Journal of Spatial Analysis

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Global temperatures have increased in the past 100 years by an average of 0.74°C (IPCC, 2013), with minimum temperatures increasing faster than maximum temperatures and winter temperatures increasing faster than summer temperatures (IPCC, 2013). Total annual rainfall tends to increase at the higher latitudes and near the equator, while rainfall in the sub-tropics is likely to decline and become more variable (Asseng et al., 2016). Considering probability of occurrence climate change and its hazardous impacts, it seems essential to clarify future climate. General Circulation Models is widely used to assess future climate and its probable changes. Although the outputs of these models are not appropriate for small-scale regions because of its coarse resolution. Thus, statistical or dynamical techniques are used to downscaling the outputs of these models using observed data in weather stations. Despite the fact that frequent researches has done in relation with climate and climate change, but it is unclear yet future climate, especially climate change, in Iran. The goal of this study was to present the results of climate change predictions which has been done so far in Iran, in order to help prospective studies in this field. This step can be important to consider new questions and challenges. In this study, we assessed future climate change in Iran using results of statistical downscaling studies of atmospheric-oceanic General Circulation Model’s outputs. To do this, studies on prediction of precipitation and temperature parameters in Iran by different emission scenarios, atmospheric-oceanic General Circulation Model’s outputs and statistical downscaling techniques were gathered. Then a comprehensive view about Iran's future climate and specifically the climate changes presented by descriptive-content based analysis and comparison of their results. Used downscaling techniques in these researches were included: LARS-WG, SDSM, ASD, Clim-Gen and used General Circulation Models were: HADCM3, BCM2, IPCM4, MIHR, CGCM3, CCSM4 and finally used emission scenarios were A1B, A1, A2, B1, B2, RCP4.5. Based on climatically geographical differences in Iran, the results discussed separately in six different regions across Iran. The results of various regions are different because of usage of different models and different climatological and geographical conditions. These models simulate temperature more accurate than precipitation, because of more variability and temporal discontinuity of the precipitation relative to temperature. Assessment of results in 30-year periods from 2011 to 2099 showed that in North West of Iran (Ardebil, Azarbayejan- Sharqi and Azarbayejan- Qarbi provinces), precipitation will be decreasing, decreasing- oscillating, decreasing- transitional and temperature will be increasing. Decreasing- transitional trend, in other words decrease precipitation in cold seasons and increase of it in warm seasons, lead to a decrease in the snow occurrence and an increase in the rainfall occurrence. Thus, it can affect the frequency of floods occurrence. In west and southwest region of Iran precipitation has been predicted to have different changes in various sections of it. It will be decreasing-oscillating in Kermanshah and Kordestan provinces and oscillating in Hamedan province. Precipitation will increase in Lorestan and finally it expected to decrease in Khoozestan, Chaharmahal-va-Bakhtiari, and Ilam. However Temperature will rise across this region. In south and south east region of Iran (Fars, Hormozgan, Kerman and sistan-va-Baloochestan provinces), precipitation will be decreasing, decreasing-oscillating, oscillating and increasing-oscillating. Also in this region, temperature expected to increase similar to other regions. In east and north‌ east of Iran (Khorasan Shomali, Khorasan Razavi and Khorasan Jonobi provinces), temperature predicted to be increasing-oscillating, that it is different with other regions. Changes in precipitation will be oscillating and decreasing-oscillating. In the northern coasts of Iran (Gilan, Mazandaran and Golestan provinces), precipitation changes will be decreasing and increasing-oscillating and temperature changes expected to be increasing and increasing-oscillating. Thus, it expected to increase heat wave, drought, and aridness condition as the results of these changes. Precipitation changes in south of Alborz region and center of Iran (Semnan, Tehran, Qazvin, Markazi, Esfahan and Yazd provinces), will be decreasing, oscillating, increasing-oscillating. Also temperature will be increasing in this region. Considering the decreasing trend of precipitation and the increasing trend of temperature in the most of Iran, it is probable to increase the occurrence of climatic and environmental hazards such as flood, drought and heat waves in the future. These events can have serious effects on water resources, agriculture and tourism, especially in regions such as Iran where have sensitive environment.

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Prediction of Climate Change in Western of Iran using Downscaling of HadCM3 Model under Different Scenarios
 
Hassan Zohrehvandi ¹, Ali Mohammad Khorshiddoust ², Behrouz Sari Sarraf ³

1- Ph.D student of Climatology, University of Tabriz, Email:  H.zohrehvandi@gmail.com 
Mobile number:+989181502513
2 - Associate Professor of Climatology, University of Tabriz, Email:         
 Mobile number:
 3- Associate Professor of Climatology, University of Tabriz, Email:      
 Mobile number:
 
Abstract
   Considering that water resources are at risk from climate change, the study of temperature and precipitation changes in the coming years can lead to droughts such as droughts, sudden floods, high evaporation and environmental degradation. To this end, global climate models (GCMs) are designed to assess climate change. The outputs of these models have low spatial accuracy. In order to increase the spatial accuracy of this data, downscaling methods are used which are divided into statistical and dynamic methods. One of the reasons for using these models is their quick and easy operation compared to other methods. Our study area consists of Kurdistan, Kermanshah and Hamedan provinces in the west of the country. In this study, observational data of minimum temperature, maximum temperature, precipitation and radiation of 6 synoptic stations in the studied area in the statistical period of 1961 until 2005. In this study, the LARS-WG model was used for downscaling of HadCM3 global model data. The LARS-WG model is one of the most popular weather generator models that which to generation for maximum and minimum temperature, rainfall and radiation are used daily under current and future climate conditions. This model as a downscaled version of the same process less complex and simulated data input and output, high ability to predict climate change. The HadCM3 model is also a type of atmospheric- oceanic circulation model developed at the Hadley Center for Climate Prediction and Research, which has a 2.5 degree latitude network at 3.75 degrees longitude. Also, three climate change scenarios A1B, A2 and B1 have been used, each of which reflects the characteristics of the world's economic growth, the world's population and social awareness. The methodology is that the model receives the monitored data of the basic course; by examining them the statistical characteristics of the data are extracted. Then, in order to validate and ensure the model's capability for the basic statistical period, the model is implemented to re-establish a series of artificial data in the base period. Then the outputs to evaluate the performance of the model in the reconstruction of the data, the statistical characteristics of observations to test and compare various criteria. MAE, MSE, RMSE and R2 criteria were used to evaluate and analyze the performance of the downscaling model. The results showed that the accuracy of the model varies in different stations and parameters, so that the model in simulation of temperature and radiation is more suitable than rainfall simulation. Also, the model has more successful in simulation of maximum temperature in comparison with minimum temperature. In sum, the results of different evaluation criteria indicate that the LARS-WG model has a good accuracy for the downscaling of the parameters studied in the study area. After evaluating the LARS-WG model and ensuring its appropriateness, the data was generated by the model for three climate change scenarios using the HadCM3 model. The results of the monthly review of the parameters studied at the station indicate that precipitation in the 2050s at all stations except Saralpul Zahab and Sanandaj stations according to the three scenarios studied in most months except December, January And at some stations, sometimes in November and February, they were lower than the base period, and rainfall is expected to decrease over the 20 years period (2046-2065), but the situation for Sanandaj and Saralpul Zahab stations is somewhat different, which, according to some scenarios, has increased in most months of the year, and according to some scenarios, rainfall has decreased in some months and it seems that the precipitation pattern is shifted The end of the warm season. But the rainfall situation is completely different in the 2080s, and rainfall has decreased in all stations and in most months of the year. The average monthly of the minimum and maximum temperatures as well as the amount of radiation shows that all three parameters will increase in all months of the year based on all three scenarios, as well as in the two decades studied (2080 and 2050) And its rate would increase in the decade than in the previous decade. According to the results, the amount of precipitation decreases in study area and the temperature and radiation will increase as well. The rate of precipitation decrease in the following periods will be 7.7% in the region than in the base period, and the minimum and maximum temperatures in the long-term was increase at the region 3.4 and 3.4 degrees Celsius, respectively, compared to the average period of the base. The radiation increase was 0.38 mJ /m² in Area level. The results of this research can help to solve the challenges of water resource managers and planners in future periods.
 
Keywords: Climate Change, downscaling, west of Iran, General Circulation model, LARS-WG
 
 
 
 

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Cold and frost are one of the climatic hazards that cause damage to various activities every year. Climate change, on the other hand, causes spatial and temporal changes in glaciation. The purpose of this study is to analyze the temporal-spatial changes and predict the future of glaciers in Hamadan province. CanESM2 model was used to predict the minimum daily temperature in the province. Data mining of general circulation models was Downscaling using LARS-WG model. The above parameters were simulated for a period of 30 years (2050-2021) under three scenarios RCP2.6, RCP4.5 and RCP8.5 for selected stations. The results of the monthly minimum temperature survey in the study stations of the province showed that the minimum temperature in the period (2050-2021) in all studied stations according to all three scenarios will increase in all months of the year compared to the base period. The average minimum temperature of the province is equal to 2.5 degrees Celsius, which in the coming decades based on the scenarios of RCP2.6, RCP4.5 and RCP8.5 will reach 6, 6.2 and 6.3 degrees Celsius, respectively, which is the highest The changes are related to Nojeh station and the lowest is related to Hamedan. The spatial distribution of the beginning and end of freezing in the future period indicates that freezing in the northeastern and northern parts of the province starts earlier and ends later than in other parts of the province, while in the southern parts of the province it starts later and ends earlier. The results of examining the changes in the onset of frost in the next decade compared to the base period showed that in all stations studied the onset of frost will decrease between 3 to 11 days.