Showing 32 results for Precipitation
Sahar Nasiri, Boroumand Salahi, Aliakbar Rasouli, Faramarz Khoshakhlagh,
Volume 22, Issue 66 (9-2022)
Abstract
Atmospheric circulation is important to determine the surface climate and environment, and affect regional climate and surface features. In this study, to quantify its effect, the classification system, developed by Lamb is applied to obtain circulation information for Ardabil, North West Province in Iran, on a daily basis, and is a method to classify synoptic weather for study area. For that purpose, daily mean sea-level pressure (MSLP) for extreme precipitation days from 1971 to 2007 is used to derive six circulation indices and to provide a circulation catalogue with 27 circulation types. The frequency of circulation types over different periods is computed and described. Five circulation types are most recognised in this study: E, SE, A, C and CSE. The catalogue and the associated indices provide a tool to interpret the regional climate and precipitation, and deal with the linkage between the mean extreme regional precipitations in north western of Iran and the large-scale circulation. Five circulation types E, A, SE, C and CSE are associated with high precipitation and rainy seasons (spring and September) but the most precipitation rate is resulted of cyclone family. Low pressure of north latitudes and central area of Iran with low pressure of gang from Pakistan and India. SE is almost dominant circulation type over the years. The cold season started from august to march is characterized by frequent directional flows, especially E, SE, A, C and CSE whereas in warm period (Apr–Aug) SE, NE, AE have smaller role, especially in July, August and September more frequent flows dominated by SE and E.
Mina Mirian, Mostafa Karampoor, Mohamd Moradi, Houshang Ghemi, Behrouz Nasiri,
Volume 23, Issue 68 (3-2023)
Abstract
The purpose of this study is to determine the long-term variations in rainfall data as well as to identify wet and dry periods of 35 synoptic stations in Iran. In order to know the variation of rainfall in studied stations, average maps, coefficient of variation and skewness were drawn. Then, using the Mann-Kendall test, the significance of the trend on each station was tested at 95% confidence level. Finally, wet and dry periods were identified by using 20% high and low extreme rainfall during the 50-year study period. The results show that the general model of the country's regime is that the rainfall levels from the north to the south-east and from the west to the east of the country are reduced. The lowest values of the coefficient of variation and skewness are related to the northern regions especially the Caspian seaside and the highest amounts are in the southern regions, especially in the south and south-east. In general, the results of the Mann-Kendall test show that rainfall data in the seasonal scale, with the exception of several synoptic stations, do not show a significant trend. Most wet periods occur in the spring and the lowest in summer and the highest dry periods occur in the autumn and the lowest in spring. The number of droughts in the cold periods is significant. Also, the frequency of occurrence of dry periods is more than wet periods.
Hadi Zare Khormizie, Hamid Reza Ghafarian Malamiri,
Volume 23, Issue 69 (6-2023)
Abstract
Knowledge of rangeland vegetation characteristics as well as factors affecting it in environmental planning, land management and sustainable development is very important. However, regional and up-to-date maps of pasture vegetation cover are not always available. In this study, in order to plot the vegetation cover percentage of the rangelands and monitor its changes in drought and wet periods, NDVI products of MODIS sensor during the years from 2000 to 2017 with a spatial resolution of 250 m and a 16-day time resolution, and The SPI drought index were used. The study area is the part of the rangelands located in the Southern province of Yazd. In 2013, in order to provide ground truth data, a field work was done to take the sampling rate of vegetation from the rangeland level in the study area. According to the results, the NDVI index has a good ability to map vegetation cover, so the coefficient of determination (R2) between this index and the sample points was 0.71. Based on the results, the average vegetation cover of the studied area was 11.3% during the years 2000 to 2017. The highest and lowest amount of vegetation cover in the study area was in 2000 and 2002, with moderate mild conditions and very severe drought, respectively (14.6% and 9.2% respectively). The most important factors influencing the vegetation cover in the study area are rainfall and drought periods, so that the coefficient of determination (R2) between the SPI drought index and the average vegetation percentage was 0.85. In general, based on the results there is a high potential for assessing and monitoring rangeland vegetation changes using satellite data and remote sensing technique.
Dr Raoof Mostafazadeh, Engr. Roghayeh Asiabi-Hir, Engr. Seyed Saied Nabavi,
Volume 23, Issue 69 (6-2023)
Abstract
Drought is the main causes of significant water imbalance, increase of crop losses or limitation in water consumption, and finally large number of socioeconomic and environmental problems. Precipitation amount is the most important climatic variables that its spatiotemporal variability has a great influence on water resources availability along with the effects of climate change. The Angot index is an indicator to determine the climatic cycles of precipitation as the ratio between the average values of multiannual precipitation over wet and dry periods which highlights the climate significance of monthly precipitation to detect dry or rainy intervals. The aim of this study is to assess and calculation of the Angot inxed in analysis of dry and wet periods of monthly rainfall in rain gauge stations of Ardabil province. The maximum values of Angot index were observed in November and May months. The results proved the suitability of the Angor index in determining wet and dry months and the comparison of the employed index with other common drought indices (e.g. Standardized Precipitation Index) and also different climatic zones of Iran needs further investigations.
Maryam Saghafi, Gholamreza Barati, Bohloul Alijani, Mohammad Moradi,
Volume 23, Issue 71 (12-2023)
Abstract
Precipitation is a phenomenon resulting from complex atmospheric interactions and among climatic events, due to its vital role, it has special importance. The importance of precipitation durability, especially in arid and semi-arid regions, which includes most of Iran, is greater than its volume. The purpose of this study is to identify Iran's precipitation areas in terms of precipitation durability and its characteristics in each area. In order to investigate the durability of Iran's precipitation and to define a precipitation day as " a day with equal precipitation or greater than 0.5 mm", used from daily precipitation data of 80 synoptic stations of the country during the 6 cold months of the year from October to March in a period of 30 years (2016 - 1987). Setting data in daily tables in the first step, made possible to program in MATLAB environment to separate precipitation in ten groups from "one day" to "ten days" and in the second step in SPSS environment based on frequency characteristics, amount and precipitations average in the mentioned groups was done by the method of Ward merging and clustering. The process of the clustering on Iran's durability precipitation showed that there are seven almost homogeneous precipitation zones in Iran; the geographical arrangement of Iran's precipitation areas, reveals the dependence of Iran's precipitations amount on roughness, the path of precipitation systems, its proximity to humidity sources, and the effect of the sea. In terms of area’s location, it can be said that; the settlement of the four zones in the western half of Iran, despite its small size in front of the eastern half, is a reason for its heterogeneity.
Mr Danesh Nasiri, Dr Reza Borna, Dr Manijeh Zohourian Pordel,
Volume 24, Issue 72 (3-2024)
Abstract
Knowledge of supernatural microphysical properties and revealing its relationship with the spatial temporal distribution of precipitation can significantly increase the accuracy of precipitation predictions. The main purpose of this study is to reveal the relationship between the Cloud microphysical structure and the distribution of precipitation in Khuzestan province. In this regard, first 3 inclusive rainfall events in Khuzestan province were selected and their 24-hour cumulative rainfall values were obtained. The rainfall event of 17December2006, was selected as a sample of heavy rainfall, 25 March 2019, as a medium rainfall case, and finally 27 October 2018, as a light rainfall case. Microphysical factors of clouds producing these precipitations were obtained from MODIS (MOD06) cloud product. These factors included temperature, pressure, and cloud top height, optical thickness, and cloud fraction. Finally, by generating a matrix with 64000 information codes, and performing spatial correlation analysis at a confidence level of 0.95, the relationship between the Cloud microphysical structure and the spatial values and distribution of selected precipitates was revealed. The results showed that in the case study of heavy and medium rainfall, the spatial average of 24-hour cumulative rainfall in the province was 36 and 12 mm, respectively. A fully developed cloud structure with a cloud ratio of more than 75% and a vertical expansion of 6 to 9 thousand meters, with an optical thickness of 40 to 50, has led to the occurrence of these widespread and significant rainfall in the province. While in the case of light rain, a significant discontinuation was seen in the horizontal expansion of the cloud cover in the province and the cloud cover percentage was less than 10%. In addition, the factors related to the vertical expansion of the cloud were much lower, so that the height of the cloud peak in this rainfall was between 3 to 5 thousand meters. The results of this study showed that in heavy and medium rainfall cases, a significant spatial correlation was observed at a confidence level of 0.95 between MOD06 Cloud microphysical factors and recorded precipitation values, while no significant spatial correlation was observed in light rainfall case.
Zoleikha Khezerluei Mohammadyar, , Bohloul Alijani,
Volume 24, Issue 73 (6-2024)
Abstract
The purpose of this article is to analyze the frequency and severity of the one to six days of rainfall in Iran. The trend of frequency changes and severity of each course was identified using my-candle test and the slope estimator during the 1968-1988 period. Then, using the main component analysis method and cluster analysis method, the entire stations were categorized in five clusters (abundance) and four (intensity) based on the annual changes of frequency indicators and intensity of precipitation. Cluster 1 and 2 stations represent the frequency of precipitation periods with a severe or without trend. The two clusters were mostly established in the southern half of Iran. Cluster 4 and 5 stations represent the frequency of precipitation periods with a positive (mild) trend, mainly in the northern part of the country. Cluster 3 stations represent the frequency of precipitation periods with decreased (mild) trends, which are mostly focused on west and southwestern Iran. The clustering results of the stations based on the intensity index of precipitation periods, contrary to many results; do not show a specific pattern. But in the cluster, there has been a severe decrease in the last half century. The stations of this cluster are mostly concentrated in the northern parts of the country. Other clusters are scattered in almost all parts of the country. Accordingly, it can be concluded that the frequency of precipitation periods in the northern latitudes of incremental processes (average or weak) and the severity of precipitation periods in these latitudes (north of the country) had severe declining trends.
Keywords: Frequency of precipitation, intensity of precipitation, analysis of main components, clustering, process.
Saeed Jahanbakhshasl, Ali Mohammadkhorshiddoust, Fatemeh Abbsighasrik, Zahra Abbasighasrik,
Volume 24, Issue 75 (12-2024)
Abstract
Assessing and predicting future climate change is of particular importance due to its adverse effects on water resources and the natural environment, as well as its environmental, economic and social effects. Meanwhile, rainfall is also an important climatic element that causes a lot of damage in excess conditions. West Azerbaijan Province is no exception. The aim of this study is to model and predict 30 years of rainfall in West Azerbaijan province. The statistical period studied is 32 years (2019-1987). Selected stations in the province include Urmia, Piranshahr, Takab, Khoy, Sardasht, Mahabad and Mako stations. Average slider time series models, Sarima (seasonal Arima), Health Winters were used for analysis and prediction and also linear regression and Mann-Kendall test were used to determine the data trend. The results show an increasing trend of precipitation in Urmia, Piranshahr, Khoy, Sardasht and Mako stations and a decreasing trend in Takab and Mahabad stations. According to the results of comparing the models used, the Health Winters model with the least error in the absolute mean of deviations, mean squared deviations and the percentage of absolute mean errors was introduced as the best precipitation forecasting model for West Azerbaijan province.
province. [A1]
Ali Hashemi, Hojjatollah Yazdanpanah, Mehdi Momeni,
Volume 24, Issue 75 (12-2024)
Abstract
This research study aims to investigate the effect of climatic variables, specifically precipitation, temperature, and humidity, on changes in vegetation indices of orange orchards in Hassan Abad, Darab County, using satellite data. Consequently, observational data, including orange tree phenology data and meteorological data from the agricultural weather station, were collected over a period of more than 10 years (2006 to 2016). MODIS images from 2006 to 2016 were referenced based on territorial data and 1:25000 maps from the Iran National Cartographic Center. These images were used to calculate remote sensing vegetation indices, namely the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The results demonstrated that the variables of maximum humidity, minimum temperature, and precipitation have a significant positive effect on the NDVI variable. Additionally, the variables of maximum temperature and minimum humidity have a significant negative effect on both the NDVI and EVI. To determine the significance of each independent variable in predicting the dependent variables, the artificial neural network method was employed. The findings showed that the climatic elements of precipitation, minimum temperature, maximum temperature, minimum humidity, and maximum humidity had the greatest effect on EVI, with values of 0.39, 0.3, 0.13, 0.1, and 0.06 respectively. Moreover, the effect of these variables on the NDVI index is equal to their coefficients, which are 0.2, 0.28, 0.22, 0.11, and 0.17 respectively. Finally, the ARMAX regression method was used to improve the explanatory power of the model. The results indicated that this method enhanced the explanatory power of the model and reduced the forecasting error.
Shamsallah Asgari, Tayeb Razi, Mohamadreza Jafari, Ali Akbar Noroozi,
Volume 25, Issue 76 (3-2025)
Abstract
Due to the importance of forests in natural and anthropogenic environment, the effects of meteorological drought on the dryness of oak forests in Ilam province were investigated. The main purpose of this study was to determine the relationship of Zagros forests with drought occurring in the area. The results of the Standard Precipitation Index (SPI) for the time periods showed that the most drought occurred in 2007, 2008, 2011, 2015 and 2016. Remote sensing data (MODIS images) were used to investigate the vegetation trend (NDVI) of trees during the period 2016–2016. The vegetation trend (NDVI) was significant over the period with the index drought index (SPI) with R2 = 0.9999. Ground harvesting of oak drying points and simulation using Landsat satellite imagery with 15 m pixel output from GIS software showed that 17894 hectares of area forests from 2000 to 2016 were dried and destroyed and prepared with oak forest and integrated layer. The output layers from the drought zoning were shown visually and the statistical analysis was performed in three 5-year time series. The results of these analyzes from 2002 to 2006 showed that the correlation coefficient between meteorological drought and oak drought 96.6% with a coefficient of determination R2 = 0.985, for the time series of 2007 to 2011 the correlation coefficient between scratches Meteorological and oak dryness of 95.4% with R2 = 0.980 and coefficient of correlation for meteorological drought and oak drought of 98.8% and R2 = 0.995 of coefficient respectively. Its fluctuations in time series show the intensity and duration of the drying up of oak forests in the region. According to the results of this study, it is predicted that if the drought goes through this process, 1118.4 hectares of oak forests in Ilam province will be dried and destroyed annually.
Zeinab Mokhayeri, Ebrahim Fatahi, Reza Borna,
Volume 25, Issue 76 (3-2025)
Abstract
To conduct this research, first, the data of monthly observations of synoptic and hydrometric precipitation from the National Meteorological Organization and the Ministry of Energy during the 30-year period (2006-2005) were obtained. To examine the prospect of future rainfall changes, the historical data of the period (1976-2005) and the simulated climate data of the period (2050-2021) using two models of CM3), (CSIRO-Mk3.6 from the series) Models (CMIP5) and according to 4 scenarios RCP2.6, RCP4.5, RCP6 and RCP8.5) that are available with a spatial resolution of 0.5 x 0.5 with the BCSD method have been used.Mean-based (MB) strategy has been used to correct the bias in the output of these models. The results of the AOGCM models showed that the CSIRO-Mk3.6 error coefficient was less than the GFDL-CM3 model for simulating precipitation in the case of Large Karun.The average future rainfall (2021-2050) in the whole basin compared to the average observed rainfall during the statistical period of 1976-2005 shows, in both models and scenarios in both basins in terms of amount and area of precipitation is decreasing significantly.Heavy rains in the Greater Karun Basin have been concentrated in all scenarios and models east of the basin. The highest rainfall was in the central foothills. The lowest rainfall is in the southwest and southeast. The final results of the present study are expected to be 83-116 mm. Both models are expected to have the highest rainfall in the Greater Karun Basin, with two scenarios: rcp4.5 and rcp2.6.
Dr Abolhassan Gheibi, Mr Ali Soleymani, Hossein Malakooti,
Volume 25, Issue 76 (3-2025)
Abstract
Nitrogen dioxide is one of the factors of reducing air quality in most regions of the world. The purpose of this research is to investigate the concentration and trend of nitrogen dioxide pollutant changes during the years 2005-2018 and also its relationship with the amount of precipitation in the region. The average vertical column concentration of nitrogen dioxide in the period between 2005 and 2018 by the OMI sensor on Iran shows that the highest concentration of nitrogen dioxide on Iran is about 3.07×10+16 
molecules per square centimeter of the air column section. Vardespehri, and in megacities, especially Tehran metropolis, which has the highest population density followed by the highest road transportation, by examining the trend of annual changes in the concentration of the vertical column of Vardespehri nitrogen dioxide and the average annual precipitation over Iran, we observe that the concentration of this pollutant with The increase in population and human activities has been increasing from 2005 to 2016 and decreasing from 2016 to 2018 due to population growth, but overall with a slope of 3/53×1013(molecule×cm
-2×year-1)
There has been an increase, in contrast to the time series of the average annual precipitation over Iran with a slope (-0.159 mm × year-1
), there has been a decreasing trend, and from the comparison of the trend of these two parameters, we can see that they have a negative effect on each other.
