Yousef Zarei; Ali Mohammad Khorshiddoust; Majid Rezaeebanafshe; Hashem Rostamzadeh
Abstract
Climate change is one of the main problems on Earth today, so predicting these changes in the future and their impacts on water resources, the natural environment, agriculture, and environmental, economic and social impacts is of particular importance. Therefore, in the present study, the effects of ...
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Climate change is one of the main problems on Earth today, so predicting these changes in the future and their impacts on water resources, the natural environment, agriculture, and environmental, economic and social impacts is of particular importance. Therefore, in the present study, the effects of global climate change on different climatic regions of the country were studied in 12 climatic regions. In this study, NCEP data and climatic elements of precipitation, maximum and minimum temperature were used for statistical downscaling with SDSM model. And using the CanEMS2 model output under RCP scenarios for the three statistical periods of 2011-2040, 2041-2070, and 2071-2099 annual climate change data were obtained. Correlation coefficient, determination coefficient and error indexes of RMSE, MSE and MAD were used to evaluate the performance of the model. However, the results showed that the accuracy of the model was different at different stations. In this way, each model performs better than rainfall in simulating minimum and maximum temperatures. The annual long-run results also show that precipitation will decrease in all climates studied in the coming decades, with the largest decrease occurring in semi-warm (35%) and very humid and temperate (32%) desert areas. But minimum and maximum temperature variations will be different in different climatic regions so that under RCP scenarios during all statistical periods at Sabzevar and Tabas stations minimum temperature changes will decrease but in other climatic regions the trend of minimum and maximum temperatures will be incremental. The highest minimum and maximum temperature increases based on RCP scenarios under RCP8.5 scenario during the period 2071-2099 in the cold mountain climatic region will be 3.03, 4.27 ° C, respectively.
Climatology
Jaber Soltani; masoud ahmadi nik; Ahmad Ahmadinik
Volume 23, Issue 69 , December 2019, , Pages 127-147
Abstract
Reference evapotranspiration is one of the necessary parameters to determine crop water requirements and irrigation planning. Having accurate estimates of this parameter is essential for planning and managing of water resources. Several experimental models have been proposed to estimate evapotranspiration. ...
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Reference evapotranspiration is one of the necessary parameters to determine crop water requirements and irrigation planning. Having accurate estimates of this parameter is essential for planning and managing of water resources. Several experimental models have been proposed to estimate evapotranspiration. According to the spatial variability of climatic parameters, using remote sensing method that considers these changes is very favorable. Among the most widely used models that accurately estimate evapotranspiration using remote sensing, can be mentioned wavelet model. In this regard, the purpose of present study is to evaluate the accuracy of wavelet models to estimate the reference evapotranspiration using parameters derived from satellite images contains the Earth's surface temperature and amount of water vapor in the atmosphere. In this study, used atmospheric and satellite images data of four station contains Anar, Kerman, Rafsanjan and Shahrebabak to develop and evaluate wavelet models. In the first scenario, temperature, in the second scenario, atmosphere water vapor parameter and in third scenario, both parameters simultaneously was used as the model input. Results of this study showed that despite the high accuracy of models in different scenarios, the wavelet model use two-parameters, temperature and steam simultaneously (third scenario), with a coefficient of 90% compared to other models had the more accurate.
Climatology
amanollah fathnia; hamid rahimi; Shoaieb Abkharabat
Abstract
Siberian high pressure (SHP) is synoptic system that during the autumn and winter seasons on Asia is religious (Msaudian and Kaviani, 2009: 15). In the cold term of the year, the vast Siberian territory due to the clear sky and away from water sources, the more energy through the long wave radiation ...
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Siberian high pressure (SHP) is synoptic system that during the autumn and winter seasons on Asia is religious (Msaudian and Kaviani, 2009: 15). In the cold term of the year, the vast Siberian territory due to the clear sky and away from water sources, the more energy through the long wave radiation loses, thereupon the around air of land gradually adjacent to becomes cold high-pressure center.
Yousef Gavidelrahimi; Manochehr Farajzadehasl; Mehdi Alijahan
Abstract
Today, global warming effects on various aspects of the Earth are no secret to anyone. Because of this, the research ahead is done for the detection of global warming on minimum temperatures, monthly and periodic (hot and cold) as well. For this study, two groups of data, temperature data of 17 synoptic ...
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Today, global warming effects on various aspects of the Earth are no secret to anyone. Because of this, the research ahead is done for the detection of global warming on minimum temperatures, monthly and periodic (hot and cold) as well. For this study, two groups of data, temperature data of 17 synoptic stations and corresponding amounts of data in global temperature anomalies were figured out over 60 years period of time (1951 to 2010). Goals, the Pearson correlation method for detecting relationships between data, linear and polynomial regression for trend analysis time series data , To illustrate the correlation between the spatial distribution of temperature data with global warming stations nationwide Geostatistical model Finally, non-parametric test for detecting significant temperature change Man - Kendall were used. Based on the results, apart from Khorramabad and urmia stations that have negative relation with global warming and Hamadan and Kerman stations that do not show any significant relationship with global warming, global warming is seen as a positive influence on the other stations. Caspian Bank stations than any other stations in the cold months of global warming have much more influence. Checking the changes of minimum temperature trend showed a significant change in several months. In the warm months the maximum temperature variability is seen in the southern stations of Ahwaz, Abadan, Bushehr and Shiraz. Results obtained from the survey period (hot and cold) minimum temperature, indicate a greater influence global temperature anomaly on the minimum temperatures are warm period of year. During the warm period, southern stations have had the highest influence on the station and during the cold period Caspian Bank stations have had the highest relationship with it. The changes were made based on both periods the obtained results are clarity significant.
Javad Behmanesh; Nasrin Azad Talatape
Volume 19, Issue 51 , April 2015, , Pages 41-58
Abstract
One of the atmospheric cycle properties is climatic changes which can cause the fluctuations in meteorological parameters. These fluctuations in many world regions are considerable and water and soil resources are affected by them. To prepare against undesirable effect of climate change and adopt suitable ...
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One of the atmospheric cycle properties is climatic changes which can cause the fluctuations in meteorological parameters. These fluctuations in many world regions are considerable and water and soil resources are affected by them. To prepare against undesirable effect of climate change and adopt suitable development programs and water resources management, it is necessary to investigate the meteorological variable changes. The objective of this research was to investigate the climate change in Urmia region. In this research, the changes trend of temperature, precipitation, relative humidity, sunshine and potential evapotranspiration were studied. To achieve this goal, Urmia synoptic station daily data with 40 years period (1971-2010) were used. The Mann-kendall statistical test at confidence level of 95% was used to investigate the significance of trend in the mentioned parameters. The results showed that the trend slope of maximum, minimum and average of temperature was positive and this trend in 95% confidence level was significant. Urmia precipitation was decreased with slope of -2.26 so that this decrease was significant. The sunshine had positive slope and significant trend, but the negative trend of relative humidity and the positive trend of potential evapotranspiration (0.0068) were not significant. The monthly investigations showed that the average temperature in all months had positive slope, but this slope was not significant in all months. The other parameters in some months had positive or negative slopes.
Hossein Babazadeh; Saeadamir Shamsniya; Fardin Bostani; Elnaz Norozyaghdam; Davood Khodadadydehkardy
Volume 16, Issue 41 , November 2012, , Pages 23-47
Abstract
Stochastic models have been used as one technique to generate scenarios of future climate change. Temperature and precipitation are among the main indicators in climate study. The purposes of this study is analysis of the status of climatic parameters of monthly precipitation and mean monthly temperature, ...
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Stochastic models have been used as one technique to generate scenarios of future climate change. Temperature and precipitation are among the main indicators in climate study. The purposes of this study is analysis of the status of climatic parameters of monthly precipitation and mean monthly temperature, years of drought and years of wetness due to precipitation deficiency, simulation and forecasting using stochastic methods. In this study, the 21 year data on the precipitation and mean monthly temperature at shiraz synoptic station are used and based on ARIMA model, the autocorrelation and partial autocorrelation methods, evaluation of all possible models regarding their invariability, examination of parameters and types of model, the suitable models for prediction of monthly precipitation: ARIMA (0 0 0)(2 1 0) 12 and for forecasting of the mean monthly temperature: ARIMA (2 1 0)(2 1 0) 12 were obtained. After validation and evaluation of the model, the forecasting for the agriculture years 2008-09 and 2009-10 were made. In view of the forecasting made, despite of a continuing drought, it is likely that the precipitation will improve. As regards the mean monthly temperature, the trend of increasing temperature, especially in recent years, has continued and the findings of the forecasting show an increase in temperature along with a narrowing of the range of variations.
