No abstract

Large-scale climatic teleconnections have noticeable effects on meteorological events in different regions of the world. In this study, the linkages between three major climatic indices, Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and Southern Oscillation Index (SOI), and precipitation in Iran were assessed from 1960 to 2014, at 30 synoptic stations in a time-frequency space, using wavelet coherence (WCO). The results showed that the SOI is the most effective climatic teleconnection on precipitation in Iran, although the other studied climatic indices have noticeable effects as well. The predominant and effective period of AO on precipitation was equal to or greater than 32 months at most of the stations, while the major effective period of NAO was equal to or greater than 64 months. For the SOI, most parts of the country were affected by a period of less than 64 months, while the predominant period of SOI for the northwestern part of the country was greater than 64 months. A uniform phase difference was not observed between the three studied climatic indices and precipitation in the country; instead the phase differences were usually random. For long-term periods of SOI, an anti-phase situation was detected at most of the stations. The study suggested that the WCO is a very powerful and flexible method for studying the relationship between multiple time series in a time-frequency space, and its application in hydrological and meteorological research is expected to increase in the near future.

Aridity is a permanent feature of climate based on long‐term climatic conditions over a region. Climatic indices are reliable tools to explore climate type, and climatologists have proposed various indices to classify climate and investigate the aridity or humidity in any region. In this study, we examined spatiotemporal variations of aridity in Iran during the last six decades from 1954 to 2013, using the de Martonne aridity index (IDM), which is calculated based on precipitation and temperature. Data used in this study were extracted from the Global Precipitation Climatology Centre and the University of Delaware gridded data sets, respectively. Both data sets have global high‐resolution (0.5° × 0.5°) coverage, and temporally span more than a century of data (from 1901). According to the data obtained from these data sets, more than 80% of Iran has an arid and semi‐arid climate (annually), although the spatial pattern of IDM varies throughout the year. Using the Mann–Kendall test showed a negative significant trend in IDM in 20% of Iran's total area in spring, and less than 7% in the other seasons of the year. Overall, it can be concluded that there were no significant trends in aridity for most parts of Iran during the last six decades.

Soil temperature is a very important variable in agricultural meteorology and strongly influences agricultural activities and planning (e.g. the date and depth of sowing crops, frost protection). There are many physically based studies in the literature which model soil temperature, but few are easily applicable for use in the field. Simple and precise short‐term forecasting of soil temperature with minimum data requirements is the main goal of this study. The soil temperature at 0300, 0900 and 1500 GMT was forecast based only on surface air temperatures using artificial neural network (ANN) and wavelet transform artificial neural network (WANN) models. The hourly data were collected from the Mashhad synoptic station in Khorasan Razavi province in Iran between 2010 and 2013. The results of this study showed that using a wavelet transform for preprocessing improved the accuracy of soil temperature forecasting. It was also found that changing the temporal increment in forecasting time did not have a noticeable effect on errors in the WANN models. WANN models can be used as accurate tools to forecast soil temperature 1–7 days ahead at depths of 5–30 cm.

 Since Iran's groundwater hydrochemistry has not been well understood, we explored it using a rich, nationwide data sampled from 9,468 wells. Findings indicate the dominance of mix water type in 13 out of 30 of Iran's sub-basins, followed by NaCl water type in nine sub-basins. A distinctive relationship exists between Iran's geological-geomorphological features and hydrochemical facies/groundwater quality. This study's results can be used in the formulation of new strategies and policies for Iran's groundwater quality management in the future.