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The rapid development of the radio communications system, especially in developed countries, has drawn the attention of telecommunication systems engineers to explore the frequency band above the Ku band. Because radio communication systems operating in the frequency band above the Ku band (10 GHz) suffer from rain attenuation during rainy conditions, prediction of rain attenuation using a 1-min rainfall rate distribution is indeed vital. However, a 1-min rainfall rate distribution is not widely available compared to rainfall rate distributions with longer integration times. Therefore, a suitable conversion method is required to predict 1-min rainfall rate distributions of distinct integration times. This paper presents several conversion methods such as Segal, Burgueno et al., Chebil and Rahman, Joo et al., EXCELL RSC and LG. The Segal method provides an overall Root Mean Square (RMS) error below 5% at different integration times and is suitable to be used in malaysia. [ABSTRACT FROM AUTHOR]

Accurate prediction of monsoon heavy rainfall events in the equatorial region has always been a challenge to weather forecasters. In this paper, forecast of a severe precipitation event that occurred over the eastern central coast of Peninsular Malaysia was attempted using the state-of-the-art Florida State University (FSU) Global and Regional Spectral Models. The sensitivity of parameterized convection in these models on precipitation forecast skill is studied using two different parameterization schemes for cumulus convection (the Relaxed Arakawa-Schubert scheme and the modified Kuo scheme). Low precipitation threshold of rainfall less than 2 mm day-1 was successfully predicted by both versions of the FSU model. However, the convection schemes lacked skill in predicting the correct placement of the area and amount for the high precipitation threshold greater than 40 mm day-1. Further evaluation of the predictive skills showed that the Relaxed Arakawa-Schubert scheme was a consistently better predictor of rainfall due to its low bias and lower root mean square errors (RMSEs) compared to the modified Kuo parameterization scheme. [ABSTRACT FROM AUTHOR]