STUDY ON THE IMPACT OF CLIMATE SIGNALS ON THE PRECIPITATION OF THE CENTRAL OF IRAN USING ARTIFICIAL NEURAL NETWORK

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HEJAZIZADEH ZAHRA; FATAHI EBRAHIM; SALIGHEH MOHAMMAD; ARSALANI FATEMEH

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Journal: JOURNAL OF GEOGRAPHICAL SCIENCES Year:2013 | Volume:13 | Issue:29 Page(s): 75-89

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Information Journal Paper

Title

STUDY ON THE IMPACT OF CLIMATE SIGNALS ON THE PRECIPITATION OF THE CENTRAL OF IRAN USING ARTIFICIAL NEURAL NETWORK

Author(s)

HEJAZIZADEH ZAHRA | FATAHI EBRAHIM | SALIGHEH MOHAMMAD | ARSALANI FATEMEH | Issue Writer Certificate

Keywords

: PRECIPITATIONQ2

ARTIFICIAL NEURAL NETWORKQ2

ARCTIC OSCILLATION (AO)Q3

NORTH ATLANTIC OSCILLATION (NAO)Q2

ENSOQ2

Abstract

Climate signals are large-scale models of abnormalities in circulation and pressure and spread over wide geographical area. These signals are very important in translating the climate behaviour. In this research the relationship between precipitation and the climate signals (AO, NAO, SOI, and ENSO) in the Central Iranian zone, has been studied. The signals data are acquired from the NCEP Data Centre; also the aggregate data of the monthly precipitation are obtained from the Automation Centre in Iran Meteorological Organisation. Monthly data gathered through a 30-year statistical period (between 1978 to 2008). Finally, by exploiting ARTIFICIAL NEURAL NETWORK method, the simulation models for 0,3 and 6 months intervals were created. The results indicated that among the investigated signals, signal ENSO has a meaningful impact on precipitation in NINO1.2 and NINO3 zones, and the 3 and 6 month delay has strengthened the correlation coefficient of the ENSO index in zones NINO1.2 and NINO3 in relation to precipitation in the studied stations. The 6-month delay has resulted in negative correlation coefficient between ENSO index in NINO1.2 and NINO3 zones. According to the presented models, ENSO signal in NINO1.2 and NINO3 zones combined with other effective parameters could regard as a precipitation forecast model. Other climate signals do not have a meaningful impact of precipitation in the stations under study.

Cites

STUDY OF ARCTIC OSCILLATION EFFECT ON TEMPERATURE AND PRECIPITATION FLUCTUATIONS AT WINTER IN CENTRAL IRAN

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APA: Copy

HEJAZIZADEH, ZAHRA, FATAHI, EBRAHIM, SALIGHEH, MOHAMMAD, & ARSALANI, FATEMEH. (2013). STUDY ON THE IMPACT OF CLIMATE SIGNALS ON THE PRECIPITATION OF THE CENTRAL OF IRAN USING ARTIFICIAL NEURAL NETWORK. JOURNAL OF GEOGRAPHICAL SCIENCES, 13(29), 75-89. SID. https://sid.ir/paper/102266/en

Vancouver: Copy

HEJAZIZADEH ZAHRA, FATAHI EBRAHIM, SALIGHEH MOHAMMAD, ARSALANI FATEMEH. STUDY ON THE IMPACT OF CLIMATE SIGNALS ON THE PRECIPITATION OF THE CENTRAL OF IRAN USING ARTIFICIAL NEURAL NETWORK. JOURNAL OF GEOGRAPHICAL SCIENCES[Internet]. 2013;13(29):75-89. Available from: https://sid.ir/paper/102266/en

IEEE: Copy

ZAHRA HEJAZIZADEH, EBRAHIM FATAHI, MOHAMMAD SALIGHEH, and FATEMEH ARSALANI, “STUDY ON THE IMPACT OF CLIMATE SIGNALS ON THE PRECIPITATION OF THE CENTRAL OF IRAN USING ARTIFICIAL NEURAL NETWORK,” JOURNAL OF GEOGRAPHICAL SCIENCES, vol. 13, no. 29, pp. 75–89, 2013, [Online]. Available: https://sid.ir/paper/102266/en

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