Quantifying climate control on rainfall and river water level in the Cameron Highlands area.

Rahimi, Ali (2017) Quantifying climate control on rainfall and river water level in the Cameron Highlands area. [Project Paper] (Submitted)

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Abstract

Climate is the conditions dominant in an area in general or over a long period of time. Climate change, on the other hand, describes the understanding and predicting of the changes which are mostly affected by human being activities. However, in some cases, this climate changes are happening due to some kind of natural activities, which means climate is naturally varied on a whole series of time-periods. These variations can have profound impacts on climate or weather conditions around the world such as storms and heavy rainfall These variations are mentioned by scientists using a range of climate indices. In this project, the objective is to study the relationship over a large distance between the rainfall data times series, as well as the water level data time series with climate indices such as the Southern Oscillation Index (SON), Nino 3, Nino 4, Nino 3.4, and Nino 1+2, that represent the El Niño-Southern Oscillation phenomena. In this study, a number of ENSO records (SOI, Nino 3, Nino 3.4, Nino 4, and Nino 1+2), obtained from National Oceanic and Atmospheric Administration (NOAA) in the USA were examined against the rainfall data and water level data provided from Department of Irrigation and Drainage in Malaysia. Using the data given (34 years rainfall data and 22 years water level data) mostly anomaly was computed in order to provide a fair comparison to the climate indices (SOI, Nino 3, Nino 3.4, Nino 4, and Nino 1+2). In order to check the strength of two variety, correlation analysis is carried out which is a statistical technique used to determine the strength of the strength of the relation between two variables. So, a measurement of the strength of the association between two variables is called coefficient of correlation, which is in a range of -1 (negative strong correlation), and zero (no correlation), and +1 (positive strong correlation). Moreover, testing the significance of the coefficient of correlation is essential to decide whether the correlation in data given is representative of an entire population, which can be determined by a critical value which is found to be 2.576 with 99.5% probability.

Item Type:	Project Paper
Faculty:	Faculty of Engineering
Depositing User:	Ms Siti Mariam Giman
Date Deposited:	29 Oct 2024 08:32
Last Modified:	08 Nov 2024 08:36
URI:	http://psaspb.upm.edu.my/id/eprint/2125

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