Comparative Analysis of ERA5 Precipitable Water Vapor and Precipitation Data Against Ground Observations and GNSS Measurement in Thailand

ผู้แต่ง

  • Sothyda Khor Department of Water Resources Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
  • Chaiyut Charoenphon Department of Survey Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
  • Supattra Visessri Department of Water Resources Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand

คำสำคัญ:

ERA5, GNSS, PWV, PE, Extreme weather events

บทคัดย่อ

ERA5 reanalysis data and Global Navigation Satellite System (GNSS) provide valuable atmospheric and hydrological data for weather and climate analysis. Both ERA5 and GNSS-derived precipitable water vapor (PWV), along with precipitation data, have potential applications in predicting extreme weather events. This study evaluates the accuracy of ERA5 precipitation data by comparing it with ground-based observations and ERA5 PWV data by comparing it against GNSS PWV measurements at six stations across different geographical regions in Thailand over the period of 2019 to 2023. Each precipitation dataset is used to compute the precipitation efficiency (PE), defined as the percentage of total precipitable water vapor that falls as measurable precipitation. The results indicate that ERA5 effectively captures seasonal precipitation and PWV patterns, but it underestimates high-intensity rainfall, particularly in coastal and complex terrains. In contrast, inland regions show better alignment with ground-based data. For PWV, ERA5 generally underestimates values in mountainous and coastal regions but performs better in flatter, more stable areas. Consequently, PE values from ground-based data show strong regional variation. These results make ERA5 particularly useful for climate monitoring and large-scale weather forecasting in low-lying or stable regions of Thailand. Its consistent spatiotemporal coverage, combined with PWV data, remains valuable for flood forecasting, especially in data-scarce areas for enhanced early warning systems.

ดาวน์โหลด

เผยแพร่แล้ว

2025-06-25