Spatio-temporal analysis of temperature variability, trend, and magnitude in the Hindu Kush region using Monte Carlo and Sen’s slope approaches

  • Muhammad Dawood
  • Atta-ur Rahman
  • Sami Ullah
  • Ghani RahmanEmail author
  • Kamran Azam
Original Paper


The present study explores the spatial and temporal deviations in temperature using Monte Carlo (MC) and Sen’s slope (SS) approaches in the Hindu Kush (HK) region. Climate change holds sturdy association against the temperature trend that has generated adverse impacts in the form of floods. In this attempt, for trend analysis, temperature has been selected as a meteorological parameter. This study mainly focuses on exploring the tendency in average temperature with respect to time and the consequential flood recurrences in the region. For the current study, data regarding temperature were typically collected from Pakistan Meteorological Department. In the study region, there are a total of seven meteorological station falls namely Dir, Chitral, Drosh, Saidu, Malam Jabba, Kalam, and Timergara. The temperature time series data was calculated and analyzed using MC and SS approaches for trend detection in order to demonstrate the kind of fluctuation in the Hindu Kush region. The resultant analysis further revealed that in the meteorological station of Dir, a more significant positive trend (α = 0.0001) was found in mean monthly maximum, minimum, and monthly normal temperature. Likewise, at Drosh, a positive trend is detected in mean monthly maximum (α = 0.04), monthly minimum (α = 0.003), and monthly average (α = 0.0005). Moreover, at Saidu met station, there is also a trend detected in temperature sub-variables such as monthly maximum (α = 0.0001) and monthly minimum (α = 0.001). In addition to these, at Kalam, there is a temperature trend noted for monthly minimum (α = 0.01) and monthly average (α = 0.02). Furthermore, the analysis demonstrates that there is no trend detected in the remaining stations, i.e., Chitral, Malam Jabba, Drosh, and Timergara. The overall analysis discovered that there is a sturdy relationship between climate change phenomenon and temperature variability. After using SS test to the temperature data of mean monthly maximum (TMMMax), the results explored that Kalam station grips the highest magnitude, i.e., Q = 0.76; however, Timergara shows the lowermost, i.e., Q = − 0.34. For the monthly minimum temperature (TMMMin), at Kalam again, the highest value (Q = 0.005) was detected; however, other stations revealed a negative trend, except Drosh which express no change in terms of magnitude. Similarly, in terms of monthly normal temperature (TMNor), Timergara station (Q = − 0.4) verified a negative trend magnitude and Malam Jabba station again trendless. Among all, the met station of Malam Jabba which holds an altitude of 2591 m is a hilly station just followed by Kalam having 2103 m height; however, Dir holds 1375 m height and the rest of the met stations show low elevation. The main reason for the temperature difference is the altitude of the study region.


Temperature Magnitude Trend Monte Carlo simulation model Sen’s slope estimator test 


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Copyright information

© Saudi Society for Geosciences 2018

Authors and Affiliations

  • Muhammad Dawood
    • 1
  • Atta-ur Rahman
    • 1
  • Sami Ullah
    • 1
  • Ghani Rahman
    • 2
    Email author
  • Kamran Azam
    • 3
  1. 1.Department of GeographyUniversity of PeshawarPeshawarPakistan
  2. 2.Department of GeographyUniversity of GujratGujratPakistan
  3. 3.National Defence University IslamabadIslamabadPakistan

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