Validation of Rainfall Data Analysis Using Disdrometer Data Under Wet-Bulb Temperature Conditions

Abstract

To enhance the accuracy of rainfall estimation using remote sensing data, such as radar and satellite, it is crucial to improve the accuracy of the estimation relationships. Rainfall estimation is influenced by various factors, including rainfall type, geographical characteristics (e.g., inland and oceanic rainfall), and orographic rainfall features. Developing estimation formulas that account for variations in rainfall characteristics based on topography (elevation) and seasonal temperature changes is essential. Ensuring the reliability of observation data used in deriving these formulas is a top priority for achieving accurate rainfall estimation. This study evaluates the effectiveness of utilizing rain gauge data under varying wet-bulb temperature conditions to improve the reliability of rainfall analysis. The analysis employed disdrometer data collected over five years (2020–2024), applying channel-based particle diameter information and number concentration-based variable calculation methods to enhance the generalizability of the findings. Quantitative comparisons of rain gauge observation accuracy under different wet-bulb temperature conditions were conducted, alongside an analysis of the temperature ranges in which two types of rain gauges (tipping-bucket and weighing gauges) could be effectively utilized. Furthermore, we assessed the quality management of rain gauge data preprocessing for raindrops across various temperature conditions. The results indicate that when the wet-bulb temperature exceeded 2°C, the difference (RMSE) in rainfall between disdrometer and rain gauge observation data was less than 0.2 mm. However, this difference increased significantly to over 0.4 mm when the wet-bulb temperature was below 2°C, with particularly large differences exceeding 1.0 mm when disdrometer data were not preprocessed. These discrepancies reflect variations in hydrometeor characteristics and particle fall velocities due to temperature changes. This study underscores the necessity of establishing meteorological conditions for rainfall analysis.

 

Keywords: Disdrometer, Wet-bulb temperature, Long-term observation, Hydrometeor

 

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education (RS-2022-NR071182).