Study of Quality Control Methods for Moored Buoys Observation Data

Marine meteorological observation is an important means for us to understand the characteristics of marine meteorology. At present, China Meteorological Administration has built several buoy stations, island stations, weather radars and meteorological satellites. Moored buoy data is an important part of the integrated observation system as the measured data at sea, but there is no effective data quality control for the data in China. On the basis of traditional quality control methods, according to the principles of meteorology, Synoptic meteorology and climatology, and taking the laws of the relationship between meteorological elements of moored buoys as clues, the data quality control techniques, including range inspection, extreme value inspection, internal consistency inspection, statistical inspection and homogeneity inspection, were studied in this study. The 9 moored buoys stations were divided according to the sea area (Bohai Sea, Yellow Sea). According to the season (spring, summer, autumn, winter), the boundary values and continuous changes of meteorological elements such as air pressure, temperature, wind speed and visibility were counted, and the quality control threshold was determined. In order to test the effect of the data quality control method, the air pressure, temperature and wind speed data of four moored buoy stations in different sea areas (Bohai Sea, Yellow Sea) from January 1, 2019 to October 1, 2019 were selected for independent sample test. Through time-space matching and comparison analysis with the initial field data reported by GRAPES models at 20:00 every day, the results showed that: after being processed by the quality control algorithm and eliminating the marked abnormal data, the data quality raised. The method effectively marked the suspicious data and obviously reduced the mean absolute deviation from the mode-assimilating data. The data quality control in different sea areas were divided and counted according to the climate characteristics of different areas, which could mark the abnormal data more accurately and carry out the moored buoy data quality control more effectively.