Climatology
behrouz sobhani; minoo ahmadyan; Saeed jahanbakhsh
Abstract
the statistics of the ECMWF database were used for the observation data of the two stations of Semiram and Urmia during a 21-year period (1996-20016).In order to investigate the effects of climate fluctuations, the daily data of dynamic micro-rotation of the CORDEX project was used for the output of ...
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the statistics of the ECMWF database were used for the observation data of the two stations of Semiram and Urmia during a 21-year period (1996-20016).In order to investigate the effects of climate fluctuations, the daily data of dynamic micro-rotation of the CORDEX project was used for the output of the ICHEC-EC-EARTH model under the RCP8.5 and RCP4.5 radiative forcing (RCP) scenarios for the period (2017-2037). By using the data of the stations and the outputs of the micro scale model, and by using the perceptron neural network and linear regression, the performance was simulated. Then, to evaluate the efficiency of the models, R, R2, MSE, RMSE, and NRMSE statistics were used, and the non-parametric Menkendall test and age slope were used for the performance trend. The result of comparing the output of artificial neural networks with the linear regression model shows that the error rate of the neural network is less and the simulated results are close to the real observations to a very acceptable extent. The phenological stages, including bud blooming to fruit ripening in the stations under both scenarios, and in all the phenological stages in the future period will be completed earlier than the base period, and the length of the growth period will also decrease. The amount of future yield in Urmia station under RCP4.5 and RCP8.5 scenarios respectively yield 3.7 and 2.2 tons per hectare and in Semiram station yield 1.4 and 3 respectively tons per hectare will decrease. The results show that in the future in the study areas, with the change in the time of occurrence of the length of the growth period, all the phenological stages as well as the declining performance of apple trees will be subject to climatic fluctuations
GIS&RS
fakhry sadat fateminiya; behrouz sobhani; Seyed Abolfazl Masoodian
Volume 23, Issue 69 , December 2019, , Pages 213-231
Abstract
Satellite images as new tools, provide new dimensions for land monitoring. In this study, in order to determine the homogeneous geographical areas in terms of leaf area, the remote sensing images of the Terra-Aqua Modis during the period of 2002-2016 with a spatial resolution of one kilometer and 8 days’ ...
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Satellite images as new tools, provide new dimensions for land monitoring. In this study, in order to determine the homogeneous geographical areas in terms of leaf area, the remote sensing images of the Terra-Aqua Modis during the period of 2002-2016 with a spatial resolution of one kilometer and 8 days’ time interval used.Leaf area was Zoning and analysis using the Matlab software and the Google Earth database. For this purpose, first, the mosaic and determination of the territory of Iran in the satellite data set of the Modis was determined. Then, a database in the field of cluster analysis, choropleth zoning created. Long-term mean temperature and precipitation data were also used in order to better understand the range of the leaf area. According to this analysis, 39.9 percent of Iran's vast vegetation is governed. The four zones identified in the country are the large, massive, moderate, and narrow areas. These four domains are respectively 0.89, 0.001, 3.31, and 35.76 of the land. The results showed that in all studied areas, the leaf area had a higher percentage during The warm period of the year due to the high temperature in this period and the presence of precipitation in the early cold season. The northern slopes of the Alborz, Hyrcanian forests, Golestan forests, Arasbaran forests are areas where there are different regions in all zones. In addition to forests, the areas identified for each generally include fields.
Climatology
Mahmoud Houshyar; Behrooz Sobhani; Seyed Asaad Hosseini
Abstract
With the seriousness of the climate change debate in the world, the study of parameters and elements of the climate has been widely considered. With changes in climate patterns and changes in temperature and precipitation patterns, other components such as runoff and soil moisture, which are important ...
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With the seriousness of the climate change debate in the world, the study of parameters and elements of the climate has been widely considered. With changes in climate patterns and changes in temperature and precipitation patterns, other components such as runoff and soil moisture, which are important for natural and human systems, will undergo metamorphosis. Therefore, long-term prediction of climatic variables has been considered by many scientific communities worldwide in order to know about their changes and considering the necessary measures to moderate the adverse effects of climate change. The phenomenon of climate change is of increasing importance due to its scientific and practical dimensions, since human systems dependent on climatic elements such as agriculture, industry and the like are designed and operated on the basis of the stability and stability of the climate. Accordingly, general circulation models (GCMs) have been developed. Although these models represent significant results on the atmospheric and continental spatial scales, they combine a large part of the complexity of the planet's system, but they are inherently unable to control the dynamics and forms with a fine grid Local scalability. Therefore, an assessment of the effect of climate change on a local scale requires an interim and spatial gap between large-scale climatic variables and meteorological variables with local scale, in which case the main approach is the same downscaling models. The SDSM model is one of the most widely used statistical microscopic instruments, which has many uses in meteorological, hydrological, geographic and environmental studies. Because in this method, large-scale daily circulation patterns are used on a stationary scale; and when used for the rapid and cost-effective estimation of climate change, and for randomized meteorological generators and modified functions, have given acceptable results. Given that global models have generally simulated climatic elements until the year 2100, it is possible to use global model data to simulate the desired variables such as precipitation and temperature on a station scale. The Intergovernmental Panel on Climate Change (IPCC) has used its latest assessment report (AR5) on new scenarios for the RCP as representatives of different levels of greenhouse gas emissions. The new emission scenarios have four key paths RCP2.6, RCP4.5, RCP6 and RCP8.5, which are named after their radiation in 2100, Future Perspective. The variation of the maximum temperatures of the synoptic station of Urmia during the period (2021-2050) of the CanESM2 global model has been used under three scenarios RCP2.6, RCP4.5 and RCP8.5.
Climatology
Behrouz Sobhani; Mohammad Framarzi
Volume 20, Issue 56 , August 2016, , Pages 171-191
Abstract
Crop production ability and its potential are significantly up to climate, topography and land use which are the most important environmental factors. In this study, using climatic data such as temperature, precipitation, number of frost days, sunny hours and relative humidity related to phonology steps ...
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Crop production ability and its potential are significantly up to climate, topography and land use which are the most important environmental factors. In this study, using climatic data such as temperature, precipitation, number of frost days, sunny hours and relative humidity related to phonology steps of saffron growing, Also ground resource data such as topography, land use layers which are prepared by Landsat 8 satellite imagery dated 14/5/2013. Evaluating each of these parameters have been taken in relation to the climate and ecology needs of saffron. Information layers of them were prepared by adjusting data to the surface, and processing them by GIS technology. Multi-criteria decision analysis methods (MCDM), based on vikor were used in order to prioritize and evaluate information layers and their weights in connection with each other. Then layers were weighted based on the criteria and subject model also these layers were overlapped and analyzed in GIS environment. Consequentially, the final layer of land suitability was prepared for saffron cultivation. In this study, 10.23, 45.25 and 45.52 percent of the total area are good, average and weak suitability lands respectively. According to this research, vikor method can have an acceptable function over selecting the fitness values for each class.
