XML Persian Abstract Print

1- Associate Professor of climatology, Seyed Jamaleddin Asadabadi University, Asadabad, Iran , maryanaji@sjau.ac.ir
2- PhD in Climatology, Kharazmi University, Tehran, Iran
3- K. N. Toosi University of Technology, master of science in Remote sensing engineering
Abstract:   (2587 Views)
Understanding and predicting future climatic conditions and characteristics is essential because of their importance in all aspects of life. This study seeks to examine the process of modifying temperatures in the Hamedan region by using Downscaling data to predict the public circulation data and its changes. The Lars Explore Downscaling Model has been used to fine-tune the data of the General Transport Model (HADGEM2-ES) and the paired model (CMIP5) and under the three release scenarios RCP2.5, RCP4.5, and RCP8.5). Estimates of the correlation of simulated data and actual data show values of more than 0.95 for all months. P_value also showed the statistical tests of model output, acceptable values in model performance in production and simulation. As a result, the data were extracted from 2011 to 2050. Data were examined in three intervals to detect trend changes. The results show that in the optimistic scenario (RCP2.5) there is no tangible trend in the mean and minimum temperature, while in the RCP4.5 and RCP8.5 scenario there are significant trends in temperature data and accordingly increase the minimum temperature, according to the increase in the minimum temperature, according to the increase in the minimum temperature, according to the increase 1 degree in the average temperature. It shows severe climate change that, especially in the cold season, changes the type of precipitation. Also, based on the data process, the significant increase in the average annual and monthly scale temperature in all three scenarios under study will indicate the environmental crisis ahead.
Type of Study: Research | Subject: climatology

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Applied researches in Geographical Sciences

Designed & Developed by : Yektaweb