Hourly rainfall data between the years 1975 and 2010 across the Peninsular Malaysia were analyzed for trends in hourly extreme rainfall events. The analyses were conducted on rainfall occurrences during the northeast monsoon (November-February) known as NEM, the southwest monsoon (May-August) known as SWM, and the two inter-monsoon seasons, i.e., March-April (MA) and September-October (SO). Several extreme rainfall indices were calculated at the station level. The extreme rainfall events in Peninsular Malaysia showed an increasing trend between the years 1975 and 2010. The trend analysis was conducted using linear regression; no serial correlation was detected from the DurbinWatson test. Ordinary kriging was used to determine the spatial patterns of trends in seasonal extremes. The total amount of rainfall received during NEM is higher compared to rainfall received during inter-monsoon seasons. However, intense rainfall is observed during the inter-monsoon season with higher hourly total amount of rainfall. The eastern part of peninsular was most affected by stratiform rains, while convective rain contributes more precipitation to areas in the western part of the peninsular. From the distribution of spatial pattern of trend, the extreme frequency index (Freq >20) gives significant contribution to the positive extreme rainfall trend during the monsoon seasons. Meanwhile, both extreme frequency and extreme intensity (24-Hr Max, Freq >95th, Tot >95th, Tot >99th, and Hr Max) indices give significant contribution to the positive extreme rainfall trend during the inter-monsoon seasons. Most of the significant extreme indices showed the positive sign of trends. However, a negative trend of extreme rainfall was found in the northwest coast due to the existence of Titiwangsa Range. The extreme intensity, extreme frequency, and extreme cumulative indices showed increasing trends during the NEM and MA while extreme intensity and extreme frequency had similar trends during the SWM and SO throughout Peninsular Malaysia. Overall, the hourly extreme rainfall events in Peninsular Malaysia showed an increasing trend between the year 1975 and 2010 with notable increasing trends in short temporal rainfall during inter-monsoon season. The result also proves that convective rain during this period contributes higher intensity rains which can only be captured using short duration rainfall series.

Classroom management problems must be addressed with management corrective action, whereas teaching problems must be addressed with instructional corrective action. The teacher's actions can be in the form of preventive measures, namely by providing both physical and socio-emotional conditions so that students feel right with a sense of comfort and safety to learn. Other actions can be in the form of corrective action against the deviant behavior of students and damage the optimal conditions for the ongoing teaching and learning process. The purpose of this study was to describe the implementation of classroom management teaching skills by teachers in the teaching process at SD Negeri 34 Banda Aceh. The approach used in this research is a qualitative descriptive approach. The research subjects were 8 classroom teachers with permanent teacher status. Data collection techniques used observation and interview techniques. After the data collected is analyzed using data reduction, data presentation and conclusions. The results of this study indicate that the implementation of classroom management teaching skills carried out by teachers at SD Negeri 34 Banda Aceh has been carried out effectively and efficiently in the learning process in the classroom. A total of 6 teachers have implemented classroom management in the learning process in an optimal, effective and efficient manner, the creation of learning conditions in the classroom is very conducive and comfortable, learning time is in accordance with the plan, the distribution of attention carried out by the teacher visually and verbally is maximized, able to focus The attention of students to learn individually and in groups and provide reinforcement to students, can arrange class layout and maintain class cleanliness and comfort by adjusting class conditions so that students are comfortable in learning and can create a conducive learning climate. Meanwhile, the other 2 teachers are still not able to carry out the teaching skills to manage the class properly, which is related to the time and the creation of learning conditions in the classroom which are not conducive and comfortable, the distribution of attention made by the teacher visually and verbally is not optimal, and cannot maintain class conditions orderly.

In Malaysia, extreme rainfall events are often linked to a number of environmental disasters such as landslides, monsoonal and flash floods. In response to the negative impacts of such disaster, studies assessing the changes and projections of extreme rainfall are vital in order to gather climate change information for better management of hydrological processes. This study investigates the changes and projections of extreme rainfall over Peninsular Malaysia for the period 2081-2100 based on the RCP 6.0 scenario. In particular, this study adopted the statistical downscaling method which enables high resolution, such as hourly data, to be used for the input. Short duration and high intensity convective rainfall is a normal feature of tropical rainfall especially in the western part of the peninsular. The proposed method, the Advanced Weather Generator model is constructed based on thirty years of hourly rainfall data from forty stations. To account for uncertainties, an ensemble multi-model of five General Circulation Model realizations is chosen to generate projections of extreme rainfall for the period 2081-2100. Results of the study indicate a possible increase in future extreme events for both the hourly and 24 h extreme rainfall with the latter showing a wider spatial distribution of increase.

Generalized Extreme Value (GEV) model is the combination of three types of distribution class namely Gumbel, Fréchet and Weibull distributions of the Extreme Value Theory (EVT). In hydrological studies, GEV model is widely applied in the modelling of extreme rainfall. The nature of hydrological variables is highly complex, especially with the changing climate and frequent occurrences of extreme events. As such, some rainfall models assume rainfall series as stationary, while some as nonstationary. In this study, GEV models based on stationary and nonstationary data are used to assess monthly maximum rainfall data within Sabah, Malaysia and performance comparison between both GEV models is conducted. Theoretically both stationary and nonstationary GEV models are based on the same foundation, however nonstationary GEV model allows the location and scale parameters to be expressed as cyclic function of time. In this study, the stationary and the nonstationary GEV models are individually fitted to rainfall data at selected stations. Monthly maximum rainfall is blocked, and the estimated location (μ), scale (σ) and shape (ξ) parameters are estimated by using Maximum Likelihood Estimation method. Performance of both GEV models are compared based on the Akaike Information Criterion, Bayesian Information Criterion and the likelihood ratio goodness of fit tests. Results showed that nonstationary GEV model is the best fit. The inclusion of cyclic covariates in the GEV model gives improvement on the stationary GEV model at the study region. It is also concluded that, Gumbel is identified as the significant distribution for monthly maximum rainfall in Sabah at 5% significance level.

Weather generator is a numerical tool that uses existing meteorological records to generate series of synthetic weather data. The AWE-GEN (Advanced Weather Generator) model has been successful in producing a broad range of temporal scale weather variables, ranging from the high-frequency hourly values to the low-frequency inter-annual variability. In Malaysia, AWE-GEN has produced reliable projections of extreme rainfall events for some parts of Peninsular Malaysia. This study focuses on the use of AWE-GEN model to assess rainfall distribution in Kelantan. Kelantan is situated on the north east of the Peninsular, a region which is highly susceptible to flood. Embedded within the AWE-GEN model is the Neyman Scott process which employs parameters to represent physical rainfall characteristics. The use of correct probability distributions to represent the parameters is imperative to allow reliable results to be produced. This study compares the performance of two probability distributions, Weibull and Gamma to represent rainfall intensity and the better distribution found was used subsequently to simulate hourly scaled rainfall series. Thirty years of hourly scaled meteorological data from two stations in Kelantan were used in model construction. Results indicate that both probability distributions are capable of replicating the rainfall series at both stations very well, however numerical evaluations suggested that Gamma performs better. Despite Gamma not being a heavy tailed distribution, it is able to replicate the key characteristics of rainfall series and particularly extreme values. The overall simulation results showed that the AWE-GEN model is capable of generating tropical rainfall series which could be beneficial in flood preparedness studies in areas vulnerable to flood.