Journal of Spatial Analysis

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We can identify the flood not only considering circulation pattern in occurring day but also by studying circulation pattern a few days before fresh event. This subject has mutual approach. In one hand, it indicates  that circulation patterns which were before flood event have important role in determining the conditions and moisture content of studied area and playing the fundamental role in few coefficient of region because it determines the previous moisture. On the other hand, it indicates that we should tracking the rain-genesis synoptic systems from source to end place of their activity for studying floods and their meteorology factors which have created them. By this way, we can acquire more comprehensive recognition about the relationship between circulation pattern and floods. In the other words, the identification of synoptic patterns that have created the flood reveals not only the mechanism of their emergence but also is useful for prognosis and encountering with them. The extensive researches have been accomplished about Inundation in the world and Iran, but Iran haven’t much antiquity about synoptic researches. For foreign researches, we can name researchers such as Hireschboeck (1987), Kutiel et al(1996), Komusce and et al (1998), Krichak  and et al (2000), Rohli and et al (2001), Kahana (2002), Teruyuki Kato(2004), Ziv and et al (2005), Carlalima and et al (2009). The numerous researchers have studied the Inundation climatology in internal of country such as Bagheri (1373), Ghayour (1373), Kaviani and Hojatizadeh (1380), Moradi (1380), moradi (1383), Mofidy (1383), Masoodian (1384), Masoodian (1384), Hejazizadeh et al(1386), Parandeh Khozani and Lashkari (1389). In this research, we considered the heavy precipitation of Azar 1391 in southwestern of Iran that resulted in flood phenomenon in the cause and effect manner so that can do necessary prevention actions before occurring the flood for preventing the probable damages and optimal use of precipitations by forecasting the patterns that have created the flood.

In this synoptic study, we need to two database: one group is variables and atmospheric data consisting of geopotential height of 500 hpa level (in meter geopotential), zonal wind and meridional wind (in m/s) and special humidity (in gr/kg) during this times 00:00, 06:00, 12:00 and 18:00 Greenwich in 0-80° northern and 0-120° eastern with local resolution of 2.5*2.5 Arc that have been borrowed from database of (NCEP/NCAR) dependent to National Atmosphere and Oceanography Institute of USA, and other group is daily precipitation data of region rain gauge stations during 4-8^th Azar of 1391 (24^th November – 28^th November 2012). In continuation. By applying the environment- circulation approach, we took action to drawing circulation pattern maps of 500 hpa level, thickness of atmosphere patterns of 500-1000 hpa and moisture flux convergence function from 4-8^th Azar of 1391 (that for calendar, conform with 48 hours before beginning the showery precipitation until ending the storm activity) by using data which obtained from database of NCEP/NCAR and the synoptic conditions of above flood have been studied and interpreted in the region.

Flood is one of the most destructive natural hazards that have imposed and impose many damages to people during the history. Hence, the final aim of this research is to explain the key interactions between atmosphere and surface environment and in other words exploration of the relationship between circulation patterns leading to the flood generating precipitation in the southwestern of Iran for forecasting the time and intensity of showers occurrence that lead to flood. For this purpose, by applying environmental-circulation approach, the circulation patterns identified and studied which resulted in flood generating precipitation. The result of this research indicated that torrential precipitations in the region have formed the deep trough in days 4-8 of Azar on the east of Mediterranean and the studied region placed in the east half of this trough that is the location of atmosphere instability. At same time, thickness patterns, indicate the flux of cold air from northern Europe to lower latitudes and spreading the warm air of north of Africa to latitude 50° northern. As a result we expected the frontal discontinuity in the encountering place of these two air mass. Analysis of the moisture flux convergence patterns also indicated that torrential precipitations were the result of moisture flux from Mediterranean and Persian Gulf; and Red Sea and Arab Sea taken into account as reinforced sources.

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Drought is the most important natural disaster, due to its widespread and comprehensive short and long term consequences. Several meteorological drought indices have been offered to determine the features. These indices are generally calculated based on one or more climatic elements. Due to ease of calculation and use of available precipitation data, SPI index usually was calculated for any desired time scale and it’s known as one of the most appropriate indices for drought analysis, especially analysis of location. In connection time changes, most studies were largely based on an analysis of trends and changes in environment but today special attention is to the variability and spatial autocorrelation. In this study we tried to analyze drought zones in the North West of Iran, using the approach spatial analysis functions of spatial statistics and detecting spatial autocorrelation relationship, due to repeated droughts in North West of Iran and the involvement of this area in the natural disaster.

In this study, the study area is North West of Iran which includes the provinces of Ardebil, West Azerbaijan and East Azerbaijan. In this study, the 20-year average total monthly precipitation data (1995-2014) was used for 23 stations in the North West of Iran. In this study, to study SPI drought index, the annual precipitation data of considered stations were used. According to the statistical gaps in some studied meteorological stations, first considered statistics were completed. The correlation between the stations and linear regression model were used to reconstruct the statistical errors. Stations annual precipitation data for each month, were entered into Excel file for the under consideration separately and then these files were entered into Minitab software environment and the correlation between them was obtained to rebuild the statistical gaps. Using SPI values drought and wet period’s region were identified and zoning drought was done using ordinary kriging interpolation method with a variogram Gaussian model with the lowest RMS error. Using appropriate variogram, cells with dimensions of 5_×5km were extended to perform spatial analysis on the study area. With the establishment of spatial data in ARC GIS10.3 environment, Geostatistic Analyze redundant was used to Interpolation analysis Space and Global Moran's autocorrelation in GIS software and GeoDa was used to reveal the spatial relationships of variables.

The results showed that most studied stations are relatively well wet and this shows the accuracy of the results of the SPI index. Validation results of the various models revealed that Ordinary Kriging interpolation method with a variogram Gaussian model best explains the spatial distribution of drought in North West of Iran. So, using the above method the stations data interpolation related to SPI index in North West of Iran was done. The results showed that Moran index values for the analysis of results of standardized precipitation index (SPI) in all studied years, is more than 0.95. Since Moran’s obtained values are positive close to 1, it can be concluded that drought, in the North West of Iran during the statistical period has high spatial autocorrelation cluster pattern of 90, 95 and 99 percent. Results also showed that in all the years of study, Moran's global index is more than 0.95 percent. This type of distributed data suggests that spatial distribution patterns of drought in North West of Iran changes in multiple scales and distances from one distance to another and from scale to another and this result shows special space differences in different distances and scales in this region of the country. Results also showed that drought in North West of Iran in 2008 is composed of two parts: Moderate drought in parts of West and North West region (stations of Maku, Khoy, Salmas, Urmia, naghadeh, Mahabad and Piranshahr) and severe drought in the southeastern part of the study area (stations: Sarab, Khalkhal, Takab, Tabriz and Mianeh). So the pattern of cluster drought in the North West of Iran in 2008 is on the first and fourth quarter. The results of this index showed that drought and rain periods are similar in the studied stations. The results of the application of Moran's index about identifying spatial distribution of drought patterns showed that The values of the different years during the period,  have a positive a positive coefficient close to 1 (Moran's I> 0.959344) and this shows that the spatial distribution of drought is clustered. The results of the standard score Z values and the P-Value proved the clustering of spatial distribution of drought.

The results of the analysis of G public value, In order to ensure the existence of areas with clusters of high and low values showed that The stations of Maku, Khoy, Salmas, Urmia, naghadeh, Mahabad, Piranshahr and Parsabad follow the moderate drought pattern in the region and are significant at the 0.99 level. Jolfa station also has a mild drought of 0.95 percent confidence level and for Sardasht station is significant in 0.90 percent. High drought pattern in Sarab, Khalkhal, Takab, Tabriz and Mianeh stations was significant in 0.99 percent level and also for Ardabil, Sahand and Maragheh stations very high drought pattern was significant in 0.95 percent level and for Meshkinshahr and Ahar high drought pattern is significant in 0.90 percent. By detection of clusters of drought and rain in the North West of Iran using Moran’s spatial analysis technique and G general statistics a full recognition of the drought affected areas in this region can be obtained and take the necessary measures in its management 

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Understanding the changes in extreme precipitation over a region is very important for adaptation strategies to climate change. One of the most important topics in this field is detection and attribution of climate change. Over the past two decades, there has been an increasing interest for scientists, engineers and policy makers to study about the effects of external forcing to the climatic variables and associated natural resources and human systems and whether such effects have surpassed the influence of the climate’s natural internal variability. The definitions used in the 5th assessment report were taken from the IPCC guidance paper on detection and attribution, and were stated as follows: “Detection of change is defined as the process of demonstrating that climate or a system affected by climate has changed in some defined statistical sense without providing a reason for that change. An identified change is detected in observations if its likelihood of occurrence by chance due to internal variability alone is determined to be small.  Attribution is defined as the process of evaluating the relative contributions of multiple causal factors to a change or event with an assignment of statistical confidence”. Detection and attribution of human-induced climate change provide a formal tool to decipher the complex causes of climate change. In this study the optimal fingerprinting detection and attribution have been attempted to investigate the changes in the annual maximum of daily precipitation and the annual maximum of 5-day consecutive precipitation amount over the southwest of Iran.

This is achieved through the use of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources Project(APHRODITE) dataset as observation, a climate model runs and the standard optimal fingerprint method. To evaluate the response of climate to external forcing and to estimate the internal variability of the climate system from pre-industrial runs, the Norwegian Climate Center’s Earth System Model- NorESM1-M was used. We used up scaling to remap both grid data of observations and simulations to a large pixel. This remapped pixel coverages the area of the southwest of Iran. The optimal finger printing method needs standardized values like probability index(PI) or anomalies as input data, since the magnitude of precipitation varied highly from one region to another. The General Extreme Value distribution (GEV) is used to convert time series of the Rx1day and Rx5day into corresponding time series of PI.  Then we calculated non-overlapping 5-year mean PI time series over the area study. In this research, we applied optimal fingerprinting method by using empirical orthogonal functions.  The implementation of optimal fingerprinting often involves projecting onto k leading EOFs in order to decrease the dimension of the data and improve the estimate of internal climate variability. A residual consistency test used to check if the estimated residuals in regression algorithm are consistent with the assumed internal climate variability. Indeed, as the covariance matrix of internal variability is assumed to be known in these statistical models, it is important to check whether the inferred residuals are consistent with it; such that they are a typical realization of such variability. If this test is passed, the overall statistical model can be considered suitable.

Results obtained for response to anthropogenic and natural forcing combined forcing (ALL) for Rx1day and Rx5day show that scaling factors are significantly greater than zero and consistent with unit. These results indicate that the simulated ALL response is consistent with Rx1day observed changes. Also, it is found that the changes in observed extreme precipitation during 1951-2005 lie outside the range that is expected from natural internal variability of climate alone and greenhouse gasses alone, based on NorESM1-M climate model. Such changes are consistent with those expected from anthropogenic forcing alone. The detection results are sensitive to EOFs. We estimate the anthropogenic and natural forcing combined attributable change in PI over 1951–2005 to be 1.64% [0.18%, 3.1%, >90% confidence interval] for RX1day and 2.5% [1%,4%] for RX5day.

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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.