Cosmogenic Radionuclide Beryllium-7 Skewed Data Preprocessing for Northeast Monsoon Forecasting in Malaysia

The onset of the Northeast Monsoon (NEM) in Malaysia, as defined by The Malaysian Meteorological Department (MET Malaysia), relies on the sustained easterly wind component for at least seven days, with at least one day featuring a speed greater than 5 knots (2.5m/s). While meteorological parameters have historically been crucial in predicting these kinds of events, new research, like that carried out in Kerala, India, has demonstrated the potential to use nontraditional indicators, such as the concentration of the cosmogenic radionuclide Beryllium-7 (7Be) in the north and south hemispheres for monsoon prediction. This article zooms in on a fundamental aspect of monsoon forecasting: raw data preprocessing. It looks into using R statistical tools to refine and recalibrate datasets using this recently introduced parameter, 7Be, for NEM forecasting focusing on Malaysia. By meticulously adjusting and cleansing raw data, this preprocessing stage aims to align the data with the specific requirements of NEM prediction models, thus enhancing their accuracy and reliability. The significance of robust data preprocessing cannot be overstated, particularly in the context of NEM forecasting, where the accuracy of predictions holds profound implications for various sectors such as agriculture, tourism, and infrastructure planning. Potential biases, anomalies, and inconsistencies in the data can be eliminated with careful preparation, resulting in more reliable projections and well-informed decision-making. As such, this article underscores the critical role of data preprocessing in laying the groundwork for reliable and actionable NEM forecasts, ultimately contributing to the resilience and adaptability of Malaysia’s socio-economic landscape.