Advances in Environmental Biology, 9(10) Special 2015, Pages: 14-18 AENSI Journals Advances in Environmental Biology ISSN-1995-0756 EISSN-1998-1066 Journal home page: http://www.aensiweb.com/AEB/ Corresponding Author: Jedol Dayou, Energy, Vibration and Sound Research Group (e- VIBS), Faculty Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia. Tel: +0688-320000; Faks:+6088-435324; E-mail: jed@ums.edu.my. Variation Over Time of the Du Mortier Calibration Algorithm for Ground-Based Spectrometer Rubena Binti Yusoff, Natalie Vanessa Boyou, Jedol Dayou, Chin Su Na, Ag. Sufiyan Abd. Hamid, Fauziah Sulaiman, Nur Hasinah Najiah Binti Maizan Energy, Vibration and Sound Research Group (e-VIBS), Faculty science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia. ARTICLE INFO ABSTRACT Article history: Received 22 February 2015 Accepted 20 March 2015 Available online 23 April 2015 Keywords: Spectrometer, Du Mortier Calibration Algorithm, Du Mortier Model, Improved Langley Method. Background: Having a stable and steady calibration constants increases the likelihood of a spectrometer to perform as expected over a reasonable period of time. The purpose of this paper is to study the variation over time of the Du Mortier calibration algorithm used in a spectrometer for atmospheric condition measurement. This is carried out over a course of six months and the measurements were taken for every minute intervals from 8.30am to 4.30pm in three locations in Kota Kinabalu. By using the improved Langley method, monthly calibration constants for eight wavelengths were determined for Du Mortier model. Results shows that there were statistically significant differences between mean calibration constants when comparing the selected months. However, if only wavelengths of 460nm, 500nm, 540nm, 580nm and 620nm are taken into account, the results say otherwise. © 2015 AENSI Publisher All rights reserved. To Cite This Article: Rubena Binti Yusoff, Natalie Vanessa Boyou, Jedol Dayou, Chin Su Na, Ag. Sufiyan Abd. Hamid, Fauziah Sulaiman, Nur Hasinah Najiah Binti Maizan., Variation over Time of the Du Mortier Calibration Algorithm for Ground-Based Spectrometer. Adv. Environ. Biol., 9(10), 14-18, 2015 INTRODUCTION Malaysian government is enhancing the utilization of renewable energy and venturing its possibility as the sole energy provider in Malaysia. Solar energy have the highest potential to become primary sources of renewable energy in Malaysia because it is located in tropics and receives abundant sunlight throughout the year [6] with sunshine duration greater than 2200 hour per year [3]. Sabah can achieved of about 6.027 kWh/m 2 per year [4]. Therefore, this advantage should be fully utilised as an alternative electric power generation in Sabah. By assessing solar radiation spectrum, it can help us to identify solar intensity in particular location in Sabah and by doing so, it help to model the spectrum references. This ground-based measurements data is obtained using a spectrometer. However, to have a reliable data, the spectrometer must be calibrated. This study is carried out to evaluate the consistency of calibration constant using Du Mortier Method. Jackson et al. [10] has developed a new langley calibration algorithm which combined the clear-sky condition, Perez-Du Mortier model to allow frequent calibration, even in near-sea-level site. The Du Mortier are used to determine sky condition over the area of study. From the sky condition models, the calibration constants can be determined by using the improved Langley method. The calibration constants over time then is statistically analysed by using ANOVA. 1. Sky classification Using Du Mortier Model: According to Zain-Ahmad et al. [9], this model has been used to predict the sky condition at Shah Alam site located in West Malaysia. According to this model, the Nebulosity Index (NI) as indicators of sky type can be computed by the following equations [5]:     r eg ed C I I NI    1 / / 1 (1) The theoretical cloud ratio r C is defined as [5]: