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This paper presents the modelled raindrop size parameters in Skudai region of the Johor Bahru, western Malaysia. Presently, there is no model to forecast the characteristics of DSD in Malaysia, and this has an underpinning implication on wet weather pollution predictions. The climate of Skudai exhibits local variability in regional scale. This study established five different parametric expressions describing the rain rate of Skudai; these models are idiosyncratic to the climate of the region. Sophisticated equipment that converts sound to a relevant raindrop diameter is often too expensive and its cost sometimes overrides its attractiveness. In this study, a physical low-cost method was used to record the DSD of the study area. The Kaplan-Meier method was used to test the aptness of the data to exponential and lognormal distributions, which were subsequently used to formulate the parameterisation of the distributions. This research abrogates the concept of exclusive occurrence of convective storm in tropical regions and presented a new insight into their concurrence appearance.

Rain event is normally an expression of varied composition of raindrops diameters as a function of their volumetric diameters per unit volume of space [

Although studies of DSD were carried out in other tropical regions [

Techniques used to measure raindrop diameter, and its distribution, can broadly be classified into two: the automatic equipment and the manual methods. The absorbent paper method devised by Lowe [

A raindrop breaks into smaller diameters when it reaches its limiting size of about 5 mm to 8 mm [

The map of the study area is shown in Figure

Location map of the study area.

A highly sensitive tipping bucket (model RG3-M) that can record up to 3,200 rainfall events was equipped with an event data logger and mounted on coordinate 103°38′39.5′′E 1°33′41.6′′N inside Universiti Teknologi Malaysia (UTM) away from any lateral obstructions. Before its use, the rain gauge was recalibrated according to manufacturer’s instruction to ±1% accuracy. Intensities were recorded on one-minute basis. The exact time and temperature were also recorded, which were used in the estimation of the rain intensity and the drop diameter, respectively. The equipment was checked every fortnight to ensure its proper functioning and to ensure it was on upright position of 1.8 m above ground level.

At selected storms, the flour pellet method was used to trap raindrops as they approach the ground. A 3 mm thick flour was spread on a 0.15 m^{2} rectangular tray and briefly exposed to seventeen different rain intensities for about 3–5 seconds, depending upon the strength of the intensity, such that enough raindrops would have been trapped. The profile of the sampled storms and the number of samples in each storm was presented in Table

Sampled storm profile.

Sampling |
Duration |
Average storm intensity ^{−1}) |
Number of samples |
---|---|---|---|

09/10/12 | 120 | 35 | 2 |

01/11/12 | 60 | 12 | 7 |

27/6/13 | 33 | 12 | 1 |

16/7/13 | 47 | 16 | 1 |

18/08/13 | 22 | 29 | 1 |

24/08/13 | 15 | 8 | 1 |

26/08/13 | 110 | 65 | 1 |

03/10/13 | 56 | 32 | 1 |

05/10/13 | 13 | 21 | 1 |

12/10/13 | 34 | 23 | 1 |

The formed capsules were marked and immediately transported to a laboratory and oven dried using automated universal oven (Memmert, model 16.1) for 12 hrs at 105°C. The flour capsules were divided into different size fractions according to BS 812-103.1:1985 method for determination of particle size distribution. Thus, the oven dried flour samples were poured into 300 mm diameter standard sieves. The sieves were then stacked in decreasing size (6.30, 5.00, 4.47, 2.36, 2.00, 1.18, and 0.60 mm) and secured onto a mechanical shaker. The contents were allowed to vibrate for 10 min. The retained pellets were carefully dislodged and emptied into a preweighted stainless steel container with the help of a handheld brush. The weight of each particle size fraction retained in any given sieve was obtained using a weighing balance accurate to 0.001 g. A total of 720859 capsules were counted and measured. The drop diameter for each sieve class in a given sample was then calculated by converting the weight of the flour capsule into an appropriate raindrop diameter using the Hudson [

Hudson [

Raindrop distribution can be estimated from exponential equation suggested by Marshall and Palmer [^{3} mm^{−1}) that corresponds to ^{−1}) that depends on the rainfall intensity (

The basic difference between (^{−3} mm^{−1}), ^{−3}), and

The quantile-quantile (Q-Q) and probability plots were respectively used to test whether our study data follows the exponential and lognormal distributions. The Kaplan-Meier method was used for the survival analyses. The Q-Q and probability plots for the median drop diameter for each intensity were presented in Figures

Exponential Q-Q plot.

Lognormal probability test plot.

The difference between the two figures is the representation of the values in percentiles in Figure

The exponential ^{−1} with only two of the intensities higher than 70 mm h^{−1}. The

Figure

Figure

Exponential and lognormal DSD of Skudai.

Both the lognormal and the exponential models show consistent trends at drop diameter of less than 3.3 mm. The result also shows that higher rain intensities are composed of larger proportions of raindrop diameters than lighter intensities. The rain intensity in Skudai is considerably composed of raindrop diameters of less than 4 mm in large part. Taking into cognisance the

The exponential DSD model obtained from this study is compared with Marshall and Palmer [^{−1} and 25 mm h^{−1} as shown in Figure

Modelled drop size distribution using exponential distribution density function.

The lognormal parameters of the DSD obtained in (

Drops count-intensity relationship.

Logarithmized standard deviation-intensity relationship.

Logarithmized mean-intensity relationship.

Figures ^{−1}. But the

A differentiation between the convective and stratiform storms is very valuable in the tropics and in mid-scopes in the warm season of other geographies, as condensation peaks during the latent heat liberation in troposphere zones of stratiform precipitation. Therefore, a combined model of the exponential and the lognormal distributions could describe tropical storm of both convective and stratiform storms in more appropriate manner than using a single model.

Five different parametric expressions describing the rain rate of Skudai were established from this study. The exponential and the lognormal models were used to describe the DSD of the study area. The parameters of these models were empirically instituted from the experimental result using regression analysis on the data. The modelled rain rate and the drop count per unit volume of rain obtained from this study infer that the study area experiences uniform precipitation. This research also demonstrated that the convective storm in the tropical region of Skudai occurred concurrently with stratiform storm.

The advantage of using more than one model to predict storm behaviour has been put forward in this study. The results of the two models are in agreement, with a maximum divergence at a higher raindrop diameter. The lognormal model tends to underestimate the DSD of lighter rain intensities at drop diameters smaller than 4 mm, while the exponential model was predisposed to the bigger diameters at moderate to severe rain intensities. The ^{−1}. But the

The authors declare that there is no conflict of interests regarding the publication of this paper.