JOURNAL OF CLIMATE RESEARCH
Year:2017 | Volume:8 | Issue:29-30 |Papers Count:9

Rain is one of the most crucial elements in any climates. Knowing the methods of estimating rainfall can have be a very important role in understanding and predicting climate system. The old ways of measuring precipitation, is usually based on climatology stations, synoptic and rain gauge. In the recent years, new methods, based on the technology of measuring, have been used by specialists, to measure the precise amount of rainfall and other climatic factors through satellites and meteorological radars (Robinso and Kulielt, 2000). TRMM is the first satellite that can measure the precipitation rate and distribution, using a combination of microwave and radar sensors. In studies such as Sharma (2003) and Prakash and Gairola (2013) in India, and Zang et al. (2011) in China, analysis has shown, a high correlation between satellite data and ground. In this study also, for the Spatial-Temporal evaluation of rainfall data from TRMM satellite radar was used, and was compared Satellite data of climate stations, in Khorasan Razavi Province.

Since long time ago, prediction of precipitation status and investigation of drought hazards in catchment areas of North West of Iran, due to the critical importance of discharge rate of related catchments for Lake Uromia, has been one of the most important challenging issues in efficient management of water resources; management of vast capital of water resources and energy production of the country is highly affected by the aforesaid factors. Therefore, application of dynamic methods may play significant role in adjustment of such conditions concerning the frequencies of climate parameters and occurrence of imbalance behaviors in precipitation pattern of the country. In this regard, application of Aphrodite data can greatly reduce calculation errors and considers proper distribution of time and place in the category of post-processing framework. A wide range of methods has been used in the post-processing analysis of the output of dynamic methods; Therefore, application of post-processing technique may develop outputs of dynamic models to be used in subscales and the outputs of these models may be implemented in macro-environment management with a more comprehensive approach. Main objective of the present research consisted of developing the accuracy of seasonal predictions of precipitation of North-west of the country using dynamic model output post-processing method used toward managing the drought hazard.

Global climate change is relatively depending on human activities which have important impacts on the environment. So the climate change is a very important issue in the recent age. Climate change is the impact on human lives so the climate change increase their temperature and also is very important global problem and monitoring of the climate conditions in early region is a good solution for combating the national housing regarding to climate change large floods and other disasters. There are different climate models and in the CORDEX projects there are regional climate were included in some domains. The main objective of the present work is to evaluate CORDEX-WAS with a spatial resolution of 50 kilometer compared with observational data over Isfahan province. At the end we are evaluating the creation the variation of the minimum and maximum temperature during 2017-2050 according to model outputs for three models with 2, RCP4. 5 and RCP8. 5 emissions scenarios.

In the upper level (300 hPa) a widespread positive vorticity has seen on the Mediterranean and the Black Sea. In this level, the length of summertime became more than ago from 1990s and the negative vorticity has increased in the recent decades. In the 500 hPa level the positive vorticity intensity on the Cyprus and Turkish area has decreased from 1990s. The cold season in the lower level is finished earlier than middle level because at this time air is warmer than sea but at the middle level the cold period takes longer so in this level cold air mass privates yet. There is an increasing trend of negative vorticity in the west and positive vorticity in the east of the Caspian sea in the cold period of the 850 hPa level that is in agreement with a decreasing of the intensity of Siberian high pressure and a weakening of the Black Sea low pressure system from 1980s.

Drought of Groundwater happens when aquifers as an important source of supplying water, are effected by long-term drought. Groundwater resource index (GRI) have been used for long-term change of piezometric and observational data depth of aquifers. In this research, the results of calculations about drought happens with regard to spatial distribution of it within 609 plain of Iran, in GIS software have been compared with calculations results about drinkable water quality index of aquifers resources. This comparison has been done by using FAHP method and in two consecutive ten-year periods and long-term period from 1994 until 2015. In order to calculate of GRI index, in first step in the spreadsheet, 76% of primary missing data, by using R-squared method have been reconstructed, scrutinized, and outlier data have been eliminated. In order to create the interpolation map, we needed to evaluate and process raw data. In this regard, first, by using existence assessment tool of improbability trend in data, this purpose has been achieved in 3 dimensional diagrams. The existence of second-rate improbability trend from north to south and east to west in the first mean data of GRI index in long term period was approved. By recognizing the main factor approach of creating interpolating layers through geostatistical tool we created continuous level of GRI index number for all years and for three intervals of ten, ten and twenty years. Selection of best method based on the comparative evaluation among created samples and average comprehensive range of 1994-2015 period. For this purpose, in two class of deterministic methods of Inverse Distance Weighting (IDW) with three powers of 1, 2, 3. In addition by using GPI with three rates of 1, 2, 3 and RBF method and geostatistical class methods including; ordinary kriging, universal kriging and simple kriging with 4 mathematical functions: Stable, J-Bessel, Gaussian and spherical continuous maps have been created. With another exclusive method of geostatistical method called; Empirical Bayesian kriging by using 100 repetitions of Semivariogram continuous amount was created. The reason for selecting simple Kriging with stable function as final approach was that, with comparison with all samples, mean error decreased to 0. 002 unit, Root-Mean-Square (RMS) decreased to 0. 669 unit, Mean-Square (MS) decreased to 0. 003 unit, Root-Mean-Square Standardized (RMSS) decreased to 0. 958 unit, and last ASE decreased and reached close to 0. 699, equal to amount of RMS. Similar correlation of changes in two categories of time for GRI and drinkable water quality, revealed a close and direct relation between decrease of aquifer water level and increase of class number that means the decrease of water quality. The result of GRI index calculation was shown that only 3. 3% drought close to normal in first decade, in second decade reach to 70. 8%. And in similar manner, Wet year class number close to normal have been decreased from 87. 1% to 27. 7%. these changes in term of type, were also seen in Wet year mild class, sever class and very severe class. Finding revealed this fact that central regions of Iran, some parts of Khorasan Razavi province, northern Khorasan province, extensive area of Fars province and major part of south of Iran have experienced severe drought class. Based on the evaluation of drought maps and diagram of increase the volume of withdrawal from the Groundwater operation resources, between 1994 until 2015, it can be stated that, the most important factor for changes is the wasteful withdrawal from operation wells with agricultural function. Specifically, in second decade of evaluation period in this research, drought index near to normal has continued with sever slope. Therefore, replacement a major part of cells in middle drought class and severe drought class have been observed, especially in last year. Only in 2001-2007 period, there is no special drought and wet near to normal has been happened repeatedly. In order to evaluate the relation between decrease of Groundwater and decrease of water resource quality by using current calculation it was necessary to continuous level map of first and second period of GRI and Groundwater quality index by using date functions be standardize. Current statistics has been placed between two amounts of 0 and 1 by using linear date function, with regard to these principles that minimum amount be referred to maximum happens of drought and maximum amount be referred to maximum happens of wet year. The output results of FAHP were between 0 and 1, and higher values represent the areas with higher qualitative potential with aim of using for drinkable water sources or more desirable water resources. In FAHP method the quantitative final results value depends completely on the kind of operator. By selecting Gama operator, for 20 years period, maximum calculated amount was equal to 0. 148 with 0. 136 average and 0. 011standard deviation. In contrast, for ten years period from 1994 to 2004, in sum, 13657 Raster cells layer, for maximum, average and standard deviation; were respectively 0. 149, 0. 136 and 0. 011. And in ten years period between 2004-2015 years, decrease of water quality was determined with average of 0. 124 and maximum amount of 0. 147 and standard deviation of 0. 015. scatter points vector, revealed this fact that there is 43% correlation between two columns of GRI standard statistics in two periods, 1994-2004 and 2004-2015. In addition, by drawing the scattered points between two column of standard value data of drinkable water quality index in FAHP method and in two ten periods, 1994-2004 and 2004-2015; 39% correlation was approved.

Today powerful dust storm destroys people lives and causes severe damages to their life and also causes financial problems in most regions of the world especially in west and southwest of Asia. Dust storm is one of the most important natural phenomena and also a kind of severe natural disaster that influence Iran and its west and southwest parts. The location of Iran on the desert belt is accompanied by frequent increasing of sand and dust storms. Integral prediction of dust storm phenomena can be useful in decreasing damages caused by these storms. So synoptic-dynamic analysis of dust storms and their simulation plays an important role in achieving to this goal. In this research, we investigate 4 severe dust storms in August 2005, September 2008, July 2009 and June 2012 that affected a large area of our country. Select of dusty days were based on minimum visibility and maximum durability of that dust storm. At first, we show the minimum of daily visibility table. These data has been provided by Meteorological Organization in 5 western cities. The synoptic maps were related to these phenomena derived from NOAA website and synoptic and dynamic interpretation has been done. We have got the data with resolution of 2. 5 degree from NOAA website. Then 700 hpa relative vorticity maps were drawn. We investigate MODIS images instrument on Aqua satellite and evaluate the amount of mass concentration of dust particles. Then the Lagrangian Integrated Trajectory Model has been used to determine the backward trajectory of dust particles. We run HYSPLIT model by GDAS data with a resolution of 0. 5 degrees. At last we investigate the outputs of the WRE-CHEM model. This model was run to simulate dust storms by FNL data with a resolution 1 degree use for initial and boundary conditions. WRF-CHEM is used to simulate dust condition and transmission. As a part of WRF model, its main application is the study of atmosphere chemistry. At 500 hpa a very strong ridge entered Iran from the southwest. It covered all areas of our country which prevents the transference of dust to high levels of atmosphere. In 700 hpa relative vorticity maps show one day before dust storms reach to Iran a Positive voriticity is located in Iraq and Syria. So dust comes up to higher levels of the atmosphere and in dusty days in our country. There is a negative voriticity located in our country and because of downside movement of the air, dust storm happen in Iran. The time series of dust concentration of output models for Ahvaz are compared with the concentration data of Environmental Organization and visibility data. Results show that a low pressure system is located over the Oman sea that its blaze has been extended to the northwest of Iran. On the other hand a high pressure center is located in the Europe that extended to the east of Mediterranean. So strong pressure gradient were in Iraq and Syria and they caused the creation of strong winds in their deserts which caused dust emission. Satellite images showed that WRF/CHEM model is simulated very well in emission, source, diffusion and the extent of the areas covered with dust. Comparing PM10 concentration of the model outputs with Environment Organization data, show that WRF/CHEM model forecast daily changes well. But model underestimate significantly in quantity of concentration. These errors may be are due to a model considering only dust quantity but other pollutants affected on visibility. In general it can be said that in this event, dust concentration has been underestimated by WRF/CHEM model especially in maximum amount of PM10 concentration.

In recent years, there is an increasing concern in weather and climate extremes, since they may cause serious disasters to human society and nature and seem to more sensitive to climate change than the mean value. The rise in greenhouse gas emissions arising from increased industrialization and urbanization has, in recent years, contributed significantly to global warming. This global warming leads to the change of climatic extreme index and increases the intensity and frequency of occurrence of extreme climate events. Extreme events are relatively rare, unpredictable and often brief but they are highly destructive. Many studies show that climate extremes cause significant damage to crop growth and final yields, and the various frequencies and intensities of extreme events result in differing degrees of soil erosion and flooding. Climate variability is largely influenced by temperature change, which is particularly important through its role in the global climate system and energy cycles. Analyses of observed temperature in many regions of the world have already shown some important changes in the extremes. To predict future change in extremes understanding the recent past is essential. The objective of this study was to investigate the spatial and temporal distribution of temperature extremes in Khorasan Razavi province during 1990– 2015 based on 15 climate indices proposed by the Expert Team on Climate Change Detection and Indices and to detect the effect of climate change.

Over the last few decades, the growth of industries and factories on the one hand, and deforestation and degradation of the environment has, on the other hand, led to an ever-increasing rise in the degradation of nature and increased greenhouse gas emissions on the planet. This negative consequence has led to significant changes in the climate of the planet. However, in recent years, the severity of droughts and floods and extreme phenomena in different parts of the planet has increased significantly. Climate variability can be accomplished using longitudinal climatic methods, integrated analysis, statistical models, analogical models and identifying the causes of a phenomenon. Therefore, recognizing the temporal changes, the location of these metamorphic meters in the coming decades, and the zoning of the regions in terms of the need for cooling energy can be a step in the development of the country's economy by saving huge amounts of energy and leading national, regional and local plans to modify energy consumption patterns. 1-Development and implementation of a system for zoning of different regions of the country in terms of altitude and humidity and temperature. 2-Select the temperature thresholds for each area to calculate the cooling day 3. The simulation of the monthly and seasonal average of the country's cooling-off day is for the first time the most important goal of this study.

Transportation is one of the subs tractor parts in Economy of each country. Road transportation depends on atmospheric conditions. Weather is one environmental risk factor that is known to affect road crash rates in IRAN and elsewhere. Weather that reduces road friction, impairs visibility and/or makes vehicle handling more difficult creates a serious road safety threat Weather and climate, as represented by several indicators (e. g. rain, storms, winds, etc), contribute to several hazards or sensitivities within the transportation sector (e. g. landslides, reduced visibility, road traction, etc). Unfavorable atmospheric conditions may damage the soil of levees and make the road unused. In addition, adverse weather conditions make travel dangerous for humans and impose financial risks on travelers and those who use the roads. A number of factors measured in road weather stations, such as destruction of atmospheric phenomena, effective elements in reduced visibility, analysis of rainfalls, showers, snow and avalanches, dust storms, frost, freezing, and etc. Environmental Sensor Station categories provide information to identify roadway weather conditions of interest. ESS data are collected in a remote processing unit (RPU) and transmitted to a central processor. Resulting road weather information is used to activate automated warning systems and provide decision support to managers in traffic management centers, road maintenance facilities, and emergency operations centers. By monitoring road conditions using pavement sensors or video, operations and maintenance personnel are able to assess how well their traffic management or winter maintenance strategies are performing, or to determine what additional actions are required. The purpose of this project is to identify the different climatic conditions over Iran in order to detect the most suitable meteorological road sensors for each region according to its climate. The results of this survey would be useful for the road transportation management and appropriate use of sensors according to climate zones. The aim of this study is to identify reputable companies producing sensors and road weather sensors.