UJI KEAKURATAN DATA SUHU UDARA, KELEMBABAN UDARA, TEKANAN UDARA, DAN CURAH HUJAN DARI ALAT AUTOMATIC WEATHER STATION TERHADAP PENGUKURAN MANUALNYA

Abstract

To determine the performance of AWS in observing the weather, the AWS output data accuracy test is carried out. AWS can work without an operator and can be operated from anywhere so that AWS can improve observation networks and early warning systems. The data used in this study are air temperature, humidity, air pressure, and rainfall measured by AWS and manual observations with conventional tools located at the Konawe Selatan Climatology Station. A simple statistical method by calculating the correlation coefficient (r), Mean Absolute Error (MAE), and percent accuracy was used to compare the data. The results show that AWS Konawe Selatan Climatology Station has good performance in measuring weather parameters such as average temperature, maximum temperature, minimum temperature, humidity, air pressure, and rainfall which is indicated by the correlation coefficient is high (r> 0.8), the percentage of accuracy is high (> 94%), and the average error is low. However, some parameters do not meet the fault tolerance values ​​that have been set by WMO that is the maximum and minimum temperature, and air pressure variables. With the quality control of data through an error detection system and eliminating incomplete data, it can improve the accuracy of the AWS data.