spatial analysis of humidity propagation over iran

introduction the consequence of cooperation between environmental factors and circulation patterns in a long time can determine the arrangement of type and manner in humidity in geographical area. the knowledge about space dispersion in geographical areas assists preparing sound programming and proper environmental decision making. relative humidity is the most commonly used measurements of moisture content in the air. the key to understand relative humidity is to understand that it is a measure of the ‘actual humidity’, relative to the maximum possible humidity at a given temperature. let’s explain it a bit further. in this context a number of studies have been conducted to refer this. some of these studies are diffenbaugh and et al. (2008), ohayon (2011), jia and et al. (2011), homar and et al. (2010), chao-bing and et al. (2011), allard and soubeyrand (2012), ageena and et al. (2013), del río and et al. (2013), kim and et al (2014) and bajat and et al. (2014). this research is fulfilled to detect the temporal and place spatial autocorrelation of humidity in iran.   materials and method in order to reach the expressed goal, the base of network data of relative humidity in iran has been established. similarity of data of the stations has been evaluated by the kolmogorov-smirnov test in spss software and their similarity has been proved. then, from the data of the stations a statistical period of 30 years in a daily period from 1982/1/1 until 2012/12/31 is used as the base of the present research and a network in range of 15×15 kilometer have been spread over the study area. in reviewing the changes of transmittal humidity of iran during a year, modern spatial statistics method such as spatial auto correlation global moran, local insulin moral index and hot spots were used by using (gis) and matlab.   results and discussion the results of this research showed that the global moran index for each 12 monthes of a year is one more than 0.90. this point indicates that in accordance to global moran, transmittal humidity of iran in the study period has the high cluster pattern in 90, 95 and 99 level percent. then, the highest index of global moran in scale of 0.97 is related to the february in winter. z statics for every 12 monthes of a studied statistic period is high and between 247 and 263. therefore, according to global moran it can be concluded that during a year in the index in iran shows a very high cluster pattern. alteration of spatial autocorrelation of transmittal humidity of iran used the local moran index and analysis of hot spots. according to both the indicators, the north, north west, north east, west and south west areas like east azarbaijan, west azarbaijan, ardabil, zanjan, guilan, mazandaran, ghorgan, khorasan and kermanshah stations plays a significant role in forming the humidity patterns with high cluster. this is in a way that the named areas of iran have positive spatial autocorrelation. this is while the regions have negative spatial auto correlation or in other words dry humidity in 12 months of a year limited to high regions. totally, a considerable area of the province in all 12 months is without significant or disciplined pattern or they lack sound virtual spatial autocorrelation statistically. the results of this research showed the humidity pattern is formed through a long time period and under local and distributional elements with a different role.   conclusion generally, the geographical arrangement of humidity patterns are formed by regional factors specially heights, latitude and in a clearer explanation formation and structure and the role of latitude. this is while we should not ignore the role of outer factors in formation of humidity patterns. outer factors or the general circulation atmosphere elements play a significant role in determination of a humidity regime and humidity lapse. if we look at the humidity cluster of iran we see that the clusters in high and low level are not the same. this contrast is because of influence of circulation element factors.