Journal of Spatial Analysis

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Climatic extremes are the special status (high or low) of climatic elements. In spite of the unique definition, there are a lot of thresholds which have been illustrated for extremes. For example, Bonneted (2006) has defined the climatic extremes as intensive and abnormal events that include the lowest and highest values in a time series. Becker et al. (2007) have referred to the extremes of climate as events in every given point that exceeds a special threshold in that place. High extremes and the upper tail of precipitation distribution of frequency have attracted a lot of attention of experts. The thresholds of extremes have been chosen based on geographic situations. The Joint World Meteorological Organization Commission (CCL) for Climatology on Climate Variability and Predictability (CLIVAR) Expert Team on Climatic Change Detection, Monitoring and Indices (ETCCDMI) have been established in 1998 in order to study and determine the indices of climatic extremes. They have introduced quintile indices. Due to consequences of extreme precipitation characters e.g. frequency, duration and intensity, the precipitation extremes have been in the center of attentions of many branches of science. Some experts call these events as social challenges that can determine economic sustainable development.  Extremes analyses are based on investigating the tails of statistical distribution of daily observations, because the longest time scale couldn’t show what it should have shown for extremes. Heavy precipitation for each day is defined as precipitation which is more than normal precipitation of that day in every given place. For this amount of precipitation absolute and relative thresholds have been defined. In present research, heavy precipitation is defined based on relative index and percentile parameter. By using 90th percentile, some characters of tempo-special distribution of extreme precipitation in Northwest of Iran are analyzed based on 729 stations. Northwest of Iran includes four province East and west Azerbaijan, Ardabil and Zanjan. This part of country has 126544.4 and occupied 7.2% of the entire country mainland. Geographic location of Northwest of Iran is located between the following coordinates:    The averages of sea level pressure (SLP) and 500 hp level patterns have been examined. Therefore, two data groups, station based and atmospheric based, have been used. Station based data include precipitation measurements during 1968-2007 synoptic , climatology and rain gauge stations related to Islamic Republic of Iran Meteorology Organization (IRIMO), rain gauge stations of Ministry of Power. Kriging Method is used as optimum interpolation method in order to provide maps of 14975 days. The pixel size of interpolation is chosen with 33× 33 kilometers dimension (approximately 116 pixel). Thus, data set of northwest precipitation with 14975 × 116 dimension and S-mode have been arranged. Atmospheric data include SLP and 500 hp data have been derived from NCEP/NCAR. The area experiencing heavy precipitation from 10-20 to 60-70 percent have been investigated. The map average and precipitation and precipitation center for all of these cases have been estimated. Some characters, for instance tempo-spatial presentation of heavy precipitation has determined by using Geostatistics Methods. A 14975  116 pixel data network was defined. According to 6 categories of extreme precipitation have been recognized. These categories are based on the extent of the area under extreme precipitation. It has been discovered 6 categories 10-20 percent to 60-70 percent of space under investigation. With the average increase of extreme precipitation amounts, the central mean of precipitation has centralized and the isohyets have become irregular. The small change in central mean of precipitation, a serious change had happened in precipitation distribution.   Mean of SLP pattern showed Siberian high pressure system that extended from east to west and indicated positives anomalies. low pressure system in the Red sea which is extended to Europe region and its extension to eastern of Mediterranean sea, south and north of Saudi Arabia as well as its extension to northwest and sometimes the whole west parts of Iran, formed an area with negative anomalies. The low pressure system which was close to European high, formed extreme pressure gradients. In the 500 hp level, the northwest of Iran is in front of the trough which is located in the east of Mediterranean Sea. As the depth of the trough increased, the area where experiencing heavy precipitation increased and the axis of the trough changed from vertical into horizontal shape. The occurrence of the trough formed negative anomalies in the area. In all cases, there are two ridges immediately in west and east of the trough  of the Mediterranean Sea. The occurrence of the western ridge caused cold air mass flowing in the trough where the Mediterranean’s warmer air mass exists and made the front’s formation possible. As the eastern ridge moved eastward, the area where experiencing heavy precipitation increased.

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The study of temporal - spatial changes of high extreme rainfalls in west of Iran (1965-2016)
 
 Extended Abstract
Introduction                                   
Rainfall is one of the appropriate weather parameters not only in describing weather condition in one specific area but also is in estimating potential impacts of climate change in the environment and in many economic and social systems. Some studies show that during half a century weather patterns by more and severe raining events and by changes in scheduling and rain status has been changed. From 1960s with its much slope, the abundance and severity of extreme rainfalls throughout the world has increased and it is expected to continue the increase until the end of the current century. So understanding the behavior of extreme events is one of the main aspects of climate change and the increase of information about heavy rains has utmost importance for society, especially for the population who lives in areas with increased flood risk.
According to above mentioned cases and abnormal behavior and irregular rainfalls in Iran and its high variability from one hand and Iran's west region ability to heaviness and extension of rainfalls on the other hand, the necessity of understanding and study of temporal and spatial dangerous rainfalls is recognized. Among extreme rainfall characteristics, the portion of such rainfalls in total rain production is studied less.   Due to the experiments carried out, the increase of annual rainfall in Iran happens through heavy rainfalls. Therefore heavy rainfall portions out of total annual rainfalls can be defined as an index of crisis. The increase of this index implies the heavy floods in rainy years and severe drought and drought years.
 
Data and Method
Iran's west region including East and West Azerbaijan provinces, Zanjan, Kurdistan, Kermanshah, Hamadan, Lorestan, and Ilam consists of about 14 percent of Iran's total area. The height of this region includes a domain of 100 to about 4000 meters. Zagros mountain ranges are the most important characteristic of west of Iran, which are drawn from north-west to south-east.
In this research, we used network data from interpolation daily rainfall observation of 823 meteorology stations from January 1st up to December 31st, 2016 by using Kriging interpolation method and by separating 6×6 km spatial. The results formed matrix interpolation process by dimension of 18993×6410. This matrix has the rain status of 6410 points of west of Iran for every day rainfall (18993). Extreme rain falls are identified in terms of threshold of 95 percentile in each point and each day of year. The rainfall of each day and each pixel is compared to that related pixel and corresponding to that day and those days which their rainfalls rates were equal to or larger than threshold were identified for studying extreme rain fall portion in total yearly rainfall, the total of equal rainfalls and more than 95 percentile is calculated for each year and each of pixel and, it is divided to total of the same pixel rainfalls in that year.
We used the least squarely error for understanding temporal- spatial behavior of regression.
 
Results and Discussion
The average extreme rain falls in west of Iran is under the influence of their roughness and placement and also synoptic rainfall. The proof of this claim identifies through placement of average extreme rainfall over altitudes of region. By increasing geographical latitude in Iran's western provinces, it is decreased both of total extreme rainfalls and portion of such rainfall out of total yearly rainfall. Total extreme rainfall trend shows a frequency in a domain with 16 mm in each year. The negative trend of total rainfall with the area of 74.72 percent consists of three quarters of Iran's west.
The narrow strip of the west of Kurdistan and south-west of west Azerbaijan have the highest amount of positive trend which is meaningful in certainty level of 95 percent.
The study of process showed the ratio of extreme rainfalls portion to total yearly rainfall, which is increasing about 60.7 percent of west area of this country extreme rainfalls in total yearly rainfall and the greatest part of this area is located in southern half of the studied area.
The negative trend also is located in northern half and they have consisted of 39.29 percent of studied area of these, only in 29.81 percent of region, the trend ratio of extreme rainfalls to total yearly rainfalls are meaningful in certainty level of 95 percent.
Keywords: Extreme Rainfalls, Trend, 95 Percentile, Rainfall Portion, west of Iran.
 

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understanding the behavior of extreme events is one of the main aspects of climate change.
In this research, we used network data from interpolation daily rainfall observation of 823 meteorology stations from January 1st up to December 31st, 2016 by using Kriging interpolation method and by separating 6×6 km spatial. The results formed matrix interpolation process by dimension of 18993×6410. This matrix has the rain status of 6410 points of west of Iran for every day rainfall(18993). Extreme rain falls are identified in terms of threshold of 95 percentile in each point and each day of year. for studying extreme rain fall portion in total yearly rainfall, the total of equal rainfalls and more than 95 percentile is calculated for each year and each of pixel and, it is divided to total of the same pixel rainfalls in that year. We used the least squarely error for understanding temporal- spatial behavior of regression. By increasing geographical latitude in Iran's western provinces, it is decreased both of total extreme rainfalls and portion of such rainfall out of total yearly rainfall. Total extreme rainfall trend shows a frequency in a domain with 16 mm in each year. The negative trend of total rainfall with the area of 74.72 percent consists of three quarters of Iran's west. The narrow strip of the west of Kurdistan and south-west of west Azerbaijan have the highest amount of positive trend which is meaningful in certainty level of 95 percent. The study of process showed the ratio of extreme rainfalls portion to total yearly rainfall, which is increasing about 60.7 percent of west area of  this country extreme rainfalls in total yearly rainfall and the greatest part of this area is located in southern half of the studied area. The negative trend also is located in northern half and they have consisted of 39.29 percent of studied area of these, only in 29.81 percent of region, the trend ratio of extreme rainfalls to total yearly rainfalls are meaningful in certainty level of 95 percent.
 

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Introduction
Geographical situation of Iran is a place for interacting many physical and human processes which lead to specific precipitation climatology in the country. The month to month variation of precipitation is one of  the features which the precipitation climatology may reflect due to tempo - spatial characteristics. In fact, monthly distribution of precipitation is one of precipitation normal features building up the climate structure. In order to recognize this fundamental characteristic three following questions have been raised:
1) Have the month to month distribution of precipitation changed over recent four decades?
2) How is the pattern of relationship of month to month distribution of precipitation and spatio - topographical variables?
3) Is it possible to find a spatial pattern for decadal changes of precipitation of month to month distribution?

Data and Methods
In order to find a responses for the abovementioned questions the distribution of month to month precipitation and its decadal changes was considered by adopting coefficients of variations (CV) for 46 years (1970-2016)  and using the third version of Asfazari dataset. The relationship of precipitation data and spatio-topographical variables calculated based on regression techniques. Moreover, the spatial pattern considered by using cluster analysis.  The CV calculated as follow:

here ،،  are ith raw's and jth column's CV, standard deviation, and monthly mean, respectively.
CV and its relationships with spatio-topographical variables were calculated in two temporal scale, for whole the under investigation period (1970-2016) and in decadal period for four decades (1977-1986, 1987-1996, 1997-2006, 2007-2016).
Discussion
 The results of current study proved that the month to month different in precipitation amounts have had spatial variations, whilst the temporal trends is not statistically significant. In addition, the minimum, maximum, and consequently, the range of values also the averages have not experienced significantly changes. However, the region experiencing the same values of precipitation illustrated oscillatory behavior. Accordingly, the decadal variations have happened in different areas. Although the there have been statistically significant relationships between monthly CV and spatio - topographical factors, the correlations were low. Based on cluster analysis, we found 5 regions according to CV and its anomalies in compares with normal CV for all under investigation period. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns.
Results
Precipitation is known a chiastic and complicated climate element. One of chiastic behaviors which precipitation shows in its different time - scale behavior is its month to month distribution among a given year. In current research the decadal variation of  above-mentioned behavior among recent four decades and the variation of its relationships and the spatio - topographical features , as parts of climate structure of the country, have investigated in details. 
Our finding illustrated that the month to month different in precipitation amounts have had tempo - spatial variations, whilst the temporal long - term trends is not statistically significant. Moreover, the values of minimum, maximum, and consequently, the range of month to month CV also the decadal averages have not experienced significantly changes over four under study decades. However, the region experiencing the same values of precipitation depicted oscillatory behavior. consequently, the decadal variations have happened in different areas. Although there have been statistically significant relationships between monthly CV and spatio - topographical variables, the correlations were not considerably high. Based on cluster analysis technique, we found 5 regions according to CV and its anomalies in compares to normal CV for all under study decades. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns.

KeyWords: Iran precipitation, Month to month changes in precipitation, Inter annual variation of precipitation, Precipitation anomaly, Spatial analysis of precipitation

 

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The expansion of the pole toward the tropical belt is thought to be due to climate change caused by human activities, in particular the increase in greenhouse gases and land use change. The variability of the tropical belt width to higher latitudes indicates the expansion of the subtropical arid region, which indicates an increase in the frequency of drought in each hemisphere. In order to change the width of the tropical belt of the Northern Hemisphere in the middle offerings, indices of  precipitation minus evaporation, wind vector orbital component, stream function, tropopause surface temperature, OLR, and SLP have been used. Findings showed that the expansion of tropical belt latitude with stream function to higher latitudes with 1° to 3° latitude and the effect of Hadley circulation subsidence has increased the amplitude of evaporation minus precipitation has shown that the fraction of precipitation minus evaporation 1° to 3° latitude geographically increased. The subtropical jet has increased the movement of the upper branches of troposphere from the Hadley circulation by 2° to 4° latitude, which can have a negative effect on transient humidification systems as well as on the amount of precipitation. The extension of the pole towards the tropical belt, which is a consequence of climate change and hazards, will lead to the displacement of the pole towards the tropical side of the river, thus providing dry tropical belts to the pole; Also, the long-wave radiation of the earth's output has increased by 1° to 2° latitude and has caused an increase in heat in the upper troposphere, which has increased the dryness and slightly reduced the clouds in the upper troposphere and also caused the tropical belt to expand to higher latitudes. Has been. In general, the research findings showed that most tropical belt indicators have been increasing since 1979.

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In the present study, the data of the ECMWF for a period of 1979 to 2018 was adopted to analyze the long term changes (trends) of the number of cyclones centers of the Mediterranean Sea.There are many methods (e.g. parametric and non- parametric)  for examining changes and trends in a given dataset. The linear regression method is of parametric category and the most common nonparametric method is Mann-Kendall test. By fitting the Mann-kendall model and the linear regression model, the frequency of the cyclone centers of the Mediterranean basin was evaluated in seasonal and annual time scales. Analyzing the trend of changes of the number of cyclone centers on a seasonal scale showed that the five-day duration have had a significant trend in spring, autumn and summer. Whilest on an annual scale, there was no significant trend in any of the duration. By fitting the regression model on seasonal and annual scale, one- and two-day duration have a positive regression line slop.

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Simulation of Zanjan temperature trends based on climate scenarios and artificial neural network method

Abstract
Severe climate changes (and global warming) in recent years have led to changes in weather patterns and the emergence of climate anomalies in most parts of the world. The process of climate change, especially temperature changes, is one of the most important challenges in the field of earth sciences and environmental sciences. Any change in the temperature characteristics, as one of the important climatic elements of any region, causes a change in the climatic structure of that region. The summary of the investigated experimental models on climate change shows that if the concentration of greenhouse gases increases in the same way, the average temperature of the earth will increase dangerously in the near future. More than 70% of the world's CO2 emissions are attributed to cities. It is expected that with the continuation of the urbanization process, the amount of greenhouse gases will increase. According to the fifth report of the International Panel on Climate Change, the average global temperature has increased by 0.85 degrees Celsius during 1880-2012. Therefore, knowing the temperature changes and trends in environmental planning based on the climate knowledge of each point and region seems essential. For this reason, the present study simulates the daily temperature (minimum, maximum and average) of Zanjan until the year 2100.

Research Methods
The method of conducting the research is descriptive-analytical and the method of collecting data is library (documents). To check the temperature of Zanjan city, the minimum, maximum and average daily temperature data from Hamdeed station of Zanjan city during the period of 1961-2021 were used. The data of general atmospheric circulation model was used to simulate climate variables (minimum, average and maximum temperature) using artificial neural network and climate scenarios in future periods. The output variables in this study are minimum, maximum and average daily temperature. Therefore, three neural network models were selected. For model simulation, model inputs (independent variables) need to be selected from among 26 atmospheric variables. Therefore, two methods of progressive and step-by-step elimination were chosen to determine the inputs of the model. In these methods, climate variables that have the highest correlation with minimum, maximum and average daily temperature were selected. By using RCP2.6, RCP4.5 and RCP8.5 scenarios, variables were simulated until the year 2100. Markov chain model was used to check the possibility of occurrence of extreme temperatures of the simulated values.

results
According to the RCP2.6, RCP4.5 and RCP8.5 scenarios and the simulation made by the neural network model, it is possible that on average the minimum temperature will be 3.6 degrees Celsius, the average temperature will be 3.3 degrees Celsius and the maximum temperature will be 2.7 degrees Celsius. Celsius will rise. The monthly review of the simulated data for all scenarios and the observed data of the studied variables shows that the average minimum, average and maximum temperatures in January and February, which are the coldest months of the year, will increase the most and become warmer. While the average minimum temperature in August, the average temperature in April and the maximum temperature in October will have the least increase. According to the simulated seasonal temperature table based on all scenarios, it was found that the average minimum, average and maximum temperature observed with the maximum simulated conditions were 6.9, 5.5 and 5.4 respectively in the winter season, and 3.3 in the spring season. 4, 2.3 and 3, in the summer season it increases by 3.3, 3.4 and 1.4 and in the autumn season it increases by 4.6, 4.5 and zero degrees. The frequency of extreme temperatures observed in all three variables of minimum, average and maximum temperature for the 25th and 75th quartiles is less than the number of occurrences of extreme temperatures simulated in all three scenarios. Based on this, all three variables will increase and there will be fewer cold periods. An increase in night temperature and average temperature in winter season and maximum temperature in summer season will occur more than other seasons. The difference between day and night temperature will be less in autumn and summer. Also, all seasons, especially the summer season, will be hotter and the occurrence of extreme temperatures is increasing for the coming years.

Keywords: climate scenarios, simulation, extreme temperatures, artificial neural network, Zanjan