Variability of extreme temperature and precipitation in Iran during Recent decades

Atmospheric Science and Meteorological Research Centre (ASMERC), Tehran, Iran
International Journal of Climatology (Impact Factor: 3.16). 03/2009; 29(3):329 - 343. DOI: 10.1002/joc.1739


We examined extreme temperature and precipitation as indicative climatic variables to determine recent climatic changes over Iran. We present the results from 27 synoptic stations which have been quality controlled, tested for homogeneity and have less missing data. For each station, 27 indicative climatic indices recommended by the joint World Meteorological Organization CCL/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI) were calculated.
Marked negative trends for indices like frost days (FD), ice days (ID), cool days (TX10p), cool nights (TN10p) and diurnal temperature range (DTR) were found over most regions of Iran. Conversely, positive trends were found for summer days (SU25), warm days (TX90p) and tropical nights (TR20) over most regions of the country. For indices such as Cold Spell Duration Index (CSDI) and Warm Spell Duration Index (WSDI), both positive and negative trends were obtained.
We found negative trends in consecutive dry days (CDD) over most of the country. A negative trend was observed for about two-thirds of the country for annual total wet days precipitation (PRCPTOT). Positive trends in the Simple Daily Intensity Index (SDII) were found for the northern half of the country, and concurrently negative trends in total wet days for many places within the same region. We observed a negative trend in very wet days exceeding the 95th percentile (R95p) over the eastern and western regions, and a positive trend over the central region of the country, although a clear negative trend was observed for extremely wet days exceeding the 99th percentile (R99p) over most of the country. No similar trends in either the maximum 1-day precipitation (Rx1DAY) or maximum 5-day precipitation (Rx5DAY) were found over the country. Copyright

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    • "This opportunity gives many possibilities for further applications especially for distributed modeling of environmental processes (Debesch et al. 2010). There are many studies on temperature extremes in Iran on regional and global scales without using of climatic gridded data, e.g., Alexander et al. (2006), Zhang et al. (2005a), Rahimzadeh et al. (2009), and Marofi et al. (2011). Their results have indicated that the temperature indices are consistent with global warming. "
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    ABSTRACT: An investigation of climatic extreme events presents the valuable opportunities to evaluate the potential impacts of climate change on human activities, agriculture, and economy. These analyses are useful procedures in monitoring climate change on a synoptic scale. The present study is a trend analysis of the extreme temperature events, which have been based on the gridded daily temperatures of Iranian climatic database within 1962–2004. The aim of the present study is to identify the frequency and intensity of extreme events, which have been increased with over Iran in the last four decades. Both the Mann–Kendall trend test and simple linear regression were utilized to detect trends in annual temperature extremes. The results showed that the frequency of hot extreme temperature events has increased over the studyarea within 1962–2004, while a negative trend has been observed in the frequency of cold extreme temperatures. About 66 % of the surface area has a significant positive trend in frequency of hot days and nights, while about 40.9 and 68.5%of surface area have a significant decrease in frequency of cold days and nights, respectively. The strongest increasing tendency is detected in the case of the annual numbers of hot nights, warm nights, summer days, warm days, and the heat wave duration indices.
    Arabian Journal of Geosciences 10/2015; 8(10):8469–8480. DOI:10.1007/s12517-015-1840-5 · 1.22 Impact Factor
    • "As with reported changes in crop proportions on a global scale, growing areas of major crops in Iran have changed quite dramatically during the last decade (Fig. 1) and climate change impacts are expected to become a challenge for crop production in the study area. Temperature shows a significant increase during the last 60 years in the northeast of Iran (Rahimzadeh et al. 2009) while Ragab and Prudhomme (2002) predicted for Iran a 20–25 % reduction in average rainfall and 2 to 2.75 °C increase in mean temperature for the future (2000–2050). Koocheki et al. (2006), found for northeastern Iran a 21 % to 41 % decrease in rainfed wheat yield under future climate conditions (2025–2050) in contrast to the baseline, without considering any changes in management and adaptation strategies. "
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    ABSTRACT: Research on the impact of climate change on agricultural production has mainly focused on the effect of climate and its variability on individual crops, while the potential for adapting to climate change through crop substitution has received less attention. This is surprising because the proportions of individual crops in the total crop area have changed considerably over periods of time much shorter than those typically investigated in climate change studies. The flexibility of farmers to adapt to changing socioeconomic and environmental conditions by changing crop type may therefore also represent an alternative option to adapt to climate change. The objective of this case study was to investigate the potential of crop substitution as an adaptation strategy to climate change. We compared biomass yield and water use efficiency (WUE) of maize (Zea mays L) and pearl millet (Pennisetum americanum L.) grown in the semi-arid northeast of Iran for fodder production under present and potential future climatic conditions. Climate change projections for the baseline period 1970-2005 and two future time periods (2011-2030 and 2080-2099) from two emission scenarios (A2 and B1) and four general circulation models were downscaled to daily time steps using the Long Ashton Research Station-Weather Generator (LARS-WG5). Above-ground biomass was simulated for seven research sites with the Decision Support System for Agrotechnology Transfer (DSSAT 4.5) model which was calibrated and tested with independent experimental data from different field experiments in the region. The analysis of observations across all study locations showed an inverse relationship between temperature and biomass yield for both pearl millet and maize. Biomass yield was most sensitive to the duration of the phenological phase from floral initiation to end of leaf growth. For this phase we also found the highest negative correlation between mean temperature and biomass yield, which was more pronounced for pearl millet than for maize. This relationship was well reproduced by the crop model, justifying its use for the assessment. Due to the higher sensitivity of pearl millet to temperature increase, simulations suggest that the maximum benefit of crop substitution for biomass yield and WUE is to be gained for present-day conditions and would decline under future warming. The simulated increase in biomass yield due to substitution of maize by pearl millet was nevertheless larger than the yield decrease from potential climate change. Therefore, substituting maize by pearl millet should be considered as a measure for increasing fodder production in the investigated region. Differences in yields of crops that may substitute for each other because of similar use have been shown for other regions under current and potential future climatic conditions as well, so that we suggest that our findings are of general importance for climate change research. More research is required to quantify the effects for other crop combinations, regions, and interactions with other adaptation measures.
    Mitigation and Adaptation Strategies for Global Change 09/2015; 20(7):1155-1174. DOI:10.1007/s11027-013-9528-1 · 2.67 Impact Factor
    • "The method has been used by many investigators for trend analysis in meteorological time series and found to produce reasonable results (e.g. Hirsch et al., 1982; New et al., 2006; Rahimzadeh et al., 2009; Chaouche et al., 2010; Kumar and Jain, 2010; Xu et al., 2010; Tabari and Talaee, 2011; Patra et al., 2012; Rehman et al., 2012; Mackellar et al., 2014). Details of the method appear in many peer-reviewed papers; however, to make this paper self-contained, the mathematical expressions of the Mann–Kendall test statistics S and Kendall tau coefficient í µí¼, appear in Appendix A. The annual and seasonal indices computed from the monthly data as given by the outputs of the RClimDex software were used as input in the R-package 'fume'. "
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    ABSTRACT: This study analyses spatial and temporal trends in extreme temperature indices over Nigeria. The percentile indices were calculated from newly homogenized daily minimum and maximum temperature data for the period 1971–2012 for 21 stations in Nigeria. Indices describing the characteristics of hot extremes and cold extremes are calculated with the RClimDex software. The annual and seasonal trends in these indices are obtained using the ordinary least square fit and the statistical significance tested using the R-based modified Mann–Kendall test. We examine characteristics of these indices for the entire country and separately for the three geographical zones in Nigeria: Guinea, Savanna, and Sahel. The spatial and temporal patterns of trends in the indices indicate that Nigeria has experienced statistically significant increase in the frequency of hot extreme and decrease in cold extreme events. Although majority of the stations have significant trends in warm days and warm nights, the annual trend is greatest in warm nights. In addition, the rate of warming in minimum temperature (‘warm nights’) is stronger in June, July, August (JJA) and September, October, November (SON) compare with December, January, February (DJF) and March, April, May (MAM). As for the trends in cold days and cold nights, the trends in cold nights are larger than for cold days at both the annual and seasonal scales. The regional analysis indicates that trends in warm nights and cold nights are most pronounced in Guinea and Sahel regions.
    International Journal of Climatology 09/2015; DOI:10.1002/joc.4510 · 3.16 Impact Factor
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