02367ntm a2200277 a 4500 vtls000102645 KUKTEM 20251117113354.0 171227s2017 my da f am 000 0 eng d THE0000814(Local) 201905271150 nazirah 201712271511 saini UMP FKASA .Z87 2017 r Bc. Zuraida Hasbullah Application of bias correction in climate prediction / Zuraida Hasbullah Kuantan, Pahang : UMP, 2017 xii, 74 p. : ill. (some col.), charts ; 30 cm. + 1 CD-ROM Faculty of Civil Engineering and Earth Resources Project Paper (Bachelors of Civil Engineering) -- Universiti Malaysia Pahang – 2017 Bibliography : p. 51 The issue of climate change and its effects on many aspects of the environment become more challenges for society. The emission and concentration of carbon dioxide and greenhouse gases give impact to the increase in temperature, and thus leading to global warming. It is important and desirable to analyze and predict the changes of climatic variables especially for rainfall. However, the accuracy in the climate simulation is becomes significant to ensure the reliability of the projection results. Thus, the bias correction (BC) methods were suggested to imply to treat the gaps between observed and simulated results. This study is focus on analysis the prediction patterns of rainfall in Lubuk Paku and Temerloh in Pahang state based on the historical rainfall. The rainfall pattern can be estimate the future climate change, general circulation models (GCMs) are applied. Therefore, Statistical Downscaling Model (SDSM) is applied in order to convert the coarse spatial resolution of the GCMs output into a fine resolution. However, there are biases in SDSM result and GCMs result. Therefore, two bias correction methods which are Linear Scaling (LS) and Local Intensity Scaling (LOCI) are applied to reduce the bias of those model and the performance of those methods are being compared. Faculty of Civil Engineering and Earth Resources Dissertations Universities and Colleges Dissertations Theses 0 0 0 1 10000 10000 2019-09-04 0 FKASA .Z87 2017 r Bc. 0000120840 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 10000 10000 2019-09-04 0 CD 10966 | FKASA .Z87 2017 r Bc. 0000120841 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 7543 7549 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5000*5020*5040*5200*6100*6500*6501*9992