Review of the development of hydrological data quality control in Typhoon Committee Members

Abstract

Nowadays, with the continual development of the science and technology applied in data observation, monitoring and collection, human has more and more means and channels to obtain various data, consequently, the amount of collected and stored data is also getting bigger and bigger. In recent years, hydro-meteorological data have multiplied in some Typhoon Committee (TC) Members. Data-based advanced technology applications in TC, such as application of Artificial Intelligent (AI) and impact-based typhoon disaster forecasting and early warning, has emerged one after another. A consistent and integrated data quality management system is crucial for ensuring accurate hydrological and meteorological analysis and prediction. Considering the importance and urgent necessary, TC working group on hydrology (WGH) conducted a cooperation project on data quality management in the past years with the major objective of improving the capacity of TC Members on integrated data quality control and processing. Despite the significant improvements, the uncertainties and difficulties in processing the full-elements of hydro-meteorological data still persist in hydro-meteorological data. To tackle these challenges and further enhance the data quality management system, the integration of AI technology shows great promise. By examining the data quality management system at World Meteorological Organization (WMO) as a starting point, this paper explored how related organizations in China, Japan, Malaysia, Philippines and Republic of Korea, manage the quality of hydro-meteorological data; reviewed the current status of hydro-meteorological data quality control in TC Members, and discussed the potential areas to be enhanced in future.