Modeling of Trends of Temperature and Precipitation Extreme Indices in Urmia Lake Basin

Document Type : Original Article

Authors

1 Professor of Climatology, University of Tabriz, Tabriz, Iran

2 PhD Student of Climatology, University of Tabriz, Tabriz, Iran

Abstract

Temperature and precipitation are the basic elements of climate. Therefore, sudden or short-term and long-term changes may change the climate of any location. The aim of this study was to predict trend indices of climate extremes using statistical downscaling methods and artificial technical data generation. In this study, in order to achieve these goals, The climate data of temperature, precipitation and sunshine hours during the period 1981 to 2010 was received from Meteorological Organization. Then, using CLIMGEN statistical models and observational data of selected stations of the basin, data produced over the period of 2020-2050. Then, using RClimDex software, extreme temperature and precipitation indices were extracted. Finally, the by use of MINITAB software the climate trend indices were drawn at selected stations of Urmia Lake basin. For validation, the prediction was accomplished by observational database period of 2001-2010 through the model. The relationship between generated data with the observational data was analyzed by SPSS, which showed high accuracy in most stations. The maximum absolute error of precipitation in the station of Orumieh was 4.69 mm and the lowest in Tabriz station with 3.7 mm. The highest mean squared error of precipitation in the Takab station was obtained with 6.4 mm and the lowest in the Tabriz station was 4.14 mm. Results indicated an increase in temperature and precipitation extreme events including increases in summer days, and very humid days of consecutive dry days at selected stations proved to be located on West and East basins. The increase of icy days and the reduction of summer days were shown while very wet and dry consecutive days were observed in the southern selected station.

Keywords

References

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History

  • Receive Date: 28 January 2017
  • Revise Date: 19 October 2017
  • Accept Date: 31 December 2017

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