M.S. Ghazanfari Moghadam; A. Alizadeh; M. Mousavi baygi; A.R. Farid-Hosseini; M. Bannayan Aval
Abstract
Abstract
Precipitation as the most important factor plays the main role in many application researches which are based on climatic parameters. Many researches in the field of hydrology, hydrometeorology and agriculture employs rain-gauges (such as synoptic and climatologic stations) data. Precipitation ...
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Abstract
Precipitation as the most important factor plays the main role in many application researches which are based on climatic parameters. Many researches in the field of hydrology, hydrometeorology and agriculture employs rain-gauges (such as synoptic and climatologic stations) data. Precipitation characteristics, such as rainfall intensity and duration, usually exhibit significant spatial variation, even within small watersheds; while rain gauge network density could not provide desirable cover. Nearly all related researches use interpolation methods for places without rain gauge data. Many studies showed that the estimated error was usually high by usual interpolation methods. Employing satellite data with high spatial and temporal resolution could provide accurate precipitation estimation. PERSIANN (Precipitation estimation from remotely sensed information using artificial neural network) model works based on the ANN (artificial Neural Network) system which uses multivariate nonlinear input-output relationship functions to fit local cloud top temperature (Tb) to pixel rain rates (R). In this study, PERSIANN model and two interpolation methods (Kriging & IDW) were employed to estimate precipitation for North-Khorasan between the years 2006 until 2008. Results show better correlation between PERSIANN outputs and station data than other two interpolation methods. while correlation coefficient for Kendal`s test is 0.805 between model and Bojnord Station data, this coefficient is 0.488 for IDW and 0.565 for Kriging methods.
Keywords: PERSIANN model, IDW, Kriging, Interpolation methods, Precipitation estimation
M.S. Ghazanfari Moghadam; A. Alizadeh; M. Naseri; M. Mousavi baygi
Abstract
Abstract
The limitation of water sources in most places all over the world, especially in arid and semi-arid lands is an important Issue for those who live in these areas. Many governments have dedicated their efforts toward finding new water resources to obtain water. Fog and cap clouds harvesting ...
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Abstract
The limitation of water sources in most places all over the world, especially in arid and semi-arid lands is an important Issue for those who live in these areas. Many governments have dedicated their efforts toward finding new water resources to obtain water. Fog and cap clouds harvesting are one of the candidate methods to produce pure water. Many countries including Chile, Peru, Ecuador, Canada, Namibia and Nepal Have yet invested on fog harvesting. On the other hand, no significant calculation studies have been yet carried out on quantifying fog harvesting. In this work, we examined the Physical and dynamic relationship between cloud physics and atmosphere humidity; factors such as distribution of particle amounts, collection efficiency, water including base cloud and vapour flux were all considered. We also presented a new method to estimate fog harvesting, based on fractal theory and concerning the characteristics of collecting devices. Finally, we successfully evaluated the theories for fractal dimension of particle distribution, using the real data of fog harvesting. The incremental fractal dimension reliability was found to be 83% acceptable.
Keywords: Cap cloud, Fog, Fog harvesting, Fractal theory
M. S. Ghazanfari; A. Alizadeh; M. Naseri; A.R. Farid-hosseini
Abstract
Abstract
Urban expansion, pollution augmentation, and extention of major industrial activities in metropolitan areas impacted local climates of major cities. Transforming big cities into heat islands is one of the most prominent results of such a micro-climate change. In this study, variation of precipitation, ...
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Abstract
Urban expansion, pollution augmentation, and extention of major industrial activities in metropolitan areas impacted local climates of major cities. Transforming big cities into heat islands is one of the most prominent results of such a micro-climate change. In this study, variation of precipitation, temperature and some other important climatic parameters including relative humidity, and percentage of cloudiness were reviewed in order to study micro-climate change. The city of Mashhad selected for this study, as metropolitan area. The study was performed by comparing the climate parameters of this city with the neighboring regions, which were identified as the same climate category. Due to the effective role of rainfall in the urban weather modification and decreasing of pollution, rainfall variation is more important and crucial. The result of this research showed that the rainfall variation followed the temperature trend. A significant correlation between temperature and precipitation change showed the effect of heat island on urban climate parameters. The urban heat island phenomenon increase the hot season rainfall while its effects on cold season rainfall decrease.
Keywords: Urban Heat Island, Air pollution, Microclimate, Climate change
M.S. Ghazanfari Moghadam; M. Mousavi baygi; S.H. Sanaei-Nejad
Abstract
Abstract
Topography is the most important parameter which produces minimum temperatures in complex terrain. Radiative inversion occurs in the mountains and produces radiative freezing. When the land surface is cooled, a boundary layer forms. Since cold air is heavier than warm air, therefore, it flows ...
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Abstract
Topography is the most important parameter which produces minimum temperatures in complex terrain. Radiative inversion occurs in the mountains and produces radiative freezing. When the land surface is cooled, a boundary layer forms. Since cold air is heavier than warm air, therefore, it flows toward the down slope, which is named Katabolic flow. When Katabolic flows are formed, cold air accumulates in the valleys and thereafter in places which do not have a good drainage of air. Based on thermodynamic equations a model was developed to consider the accumulation of cold air in each point of a complex terrain. Minimum temperature prediction model (MTPM) was developed and used to predict the minimum temperature in complex terrains. This thermodynamic model uses digital elevation model to produce minimum temperature maps. Running MTPM for North Mountains of Tehran showed a good correlation between modeled and actual minimum temperatures.
Key words: Katabolic flow, Minimum temperature, Freezing ponds, Complex terrain, Thermodynamic models