Change point analysis of mean annual air temperature in Iran

Analysis of recent changes in maximum and minimum temperatures in Pakistan

“…Cheema et al (2006) for Faisalabad and Sadiq and Ahmed (2012) examined variations in diurnal maximum temperature over Chaklala (Islamabad). At regional scale some researches can be mentioned for the northern areas of Pakistan: Hussain et al (2005) studied the climatic variability in the mountain regions of the country in winter and monsoon seasons and its implications for water and agriculture; Fowler and Archer (2006) Subash and Sikka (2014) in India; , Kousari et al (2013) and Shirvani (2015) in Iran; and Su et al (2006), Qin et al (2010) and Wang et al (2014) in China.…”

Change in annual precipitation in the northwest of Iran

“…Precipitation and air temperature are the main factors influencing seasonal changes in the water level of Lake Oroomieh (Jalili et al ., ). There is a change point in the annual air temperature time series of Tabriz station in 1994 (Shirvani, ). Hassanzadeh et al .…”

“…Change point detection has been studied in meteorology (Reeves et al ., ; Jandhyala et al ., ; Itoh and Kurths, ; Beaulieu et al ., ; Guerreiro et al ., ; Shirvani, , ) and hydrology (Buishand, ; Salas, ; Kiely, ; Ngongondo, ). Because it is difficult to express the distribution of the test statistic under the null hypothesis of no change, the asymptotic distribution (Csörgö and Horváth () and Monte Carlo methods (Antoch and Hušková, ; Ross, ) are used to obtain the distribution of the test statistic approximately.…”

Detecting breakpoints in artificially modified- and real-life time series using three state-of-the-art methods

“…a nite sequence of independent random variables (X , ·, Xn), where x t is a particular realization of X i at the point in time (t i ), the segments before {X , ·, X k } and after {X k+ , ·, Xn} a breakpoint (T = k) the distribution of the data is di erent, and this change can indeed be detected using a two sample hypothesis test [28]. In the present study, since the modelled time series were of Gaussian distribution, the Student-ttuned for detecting changes in the mean [36] -Bartlett -designed for nding changes in the variance [50] -and Generalized Likelihood Ratio (GLR) statistics -originally tuned for detecting changes in both [51] -were used and compared on the di erently modi ed time series.…”

“…In the case of climatic time series, since instrumental meteorological recordings began [26] it has always been a problem to determine if a conspicuous change occurring in the data is just an artefact, or an actual breakpoint [27]. Thus, numerous studies exist dealing with climate conditions -regardless whether the subjects of the analysis are instrumental [28] or proxy data -where, e.g. abrupt changes are sought after [7,8,10,29].…”