Change in annual precipitation in the northwest of Iran

Abstract

The detection of changes in precipitation is important in water resources research and hydrological modelling studies. In this study, the Mann-Whitney non-parametric change point model (CPM) was applied to indicate whether a change point has occurred in the mean of annual precipitation in 18 synoptic stations in different regions of Iran for the period 1951-2010. The parametric likelihood ratio test (LRT) and the non-parametric Thiel-Sen slope were also employed to evaluate the detected change points. The precipitation time series (PTS) of the stations, which were serially correlated, were transformed to produce uncorrelated pre-whitened time series. The pre-whitened time series were then used as input file for the CPM, LRT and Thiel-Sen slope. The non-parametric CPM estimated change points in the PTS of Kerman, Oroomieh, Shahroud and Tabriz in 1997, 1994, 1967 and 1994. The results of the LRT indicated that the PTS before and after these change points follow a gamma distribution but with different means. The difference in annual precipitation means before and after the detected change point for Oroomieh station, located in the northwest of Iran, is 67 mm, as an example. The Thiel-Sen slope estimated a greatly decreasing rate of change for Kerman station after 1997.

Understanding spatiotemporal variability of drought in recent decades and its drivers over identified homogeneous regions of India

“…This choice of the test statistic in the CPM defines the class of changes which it is optimized toward detection. This has been already applied in other climatic studies (Shirvani, 2017).…”

Evaluation of the forecast skill of North American Multi‐Model Ensemble for monthly and seasonal precipitation forecasts over Iran

“…The latest versions of the NMME models and skill of these models for forecasting Iran's precipitation has not been evaluated thus far. A substantial ENSO influence has been documented in the previous work (Nazemosadat and Cordery, 2000;Barlow et al, 2002;Nazemosadat and Ghasemi, 2004;Mariotti, 2007 , 2017;Alizadeh-Choobari et al, 2018). The focus of the current study is to investigate how well that influence translates to MMM forecast skill for Iran, and whether there is MMM forecast skill that is in addition to the ENSO influence.…”

“…Iran lies within the western Alpine-Himalayan chains with the Alborz and Zagros mountain ranges. These two mountain ranges play a vital role in the Iranian atmospheric systems, consequently influencing the amount and distribution of precipitation over Iran (Shirvani, 2017). Using the GPCC data, Figure 1 depicts the percentage of the climatological mean of monthly precipitation over the study area, taken here as the region bounded by the rectangle 26 -39 N and 44 -62 E. The wet season spans from October through May, with the largest precipitation totals observed from December through March.…”

Spatiotemporal Variations of Precipitation over Iran Using the High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR Dataset

“…Annual precipitation [39] 1955-2000 Arid and semi-arid regions Significant trend in two stations [40] 1966-2005 Throughout Iran Significant negative trend in seven stations, which occurred mostly in the northwest [41] 1951-2005 Throughout Iran Significant negative trend in three stations, which observed in the northwest [42] 1966-2005 West, South and southwest Significant negative trend in only one station [43] 1967-2006 East, central, and north Significant negative trend in three stations, which happened mainly in the northwest [44] 1951-2005 Throughout Iran Significant negative trend in five stations [45] 1950-2007 Southwestern Significant positive trend in seven stations [38] 1961-2010 Throughout Iran Significant negative trend in eight stations [46] 1951-2010 Throughout Iran Significant negative trend in five stations [47] 1967 The remainder of this paper is organized as follows. Sections 2 and 3 provide information on the study area and the methodology, respectively.…”