simulations to the different three air–sea fluxes parameterization for simulations of Gonu at 27-km grid resolution at 0000 UTC 02 June 2007 (144-h model forecast). The Donelan-Large formulation, with less drag and steady Ckthan the Charnock-Carlson formulation that have higher drag and increasing Ckwith wind speed, results in higher wind speeds also lower central pressures. This happens after 48-h simulation where that wind speed increase until 78-knot. After this condition, high drag in the Charnock-Carlson formulation tends to oppose increasing wind speed. Comparison between Donelan-Large formulation and Donelan- Garratt simulation results with the same drag but different Ckin this interval shows Ck decreasing with wind speed that it tends to oppose wind speed increasing. Also Fig.2 shows steadily wind speed increase and decrease during first 48-h and last 48-h simulation for all three parameterizations for air–sea fluxes. The comparison of the sensitivity of simulated Gonu intensity with air–sea exchange parameterizations clearly showed that the Donelan-Large configuration has achieved significantly better simulated results at 27-km grid resolution but with 30-knot wind speed less than reported speed by IMD.
In order to study sensitivity of simulated Gonu intensity to horizontal grid resolution, it was conducted three experiments at 9-km grid resolution similar to last three experiments. The results were showed similar sensitivities at 27-km grid resolution but it was significantly improved the wind speed at the peak of cyclone intensity for these three air–sea exchange parameterizations (Fig. 3). Also these results showed that the central pressure simulated by Charnock-Carlson formulation, has been better compared to the 27-km resolution (as Donelan-Large formulation).
The results of simulated tracks were not significantly sensitive to these surface exchange parameterizations (not shown) but it showed more sensitivity to horizontal grid resolution (Fig.4). As can be seen in Fig. 4, the simulated track for 27-km resolution is better than the 9-km resolution that it consistent with the results of Goerss (2006). This proved that high resolution is not a requirement for improvement of track prediction.

In this study, it is seen a significant sensitivity of simulated intensity of one TC to air–sea exchange parameterization and horizontal grid resolution. For selected TC, the experiment with Donelan parameterization for momentum exchange and Large - Pond parameterization for heat and enthalpy are found more efficient. Also the results showed that simulated track could be more sensitive to horizontal grid resolution than applied air–sea fluxes parameterization. The difference in drag between the two drag formulations (Donelan and Charnock) is relatively smaller than reality. It must be pointed out that the real drag force on surface winds is determined by the time-evolving ocean wave spectrum, prediction of which requires a wave model (e.g., Chen et al. 2007). Therefore the drag parameterizations discussed above must be considered as crude representations of the bulk effects of waves in TCs. This sensitivity of differences in the three air–sea fluxes parameterization is less than would be inferred from the dependence of maximum wind on (Ck/Cd)1/2, derived by Emanuel (1995), While the proper wind speed dependence of Ck remains a topic of active research.

Increasing of extreme events such as flood, hailstorm, drought, thermal waves, dust storm and other dangerous climatological events, especially in local scale, could be the result of the climatic change over the globe. The characteristics and impacts of severe weather are function of place and time of occurrence. Severe weathers are usually accompanied by strong winds and heavy hailstones, which are very destructive. They develop and then downfalls very fast. This is the reason that makes forecasting of these phenomena difficult. It is very important to study severe weathers from both thermodynamic and dynamic points of views. The aim of this study was to improve forecasting by investigating the relationship between upper atmosphere conditions and surface weather conditions in Mashhad, Iran.
Showalter (1953) introduced an index named SI for determining the amount of instability and prediction of the thunderstorm and hailstorm. Galway (1956) extracted the lifting index of LI among his studies over convective events. His index is more or less similar to that of SI index and their thresholds amount for occurring the thunderstorm and hail are same. George (1960) developed a simple formula for calculating K index using dry bulb and dew point temperatures in different atmospheric level. Miller (1972) introduced the SWEAT and TT indices by combining some different indices. Miller and Mancriff (1976) have been finally developed a strong index of CAPE for evaluating the potential activity of the thunderstorm.

In this research, Mashhad synoptic and upper atmosphere station, is located in the northeast of Iran with 36° 16´ N latitude and 59° 38´ W longitude, was selected as the study area, and severe instabilities that occur during 1980-2009 were used for analysis.

In this research, we try to introduce the parameters and instability indices and try to prepare the summary of their thresholds to anticipate the kinds of instabilities. Therefore, set of parameters and indices is calculated specifically for Mashhad station as follows: showalter index, lifted index (LI), SWEAT, K index (KI), total totals (TT), convective available potential energy (CAPE), CIN, and equilibrium level pressure(EL), precipitable water (PW), Bulck Richardson number (BRN). Severe instabilities which occurred during 1980- 2009 are used in this analysis. The severe instability reports were obtained from the METAR, SYNOP, and Special meteorological reports, and also from synoptical notebooks. The international criteria for severe instabilities [winds greater than 50 knot (25 m/s), all kind of hail reports, all kind of thunderstorms, lightnings, squalls, funnel clouds, and tornado or waterspout] were used. All of these reports have been classified in three categories: Lightning, thunderstorm, and hail. The days with no of these criteria are called no-instability. Instability Indices were derived from radiosonding data of Mashhad upper air synoptic station that collected in Wyoming University database.

For most indices, the threshold that gives the best prediction was determined using statistical methods, box plots, and scatter plot diagrams.
For achievement to better results, relationship between two different indices in forecasting of phenomena was analysed, and complex of each pair of indices such as CAPE with lifted index (LI), and lifted index with equilibrium level pressure (EL), that had a strong relationship, introduced as the best combination indices.

Table 1 Lower and upper thresholds for instability indices during various severe weathers in Mashhad.

Lightning threshold Thunderstorm threshold Hail threshold Indices & Units

-

CAPE (J/Kg)
-

SWEAT



SI(°C)



LI(°C)



KI(°C)



TT(°C)
- -
PLCL (hPa)



TLCL (°K)
-

LFC (hPa)



EL (hPa)



(g/Kg)

The threshold of most individual indices, which gives the best prediction for different kinds of phenomena was determined and introduced, that are summarized in table 1. Then upper and lower thresholds of different indices in forecasting of severe weathers were showed in box plots, and scatter plot diagrams. Finally, relationship between two different indices in forecasting of phenomena was discussed, and complex of CAPE with lifted index (LI-CAPE), and lifted index with equilibrium level pressure (LI-EL), had a power relationship and introduced as the best combination indices.

A set of sounding data was carried out in Mashhad station, in the period 1980-2009 were analyzed and the result is that using instability indices, has very good performance in predicting and warning of severe weathers. In this study, 12UTC sounding has better result than 00UTC for severe weather forecasting. For some indices such as Richardson number (BRN), convective inhibition (CIN), and thickness results were not favorable. Using these parameters individually may result in error for prediction, and it is necessary that all indices are used in combination with each other and, synoptical methods of forecasting.

Urban development on vulnerable areas is main problem in recent years due to catastrophic responses of geosystems such as fault activity, flood and many geomorphological hazards following equilibrium changes of geosystems. Mashhad, the second metropolitan of Iran, with population over 3 million, according to existence shrine of Emam Reza, welfare facilities and educational centers, have been caused high immigration in recent decades and over constructions in vulnerable areas.
Urban development on alluvial fans, faults lines, high risk of subsidence, also land use changes, water and air pollutions are main factors that intensify environmental hazards for this city.
Applying ranking and outranking methods, statistical algorithms, linear programming and multi-criteria decision making methods are some approaches for choosing criteria affecting urban development.
Linear programming is the process of taking various linear inequalities relating to some situation, and finding the "best" value obtainable under those conditions.
More formally, linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. Its feasible region is a convex polyhedron, which is a set defined as the intersection of finitely many half spaces, each of which is defined by a linear inequality. Its objective function is a real-valued affine function defined on this polyhedron. A linear programming algorithm finds a point in the polyhedron where this function has the smallest (or largest) value if such a point exists.
In this study, the SIMUS methodology, Sequential Interactive Model for Urban Sustainability, was used for mapping environmental hazards. SIMUS develops a methodology to work with subjective criteria, something that is not allowed in the conventional LP method.
The main goal of this research is mapping environmental hazards susceptibility of urban region of Mashhad metropolitan based on linear programming algorithm and presenting sustainable strategies based on the susceptibility severity.

Metropolis of Mashhad, the centre of Khorasan Razavi Province, with an area of 204 Km2 located in the North East of Iran, surrounded between mountain ranges of Binalud and Hezar Masjed. This city is second metropolitan of Iran, absorbed more than 30 million tourist per year, so has main social-economic role.

In the first step, four geomorphological criteria including, flooding, fault, seismic risk, and liquefaction, also five environmental criteria including water pollution, air pollution, population density, land use alterations and informal settlements have been selected based on Delphi algorithm and expert’s opinions. In the next step, using SIMUS algorithm, was determined the sustain degree and susceptibility of urban regions to environmental hazards. SIMUS simultaneously considers both qualitative and quantitative values, with any number of thresholds, with lower and upper limits for each criterion, and with any number of alternatives and criteria, and can produce an objective ranking of alternatives. The objective function in the linear algorithm was considered maximum and thresholds selected by mean amount. Ultimately accordingly susceptibility degree, strategies of increasing green space, determining urban boundary, resisting building, combating land use changes, traffic control, immigration control were selected.

simus considers simultaneously all the criteria, and recognizes the best combination of trade-offs between projects and criteria In other words, simus ranked the alternatives in accordance with their compliance with the objective, which is gauged by the criteria. The results show that urban region of 1, Samen and 9 gain maximum susceptibility to hazards. In front, the region of 2, 3, 5, 6, 7, 10 and 11 have minimum susceptibility degree. The plan of immigration control, resisting building, determining urban boundary and increasing green space should consider for sustainable development programs.
Also the results indicated that determining city border to urban development in safe areas is needed for second metropolitan of Iran, Mashhad. Attention to geomorphology concepts is fundamental element to build settlements.

Urban development must be planned base on land suitability and capability in each area. These indices determine environmental potential of an area to development programs and choosing best land use. Decision making and utility theory are methods to select regions for urban development.
SIMUS has the ability to select only one project among several, which is then the optimum, or can also make a ranking of projects. According to the SIMUS results and susceptibility map of urban areas to the environmental hazards, the urban management of the region 1, 9 and Samen are important, also land use management and immigration control plans have high preference in urban management of Mashhad.