:: Volume 21, Issue 74 (8-2021) ::
جغرافیایی 2021, 21(74): 1-14 Back to browse issues page
Predicted changes in precipitation and temperature using lars-wg5 by the year 2030 AD in Rasht
Mostafa Karampoor1 , Hosseinali Roohbakhsh sigaroodi * 1, Elham Yarahmadi1
1- lorestan univercity
Abstract:   (3255 Views)

Changes in temperature, rainfall and precipitation type organisms may be life threatening, therefore it must be studied from different aspects. The purpose of this study was to investigate changes, using random data generator LARS-WG5 in the period 2008-1981 on the one hand and to detect and predict future changes in these variables between 2011 and 2030. Using the results of this research can be reduced negative impacts of climate change in the region. And more compatible with the new conditions, particularly in terms of culture, cultures and other measures and environmental management products provided. The required data from the General Directorate of Meteorology Gilan produced and became a model format. After calibration, and evaluation of past data, survey data and the data of the previous model in the future to produce the data, the model was implemented. Study showed that average minimum and maximum temperatures predicted by the model MPEH5 by considering three scenarios, the trend is all months that It confirms the results of the three scenarios. About the average annual rainfall, the results of the model with the A1B scenario shows better serve the increasing 3.2mm. The distribution of rainfall has changed compared to the baseline. The highest rainfall in autumn and winter and summer, with average rainfall of 43.51mm faces fall. The study emphasizes that the minimum and maximum average temperature is projected to increase in all seasons and Changes in precipitation and reduced summer precipitation 43.51mm, the water resources of the region at stake. These changes reduce the amount of freezing rain and snow line altitude increases, reduced water supply in the area of agriculture is one of the poles.

Keywords: climate change, climate change scenarios, generating random data, model MPEH5
Full-Text [PDF 901 kb]   (702 Downloads)    
Type of Study: Research | Subject: Special
Received: 2015/08/4 | Accepted: 2019/04/7 | Published: 2021/09/28


XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 21, Issue 74 (8-2021) Back to browse issues page