Volume 6, Issue 1 (5-2019)                   2019, 6(1): 111-138 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Saberi Louyeh F, Alijani B, Khaledi S. Caspian Sea south coast future climate change estimations through regional climate model. Journal title 2019; 6 (1) :111-138
URL: http://jsaeh.khu.ac.ir/article-1-2735-en.html
1- Islamic Azad University, Science and Research Branch
2- Kharazmi University , bralijani@gmail.com
3- Shahid Beheshti University
Abstract:   (3211 Views)
. Caspian Sea south coast future climate change estimations through regional climate model
many physical of the procedures related to climate change are not perceived thoroughly. Scientific knowledge used to show those procedures completely, and to analyses forecasts is so complex, since most current studies about climate physical model have been done through semi experimental and random models and most of the current analysis techniques are still going through early stages. One of the important aspects of this study is modeling physical procedures of sea level rise geographical pattern, which is used practically for SLR threat evaluation of special geographical location, meaning Caspian basin. Since Caspian basin is a closed sea, it is heavily influenced by climate change and meanwhile is changing due to physical level and environmental change. It is necessary to define Caspian coast climate change possibility with specific focus on climatology and meteorology fine data, also to define the scale of sea level fluctuations for the sake of exact planning in different fields. This study aims at presenting a new dynamic method, via using an integrated model system named SIMCLIM, which can clarify SLR satellite changes well.
According to scientific examination existing in this study, based on scatter scenario 4.5 RCP and 8.5 RCP for the following years, until 2100, temperature and precipitation change proposal have been presented. On one hand, Caspian coastal climate change analysis and estimation were based on climate patterns and water flows in the form of regional climate statistical model in order to simulate and forecast, on the other hand surveying chronological changes of Caspian sea coast slope with satellite height measurement was done to measure sea surface height fluctuations The present study has used SIMCLIM model for the first time in order to clarify Caspian sea level changes, elements, and effective climate reasons, all simultaneously in one project. The project base is according to coastal systems and procedures. Coast line shore change simulations are based in Bruun law.
In future the frequency and intensity of extreme events temperature and precipitation will increase. Extreme events illustrate changes in extreme temperature and precipitation measures, in comparison with the base period of 1981-2010 which convey precipitation sum or the temperature beyond 95 percentile of base period. Temperature and precipitation coefficient of variation for the whole Caspian basin is positive and it varies from 25 to 88 percent. A disordered pattern is dominating south basin of the sea. Sea level changes, considering vertical earth movements, which is 2 mm in a year, resulted from subsidence of Caspian pit seabed have been obtained for both scenarios. In general, annual sea level average while ignoring seasonal changes, is increasing consistently and it was calculated 1.22 cm each year according to high estimation procedure in scenario 8.5 RCP and it was 0.93 cm based on scenario 4.5 RCP. Predicted results were compared with real results of base20-year period from 1995-2015. Base period results in three levels of sensitivity of low, mid, high shows 8.4, 10.1, and 11.8 cm rise; after comparing them with model forecast results, meaningful coordination at the level of 95 percent was found out. In both scenarios, all over the Caspian shoreline water advance and destruction will exist. In the worst case scenario of 8.5 RCP of 2030, current coast will decrease about 23 meters and in 2060 it will be about 53 and in 2100, there will be 117 meters advance towards land.
Precipitation and temperature percent for 2030, 2060, 2100 will change increasingly. Spatial variability and annul coefficient of variation are various in different regions. North, western north, eastern north and east will include the least temperature fluctuations, and the highest percent of precipitation with the highest coefficient of variation all convey chronological period precipitation distribution with disordered accumulation and more local difference in this region in comparison with other regions. Then Caucasus mountainous region will have the highest increase in precipitation with a suitable scatteredness, during a year. The southern part of Caspian Sea will be with the highest increase in temperature and the least amount of increase in precipitation in percent. High coefficient of variation in this area illustrates abnormal and disordered pattern on the threshold of precipitation for both scenarios.
 fluctuations in sea level based on subsidence of Caspian pit seabed was calculated.In general, average annual sea level is increasing which will be 1.22 cm, per year for scenario RCP 8.5 and 0.93 cm for scenario 4.5. Due to incapability of world community in decreasing releasing greenhouse gases, it is expected scenario that 8.5 RCP to come to reality.
 Caspian Sea shoreline is influenced by water advance and destruction. The difference between two scenarios in 2060 will be 3 meters and in 2100 will be 12 meters. Instinctually, such advances in coasts with less depth and less slope will be more. This study suggests that coastal changes are inevitable. However, this region inhabitant owns no systems or no systems have not yet developed to aid them be able to adopt with the climate changes.
Keywords: Sea level rise, South Caspian basin, Extreme event, Coefficient of variations, shoreline.
Full-Text [PDF 2279 kb]   (2184 Downloads)    
Type of Study: Research | Subject: Special
Received: 2017/11/9 | Accepted: 2018/12/22 | Published: 2019/06/22

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.

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

© 2023 CC BY-NC 4.0 | Journal of Spatial Analysis Environmental hazarts

Designed & Developed by : Yektaweb