Publish in OALib Journal

ISSN: 2333-9721

APC: Only $99


Any time

2019 ( 653 )

2018 ( 945 )

2017 ( 918 )

2016 ( 1285 )

Custom range...

Search Results: 1 - 10 of 593303 matches for " M. J. Nazemosadat "
All listed articles are free for downloading (OA Articles)
Page 1 /593303
Display every page Item
Prediction of Persian Gulf Sea Surface Temperature Using Multiple Regressions and Principal Components Analysis
M. J. Nazemosadat,A. Shirvani
Journal of Science and Technology of Agriculture and Natural Resources , 2005,
Abstract: Since the fluctuations of the Persian Gulf Sea Surface Temperature (PGSST) have a significant effect on the winter precipitation and water resources and agricultural productions of the south western parts of Iran, the possibility of the Winter SST prediction was evaluated by multiple regression model. The time series of PGSSTs for all seasons, during 1947-1992, were considered as predictors, and the time series of MSSTs during 1948-1993, as the prrdictand. For the purpose of data reduction and principal components extraction, the principal components analysis was applied. Just the scores of the first four PCs (PC1 to PC4) that accounted for the total variance in predictor field were considered as the input file for the regression analysis. For finding the dependency of each principal component to the first time series of the PGSST, the Varimax rotation analysis was applied. The results have indicated that PC1 to PC4 respectively are the indicator of temperature changes during winter, autumn, Spring and Summer. According to the regression model, the components of PC1, PC2 and PC4 were significant at 5% level. But the components of PC3 was insignificant. The results indicated that the significant variables are held accountable for the 33.5% of the total variance in the winter PGSSTs. It became obvious that for the prediction of the winter PGSST, the PGSST during the winter of the last year has a particular importance. At the next stage, autumn and summer temperature have also a role in prediction of winter PGSST.
Six-cold-month Precipitation over Southwestern and Central Iran and its Relation to E1 Ninio Southern Oscillation
M. J. Nazemosadat,A. R. Ghasemi
Journal of Science and Technology of Agriculture and Natural Resources , 2003,
Abstract: The present study evaluates the influence of the El Ninio Southern Oscillation (ENSO) phenomenon on the cold season precipitation over Isfahan, Fars, Khuzestan, Chaharmahal-Bakhtyari, Bushehr and Kohgiluyeh-Boyerahmad provinces. The results indicate that the occurrence of La Nina events caused a 20% to 50% reduction in precipitation over Bushehr, Chaharmahal-Bakhtyari and southern Fars. The cold event did not change the total precipitation over the other parts of the region. In contrast to La Nina episodes, the occurrence of El Ninio events caused a 20% to 70% increase in rainfall in most of the study area. While the most highly wet conditions are related to the El Ninio events, the occurrence probability of the severe droughts has found to be low during such events. In association with La Nina events, the occurrence probability of severe drought was found to be low. Only in Khuzestan and southern parts of the Fars Provinces, this probability has increased to about 0.5.
The Application of CCA for the Assessment and Comparison of the Capability of SOI and Nion’s SST for the Prediction of Winter Precipitation over the Caspian Sea Coasts
S. M. J. Nazemosadat,A. Shirvani
Journal of Science and Technology of Agriculture and Natural Resources , 2004,
Abstract: In Iran, about 75% of national rice production is supplied in Gilan and Mazandaran proviences which have the highest amount of precipitation. Seasonal prediction of rainfall induces significant improvement on yield production and on preventing climate hazardz over these feritle areas. Canonical correlation analysis (CCA) model was carried out evaluates the possibility of the prediction of winter rainfall according to the states of ENSO events. The time series of (southern oscilation index (SOI) and SST (sea surface temperature) over Nino's area (Nino's SST) are used as the predictors, and precipitation in Bandar Anzali and Noushahr are used as the predictands. Emperical orthogonal functions (EOF) were applied for reducing the number of original predictors variables to fewer presumably essential orthogonal variables. Four modes of variations (EOF1, EOF2, EOF3, EOF4) which account for about 92% of total variance in predictors field were retained and the others were considered as noise. Based on the retained EOFs and precipitation time series, the canonical correlation analysis (CCA) was carried out to predict winter precipitation in Noushahr and Bandar Anzali. The results indicated that the predictors considered account for about 45% of total variance in the rainfall time series. The correlation coefficents between the simulated and observed time series were significant at 5% significant level. For 70% of events the anomalies of observed and simulated values have the same sign indicating the ability of the model for reasonable prediction of above or below normal values of precipitation. For rainfall prediction, the role of Nino's SST (Nino4 in particular) was found to be around 10% more influential than SOI. .
The Influence of the Caspian Sea SSTs on Winter and Spring Precipitation over Northern and Southwestern Parts of Iran
S. M. J. Nazemosadat,A. R. Ghasemi
Journal of Science and Technology of Agriculture and Natural Resources , 2005,
Abstract: The influence of the Sea Surface Temperatures (SSTs) on the seasonal precipitation over northern and southwestern parts of Iran was investigated. The warm, cold and base phases of the SSTs were defined and the median of precipitation during each of these phases (Rw, Rc and Rb, respectively) was determined. The magnitude of Rw/Rb, Rc/Rb and Rc/Rw were used as criteria for the assessment of the effects of the alternation of SST phases on seasonal precipitation. The results indicate that in association with cold SST phase, winter rainfall is above median over western and central parts of the coastal region, central and southern parts of Fars Province and all the stations studied in Khozestan Province. On the other hand, the prevalence of warm SST phase has caused about 20% decrease in winter precipitation over the Caspian Sea coastal area and northern parts of both Fars and Khozestan provinces. In association with warm SST phase in winter, precipitation during the following spring was found to be above normal for all the stations studied in the coastal region of the Caspian Sea. The highest sensitivity levels were found in Bandar- Anzali and Astara for which spring precipitation has increased by 80% due to the dominance of warm winter phase. However, the occurrence of boreal cold SST events causes shortage of precipitation in the eastern parts of the coastal areas along the Caspian Sea. A Possible Physical mechanisem justifying the influence of the Caspian Sea SST on the Precipitation variability was introduced. According to this mechanisem, temporal and spatial variability of the Siberian High is forced by the fluctuations in these SSTs.
Evaluation of the Effects of Madden Julian Oscillation on the Occurrence of Dry and Wet Spells in Fars Province, Iran
M. J. Nazemosadat,H. Ghaedamini Asadabadi
Journal of Science and Technology of Agriculture and Natural Resources , 2011,
Abstract: The Madden Julian oscillation (MJO) is known as the primary mode of large-scale inter-seasonal variability in tropical regions, affectimg equatorial and sub-tropical climates. This study investigated the effects of the MJO on the occurrence of wet and dry spells in Fars province, central southern part of Iran, during November-April. Monthly precipitation data of nine stations spread over various parts of the province was analyzed during 1979-2005. Using two well-known MJO indices: MK and WH, the positive and negative phases of the MJO phases (enhanced and suppressed convective activity over the equatorial Indonesian region, respectively) were identified for monthly and seasonal scales. Precipitation-MJO composites were then constructed for the opposite phases. It was shown that for all the considered stations, seasonal precipitation during negative MJO phase was significantly greater (from about 2.5 to 6.0 folds) than the corresponding values during the positive phase. Moreover, the applied statistical tests proved that the frequency of wet or dry events was related to the prevalence of negative or positive MJO phase, respectively. As the positive MJO phase was engulfed, the probability of dry events varied from 60% to 84%. On the other hand, the probability of wet events was found to vary from 60% to 76% during the MJO negative phase.
Effects of El Nino Southern Oscillation on the Discharge of Kor River in Iran
Morteza Mohsenipour,Shamsuddin Shahid,M. J. Nazemosadat
Advances in Meteorology , 2013, DOI: 10.1155/2013/846397
Abstract: The objective of the study was to investigate the El Nino forcing on the discharge of Kor River located in Maharloo-Bakhtegan basin in the Fars province of Iran. Thirty-one-year (1965–1995) and twenty-year (1975–1995) monthly mean river discharge data recorded at two stations, namely, Chamriz and Dehkadeh-Sefid, respectively, were chosen in the present study. Fourier analysis was used to extract harmonic information of time series data such as amplitude and phase angle to show the maximum effect and the time of effect of El Nino on river discharge. The study revealed that El Nino events caused increase of discharge in Kor River by 15% to 20% and the maximum influence was in the months of February and March in El Nino years. 1. Introduction In normal condition, the temperature of ocean surface in the east of southern Pacific Ocean is lower than the temperature of surface water in the west of southern Pacific Ocean. Therefore, a high pressure zone and a low pressure zone dominate in the east and the west of the southern Pacific Ocean, respectively [1]. The difference between high and low pressure zones causes wind blowing, namely, trade wind or easterlies. The direction of wind is from the east to the west of Pacific Ocean. Therefore, trade wind causes the movement of surface warm water in equatorial region from the east to the west. During El Nino period, the temperature of surface water in the west is lower than the temperature of surface water in the east of southern Pacific Ocean. This large-scale pressure seesaw in Pacific Ocean is called Southern Oscillation (SO). Therefore, the direction of trade wind and also warm water changes from the west to the east. Existing warm water pool in the coast of Peru and Southern Ecuador is the sign of El Nino [1, 2]. The two phenomena, El Nino and Southern Oscillation, together are known as ENSO. The relationship between El Nino and some parameters such as temperature, rainfall, and discharge was investigated in different parts of the world. Their results have showed that El Nino causes floods and droughts on different parts around the world [3, 4]. Cayan and Peterson [5], Kahya and Dracup [6], Zhang et al. [7], Ward et al. [8], Cahoon [9], Osman and Abdellatif [10], Mu?oz-Salinas and Castillo [11], Wang and Eltahir [12], Simpson et al. [13], Kahya, and Karab?rk, [14], and many other researchers conducted the impact of El Nino on the discharge. Cayan and Peterson [5] predicted discharge anomalies in the Western United States in two seasons by using Southern Oscillation Index (SOI). Zubair [15] investigated the
Application of Dew Point in the Prediction of Chilling Stress (Case Study in Jahrom, Fars Province)
M.J. Nazemosadat,A.R. Sepaskhah,S. Mohammady
Journal of Science and Technology of Agriculture and Natural Resources , 2001,
Abstract: In the Islamic Republic of Iran, the occurrence of chilling and freezing stresses have frequently caused great damages to crops and horticultural products. In southern Fars Province (south Iran) the cultivation of citrus orchards is popular and the economic losses due to injury from chilling and freezing stresses may exceed billions of Rials annually. The drop of ambient air temperature (above zero) reduces the ordinary metabolism activity of plants and causes chilling stress. If the temperature drops below zero and remains there for a considerable time, intercellular freezing may occur. This process always kills the cells and provokes tissue injury. In the present study, the possibility of predicting daily minimum temperature using the dew point of a previous day measured at 18:30 was examined. It was found that the prediction of minimum temperature is possible if the dew points are modified on the basis of the air relative humidity. For the episodes that relative humidity varies from 45% to 55%, minimum temperature at day i+1 was found to be almost equal to the dew point on the previous day (day i). For the periods that relative humidity is above (below) this range, the minimum temperature on day i+1 was observed to be greater (lower) than the estimated dew point on day i.
Application of the Principal Component Analysis for the Regionalization of Winter Precipitation over Boushehr, Fars, and Kohgiloye & Boyerahmad Provinces
S. M. J. Nazemosadat,B. Baigi,S. Amin
Journal of Science and Technology of Agriculture and Natural Resources , 2003,
Abstract: The study of geographical extent of precipitation pattern is important because of its impact on agriculture, water resources, tourism, industry, dams, and irrigation. The principal component analysis (PCA), as an elegant mathematical tool, was applied for the regionalization of winter precipitation in central south Iran (Fars, Boushehr, and Kohgiloye and Boyerahmad Provinces). Averaging monthly rainfall data of Dey, Bahman and Esfand (20 December to 20 March) produced the time series of winter rainfall. In each individual station, correlation matrix of the normalized data was then performed for the computation of the standard PCA. Eigenvalues, eigenvectors, PC time series and the loading of the principal components were then computed. The Screet test technique was applied as a trial for addressing the problem of determining the number of PC modes that should be retained. Two of the first PCs, which account for 68.1% of total variance in the rainfall data, were kept and used for the regionalization of rainfall data. The rotation solution was then selected as a suitable tool for delineating the rainfall region associated with the retained PCs. The results indicated that for the first PC, loading became high over most part of the study area. Therefore, the time series of PC1 that accounts for about 60.4% of the variance in raw data, could be used as the regional time series of winter rainfall over most parts of the provinces studied. The second PC revealed a high loading over a small area in northern part of the regions studied (Bavanat in Fars Province). Rainfall in this station showed poor correlation with the precipitation over the neighboring station in Fars Province. It seems that the rainfall in Bavanat is mostly influenced by the Mediterranean air masses entering the area through the northern and western districts. For the other parts of the regions studied, Sudan current which encroaches the country through southwestern borders (Persian Gulf regions) make up an essential portion of winter rainfall.
Development and Evaluation of Global Solar Radiation Models Based on Sunshine Hours and Meteorological Data
A Majnoni-Heris,SH Zand-Parsa,A Sepaskhah,M.J Nazemosadat
Journal of Science and Technology of Agriculture and Natural Resources , 2009,
Abstract: Global solar radiation (Rs) has wide applications in several disciplines. The data of measured or predicted Rs are widely applied by solar engineers, architects, agriculturists and hydrologists. Due to the importance of Rs, several empirical models have been developed to predict its values all over the world. In this study, Angstrom model was calibrated based on the ratio of actual and possible sunshine hours n/N by using measured daily data of Rs at Bajghah meteorological station in Fars province during 2003-2004. The model was modified by using air temperature for considering the effect of cloudy conditions as well as n/N ratios. The results showed that using both the air temperatures and the ratios of n/N led to a higher accuracy. In regard to estimation of the Rs values, the results showed that mean air temperatures have a higher accuracy compared with differences between maximum and minimum air temperatures. Also, a new local model with higher accuracy was developed based on a number of daily meteorological parameters such as deficit vapor pressure, relative humidity, precipitation, mean air temperature, maximum and minimum air temperatures difference and n/N. This new local model that used different meteorological parameters had the highest accuracy in comparison with the other models. Also, a number of models developed by other investigators for estimation of Rs were calibrated for the study area. Finally, different selected models were validated by using the measured data of Rs in 2005. The results showed that the developed local multi-variable model provided higher accuracy results in comparison with the other radiation models.
Effect of carbon dioxide concentration and irrigation level on evapotranspiration and yield of red bean
Sh. Shams,S.M.J Nazemosadat,A.A Kamgar Haghighi,Sh. Zand Parsa
Journal of Science and Technology of Greenhouse Culture , 2012,
Abstract: Increasing atmospheric CO2 concentration affects plant activities directly. In order to investigate the effect of CO2 concentration, an experiment was conducted at Research Greenhouse of College of Agriculture, Shiraz University, Shiraz, Iran. In this research, the effects of increasing CO2 concentration from 350 to 750 mg/L were studied on growth and yield of red bean (Phaseolus vulgaris, cv. Naz) at four irrigation levels (1.2 FC, FC, 0.8 FC and 0.6 FC). In order to control CO2 concentration, at the onset of the 4-leaf stage, pots were moved to wooden chambers covered with plastic. The results showed an average 15% decrease in evapotranspiration due to increasing the CO2 concentration. Also the results indicated an increasing effect of CO2 concentration on growth and yield of bean plants. Reducing the irrigation level to 0.6 FC caused the elevated CO2 concentration not to have any significant effect (P<0.05) on growth and yield of the red bean. By increasing the CO2 concentration, number of seeds/plant at FC and 0.8 FC irrigation treatments increased by 13 and 11%, respectively. Moreover, increasing CO2 concentration caused 20% increase in total seed yield. Total dry matter increased about 15% at higher CO2 level. The conclusion of this research was that increasing CO2 concentration has significant effect on yield and reduction of evapotranspiration of red bean.
Page 1 /593303
Display every page Item

Copyright © 2008-2017 Open Access Library. All rights reserved.