How effective is the new generation of GPM satellite precipitation in characterizing the rainfall variability over Malaysia?

We investigated the potential of the new generation of satellite precipitation product from the Global Precipitation Mission (GPM) to characterize the rainfall in Malaysia. Most satellite precipitation products have limited ability to precisely characterize the high dynamic rainfall variation that occurred at both time and scale in this humid tropical region due to the coarse grid size to meet the physical condition of the smaller land size, sub-continent and islands. Prior to the status quo, an improved satellite precipitation was required to accurately measure the rainfall and its distribution. Subsequently, the newly released of GPM precipitation product at half-hourly and 0.1° resolution served an opportunity to anticipate the aforementioned conflict. Nevertheless, related evidence was not found and therefore, this study made an initiative to fill the gap. A total of 843 rain gauges over east (Borneo) and west Malaysia (Peninsular) were used to evaluate the rainfall the GPM rainfall data. The assessment covered all critical rainy seasons which associated with Asian Monsoon including northeast (Nov. - Feb.), southwest (May - Aug.) and their subsequent inter-monsoon period (Mar. - Apr. & Sep. - Oct.). The ability of GPM to provide quantitative rainfall estimates and qualitative spatial rainfall patterns were analysed. Our results showed that the GPM had good capacity to depict the spatial rainfall patterns in less heterogeneous rainfall patterns (Spearman’s correlation, 0.591 to 0.891) compared to the clustered one (r = 0.368 to 0.721). Rainfall intensity and spatial heterogeneity that is largely driven by seasonal monsoon has significant influence on GPM ability to resolve local rainfall patterns. In quantitative rainfall estimation, large errors can be primarily associated with the rainfall intensity increment. 77% of the error variation can be explained through rainfall intensity particularly the high intensity (> 35 mm d^-1). A strong relationship between GPM rainfall and error was found from heavy (~35 mm d^-1) to violent rain (160 mm d^-1). The output of this study provides reference regarding the performance of GPM data for respective hydrology studies in this region.     

2019年马六甲地区红色精灵观测及母体雷暴分析

红色精灵是一种发生于闪电放电活跃的雷暴云上空的中高层大气瞬态发光现象,它们通常由中尺度对流系统层状云降水区内的强地闪回击产生,是对流层和中间层之间的一种能量耦合过程。目前,有关中国南海及东南亚地区的红色精灵观测鲜有报道。为了进一步了解热带地区产生红色精灵事件的沿海性雷暴特征,于2019年利用低光度光学观测系统和低频磁场天线在马来西亚马六甲地区开展了地基观测。实验于11月9日、12月11日和12月15日三次在沿海雷暴上空共捕捉到7例红色精灵事件,其中包括4例圆柱型、2例胡萝卜型和1例舞蹈型。结合闪电定位、云顶亮温和低频磁场信号等同步数据,分析表明所有事件均由正极性地闪回击产生,且母体闪电回击位于雷暴对流区附近（云顶亮温≤ 210 K处）,这可能是该地区产生红色精灵的沿海性雷暴的共同特征。此外,红色精灵生成期并不是闪电活动最强期,而是发生于闪电频数短暂降低后,这表明红色精灵的发生可能是该地区成熟雷暴中对流减弱的一个信号。     

Bioenergy consumption and economic growth in the EU-28 region: evidence from a panel cointegration model

GeoJournal - The purpose of this research is to examine the correlation between the bioenergy industry and economic outgrowth. This study investigates the growth hypothesis within the setting of...     

Estimating groundwater vulnerability to pollution using a modified DRASTIC model in the Kerman agricultural area,Iran

Groundwater contamination from intensive fertilizer application affects conservation areas in a plain. The DRASTIC model can be applied in the evaluation of groundwater vulnerability to such pollution. The main purpose of using the DRASTIC model is to map groundwater susceptibility to pollution in different areas. However, this method has been used in various areas without modification, thereby disregarding the effects of pollution types and their characteristics. Thus, this technique must be standardized and be approved for applications in aquifers and particular types of pollution. In this study, the potential for the more accurate assessment of vulnerability to pollution is achieved by correcting the rates of the DRASTIC parameters. The new rates were calculated by identifying the relationships among the parameters with respect to the nitrate concentration in groundwater. The methodology was implemented in the Kerman plain in the southeastern region of Iran. The nitrate concentration in water from underground wells was tested and analyzed in 27 different locations. The measured nitrate concentrations were used to associate and correlate the pollution in the aquifer to the DRASTIC index. The Wilcoxon rank-sum nonparametric statistical test was applied to determine the relationship between the index and the measured pollution in Kerman plain. Also, the weights of the DRASTIC parameters were modified through the sensitivity analysis. Subsequently, the rates and weights were computed. The results of the study revealed that the modified DRASTIC model performs more efficiently than the traditional method for nonpoint source pollution, particularly in agricultural areas. The regression coefficients showed that the relationship between the vulnerability index and the nitrate concentration was 82 % after modification and 44 % before modification. This comparison indicated that the results of the modified DRASTIC of this region are better than those of the original method.     

Downscaling and projection of precipitation from general circulation model predictors in an equatorial climate region by the automated regression-based statistical method

The authors have applied an automated regression-based statistical method, namely, the automated statistical downscaling (ASD) model, to downscale and project the precipitation climatology in an equatorial climate region (Peninsular Malaysia). Five precipitation indices are, principally, downscaled and projected: mean monthly values of precipitation (Mean), standard deviation (STD), 90th percentile of rain day amount, percentage of wet days (Wet-day), and maximum number of consecutive dry days (CDD). The predictors, National Centers for Environmental Prediction (NCEP) products, are taken from the daily series reanalysis data, while the global climate model (GCM) outputs are from the Hadley Centre Coupled Model, version 3 (HadCM3) in A2/B2 emission scenarios and Third-Generation Coupled Global Climate Model (CGCM3) in A2 emission scenario. Meanwhile, the predictand data are taken from the arithmetically averaged rain gauge information and used as a baseline data for the evaluation. The results reveal, from the calibration and validation periods spanning a period of 40 years (1961–2000), the ASD model is capable to downscale the precipitation with reasonable accuracy. Overall, during the validation period, the model simulations with the NCEP predictors produce mean monthly precipitation of 6.18–6.20 mm/day (root mean squared error 0.78 and 0.82 mm/day), interpolated, respectively, on HadCM3 and CGCM3 grids, in contrast to 6.00 mm/day as observation. Nevertheless, the model suffers to perform reasonably well at the time of extreme precipitation and summer time, more specifically to generate the CDD and STD indices. The future projections of precipitation (2011–2099) exhibit that there would be an increase in the precipitation amount and frequency in most of the months. Taking the 1961–2000 timeline as the base period, overall, the annual mean precipitation would indicate a surplus projection by nearly 14~18 % under both GCM output cases (HadCM3 A2/B2 scenarios and CGCM3 A2 scenario). According to the model simulation, the September–November periods might be the more significant months projecting the increment of the precipitation amount around over 50 %, while the precipitation deficit would be seen in March–May periods.     

Modeling storm surges associated with super typhoon durian in South China Sea

Super typhoon Durian struck the central Philippines on November 30, 2006 and southern coast of Vietnam on December 5, 2006. The reported maximum wind exceeded 250 km/h, and the central pressure was 904 hPa during the peak of the system. The typhoon brought colossal damage, both in terms of lives and in terms of properties to the Philippines and Vietnam while Thailand and Malaysia were slightly affected. The energy from the high-velocity wind and central pressure drop resulted in the generation of storm surges along the coastal region of the Philippines including its surrounding islands as well as parts of southern Vietnam. In this paper, a numerical 2D model is used to study the oceanic response to the atmospheric forcing by 2006 super typhoon Durian in the coastal regions of the Philippines and Vietnam. The initial study of this model aims to provide some useful insights before it could be used as a coastal disaster prediction system in the region of South China Sea (SCS). The atmospheric forcing for the 2D model, which includes the pressure gradient and the wind field, is generated by an empirical asymmetrical storm model. The simulated results of storm surges due to typhoon Durian at two locations lie in the range of observed data/estimates published by the Joint Typhoon Warning Centre (JTWC).     

Fitting optimum order of Markov chain models for daily rainfall occurrences in Peninsular Malaysia

The analysis of the daily rainfall occurrence behavior is becoming more important, particularly in water-related sectors. Many studies have identified a more comprehensive pattern of the daily rainfall behavior based on the Markov chain models. One of the aims in fitting the Markov chain models of various orders to the daily rainfall occurrence is to determine the optimum order. In this study, the optimum order of the Markov chain models for a 5-day sequence will be examined in each of the 18 rainfall stations in Peninsular Malaysia, which have been selected based on the availability of the data, using the Akaike’s (AIC) and Bayesian information criteria (BIC). The identification of the most appropriate order in describing the distribution of the wet (dry) spells for each of the rainfall stations is obtained using the Kolmogorov-Smirnov goodness-of-fit test. It is found that the optimum order varies according to the levels of threshold used (e.g., either 0.1 or 10.0 mm), the locations of the region and the types of monsoon seasons. At most stations, the Markov chain models of a higher order are found to be optimum for rainfall occurrence during the northeast monsoon season for both levels of threshold. However, it is generally found that regardless of the monsoon seasons, the first-order model is optimum for the northwestern and eastern regions of the peninsula when the level of thresholds of 10.0 mm is considered. The analysis indicates that the first order of the Markov chain model is found to be most appropriate for describing the distribution of wet spells, whereas the higher-order models are found to be adequate for the dry spells in most of the rainfall stations for both threshold levels and monsoon seasons.     

Agrobiodiversity of Muda Rice Agroecosystem:A case Study in Largest Granary Area of Malaysia

A survey was carried out at the largest rice cultivation area in Peninsular Malaysia,the Muda rice agroecosystem.The main objective of this study was to document the overall biodiversity associated with this unique agroecosystem by using a combination of sampling techniques in order to record different groups of fauna and flora.The total number of biota recorded and identified from the rice field ecosystem during the study period consisted of 46 species of zooplankton,81 species of aquatic insects,5 species of rodents,7 species of bats,87 species of birds,11 species of fishes and 58 species of weeds.A long-term study should be carried out as more species are expected to be recorded when more of the Muda rice agroecosystem area has been sampled to obtain sufficient information on the Muda rice agrobiodiversity.