Showing 5 results for Trend Analysis
Dr. Mostafa Karimi, Mis Fatemeh Sotoudeh, Dr. Somayeh Rafati,
Volume 18, Issue 48 (3-2018)
Abstract
Increasing CO2 emissions and consequently, air temperature causes climate anomalies which affects all the aspects of human life. The purpose of this study was to assess the temperature changes and also to predict the extreme temperatures in Gilan and Mazandaran Provinces. To do this, the SDSM statistical and dynamical model was used. As well, it was applied the Mann-Kendal graphical and statistical technique to analyze the temperature changes and its trend. In this regard, the daily temperature was obtained from Rasht, Ramsar and Babolsar synoptic stations during 1961 – 2010, and also the general circulation models data of HadCM3 and NCEP were collected from related databases. The results revealed a significant positive trend in monthly and annual minimum and maximum temperature in all three stations in the first (1961-2010) and third (1961-2040) periods. There is not a significant trend in extreme temperatures in Ramsar and maximum temperature in Rasht in the second period (2011-2040). The Mann-Kendal graphical test was used for the yearly extreme temperatures in all periods. The results showed that it was occurred both increasing trend and suddenly changes or shifts at the 95% confidence level in all stations. It is occurred the highest of changes in monthly and annual of the minimum temperature at forecasted period (2011-2040). It was predicted extreme temperature to increase about 0.1 to 1.7° C. The short time oscillations and significant positive trend occurred in both the maximum and minimum temperature shows the temperature increase and climate changes in the future. Thus it is obvious the decrease in temperature difference in warm and cold seasons.
Rahmatollah Shojaei Moghadam, Mostafa Karampoor, Behroz Nasiri, Naser Tahmasebipour,
Volume 18, Issue 51 (6-2018)
Abstract
The purpose of this study is to analyze and analyze Iran's precipitation over the past half-century(1967-2017). For this purpose, the average monthly rainfall of Iran during the statistical period of 50 years was extracted from Esfazari databases (Which is provided using data from 283 stations of Synoptic and Climatology). Regression analysis was used to analyze the trend and to analyze the annual and monthly rainfall cycles of Iran, spectral analysis was used. Investigation and analysis of monthly precipitation trend indicates that except for central Zagros (Lorestan and Chaharmahal va Bakhtiari and Gorgan areas, where rainfall in winter season has increased trend), in other parts of the country and in other seasons, the trend of decline Precipitation is prevalent. The study of Iranian rainfall cycles has been shown that Most of Iran's rainfall cycles are 2 to 4 years old and have a short term course. Meanwhile, there are two middle-cycle 25-year cycles in January-July and two long-term 50-year cycles in March and December, indicating a trend in the March and December rainfall. The two months of February and October lacked a clear cycle. The analysis of the auto-correlation model of rainfall showed that the high spatial auto-correlation model in winter was consistent with the western, southwestern and coastal of the Caspian Sea and covered about 14% of the country's. The low spatial auto-correlation model is found in sparse spots in the southern, central and southeastern regions of the country in winter and spring, and covered about 7.5% of the country's. The results of this study indicate that the overall trend of Iran's rainfall is decreasing trend and only in winter, in the small regions of the country, the increase trend is observed.
Ali Bahri, Younes Khosravi,
Volume 20, Issue 58 (9-2020)
Abstract
Considering the vast application of sea surface temperature in climatic and oceanic investigations, this parameter was studied in Oman Sea from 1986 to 2015. The SST was surveyed using trend analysis and Global and local Moran’s I spatial autocorrelation. In trend analysis, the Mann-Kendall test was used to determine the trend of SST changes and the Sen's Estimator method was used to examine the slope of the changes. Using these methods, it was found that during January, February and December, there was no significant ascending trend in SST values, and only parts of the Strait of Hormuz had a significance descending trend. On the other hand, there was no significant descending trend in March, and the ascending trend in the SST was seen in the southern part of the Oman Sea. Other months of the year had a significant ascending and descending trend in different parts of the Oman Sea, which October had the highest ascending trend. In the annual time scale, it was also found that the southern parts of the Oman Sea had ascending trend in the SST value and Western parts had a descending trend. The occurred changes in the high amounts (positive and negative) were corresponding to the significance ascending and descending trends. The results of Global Moran for the annual time scale indicated an ascending trend of autocorrelation values and cluster patterns of SST data over time, using the local Moran analysis, it was found that warm clusters of SST are increasing in the Oman Sea, and on the other hand, cold clusters of this parameter have been reduced over 30 years. According to the results of trend and spatial autocorrelation analysis, it has been found that SST have been increasing in different parts of the Oman Sea during 30 years, so climate change and global warming may have affected this region.
Dr Behzad Amraei,
Volume 22, Issue 64 (3-2022)
Abstract
Climate change is one of the most important challenges facing water resources management, including surface water and groundwater. The main purpose of this research is to detect the effect of droughts caused by the change in groundwater resources in Birjand plain. In this regard, using two nonparametric trend tests, the SENS and MAN-Kendal gradient estimates to detect the process of underground water level in Birjand city during the statistical period of 1370-1395 according to the statistics of the field of 47 areas of observation area (census water resources) Wentified. Using Pearson correlation matrix, correlation between climatic elements (Birjand station) temperature, precipitation and evapotranspiration and potential transpiration were calculated with the level of local city of Birjand, and based on a multivariate regression model for modeling the annual time series at the level of confidence level of 95 / 0 was developed. Climatic factors of 2080-2065 using the Output of the HADGEM2-ES model through the LARS-WG exponential model for the position of the Birjand station under two scenarios RCP8.5 and RCP2.6 were simulated and based on the regression model, the surface of the water Birjand city was simulated. The results indicated that firstly, in the base period (1370-1395), the surface of water in the area with an annual gradient of 47 centimeters per year was reduced. The correlation analysis indicated that three elements of rainfall, temperature and evapotranspiration were modeled in a linear composition of 75% of the annual changes in groundwater. The results of the microsterge model implemented on HADGEM2-ES data indicate that during the period 2035-2065 under both the scenario, groundwater level between 10 and 13 meters lower than the base period, which resulted from an increase in evapotranspiration And consequently, rainfall will be effective.
Ms Zienab Hosinpoor, Dr. Aliakbar Shamsipour, Dr. Mostafa Karimi, Dr. Faramarz Khoshakhlagh,
Volume 23, Issue 68 (3-2023)
Abstract
Heat waves are important phenomena in Iran, And its upsurge in recent years seems to have a high upside trend.This climate has a negative impact on agriculture, forest fire and forestry, water resources, energy use and human health.The purpose of the research is to explain the frequency, time distribution, continuity of thermal waves, and the identification of its occurrence in the southern foothills of central Alborz.Therefore, using the statistical methods and maximum daily temperature data of Tehran (Mehrabad), Qazvin and Semnan stations for the statistical period of 30 years (1966-2016), the mentioned characteristics were extracted.In the first step, the nonparametric method of Kendal was used to understand the variability and awareness of the monthly trend of maximum temperatures in the study period.In order to determine the severity, duration and frequency of heat wave events, the percentiles (95.98) and normalized temperature deviation (NTD) were used.The results of the study showed that the frequency of short-wave heat waves was higher.Most frequencies are related to 2-day waves, respectively, and Tehran (Mehrabad), Semnan and Qazvin stations are more frequent.The highest frequency of annual events was detected at stations in Tehran (11 waves in 2010), in Semnan (9 waves in 2015) and Qazvin (7 waves in 2015), respectively.The highest frequency of monthly heat wave events was recorded in June and September.The highest continuation (15 days) was obtained in March 2008 with the percentile method at Mehrabad station.In the normalized deviation method, the temperature was calculated as a warm wave (12 days) in 2008.The highest annual frequency of heat loss occurred in all three stations in 2015.The evolution of the process indicated an increase in the incidence of thermal waves in the cold period of the year But in other chapters, no meaningful changes were made.As it says, the decline in cold winter temperatures is on the southern slopes of Alborz.The results of the two methods showed that in the normalized deviation of the temperature, the number of thermal waves more than the percentile method was recorded, but in the percentile method, the thermal wave was more prominent in the cold period of the year.
