气候变化领域集成服务门户(CCPortal): Iran's precipitation analysis using synoptic modeling of major teleconnection forces (MTF)

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DOI	10.1016/j.dynatmoce.2018.12.001
	Iran's precipitation analysis using synoptic modeling of major teleconnection forces (MTF)
	Ahmadi M.; Salimi S.; Hosseini S.A.; Poorantiyosh H.; Bayat A.
发表日期	2019
ISSN	03770265
起始页码	41
结束页码	56
卷号	85
英文摘要	In this relatively unprecedented study, the effects of thirty-four leading teleconnection Patterns (indices) of atmospheric circulation- on regional-scale for the Middle East- along with precipitation over Iran have been investigated. Different types of data including teleconnection Indices from NOAA (NCEP/NCAR, BOM) and monthly precipitation data from thirty-six synoptic stations of Iran were applied. The data have been investigated with various types of statistical and synoptical methods. The results indicate that El Niño–Southern Oscillation (ENSO) is the most effective factor and it could possibly influence the spatiotemporal variation of precipitation on all types of climate regimes in Iran. ENSO (nino3.4), The Atlantic Multidecadal Oscillation (AMO) and The Arctic oscillation (AO) are known as the first three important indices, determined by Principal component analysis (PCA) method. The research has clarified that a combination of warm phase of ENSO and a predominant Southeastern (SE) wind over the Indian Ocean can result in a significant moisture transport from the Indian Ocean to the Middle East and to Iran; a combination of cold phase of ENSO and a predominant Northwestern (NW) wind over the Indian Ocean can be followed by a widespread drought over the Middle East and Iran. The results also indicate that a combination of the first three important above-mentioned indices and the Indian Ocean Dipole (IOD) can provide a much better explanation for spatial and temporal variation of precipitation of Iran. Finally, the results of this study will enable us to present a new approach and new graphical-conceptual modeling, called “Teleconnection-Synoptic Method (TSM)”to clarify the underlying mechanism that can explain the spatial and temporal variations of global atmospheric circulation and precipitation of Iran. According to the correlation of different patterns with precipitation, the strongest relationships are related to the Scandinavia Index (SCN), Pressure Change in East Pacific (dPEPac) and Trade Wind Index at the 850 hPa (TrdWnd850), respectively. © 2018 Elsevier B.V.
英文关键词	Climate variation; Conceptual modeling; ENSO; Iran; Teleconnection
语种	英语
scopus关键词	Atmospheric pressure; Data mining; Oceanography; Precipitation (meteorology); Principal component analysis; Climate variation; Conceptual model; ENSO; Iran; Teleconnections; Climatology; Arctic Oscillation; Atlantic Multidecadal Oscillation; climate change; El Nino-Southern Oscillation; Indian Ocean Dipole; NOAA satellite; precipitation assessment; principal component analysis; spatiotemporal analysis; synoptic meteorology; teleconnection; Indian Ocean; Indian Ocean (Northwest); Iran
来源期刊	Dynamics of Atmospheres and Oceans
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178526
作者单位	Kermanshah Regional Meteorological Office, Kermanshah, Iran; Kharazmi University, Tehran, Iran; Department of Physical Geography, Mohaghegh Ardabili University, Ardabil, Iran
推荐引用方式 GB/T 7714	Ahmadi M.,Salimi S.,Hosseini S.A.,et al. Iran's precipitation analysis using synoptic modeling of major teleconnection forces (MTF)[J],2019,85.
APA	Ahmadi M.,Salimi S.,Hosseini S.A.,Poorantiyosh H.,&Bayat A..(2019).Iran's precipitation analysis using synoptic modeling of major teleconnection forces (MTF).Dynamics of Atmospheres and Oceans,85.
MLA	Ahmadi M.,et al."Iran's precipitation analysis using synoptic modeling of major teleconnection forces (MTF)".Dynamics of Atmospheres and Oceans 85(2019).