Abstract
Trend identification plays a significant role in climate change studies to make future predictions about possible consequences on the urban environment, agriculture, water availability, etc. The Variation of Extreme Temperature intensity is observed in many regions all over the globe as an outcome of abrupt changes in climate. Keeping in mind the non-stationary climate conditions, it is essential to incorporate potential future changes in climatological studies. In the present study, the statistical parameters and the variability in time series of extreme daily temperature were analyzed using Generalized Extreme Value (GEV) distribution and its suitability has been examined by superimposing onto Gringorten plotting positions. The trend analysis of extreme daily temperatures was carried out using an innovative trend template proposed by Sen [7] and non-parametric Mann-Kendall (MK) trend test. The trend detection and variability of extreme daily temperature of Abu Dhabi City station, UAE was also carried out in this study. 34 years of temperature data were used for the analysis. Also, the extreme daily temperatures time series were checked for their serial correlation.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
