نشریه نیوار
پیاپی 104-105 (بهار و تابستان 1398)

Studies of geography to urban planning, climatology, civil construction and agriculture also conducted in an area to estimate soil temperature is dependent on the area. In this study, at 50 cm soil depth by using simulated annealing hybrid algorithm and Support Vector Machine single model in the city of Adana in Turkey weather station was simulated. The results showed that the hybrid model simulation of refrigeration is based on vector support machine with 0.986 nash-sutcliuf about criteria, the absolute error mean square error equal to 0.732 and root mean square error is equal to 0.86 well estimated. As well as single machine backup rate vector model for benchmarking Nash-sutcliuf about 982.0 and the absolute error mean square error equal to 0.793 and root mean square error is equal to 0.96 is obtained. The results showed that hybrid algorithm simulation of refrigeration could be fitted as a means of efficiently in deep soil temperature modeling.

:The main purpose of this research is to improve the simulation of moderate and heavy precipitation events associated with cold anomaly in Tehran. To detect extreme precipitation events along with cold anomaly in Tehran in a sufficiently long period, the results of Khansalari et al. in the study carried out in 2017 are used. In the latter study, using statistical methods, 133 days with extreme precipitation along with cold anomaly in October to May in the 1951–2013 period were identified based on which six clusters of synoptic patterns were obtained by application of the T-mode principle component analysis to the whole dataset of 133 days. In the present study, from each cluster, one day with maximum similarity with the average pattern of the cluster was selected for numerical simulation by WRF model using the ERA-Interim data. To reach the optimal prediction of extreme precipitation events in Tehran by WRF, nine configurations consisting of four convection, two boundary-layer, three microphysics, and two short waves radiation schemes, as well as one surface-layer scheme were used. For verification, in addition to visual comparison, the forecasted data of model regular network were interpolated to irregular observation stations. Then using various verification indices, the performance of different configurations in predicting rainfall was assessed quantitatively with different thresholds. Results showed that across all the ranges of rainfall, the Tiedtke convection scheme and Mellor-Yamada-Janjic boundary-layer scheme lead to greater accuracy and better prediction of precipitation. It should also be noted that for light precipitation events, in addition to the Tiedtke convection scheme, the Kain-Fritsch scheme is also suitable

Clean and renewable energies would be as one of its fundamental growth and development in the future and by attention to reaching the end of fossil fuels and renewable discussion of the effect of pollution on Global warming, focus on free and unrenewable energy of wind has been increased. In this thesis the potential of wind energy in lorestan province synoptic stations using 3- hour data of wind speed, over the statistical from distribution and to draw windRose , Wrplot software are used. In addition using annual wind power density in different height levels of 10, 20 and 50 meters and other parametr such nominal speed of the wind, the most tolerant of wind speed, proper time of use and availability of wind time was calculated and basis of the mimistry of energy of USA, the wind speed power density was categorized. The Studies of wind power density at stations Khorramabad, Aligoodarz, Borujerd, Azna , Doroud, Norabad, Poldokhtar, Kouhdasht and alshtr stations are orderly 148, 198, 275, 244, and Norabad stations have good potential for wind energy production. Doroud and west of Aligoodarz stations in case of using the height wind turbines are suitable for the wind energy operation. And other stations donot the proper potential for energy production.

Drought monitoring of the Great Karoon basin by using SPI index (1978-2014) Abstract One of the main features of Iran's climate is low amount of precipitation and high fluctuations in daily, seasonal and annual time scales. Each drought has 4 major characteristics which include continuation, intensity, frequency and coverage. The main objective of this study is to evaluate and zoning the drought characteristics of the Great Karoon basin. In this study, the 28-year SPI drought index was used to analyze the characteristics of drought in 42 stations located inside and outside the basin three time scales of 3, 6 and 12 - months. Continuity and severity of drought were extracted at each time scale then drought maps were plotted in GIS environment. The lowest SPI of -3.29 was observed in Yasouj station at the 12 months scale , and the long lasted drought was observed in Bostan with duration of 61 months. Also the longest of continuity and coverage of drought in each year was determined. Key words: drought, continuation, severity, extent , karoon.

The precipitable water is the integrated water content in the whole column of the atmosphere that has the potential to precipitate. In more precise terms prediction of PW is one of the common issues of meteorology and hydrology. Countries facing water scarcity require an advanced management of water resources that one of the management tools in this area being knowledge of the total precipitable water content (TPW) in the atmosphere. Also accurate estimation of this quantity in many meteorological issues such as prediction of rainfall, time, dams overflow and also prediction of flood occurrence is beneficial. Iran's roughness is one of the main factors in the heterogeneous distribution of precipitable water in the atmosphere. So that most researchers believe that the main reason for the existence of many Iranian leeward deserts is the roughness such as Zagros. With the discovery of new remote sensing technology, it is possible to estimate the amount of precipitated water vapor by absorbing water vapor bands and thermal bands at any time and place and at any scale.In the first we compare the precipitable water values of two European and Chinese satellites, METEOSAT and FENGYUN respectively, with corresponding parameter of radiosound that calculated for Mashhad and Tehran airport stations. By comparing precepitable water data for about two years from two meteorological satellites and radiosound for two mentioned station, there is a good aggrement between precipitable water parameter of the METEOSAT European satellite and radiosounds. But the FY-2E Chinese satellite doesn’t have good correlation with the Mashhad and Tehran airport radiosound station. So in this article we use MET-8 satellite to post-processing precipitavle water of WRF Model in non-observational points. Finally, we compared the post-processed values and compared the MSG1 satellite values in 6 different Iranian cities with different climatic conditions.

In this study, in order to monitor the phenomenon of dust, the experimental index of dust storms in the period 2012-2015 was calculated based on Horizontal Field Measurement by Australian Meteorological Organization. The zonation of the province was based on the index values. The results indicate that at 4 stations, the dust storm has more happened than the rest of the stations, and in the north-east of Isfahan the highest volumetric values were calculated. In the year 1392(2013-2014) in Isfahan,in 258 days the dust amount was higher than the permitted limit ( 35.4 micrograms per square meter), so this year was specifically examined. Studies have shown that the establishment of a high pressure system, cold weather and sustainab conditiona of weather, have been the factors that exacerbated the phenomenon of dust in the cold season. Meanwhile, fluctuations and precipitation rates were compared between two stations in Southwest (ozonstation) and North east (airport) of Isfahan. Northeast station (airport) is located near the Segzi Desert and its dust level is more than other areas. Studies have shown that rainfall and light rainfall are less than the short-lived heavy rainfall in the northeast of Isfahan in this year. The presence of dust particles has reduced the formation of Stratus Clouds (leading to light and continuous rainfall), and the strengthening of Convective Clouds (resulting in heavy rainfall) and decreasing the size of cloud droplets and weakening the cloud formation process

Prior to the publication of the fifth Assessment Report (AR5) by the Inter-governmental Panel on Climate Change in November 2013, our researchers used data from CMIP3 General Circulation Models for future climate change projection over the country. But by 2015, access to data from the CMIP5 series of General Circulation Models has been gradually facilitated. As most research on projection of climate change is currently being carried out using data from CMIP5 models. In this research, the output of all CMIP5 models used in AR5 reporting has been used to simulate the future climate change projection of the country. The results of this study showed that with the exception of the optimistic scenario of RCP2.6, in three other scenarios, the average precipitation from the Mediterranean to Afghanistan would decrease. In the scenario of RCP8.5reducing precipitation in the west of Iran would be approximately 20% would it will be around 30% in Syria, Jordan, Palestine and Iraq. comparing to long-term. Also, in case of non-compliance with the Paris agreement, the average temperature rise in the country is about 5.2 degree of Celsius and in the case of implementation of Paris Agreement, it will be 1.3 degrees Celsius greater than the period of 1986-86. Generally, due to lower precipitation and rising temperatures, it is expected that the western parts of the country including Zagros, will be exposed to drought, water stress, reduction of forest cover, water resources and hydroelectric plants production and increase of extreme events.

In March 2019, passing frequently baroclinic waves over many parts of the country caused severe rainfall, resulting in flooding of rivers and extensive waterlogging in some of these areas. The incidence of these heavy and extensive rainfalls has been rare during the statistical period. In this study, three atmospheric systems resulted in severe rainfall in Golestan, Lorestan, Fars and Khuzestan provinces, which caused a great deal of damage to some part of these provinces, from the statistical an synoptically approaches has been investigated. The statistical results showed that the highest daily precipitation in March 2019 at Gorgan and Poldokhtar stations were extreme precipitation with a return period of 500 and 29 years respectively, but at Shiraz Station return period is less than 2 years. The climatological study showed that the abnormality in mean sea level pressure and geopotential height at level of 500 hPa, in March 2019 were negative over Iran and positive over Europe. This indicates an increase in cyclone formation in the southwest of the Mediterranean Sea and increase in the frequency of passage of these systems from Iran. The results of the synoptic survey showed that the high ascending motions with adequate moisture feed have created favorable conditions for occurrence of moderate and severe convective precipitation in Golestan and Lorestan provinces.

The temperature is the most important climate parameter with a major role in detecting the effects of climate change. This study built on a statistical-analytical approach to analyze the hourly temperature variations in Iran. A database with 3,252,800 hourly air temperature records for 28 synoptic stations in the cold season was developed and refined for the 30-year period from 1985 to 2014. Using the linear inference method, the three-hourly synopses of air temperature were converted into hourly temperature. The Non-Parametric Mann-Kendall method was used to reveal the hourly temperature changes. The results showed that a limited number of stations experienced a significant increase in November, whilst a significant decrease was found in most stations in December. The most significant increase is found in the second half of the cold season in February and March. In March, all the stations had a positive and increasing pattern in terms of hourly temperature, and this increase was observed in the minimum hours of the night and morning. On average, more than 5 hours a day, an increasing trend was observed at 0.05 and 0.01 levels at most stations. There is an increasing trend in nearly the whole 24 hours in Meshkinshahr, Karaj, Golmakan, Tehran, Tabriz, Fasa, Yasuj, Khoy, M

Increasing the demand for agricultural products and increasing the pressure on water and soil resources, and the problems of access to field data on the other, will require the use of appropriate models to predict the yield of agricultural products. The most of the input parameters of crop models are not available in our country. On the other hand, with the emergence of strong statistical techniques and neural networks, predictive models of crop yields are rapidly developing. For this purpose, the present study was aimed to evaluate the capability of Artificial Neural Networks in learning from complex crop models and their performance in predicting wheat phenology and yield as well as some input parameters of the AquaCrop model. The evaluation of the models was done by statistical indexes, coefficient of determination (R²), normal root mean square error (SRMSE). The results showed that the neural network of model No. 9 (duration of growth period from flowering to harvest) was fitted with R2 and SRMSE, 0.98 and 4.79%, respectively, and the neural network of model No. 2 (Grain DM at maturity) was fitted with R2 and SRMSE, 0.97 and 9.69%, respectively, the best performance among predictive models of duration of growth periods and yield of wheat grain. According to this paper , The efficiency of artificial neural networks has been confirmed to predict yield and duration of growth periods of wheat using climate parameters.

The common methods for estimation of evapotranspiration and water requirement are generally based on the ideal and without stresses conditions. In field conditions, different stresses such as salinity, dryness, temperature, soil fertility and other field managements effect on evapotranspiration and water requirement. In this study, AquaCrop model is used for estimation of real evapotranspiration and water requirement in Moghan Plain. The results showed that the evapotranspiration and water requirement of this model is less than the Cropwat model, which is due to consideration of the region conditions such as soil moisture, salinity, fertility and other field managements by AquaCrop model. The Cropwat model only consider climate condition. According to the results obtained from the AquaCrop model, in comparison with the Cropwat model, water requirements of Wheat, Barley and Maize were reduced about 41, 69 and 790 m3/ha, respectively. Also the evapotranspiration and water requirement of the AquaCrop model were compared with NetWat. These parameters of AquaCrop are higher for wheat and maize, and for less barley data. NetWat data has a low degree of reliability, due to being old of weather data.

Evapotranspiration (ET) is the most important parameter in climatic and hydrological studies and that of the irrigation management and planning. Estimation of reference evapotranspiration (ETo) in a simple way is of great interest, especially in developing countries, where meteorological data required for standard method of FAO Penman- Monteith (PMF-56) is incomplete or not available. Also, despite of the large amount of agricultural development in the coastal of Iran, no comprehensive research in calculating evapotranspiration on the northern and southern coastlines has not been conducted. The aims of this study were: 1. assessment of reference evapotranspiration using five methods required low data including: Hargreaves-Samani, Priestley Taylor, Makkink, Turc. 2. Evaluation of the two models of the newest methods to estimate ETo by Valiantzas along with PMF-56 method, for evaluating the methods described. For this study meteorological data from 14 synoptic stations including 8 stations located in the Southern coastline and 6 stations located in the northern coastline of Iran, were selected. The statistical results have shown that among ETo estimation methods in terms of lack of data Priestley- Taylor method because of the higher temperature and humidity for the station located in the southern coastline, and Turc method due to temperate and humid climate for stations located in northern coastline has the best performance compared to PMF-56 method. Among the methods developed by Valiantzas, method of Valiantzas 2 has the highest correspondence compared to PMF-56 method.