نشریه پژوهش های اقلیم شناسی
پیاپی 1-2 (بهار و تابستان 1389)

Introduction Daily increase of industrial activities causes effects like green house gases emission in the recent decades. This harmful effects cause considerable changes in whether condition in many parts of the planet earth. Most important effects are, increase in mean temperature, flood, storm, hail and sea level fluctuations. The forecasting and assessments of climate change have some difficulties at surface circulation of green house gases and large scales separate in general atmospheric circulation. Because of low spatial resolution of General Circulation Models, weather and climate cannot be predicted accurately. Assessment of the climate change in future needs to introduce new climate scenarios. For this purpose, the climate data should be predicted and simulated for coming periods by using outputs of Atmospheric- Ocean General Circulation Model. In this paper, LARS-WG model and A1 scenario from ECHO-G model are used for assessing and predicting climate change in Zagros (2010-2039). Materials and methodsThe region under study. The region in question is Zagros. In these research grided meteorological outputs of ECHO-G model including precipitation, maximum and minimum temperature and radiation have been downscaled over 18synoptic stations of Zagros during 2010-2039 with A1 scenario

IntroductionSea breeze system as a Meso-scale phenomenon is caused by direct radiation of the sun on land and also the energy balance between water and land. It is also observed along middle and tropical coasts (Bowers, 2004). Cool marine air propagates inland when a cross-shore meso-scale (2–2000 km) pressure gradient is created by daytime differential heating (Miller, 2003). In the clear weather, when the heat brings a pressure gradient force from sea toward the land, marine air surface layer moves toward the land. The temperature decrease on land depends on the beginning sea breeze. Sometimes, in the afternoon (when there is a maximum difference between land and sea), the heat difference reaches 4.4 centigrade (Rao, 1955). This research studies the sea breeze according to climatology parameters and numerical simulation. Actually it determines synoptic patterns providing suitable conditions for the occurrence of sea breeze along the Caspian Sea coastlines. Here it also has determined the initiating, the termiation, and the climax of sea breeze during the months and seasons.Materials and MethodsIdentification sea breeze occurrence and determining dominant days: In this study, the main filter for extracting the sea breeze days is a surface wind reversal criterion. This criterion is implemented in the following manner (M. Furberg et al, 2002): The wind must blow (onshore current) for at least three consecutive hours during the hours from sunrise to sunset. The days were selected by monitoring the speed and wind direction, air pressure, sea and land temperature, cloudiness from May to September(from 2000-2006). The daily variations of wind direction are the most important criterion for selecting the sea breeze.To have a more accurate report from sea breeze days which separate it from synoptic currents, another method was added to the above criterion. Borne et al (1998) used Tland-Tsea>3 C criterion in which Tland is the mean of daily temperature on land during sunny days and Tsea is sea surface temperature. Finally two samples (July 8th - 9th 2003 and June 5th - 6th 2003) were chosen and analyzed. TAPM is a PC-based meso-scale numerical model with meteorological and air pollution components. This model is three dimensional, controllable; it also has effective and high resolution. The meteorological module of TAPM predicts the local-scale circulations, such as sea breezes and slope flows, in conjunction with larger scale synoptic scale meteorological fields. It also enjoys high graphical representation and uses terrain database, meteorology and climatology data, and pollution data.Results and DiscussionThe highest temperature difference because of heating difference between the land and the sea occurs in the second half of spring and the first half days of summer in all of the stations. The results show that the highest differences between land and sea surface temperature in all stations have occurred in May. On average, in all stations, the sea breeze from May to August is most frequent. In this period, the sea breeze appears in 40% of all days.ConclusionAnalysis of the LARS-WG outputs for 2010-2039 show the results as bellow:• Mean amount of precipitation will be decreased by 2 percent during 2010-2039,• Summer and second half of winter rain fall will increase over the period under study,• Thresholds of heavy and extreme rainfall will increase by 3 and 19 percent, respectively,• Hot days series will be increased over the future period, Amount of freezing day lenght will decrease,• Annual station-averaged temperature has calculated to increase by 1oCin 2020s. The greatest increase inannual mean temperature has been calculated to be 1.1°C in winters.

IntroductionSince the beginning of industrial revolution and especially in the recent half of 20Th century, it is increasingly recognized that the magnitude of human influence on the Earth persistently intensified. As the first time in the history of our planet, emissions of trace gasses from human activities has been equaled, or even exceed from natural sources (Henderson et al 2001). Human influences will continue to change the atmospheric composition throughout the 21st century. (Jones et al 2003). Anxieties are now plausibly felt, and extensively uttered about the possible immense of impact on the global climate owing to the enhanced level of greenhouse gases concentrations on the atmosphere (Fischer et al 2002). The intergovernmental Panel on Climate Change (IPCC) reported that the global mean temperature has been increased 0.6oC during 20th century while the atmospheric concentration of carbon dioxide also increased from 280ppm to 370 ppm in third Assessment Report (TAR) published in 2001. Regional climate models of RegCM3 and PRECIS are performed for Carpathian basin assessment during the periods of 1961-1990 & 2071-2100. It is found that seasonal mean temperature simulation field, expect winter, are slightly underestimated by RegCM in Hungary. But they are overestimated by PRECIS simulation. Except autumn, other seasonal precipitation fields over Hungary are usually overestimated by RegCM simulation with the largest bias values in spring (Bartholy et al 2009). Climate change in the past decade in Jianghuni valley is studied by using statistical downscaling techniques. Both frequency and strength of extreme climate events such as hot weather, droughts and floods have increased remarkably since 1990s. PRECIS also is used to provide future climate prediction over the valley. The results give an average surface warming of 2.9oC under the SRES B2 emission scenario by the end of this century (2071-2100). They found that precipitation may increase on the same period (Tian et al 2006). Regarding to the role of climate change simulation in agricultural, water resources and other economical sectors, the skill of PRECIS regional climate model in simulation of the mean monthly temperature of Iran during 1961-1990 has been studied in this research.Methodology and DataIn this paper PRECIS regional climate model that has been developed by Hadley Center of United Kingdom Meteorology Office are used. PRECIS is a hydrostatic version of the full primitive equation, i.e. vertical acceleration in the atmosphere is assumed to be smaller than hydrostatic equilibrium and hence vertical motions are diagnosed separately from equations of state. It has a complete representation of the Carioles force and employs a regular latitude- longitude grid in the horizontal and a hybrid vertical coordinate. A terrain following σ-coordinate is considered at the lower four levels with purely pressure coordinate at the top three levels. The model has 19 vertical levels in the atmosphere and 4 levels in the soil. The PRECIS RCM model can be run at two different horizontal resolutions of 0.44°×0.44° and 0.22°×0.22°. The validation of model has been done by comparing observation data and model output data with two different methods of region to region and station to station. In this study, the model domain covers 23 to 45 degree in north and 43 to 68 degreeineast and its horizontal resolution is 50 x 50 km. The HadAM3P global data set is used to drive the PRECIS model. The horizontal resolution of the HadAM3P boundary data is 150 km. It covers the period of 1960-1990 and 2070-2100 respectively (Wilson et al 2005). The first year in each PRECIS experiment is considered as a spin-up period and these data are not used in any analysis. Period of study in this work is 15 years including 1976-1990. Discussion and Results Masoudian temperature zoning of Iran (Masoudian 2008) is considered for computing regional bias of the model simulations. In this approach, temperature regions of Iran have been categorized in 6 regimes of coldcool, mild, semi- warm, warm and hot. So, monthly to annual bias and standard deviation of the model outputs have been calculated using region to region method. Table 1 show that minimum and maximum annual biases have been found in cold and mild regimes with -0.3 and -2.2°C, respectively. Statistical analysis confirmed that mean and standard deviation of the observed and modaeled data are same. In this regard, F and t statistical tests show that there is no significant difference between modeled and observed data.ConclusionAs a main result, PRECIS skill in modeling regional temperature and mean temperature of Iran is well. Minimum and maximum biases of modeling over the country are -3.2 for January and 0.1°C for April and September. At monthly modeling, Validation of standard deviation shows that modeling without Sulfur cycle has lower error than modeling with Sulfur cycle included. There is no significant difference between PRECISmodeled data and actual data retrieved from weather stations. So, as a powerful regional model, PRECIS can be used for regional climate modeling over Iran and future climate change projections.

IntroductionOccurrences of heavy rainfalls depend on atmospheric circulations, geographical position and topography which lead to flash floods. They are considered as a serious threat for human beings and their properties. A major challenge associated with flash floods is the quantitative character of summer rainfall forecast. During the summer mainly in August (2001-2007), some synoptic patterns have produced wide spread heavy rain in Golestan area. Deep, moist convection normally occurs during warm season when high moisture content is possible and buoyant instability promotes strong upward vertical motions, then severe precipitations occur most frequently in the mountainous areas of Golestan province. Historically, lack of data in mountainous area makes the investigation difficult. The impact (and cost) of sever precipitations and flash flood occurrences in Golestan province has increased. Therefore, it is necessary to understand conditions that lead to heavy showers over Golestan area. In this study weather patterns leading to heavy rain falls within 7 years 2001-2007), in Golestan province are investigated. For this purpose, synoptic scale patterns have been investigated by using meteorological data and maps.Materials and methodsGolestan province is located between 36° 44΄ N (north latitude) to 38° 05΄ N and 53° 51΄ E (East longitude) to 56° 14΄ E. Summer extreme precipitation events was sometimes considerable during the recent years which produced flash floods in Golestan area, and financial losses, and fatalities had a lot to follow. The purpose of this study is to determine the pressure patterns in summer seasons that produced heavy rain falls in Golestan province. Actual weather charts at standard pressure levels and total precipitation of meteorological stations from Iran meteorological organization and also gridded sea level pressure (SLP) and 500-hpa geo-potential height data from the National Center for Environmental (NCEP) were used to the synoptic analysis. These data analyzed at 0000 and 1200UTC were prepared for the summer flash floods cases from four days before flash flood occurrence in the period of 2001-2007 over Golestan (Table 1). But here, given the limited volume of the paper, only a few maps are presented. Also, total daily precipitation of meteorological stations has investigated for theevents of Golestan floods. Finally the characteristics of effective patterns atmospheric to produce summer severe precipitations in the area are offered.Results and DiscussionThe heavy rain falls and flash floods are not typical of usual summertime regime in Golestan. The summertime heavy rain falls and storms are examined synoptically by compositing sea level pressure, 850mb and 500mb height data. All types of events are controlled by the lower and upper-level flows. This typically involves, for flash floods, the intrusion into Caspian sea of a surface high pressure ridge in the northerlies with attendant cold air advection and passing the inverted tough in 500mb height from north to southeast over Caspian sea and additionally, a few days before the occurrence, enhanced upper ridge and warm air of the subtropical anticyclones with associated heat low pressure over the region and southern Caspian sea. In conjunction with intense surface heating and topographic effects, these produce widespread atmospheric destabilization over the mountain area in Golestan. In the Golestan region, cutoff lows over Oral Lake are also to be important triggers for summer heavy rainfall primary due to instability created by their cold temperatures at mid-troposphere level.ConclusionThe results indicate that the synoptic-scale forcing such as short waves (inverted and shallow troughs) in mid troposphere, cold advection and penetration of high-pressure systems on Caspian Sea play an effective role in the summer heavy rainfall episodes in Golestan province. Within the days before the heavy rainfall period,temperature increase in low level troposphere (850hPa) in the region leads to significant evaporation in the environment and prepares considerable capacity for acceptance of humidity. Then, pass of middle shallow and inverted troughs and high-pressure penetration afterwards and existence of Alborz mountains, leads to rising of warm and humid air in low level and availability of cold air in mid atmosphere that provides suitable conditions to form potential thunder storms and cumulonimbus clouds which can cause heavy showers. Therefore, penetration of the high pressures result in establishment of the northern cold and dry flows over the Caspian Sea and transition of humid to northern Alborz slopes (southern Caspian sea), coincide with the advection of cold air in low levels of atmosphere most importantly in 850hP and crossing of inverted troughs, are the main factors of causing torrential rains in the region.

As fluctuations of ocean and sea levels on coasts especially on coastal shapes and also process of morphogenesis of it, study of these fluctuations and its causes is needed. Level fluctuations can be divided to short-term and long-term. Waves derived from wind, pressure from metrological elements and temperature are short-term elements and surface winds are most important among others on temporary sea level. Water level changes in Hormuz strait area has been studied based on the data obtained from Bandar Abbass station during 1990-1998 periods. The length of Persian Gulf as a branch of The Indian Ocean is about 990 km, its maximum width is about 330 km (at Hormuz strait about 60 km) and its depth is about 100 m. The Persian Gulf is connected to Oman Sea via Hormuz strait.Materials and MethodsIn the present study, first of all, correlations between atmospheric elements such as pressure, temperature and the density of wind energy (independent variables) with sea level changes are studied by drawing the graphs and then linear regression graphs of pressure and temperature and the density of wind energy (seasonal) with sea level changes for a 9-year period (1990-1998) and their correlation coefficient are calculated. Furthermore, wind energy calculated using empirical relationships in the area and equation of sea level changes prediction has beenobtained for the coast of this region.Results and discussionSea level changes: the results of the present study show that sea level changes can be divided into two types in the coast of this region. Temporary changes lasting from a few hours to several days and permanent changes that is seasonal and may last for several months. Air pressure changes: air pressure changes at sea level is inversely related to the water level changes in this region that means that with decreasing air pressure at sea level, water level increases and vice versa (pressureinversion effect). Using data from meteorological stations and tidal station in the region, it is distinguished that there is a strong negative correlation (-0.83) between air pressure and sea level.Effects of air temperature: air temperature has two contrastive and seasonal effects on water level. There is a strong positive correlation (0. 812) between air temperature and sea level in Bandar Abbass. In summer, air temperature increase due to seawater heating causes reduction in seawater volume, increasing salinity and density of seawater as well as increasing the volume and reduction in seawater density due to volume expansionof seawater. In winter, air temperature decrease due to seawater temperature reduction causes reduction in seawater volume, increasing the density of surface waters due to volume contraction of seawater. Effects of wind characteristics: it is distinguished that wind velocity and consequently wind power is low in the Spring based on average of wind velocity and wind power graphs in different months of the year. In summer, the power and velocity of wind increase and in autumn the increasing status will continue and in the winter they reach to a peak. In general, whenever the wind velocity was high, the wind power increased too. By studying the simultaneous wind velocity variations, the density of wind energy with sea level changes in this region, it is distinguished that sea level coming up by the start of wind (landward) and reaches to a peak and sea level retard with wind velocity decrease and come back to its former level.ConclusionIt would be concluded that there is significant correlations between temperature and pressure with sea level fluctuations and these fluctuations are seasonal. With maximum value in summer and minimum in spring and winter. When the wind starts to blow, sea levels swells and reach to maximum.An average of correlation coefficient for Bandar Abbass station was 0.733 that showed the relation between wind velocity and sea level fluctuations; these fluctuations will influence on erosion process into delta in coastal

IntroductionThe recent scientific assessment of the United Nations Intergovernmental Panel on Climate Change (IPCC, 2007) acknowledges that there is increasing concerns that extreme precipitation events may be changing infrequency and intensity as a result of human influences on climate. The conceptual basis for changes in precipitation has been detailed among many experts, and numerical climate models consistently predict an increase in extreme rainfall events in many parts of the world given the continued buildup of greenhouse gases (IPCC, 2007). In simplest terms, warming of the planet increases evapo-transpiration rates, a warmer atmosphere potentially holds more water, the higher moisture levels and temperatures tend to destabilize the atmosphere, and changes then occur in the type, amount, frequency, intensity, and duration of precipitation(Sen 2004). While the theoretical basis for expecting an increase in extreme precipitation is well-developed, many climatologists have examined records from throughout the world in an attempt to identify trends in extremerainfall events. Although it is difficult for drawing a consistent picture of changes in all over the world. Regional studies show increasing precipitation during 20th century over several regions of the world while extreme droughts were reported in some regions. In this investigation, Zanjan city is studied for trends in extreme precipitation. Extreme weather and climate events have received increased attention in the recent years due to their potentials for severe and adverse impact on human life, civil infrastructure, and natural ecosystems. Accordingly extreme climatic events have drawn more and more concerns from public, government and academic circles because of the tremendous impacts on environments. Data and Study areaThe study area is Zanjan city that located in Northwest of Iran. The main factors governing Zanjan climate are the high latitude and mountains of this region. The elevation is about 1600 m at the synoptic station.Historical daily precipitation data are available from 1961 to 2006 for this weather station. The data were obtained from the Islamic Republic of Iran Meteorological Organization (IRIMO). Prior to creating the daily databases, the station data time series were evaluated for potential irregularities through time. Then, from the daily data it has been created the annualized data throughout the 1961-2006 study periods. In the end, it has been annualized the precipitation for each year.Methods and IndicesThe objective of this investigation is to analyze trends in various extreme rainfall indices computed from Zanjan synoptic station in Northwest of Iran. Any review of the recent literature will reveal a large number of indices used to represent temporal and/or spatial variations in extreme precipitation events (IPCC, 2007). Many scientists have used measures of extreme frequency that count the number of events each year above fixed threshold values (e.g., events > 100 mm per day) or above thresholds determined by the precipitation climatology at individual stations (e.g., events > 95th percentile). Others have focused on extreme intensity levels with choices ranging from the largest one-day event to the mean of the events in the 95th percentile to the annual total divided by the number of rain days. Other popular choices involve quantifying the proportion of annual precipitation coming from extreme events (e.g., total from events in the 95th percentile/annual total). In some cases, it can be surprisingly difficult to determine exactly how the researcher provides various definitions of extreme events. Furthermore, it is not clear how these various indices of extreme rainfall events are related to one another, and how the selection of the indices influences the resulting temporal or spatial variations. It has carefully examined the methods used to quantify extreme rainfall events in many recent articles and found dozens of often redundant indices that generally fall into three broad categorie

Today accessibility to bioclimatology data is essential for application sciences including Tourism, Sport, medicine and et al. Climate-comforting conditions usually are expressed by indexes which a series of meteorological, human and environmental factors have been played a role in, and the possibility of comparison among different places is provided by. Since the 1960s, heat balance models of the human body have become more and more accepted in the assessment of thermal comfort. The basis for these models is the human energy balance equation. One of the first and still very popular heat balance models is the comfort equation defined by Fanger 1972). Comfortable climate condition generally states by indexes that involve the sets of meteorology, humanities and environmental elementary. Several thermal indices such as Predicted Mean Vote (PMV), Physiologically Equivalent Temperature (PET) and Standard Effective Temperature (SET) may be calculated for the assessment of human bioclimatics in a physiologically relevant manner as shown in several applications (Matzarakis et al., 1999; Blazejczyk, Matzarakis, 2007; etc). All indices have the known grades of thermal perception for human beings and physiological stress (Hoppe, 1999). PET is defined as a certain air temperature related to fixed standard indoor conditions at which the heat balance of the human body is maintained with core and skin temperature equal to those under the conditions being assessed. In this research, PET index has used for the mapping of Comfortable Climate inKhorasan Razavi province on monthly scale*.Materials and methods In the present study, Khorasan Razavi province has been mapping using PET index in monthly scale. For this purpose, first the daily scale of climate comfort index is calculated in the 14 number stations within the region. Then the results remove to ArcGis software for mapping. For extend result calculated to region study surface have been used Arc Gis software and karging interpolate method. The index used is physiologic equivalent temperature (PET). This index derived from body energy balance model. The Munich energy balance model for individuals” (MEMI) (Höppe 1993) is such a thermo physiological heat balance model. It is the basis for the calculation of the physiologically equivalent temperature (PET). In detail the MEMI model is based on the energy balance for the human body: M +W + R +C + ED + ERe + ESw + S = 0 The individual heat flows in Eq. 9. 1, are controlled by the following meteorological parameters (Verein Deutscher Ingenieure 1998; Höppe 1999):– Air temperature: C, ERe– Air humidity: ED, ERe, ESw– Wind velocity: C, ESw– Mean radiant temperature: RThermo-physiological parameters are required in addition:– Heat resistance of clothing (clo units)– Activity of humans (in Watt)The following assumptions are made for the indoor reference climate Frequency indicatorsFor each year, it has been determined the number of days with the threshold for the 1st, 5th, 10th, 90th, 95th and 99th percentiles based on the data for all years and identified the longest consecutive rain day streak for each year and station. Amount indicators All of the measures are used to check out the precipitation amount from each percentile.Extreme ratio The six indices, divided by the annual total precipitation; to find out the ratio of every percentiles precipitation in annual precipitation.All three categories indices have tested for long term changes (trend) based on Non- Parametric methods. The Non-Parametric trend analysis is used to analyze the trends of the frequency, amount and ratio of six indices of precipitation extreme for Zanjan station. The magnitude of a trend in a time series is estimated using a nonparametric approach hereinafter is: i j i j T T Z Z b median − − = Where b are estimate of the slope of a trend and i Z is the i-th observation in time of T. The slope determined is a robust estimate. For the non-parametric estimate of trend, the slopes b are computed between each possible pair of data points. Also Periodicities features in the time series of extreme events were analyzed by means of spectrum analyses.DiscussionPrecipitation amounts of extreme events are stable except in first and 95th percentile of precipitation that experienced a jump in 1980s as well as decreasing trends. There are same trends in precipitation ratio of extreme events and in days with extreme. There are about 2-3 year's cycles in first, 95th and 99th percentile in 99 confidence interval as well as 2, 37 year's cycles in first percentile.As a result of this study it could be concluded that the days with extreme events have reduced during recent decades, while the precipitation is stationary. So that the intensity of precipitation of Zanjan decreased during recent decades.Results and DiscussionClimate change could be investigated by frequency distribution centers (mean) studying as well as by tiles of frequency distributions (extremes). Because of tempo-spatial patterns dominant on climate change, the extreme values are determine by this patterns. So that the extreme values changes isnt the same in all time and places. Accordingly finding out climate change study needs to be in high resolutions in time and space. Finding out climatic extreme, different indices have been definite by scientific organization and experts. However in this investigation, we assembled daily precipitation records for Zanjan stations in Northwest of Iran over the period 1961-2006 and calculated 18 different annual indicators of extreme precipitation events that have been widely used in the professional literature. It has been used various unvaried statistical procedures to find significant trend in the occurrence of extreme events (extreme precipitation amount, frequency and ratio to total precipitation). There were two kinds of changes. The first is trends in precipitation extremes based on non-parametric technique. The second is cyclic behavior of precipitation. There is a decrease trends in total and ratio of first and ninety five percentileofprecipitation as well as a jump in 1980 to lower level. Also there are a 2-3 year cycles in all percentile indices. The frequency of first percentile also has reduced trends.