Quality Control of Automatic Weather Station Data: Study Case in DKI Jakarta

Automatic Weather Station (AWS) is an automatic weather station designed to measure and record meteorological parameters and transmit them automatically. To determine the validity of data from AWS equipment, quality control (QC) of the data is required. To determine the validity of AWS data, QC for the period January 2021 - July 2022 in DKI Jakarta was performed using range checks, consistency checks, and step checks. While range checks showed over 86.6% compliance, step checks indicated a lower success rate due to significant deviations. This paper proposes using local historical data for more accurate range checks and explores alternative step check methods based on weather conditions. The data is then carried out QC consistency check and step check. Consistency checks on the elements of solar radiation, wind and air temperature gave the result that more than 89.09% of the data were consistent. Step check was applied to air pressure, air humidity and average air temperature. The difference between the data and the previous data was compared with the standard deviation. This test gives a small average percentage that passes the test, namely 2.1% for air humidity and 47.4% for air pressure and average air temperature. This is due to the difference in data difference which is much greater than the standard deviation.