ABSTRACTThe reliability of ground‐based measurements is important in a variety of meteorological areas, such as weather forecasts, air quality and climate. In order to improve this reliability, closer co‐operation with the metrological community has been established. This paper looks at another possible route for improvements, based on carrying out a quality assessment of ground‐based measurements using advanced quality techniques. The quality function deployment (QFD) method was adapted so as to be able to analyse the results of a survey that was conducted among meteorological community. They were asked to analyse the key performance characteristics of typical automatic weather stations (AWSs) systematically with respect to the World Meteorological Organization (WMO) classifications and requirements. The QFD is a well‐known quality tool that connects customer expectations with technical functionalities or engineering characteristics. It makes it possible to prioritize the needs and quantify the results of the assessment. The answers from the survey's questionnaire were used as the input data for the QFD matrix. The findings reveal that the closest correlations are between the customer expectations or attributes and the engineering characteristics, e.g., the validation of the AWSs and the measurement methods, the regular calibration of sensors, and the implementation of automated and manual controls. From the second level of the QFD matrix, it was found that the most important technical solution serving the previously mentioned needs is related to having control over the development and upgrading of the AWSs' software and in terms of an automatic check and the transfer of data to the central database.