جستجوی مقالات مرتبط با کلیدواژه « نوسان » در نشریات گروه « جغرافیا »

Extreme rainfall fluctuations are one of Iran's environmental challenges. The heavy rains of 2019 and the relative drought of 2018 and 2021 show the unevenness of rainfall.

This study utilized the daily rainfall data from 360 weather stations spanning the years 1990 to 2021, along with the synoptic indices of the winter seasons of 2019 and 2021. The geographical range of the data, spanning from latitude N 10-90 to longitude E º 10-90, was chosen to provide a comprehensive view of the Iranian climate.

The probability of drought is 42%, drought is 35.5%, and normal conditions are 22.5%. Markov chain indicated the highest probability of normal drought to drought at 57% and consecutive drought at 46.2%. ANOVA showed a significant difference between the climatic variables of wet and dry years. Observational conditions showed that in the wet year (2019) sample year, the Siberian high-pressure center operator had more pressure (1054 megabytes) in 2019 and 1032 mb in 2021. In the wet year, the frequency of cyclones and the temperature difference at the level of 500-1000 are higher, but the omega values are lower. These conditions are for the drought (2021), the amount of pressure in Siberia, the temperature difference between 500 and 1000 is less, and Omega is more (stable air).

The amount of rainfall in Iran fluctuates from year to year, and low rainfall years occur more often than high rainfall years.

Innovation: 

Planners should increase the risk of water supply and development and plan based on the minimum amount of precipitation. The physical capacity of the country's ecology should be reviewed, and population concentration in limited areas should be avoided to reduce the vulnerability of the country's geographical environment.

Air temperature is considered as one of the most important criteria for detecting fluctuations or changes in the climate system, which appears as a fractal phenomenon by adopting a self-similar structure in multiple time scales; Therefore, the temperature signal has a complex and non-linear structure that shows a very complex behavior in different time. In this study, the dynamic nature of daily temperature time series (1401-1329) of Khorramabad synoptic station was identified using Hurst scale-range analysis (R/S) and detrended fluctuation analysis (DFA2). The results of (R/S) show that there are sinusoidal fluctuations with annual and seasonal scales in the time series of air temperature. Also, three points of cross in the signal of temperature fluctuations were identified, and these fluctuations have different trends and structures around these points. On the other hand, the DFA2 results revealed that the scale profile and time series correlation have been changed due to seasonal trends. In this regard, the seasonal detrending of the data revealed that the fluctuation function increases proportionally with the increase of the time scale, which indicates the fractal nature of the temperature signal. Also, the Hurst exponent was obtained as 0.77, which indicates the existence of correlation and long-term memory in the daily air temperature signal of Khorramabad.

Identifying trends and structural breaks in the rainfall time series is one of the most important challenges in climate change studies. As the discovery of such structural breaks can help assess future scenarios and atmospheric phenomena such as floods and droughts. In this study, in order to identify structural breaks in the daily and monthly precipitation time series of Khorramabad synoptic station, two approaches of multifractal detrended fluctuation analysis (MF-DFA) and Maximal overlap discrete wavelet transform (MODWT) were used. The results of applying MF-DFA on the daily rainfall time series (1961-2018) showed that there are three structural breaks in this time series that the rainfall trend around these points has changed significantly. On the other hand, the results of this approach showed that the period 1985-2002 is the most fluctuating period of precipitation and the periods 1961-1969 and 2010-2018 are the periods with the lowest fluctuations in precipitation. Calculation of the fluctuation function at time scales of 2, 5, 10 and 20 years showed that in the period 2000-2018, fluctuations of 2 to 20 years have decreased. The results of the fluctuation function with q order also showed that the periods 1965-1970 and 1989-1994 were associated with large fluctuations in precipitation. If the two periods of 1999-2004 and 2008-2013 refer to periods with small fluctuations in precipitation. Also, the results obtained from the application of MODWT on the monthly rainfall time series showed that the wavelet coefficients changed in 2007. In this regard, by dividing the high frequency signals of the wave into two periods including 1961-2007 and 2008-2018, it was found that the differences between precipitation fluctuations during the scales of 8 to 16 months have the most variability in the precipitation time series.

North Atlantic oscillation effective pattern of variability of atmospheric general circulation in the extra-tropical Northern Hemisphere are the main climatic factors that control precipitation and temperature. They have huge economic and social impacts and also on the energy section, agriculture, industry and so son. Considering the importance of the oscillation on human activities and its relationship with climatic elements including precipitation, we identified and analyzed the positive phase of the oscillation and its subsequent relationship with winter rainfall in Iran. Data needed for this study included measurements of the amount of rainfall on a daily basis in synoptic stations, Climate and rain gauge data for the entire country in the years 1340-1388 were used, the sources of which are Meteorological Organization and the Ministry of Energy. By the use of multivariate statistical methods and Matlab, Surfer and Grads software the extraction of synoptic patterns. The results indicated five patterns extractions despite the stable condition in five patterns of the earth's surface in this phase, and the measurement of atmospheric precipitation that justifies this subject, was done by using patterns in 500 hpa level. Iran is located in the axis of cyclone related to the Mediterranean basin. Therefore, atmospheric precipitation in the whole country was dominated by the low pressure occurrence in winter.

Identification and analysis of time-series behavior of the climatic elements and processes upon them are the basic factors of climatology science and has an important role in management and environmental planning. In general، the behavior of climatic elements are observed in 3 form: Trend، Oscillation and Fluctuation. These behaviors will help us to identify more the climate change. Today by changing more the trend of climatic elements، climate change has become more important than previous years. But in between the climatic elements، it has been noticed less than the other elements such as water vapor pressure. The importance of water vapor is that this climatic parameter is has an important role in explaining the climate change، because of 1) It is the main source of rainfall in all weather systems، 2) It supplies the latent heat in this process and controls the heat in the troposphere and 3) It is the intensify severe storms. Given the significant role of atmospheric moisture in the Earth''s energy equilibrium، it can be helpful in explaining climate change. Therefore، this article tries to survey two time series behaviors of climate data; the trends and fluctuations in water vapor pressure. The Mann-Kendall test is one of the popular nonparametric techniques for explaining the trend analyzing in hydrological and climatic data. The spectrum analysis is one of the best methods for extracting and analyzing visible and invisible climatic oscillations with different wavelength. In fact، spectrum show the distribution of variance along the entire range of wavelengths in time series. So in this article، we want to analyze the trend by using the Mann-Kendall test and detect and identify the fluctuations and cycles of water vapor pressure time series by using the spectrum analysis. Study area: The study area، with about 360،200 km2 area، is located in the south and southwest of Iran and approximately between 25° 00''N and 34° 25''N latitudes and between 45° 38''E and 59° 17''E longitudes. Southern and southwestern parts of the study area is located in sides of two massive sources of moisture، Persian Gulf and Oman Sea.

In this study، water vapor pressure data from 28 synoptic stations، during a period of more than 20 years in south and southwest of Iran were used that were collected by the Iranian Meteorological data website (http: //www. weather. ir). It should be noted that to survey the Mann-Kendall test and Spectral analysis، the stations with 44-years period (2010-1967) and stations that have data since their establishment were used، respectively. The methodology of this study is detecting trends and oscillation of water vapor pressure in south and southwest of Iran by Mann-Kendal test and Spectral analysis، respectively based on ground station. Tests for the detection of significant trends in climatological time series can be classified as parametric and non-parametric methods. Parametric trend tests require data to be independent and normally distributed، while non-parametric trend tests require only that the data be independent. In this study، a non-parametric method، Mann-Kendal، was used to detect trends. To analyze the Oscillation of water vapor pressure، the spectral analysis has been applied. In this function، frequency and cycles indicate the time scale and amount of variance in the time scale، respectively. After extracting all waves، in second step the proportion of each waves in explaining the total variance are specified and Finally، the significance of each waves are tested. For performing the Mann-Kendall test and spectrum analysis technique، the capability of programming in MATLAB software was used.

The results showed significant trend in most of the stations. As the results of this article، the downward significant trend in the stations of Ahwaz، Bandarabas، Shahrekord، Boroujen، Abadeh and Khorramabad، the upward significant trend in Lengeh، Bushehr، Dezful and non-significant trend in Abadan، Fasa and Shiraz was seen. By applying the spectrum analyzing in 95% confidence level on the water vapor pressure data، the multiple cycles were obtained; So that the significant sinusoidal cycles 3-2، 4 and 15-7 years were more common. Results show that the cycles of 3-2 years was most repeated in the water vapor pressure time series. 4-year cycle was the other cycle of events occurred in the study area that researchers have attributed this cycle to ENSO. The survey showed that more cycles are traceable in the southern part of the Zagros. Another cycle in the region was 15-7 year cycle that most scientists have attributed this cycle to sunspot activity. The final survey showed that the plurality of cycles in the West and South West of the study area.

In general it can be concluded that the downward significant trend of water vapor pressure was observed in the Zagros and the upward significant trend was observed in nearby the Persian Gulf. By applying the spectrum analyzing on the water vapor pressure data، the multiple cycles were obtained. Results of spectral analysis showed that the cycles of 3-2 years was most repeated in the water vapor pressure time series. The spatial distribution of this cycle was observed in the near of Persian Gulf coasts. Most scientists have attributed this cycle as a result of El Niño - Southern Oscillation (ENSO) and Quasi-biennial oscillation (QBO).

Climate change is one of the major challenges faced by man in the current age. Phenomena such as precipitation changes, global warmness, melting of polar ices, flood, unexpected and severe coldness and warmness in most parts of the world are so severe, damaging and stressful that have resulted in climate change to be at the top of the studies of climatic sciences researchers and extensive international, regional and local studies have already addressed that. In order to review the possibility of climate change in Kerman Province, precipitation average, minimum, average and maximum temperatures of synoptic station in Kerman during 1956-2005 were received from the website of meteorology organization and was adjusted in terms of time series and was then studied by using Man – Kendall test. In this research, type and time of changes in the aforesaid elements were identified by using the above model. The results obtained from the analyses indicate that commencement time of most changes is sudden and of both trend and fluctuation types. precipitation changes in warm months is considerable while minimum, average and maximum temperatures in April, November and December were more considerable. No significant changes are observed in other months. On the whole, precipitation in the station during the period of study decreased and average, minimum and maximum temperatures increased.

A spectral analysis is a technique to discover and analyses of obvious and latent different waves in climatic oscillation. The spectrum yields a measure of distribution of variance in a time series over all possible wavelengths. In this paper the periodic cycles of annual air temperature time series of Tabriz city for 1951-2005 (55 years) have been estimated based on harmonic analyses. Accordingly at first the periodogram smoothed, and then confidence interval of smoothed periodogram estimated to find out the significant cycles. The result of this method in Tabriz shows prominent sinusoidal periodicities at 2-2.6 and 4.5-5 years as well as a non – sinusoidal (trend) cycle. The periodic behaviors are proofed in many other studies as an ENSO or solar activities results and In others as a result of zonal winds change, while the 5 year cycles are related to the error of waveforms over relatively short, finite intervals.

In this paper, the temperature and annual precipitation data has been applied in 44 years for the synoptical stations northwest zone of Iran. Among the stations, eight of them, which have the perfect data and coverage, has been considered to analysis applied. In this study Transfer function models have been used to analysis time series. In this method, firstly, the stations have been modeled then the data has been analyzed and predicted on them. Finally, from the process exam the considered stations have been examined, and the significant of fluctuations process of temperature and precipitation have been characterized. The results show that Mianeh, Tabriz and Maku stations have significant process. In process of annual precipitation, according to the results of exams, Tabriz, Ardabil, Urmieh and Khoy stations have significant process and in all of them annual precipitation has falling process.

In this paper, for the aim of local climatic change detection, fluctuations of freezingdays in Mashhad during 1951-2000 were studied.Primary investigations showed that annual mean and absolute temperature have anincreasing trend in the study period. It has a suitable harmony to decreasing trend offreezing days. So, correlation equation between freezing days and statistical yearscalculated by this formula. Y=107.35X-0.53 which it was meaningful and shows –29.5 days changes in Annual freezing days in mentioned period. Using test of Mann-Kendal showed two decreasing and decreasing trend, which are significant. We canobserve a falling trend in number of freezing days after 1976.In next phase, for the purpose of fitting a suitable time series model on the data,which used in this research, the method of Box-Jenkins was applied. Finally after somestatistical works ARIMA (1,1,0) time series model was selected for the studied data.The model was able to predict the number of freezing days of Mashhad in the year2001 with an error about 3.3 percent.