Sargazi S.,Tarbiat Modares University |
Taheri Shahraiyni H.,Tarbiat Modares University |
Habibi-Nokhandan M.,Climatological Research Institute |
Sanaeifar M.,Islamic Azad University at Tehran
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2011
Spatial modeling of air pollutants in the mega cities such as Tehran is a useful method for the estimation of pollutants in the non-observed positions in Tehran. In addition, spatial modeling can determine the level of pollutants in different regions of Tehran. There are some typical interpolation techniques (e.g., Inverse Distance Weighting (IDW), Thin Plate Splines (TPS), Kriging and Cokriging) for spatial modeling of air pollutants. In this study, different interpolation methods are compared for spatial modeling of carbon monoxide in Tehran. The three-hourly data of wind speed and direction was received from 5 meteorological stations in Tehran. The hourly data of carbon monoxide in 2008 have been extracted of 16 air pollution monitoring stations in Tehran. The hourly data of 3 selected days in 2008 (72 hours) and similarly, the daily data of 36 days in 2008 (3 days in each month) were utilized for spatial modeling in this study. Different typical interpolation techniques were implemented on different hourly and daily data using ArcGIS. The percent of absolute error of each interpolation techniques for each hourly and daily interpolated data was calculated using cross validation techniques. Results demonstrated that Cokriging has better performance than other typical interpolation techniques in the hourly and daily modeling of carbon monoxide. Because it utilizes three input variables (Latitude, Longitude and altitude) data for spatial modeling but the other methods use only two input variables (Latitude and Longitude). In addition, the wind speed and direction maps were compatible with the results of spatial modeling of carbon monoxide. Kriging was the appropriate method after Cokriging. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
Shahraiyni H.T.,Free University of Berlin |
Shahraiyni H.T.,Shahrood University |
Shahsavani D.,Shahrood University |
Sargazi S.,Tarbiat Modares University |
Habibi-Nokhandan M.,Climatological Research Institute
Atmospheric Pollution Research | Year: 2015
Spatial distribution modeling of CO in Tehran can lead to better air pollution management and control, and it is also suitable for exposure assessment and epidemiological studies. In this study MARS (Multi–variate Adaptive Regression Splines) is compared with typical interpolation techniques for spatial distribution modeling of hourly and daily CO concentrations in Tehran, Iran. The measured CO data in 2008 by 16 monitoring stations were used in this study. The Generalized Cross Validation (GCV) and Cross Validation techniques were utilized for the parameter optimization in the MARS and other techniques, respectively. Then the optimized techniques were compared based on the mean absolute of percentage error (MAPE). Although the Cokriging technique presented less MAPE than the Inverse Distance Weighting, Thin Plate Smooth Splines and Kriging techniques, MARS exhibited the least MAPE. In addition, the MARS modeling procedure is easy. Therefore, MARS has merit to be introduced as an appropriate method for spatial distribution modeling. The number of air pollution monitoring stations is very low (16 stations for 22 zones) and the distribution of stations is not suitable for spatial estimation, hence the level of errors was relatively high (more than 60%). Consequently, hourly and daily mapping of CO provides a limited picture of spatial patterns of CO in Tehran, but it is suitable for estimation of relative CO levels in different zones of Tehran. Hence, the map of mean annual CO concentration was generated by averaging daily CO distributions in 2008. It showed that the most polluted regions in Tehran are the central, eastern and southeastern parts, and mean annual CO concentration in these parts (zones 6, 12, 13, 14 and 15) is between 4.2 and 4.6 ppm. © Author(s) 2015.
Danesh A.S.,ECO International |
Ahadi M.S.,ECO International |
Fahmi H.,University of Tehran |
Nokhandan M.H.,Climatological Research Institute |
Eshraghi H.,ECO International
Journal of Water and Climate Change | Year: 2016
As a result of inappropriate management and rising levels of societal demand, in arid and semi-arid regions water resources are becoming increasingly stressed. Therefore, well-established insight into the effects of climate change on water resource components can be considered to be an essential strategy to reduce these effects. In this paper, Iran’s climate change and variability, and the impact of climate change on water resources, were studied. Climate change was assessed by means of two Long Ashton Research Station-Weather Generator (LARS-WG) weather generators and all outputs from the available general circulation models in the Model for the Assessment of Greenhouse-gas Induced Climate Change-SCENario GENerator (MAGICC-SCENGEN) software, in combination with different emission scenarios at the regional scale, while the Providing Regional Climates for Impacts Studies (PRECIS) model has been used for projections at the local scale. A hydrological model, the Runoff Assessment Model (RAM), was first utilized to simulate water resources for Iran. Then, using the MAGICC-SCENGEN model and the downscaled results as input for the RAM model, a prediction was made for changes in 30 basins and runoffs. Modeling results indicate temperature and precipitation changes in the range of ±6 °C and ±60%, respectively. Temperature rise increases evaporation and decreases runoff, but has been found to cause an increased rate of runoff in winter and a decrease in spring. © IWA Publishing 2016.
Salahi-Moghaddam A.,Hormozgan University of Medical Sciences |
Mohebali M.,Tehran University of Medical Sciences |
Moshfae A.,Tehran University of Medical Sciences |
Habibi M.,Climatological Research Institute |
Zarei Z.,Tehran University of Medical Sciences
Geospatial Health | Year: 2010
Between 1998 and 2001, a total of 1,062 human cases of visceral leishmaniasis were reported from the rural district of Meshkin-Shahr in the mountainous, north-western Iranian province of Ardabil. In the summer of 2008, a cross-sectional study of dogs was conducted in this endemic area by randomly selecting 384 animals from 21 villages and testing them serologically for leishmaniasis. Villages, in which more than 10% of investigated dogs showed anti- Leishmania titres ≥1/320, were considered to be high-risk environments. Regression analysis showed no statistically significant correlation between topographic conditions and the prevalence of positive cases. However, when the results were compared with past meteorological records, a statistically significant positive correlation (P = 0.007) was found between the number of infected dogs with anti-Leishmania titres ≥1/640 and the number of days in a year with temperatures below 0 °C. While humidity showed an inverse correlation (P = 0.009) with the anti-Leishmania titres, a positive correlation (P <0.001) was found in relation to the amount of rainfall. Mapping of the areas at risk for kala-azar in the Meshkin-Shahr district supports the impression that the low temperatures prevalent in the Ardebil province constitute an important factor influencing the distribution of leishmaniasis there.
Salahi-Moghaddam A.,Hormozgan University of Medical Sciences |
Habibi-Nokhandam M.,Climatological Research Institute |
Fuentes M.V.,University of Valencia
Geospatial Health | Year: 2011
Following human fascioliasis outbreaks in 1988 and 1999 in Gilan province, northern Iran, efforts are now made to shed light on the seasonal pattern of fascioliasis transmission in this endemic area, taking into account snail host populations, climatic conditions and human cases. Populations of the intermediate host snail (Lymnaea spp.) peak in May and November, while there is a fourfold increase in the rate of human fascioliasis in February compared to that of September. Transmission is likely to occur mainly in late autumn and sporadically in late spring. Rainfall, seasonally analysed in periods of 3 years, indicates that accumulated summer rainfall may be related with the 1988 and 1999 human fascioliasis outbreaks. Although a more detailed picture, based on the analysis of further abiotic and biotic factors influencing fascioliasis transmission in this area, is required to substantiate this hypothesis, our results serve as the first step of a geographical information system project concerning the epidemiological study of fascioliasis in Iran. This local-scale study concerning the effects of climate change and natural disasters on the spread of fascioliasis aims to facilitate the understanding of what goes on at the regional scale in this respect.
Barati M.,Tehran University of Medical Sciences |
Keshavarz-Valian H.,Tehran University of Medical Sciences |
Habibi-Nokhandan M.,Climatological Research Institute |
Raeisi A.,Center for Diseases Management and Control |
And 2 more authors.
Asian Pacific Journal of Tropical Medicine | Year: 2012
Objective: To conduct for modeling spatial distribution of malaria transmission in Iran. Methods: Records of all malaria cases from the period 2008-2010 in Iran were retrieved for malaria control department, MOH&ME. Metrological data including annual rainfall, maximum and minimum temperature, relative humidity, altitude, demographic, districts border shapefiles, and NDVI images received from Iranian Climatologic Research Center. Data arranged in ArcGIS. Results: 99.65% of malaria transmission cases were focused in southeast part of Iran. These transmissions had statistically correlation with altitude (650 m), maximum (30 °C), minimum (20 °C) and average temperature (25.3 °C). Statistical correlation and overall relationship between NDVI (118.81), relative humidity (45%) and rainfall in southeast area was defined and explained in this study. Conclusions: According to ecological condition and mentioned cut-off points, predictive map was generated using cokriging method. © 2012 Hainan Medical College.
Zarghami M.,University of Tabriz |
Abdi A.,University of Tabriz |
Babaeian I.,Climatological Research Institute |
Hassanzadeh Y.,University of Tabriz |
Kanani R.,East Azerbaijan Regional Water Company
Global and Planetary Change | Year: 2011
Changes in temperature and precipitation patterns have serious impacts on the quantity and quality of water supply, especially in arid regions. In recent years, frequent climatic droughts have threatened the water supply in East Azerbaijan Province, Iran. Because of the increasing demand for water, studying the potential climate change and its impacts on water resources is necessary. To predict the climate change based on the General Circulation Models (GCM), the successful downscaling tool of LARS-WG is applied. This stochastic weather generator downscaled the climate change of six synoptic stations in the province by using the HADCM3 model and three emission scenarios, A1B, A2 and B1, with the horizons 2020, 2055 and 2090. The research outcomes, based on the A2 scenario, show an average annual temperature rise of ~. 2.3°C and an annual precipitation reduction of ~. 3% in the middle of this century. These changes shift the climate of the province from semi-arid to arid based on the De Martonne aridity index. Using the artificial neural network (ANN), a model was then built to simulate the effects of climate change on the runoffs in three watersheds; the results showed dramatic reductions in the flows. The results of this study could advise the designers and managers of this region to take suitable actions in securing the water supply. © 2011 Elsevier B.V.
Arabshahi H.,Ferdowsi University of Mashhad |
Asmari M.,Climatological Research Institute
International Journal of Physical Sciences | Year: 2010
Optical design of multilayer filter has been carried out using a particle swarm optimizer algorithm. The filters are designed to work for wavelength in the range of 1550 - 1600 nm. Our calculation results show good convergence rate and higher performance in comparison with results based on genetic algorithm. The calculated result for band pass filter layers of Sio2 and SnTe have also shown that the transmittance parameter is about 0.994. The results for narrow filters show that the values of S and P reflectance parameter are in fair agreement with other methods and average transmittance parameter is about 0.985 which is 25% better than flip-flop results. © 2010 Academic Journals.
Bannayan M.,Ferdowsi University of Mashhad |
Sanjani S.,Ferdowsi University of Mashhad |
Alizadeh A.,Ferdowsi University of Mashhad |
Lotfabadi S.S.,Ferdowsi University of Mashhad |
Mohamadian A.,Climatological Research Institute
Field Crops Research | Year: 2010
Agricultural drought occurs when there is a deficit in soil water supply to crops. Severe drought limits crop water availability and reduces yield. Rainfed crop production is very vulnerable to drought conditions and farmers in northeast of Iran who heavily depend on their rainfed cereals production usually suffer from drought occurrence. Based on history, any severe drought resulted in severe financial problems and forced the affected farmers to move to cities in search of alternative jobs. Any possibility to enable the farmers to mitigate or adapt to drought is highly required. In this study, the relationship between aridity index (AI) and detrended crop yield (1985-2005) of selected crops (wheat and barley) and the influence of three climate indices (AO, NAO and NINO-3.4) were assessed for Khorasan province in northeast of Iran. All associations were assessed at annual, seasonal (wet and dry seasons) and monthly scale considering both concurrent and lag correlations (1-year and 2-year lag). Our results indicated a significant correlation (P< 0.05) between the AI and crops yield mostly in central Khorasan province. Our study also showed that correlation coefficient between AI and barley yield was stronger than AI and wheat yield across all study locations. Seasonal (wet) AI showed significant correlation with crops yield. These results demonstrated that, in some areas of Khorasan, drought is one of the key causes of interannual yield variability. We also observed a significant association between NAO and NINO-3.4 with AI. Precipitation is one of the components of AI, so AI response to NAO and NINO-3.4 can be related to the observed association between this index and precipitation. It seems that these indices could be useful tools to monitor drought patterns and subsequent yield variability in some regions of Khorasan province. © 2010 Elsevier B.V.
Ghanbari J.,Ferdowsi University of Mashhad |
Karimian M.,Climatological Research Institute |
Babaeian I.,Climatological Research Institute |
Motiei M.,Ferdowsi University of Mashhad
Journal of the Earth and Space Physics | Year: 2013
The Islamic calendar is based on lunar months, which begin when the thin crescent Moon is actually sighted in the western sky after sunset within a day or so after the New Moon. The Islamic dates begin at sunset on the previous day. The visibility of the lunar crescent as a function of the Moon's age-the time counted from the New Moon-is obviously of great importance to Muslims. The date and time of each New Moon can be computed exactly but the time that the Moon first becomes visible after the New Moon depends on many factors and cannot be predicted with certainty. The sighting of the lunar crescent within one day of New Moon is usually difficult. The crescent at this time is quite thin, has a low surface brightness and can easily be lost in the twilight. Generally, the lunar crescent will become visible to suitably-located, experienced observers with good sky conditions about one day after the New Moon. However, the time that the crescent actually becomes visible varies quite a bit from one month to another. The record for an early sighting of a lunar crescent with a telescope is 12.1 hours after New Moon; for naked-eye sightings, the record is 15.5 hours from New Moon. For Islamic calendar purposes, the sighting must be made with the unaided eye. Obviously, the visibility of the young lunar crescent depends on atmosphere conditions, the location and preparation of the observer. The prediction of the first sighting of the early crescent Moon is an interesting problem because it simultaneously involves a number of highly non-linear effects. Effects to be considered are the geometry of the Sun, Moon, the width and surface brightness of the crescent, the absorption of the Moon's light and the scattering of the Sun's light in the Earth's atmosphere, the physiology of human vision and natural horizon. The effects of meteorological conditions such as mean sea level pressure, visibility, mean temperature and humidity on Crescent visibility are studied in this paper. Our studied sites are located in the south, center and eastern part of Iran including Mashad, Bojnord, Birjand, Isfahan, Shiraz and Kerman cities. Two series of data are used in this study. The first one data were sighting and visibility of the lunar crescents which recorded by Moon's sighting groups in the above mentioned cities and the second series of data were the meteorological observations of mean sea level pressure, mean temperature, horizontal visibility and relative humidity in the same dates and locations of Moon's sighting. Horizontal visibility is divided into two categories of bellow and above 10kM. Period of study was 8 years starting from 1423 to 1430 according to Islamic calendar. Genetic algorithm is used to formulate the relations between moon visibilities and meteorological parameters. Genetic algorithms are one of the best ways to solve a problem for which little is known. They are very general algorithms and so may work well in any search space. Genetic algorithms use the principles of selection and evolution to produce several solutions to a given problem. Two methods of linear and non-linear approaches are used to model the statistical relations between the lunar visibilities and meteorological parameters. For linear-based method the following formula is used: [equation presented] We used the bellow formula for the nonlinear approach: [equation presented] Where MSE is the Mean Square Error, Robs and Rmod represent actual and modeled visibility of the Moon. P, RH, T and V are mean seas level pressure, relative humidity, temperature and visibility, respectively. (n-p) is degree of freedom and ai is constants. One of the important factors affecting crescent visibility is meteorological parameters, but they have not been considered well up to now. In this paper a Genetic algorithm has been used to find relationship between percentage of crescent lighting and meteorological parameters such as sea level pressure; mean temperature, relative humidity and horizontal visibility. In this regards, observations have been considered during the period of 1423-1430 lunar Hejri(Islamic calender) calendar for Mashad, Kerman, Shiraz, Esfahan, Birjand, and Boujnourd for two cases with about 10 km horizontal visibility. Error, bias and weighted factor of meteorological impacts on crescent visibility have been calculated after comparing modeled and observed crescent visibility. Results generally show that non-linear parameterization equations have more bias than linear equations. Maximum bias with 3.24 has been occurred in nonlinear model for horizontal visibility less than 10km over Birjand and Bojnourd sites. The minimum bias of crescent visibility has been occurred in Shiraz by 0.01 percent. The minimum and maximum percentages of relative error are found in Shiraz and Birjand by 1.96% and 99%, respectively. We also found that in linear modeling with horizontal visibility more than 10km, weighted effect of pressure increase by decreasing altitude from mean sea level and effect of humidity decreases by increasing altitude from mean sea level. Our result confirms that the crescent visibility is more sensitive both to pressure and horizontal visibility. Overlay, linear and nonlinear equations have acceptable results for modeling crescent visibility. Results of this paper reveal that meteorological parameterization of crescent visibility can be used for prediction of crescent visibility from meteorological view point.