Analysis of Linear Scaling Method in Downscaling Precipitation and Temperature

Climate change is one of the greatest challenges in the 21st century that may influence the long haul and the momentary changeability of water resources. The vacillations of precipitation and temperature will influence the runoff and water accessibility where it tends to be a major issue when the interest for consumable water will increase. Statistical downscaling model (SDSM) was utilized in the weather parameters forecasting process in every 30 years range (2011-2040, 2041-2070, and 2071-2100) by considering Representative Concentration Pathways (RCP2.6, RCP4.5, and RCP8.5). The Linear Scaling (LS) method was carried out to treat the gaps between ground/ observed data and raw/ simulated results after SDSM. After the LS method was executed to raw/ simulated data after SDSM, the error decrease reaches over 13% for rainfall data. The Concordance Correlation Coefficient (CCC) value clarifies the correlation of rainfall amount among observed and corrected data for all three (3) RCPs categories. There are very enormous contrasts in rainfall amount during the wet season where CCC-values recorded are 0.22 and beneath (low correlation). The findings demonstrated that the rainfall amount during the dry season will contrast for all RCPs with the CCC-values are between 0.44-0.53 (moderate correlation). RCP8.5 is the pathway with the the most elevated ozone-depleting substance emanations and demonstrated that the climate change impact is going on and turn out to be more awful step by step

Analysis of Climate Variability and Trends in The Context of Climate Changes: Case Study in Terengganu

Uncertainty of climate extreme nowadays causes an alteration in the local climate trend and variability. Terengganu, Malaysia recorded series of extreme drought and flood events throughout a year affected by North-East monsoon which will change the next climate pattern. Thus, it will affecting the long-term planning and sustainability that related to the water resources in the long-term. The objective of this study was to analyse the trend changes of rainfall and temperature at Kuala Terengganu, Malaysia due to climate changes impact. The trends changes were analysed using Man-Kendall and Sen’s Slope. The climate projection result shows the annual mean temperature is expected to have decreasing trend until end of century. However Mar to June are expected to bit higher than historical reach to 29oC by RCP8.5. Then it will be dropped to 24oC (-5% from historical) during Northeast monsoon. Consistent to the annual rainfall, it was expected to have increasing trend over time. The highest increasing trend was expected to occur on Nov to Dec more than 40% by RCP8.5

Analysis of Climate Variability and Trends in The Context of Climate Changes: Case Study in Terengganu

Uncertainty of climate extreme nowadays causes an alteration in the local climate trend and variability. Terengganu, Malaysia recorded series of extreme drought and flood events throughout a year affected by North-East monsoon which will change the next climate pattern. Thus, it will affecting the long-term planning and sustainability that related to the water resources in the long-term. The objective of this study was to analyse the trend changes of rainfall and temperature at Kuala Terengganu, Malaysia due to climate changes impact. The trends changes were analysed using Man-Kendall and Sen’s Slope. The climate projection result shows the annual mean temperature is expected to have decreasing trend until end of century. However Mar to June are expected to bit higher than historical reach to 29oC by RCP8.5. Then it will be dropped to 24oC (-5% from historical) during Northeast monsoon. Consistent to the annual rainfall, it was expected to have increasing trend over time. The highest increasing trend was expected to occur on Nov to Dec more than 40% by RCP8.5

Analysis of Malaysia electricity demand and generation by 2040

Malaysia as an emerging country, increasing population, gross domestic product (GDP) growth and enhanced access to electricity lead to an expanding of demand. The crucial parameters to determine future energy demand and generation projections are GDP, population growth rates and weather implications due to climate change. The study aims to forecast the future trends based on the historical values and also to project the future electricity demand and generation. The electricity demand and generation growth evaluated based on 2 main elements which are population growth and weather parameters (maximum temperature and rainfall). The future trends are forecasted based on the historical values of population and weather parameters. There is 152.9% of population growth in 32 years. The population will keep on developing yet with the lower rate. The GDP trend and the population growth mirrors the pattern of emissions. The findings from Statistical Downscaling Model (SDSM) analysis shows that the rainfall distribution will diminish while the temperature will expand that depict the climate change impact as time passes by. In 2020, the most extreme temperature recorded is 31.7 °C while in 2040, the estimated greatest temperature is 32.3 °C. There will be a 0.6 °C increase in temperature in 20 years. The demand in 2040 will be expanded 50.3% more than demand in 2020. The estimated electricity demand per capita will continue expanding because of the augmentation of the populace and the significance of electricity in daily activities. The pattern shows that electricity demand and generation in Malaysia will be expanding massively year by yea

Analysis of climate variability and trends in the context of climate changes: Case study in Terengganu

Uncertainty of climate extreme nowadays causes an alteration in the local climate trend and variability. Terengganu, Malaysia recorded series of extreme drought and flood events throughout a year affected by North-East monsoon which will change the next climate pattern. Thus, it will affecting the long-term planning and sustainability that related to the water resources in the long-term. The objective of this study was to analyse the trend changes of rainfall and temperature at Kuala Terengganu, Malaysia due to climate changes impact. The trends changes were analysed using Man-Kendall and Sen’s Slope. The climate projection result shows the annual mean temperature is expected to have decreasing trend until end of century. However Mar to June are expected to bit higher than historical reach to 29oC by RCP8.5. Then it will be dropped to 24oC (-5% from historical) during Northeast monsoon. Consistent to the annual rainfall, it was expected to have increasing trend over time. The highest increasing trend was expected to occur on Nov to Dec more than 40% by RCP8.5

Penerapan kemahiran generik dalam pengajaran program pendidikan kejuruteraan di Politeknik Kementerian Pengajian Tinggi Malaysia (KPTM)

Kemahiran generik (KG) adalah satu kemahiran yang penting dalam melahirkan pekerja yang kompeten apabila memasuki alam pekerjaan yang sebenar. Kajian ini bertujuan untuk mengenal pasti sama ada terdapat penerapan kemahiran generik dengan berasaskan Taksonomi Bloom di politeknik dalam pengajaran program pendidikan kejuruteraan. Kajian ini berbentuk kajian kuantitatif yang melibatkan pengedaran borang soal selidik kepada sampel yang telah dipilih. Persampelan bertujuan telah digunakan dalam kajian ini. Sampel difokuskan kepada pensyarah dan pelajar dalam bidang kejuruteraan di tiga buah politeknik sahaja iaitu Politeknik Sultan Mizan Zainal Abidin, Politeknik Sultan Salahuddin Abdul Aziz Shah dan Politeknik Merlimau. Pemilihan sampel adalah sebanyak 10 % dari jumlah pelajar bagi setiap jabatan kejuruteraan dan seramai mungkin pensyarah dipilih. Data dianalisis menggunakan SPSS versi 11.5. Analisis skor min digunakan untuk menentukan domain yang menjadi teras kepada penerapan kemahiran generik di politeknik KPTM. Domain kognitif dan afektif merupakan teras penerapan kemahiran komunikasi dengan nilai skor min 3.7955 dan 3.7440. Dalam menerapkan pemikiran kritis dan kemahiran menyelesaikan masalah, domain afektif mendominasi dengan nilai skor min 3.8308 (pensyarah) dan 3.8543 (pelajar). Domain afektif dan kognitif mendominasi dalam menerapkan kemahiran kerja berpasukan bagi sampel pensyarah (skor min = 3.9093) dan pelajar (skor min = 3.8768). Ujian-t sampel bebas untuk melihat sama ada terdapat perbezaan yang signifikan antara kedua-dua sampel bagi setiap domain dalam penerapan kemahiran generik dan hasil analisis menunjukkan tidak terdapat perbezaan yang signifikan. Secara kesimpulannya, penerapan kemahiran generik dalam pengajaran program pendidikan kejuruteraan di politeknik KPTM adalah pada tahap tinggi

Climate change impacts on hydropower generation at Kenyir Lake

Climate change is triggered by human activities that produce greenhouse gas emissions and affect people in various ways. It is crucial to study the severity of rainfall in the certain potential areas that exposed to hydro-meteorological disasters in climatic trends transition. The objectives of the study are to evaluate the severity of rainfall trends and also to predict the fluctuations of hydropower generation in Kenyir Lake triggered by the variations of climatic factors under selected Representative Concentration Pathways, RCPs (RCP2.6, RCP4.5 and RCP8.5) suggested in the Intergovernmental Panel on Climate Change’s (IPCC) fifth assessment report. The historical daily data of seven rainfall stations for 30 years’ period (1988 - 2017) and global climate model data for RCP2.6, RCP4.5 and RCP8.5 also for 30 years’ period (2041-2070) were used. The statistical downscaling model (SDSM) was used to analyse the data. The predicted rainfall data from 2041 to 2070 then compared with the base period rainfall (1988-2017). Kenyir Lake received highest amount of rainfall in November to January during north-east monsoon. The significance differences were recorded in November and December where abrupt fall of rainfall distribution predicted to happen for all RCPs. The results proved that the higher emissions level will give the more effect to the climate trend as previous researcher found that warming will remain beyond 2100 for all RCP scenarios except RCP2.6. The lowest generated value at Kenyir is in 1997 and the highest value is in 2017. The increment of NUG clearly happens in 10 years’ interval where there was 78.67% of increment in 2007 compared to 1997. There is an increase that occurs although there are fluctuations every year. Increases in temperature because of climate change effects will increase the energy demand. Rising temperatures gives the varies patterns of demand because higher temperature will create higher cooling demand. Besides that, power generation can change accordingly by the decreasing stream flow and increasing water temperature. It shows that climate change tremendously affects the energy demand patterns and supply systems

Comparison of missing rainfall data treatment analysis at Kenyir Lake

Rainfall is one of the frequent data used in weather-related studies. Sometimes the data have missing information that needs the treatment to make sure the data can be useful, complete and reliable. There are many methods in treating missing data suggested by previous studies. The best selected method to estimate missing rainfall data in different regions may vary depending on the rainfall pattern and spatial distribution. Therefore, this paper discussed and compared 3 different methods in missing data treatment. The selected methods are Expectation Maximization (EM), Inverse Distance Weighted (IDW) and Multiple Imputation (MI). After analysis, the best method is IDW based on root mean square error (RMSE), mean absolute error (MAE), correlation coefficient (r) and percentage of error (% of error) values. The IDW method has RMSE, MAE values and the lowest % of error values. In addition, the r value of IDW method is highest compared to EM and MI method. MI method recorded the highest values of RMSE, MAE and % of error with the lowest r value that proved MI method is the least accurate method to use in missing data treatment. After all methods were implemented, it proved that the IDW method is the best way to treat missing data because the analysis shows monthly rainfall distribution for 4 treatment stations in line to 3 missing data stations compared to EM and MI methods