Abstract
Abstract Meteorological observations from ground weather stations are of the upmost importance to implement and run sectoral climate services and to perform scientific activities, such as models’ evaluation and data assimilation. However, meteorological observations may be affected by errors deteriorating the quality and the reliability of the products based on these data. To avoid such a cascade of effects, it is essential to quality check meteorological observations in near–real time. A new system based on several levels of increasing complexity checks is proposed here. Besides the standard quality controls, this system applies dynamic and adaptive checks targeting exactly the locations and the data under analysis. The proposed system is designed to be flexible and easily modifiable thanks to its combined R and XML implementation. To facilitate its applicability, the proposed system is made available as a free open-source software: QuackMe.
Highlights
Meteorological data from ground weather stations represent an essential source of information for modeling, monitoring and research studies
Before describing the details of the new quality control system, we introduce the design of QuackMe to ease process understanding and how the checks are applied
The converter produces the final output files with quality controlled daily meteorological parameters, currently in a simple text-format designed for its use within the European MARS crop monitoring and forecasting system
Summary
The final typeset copyedited article will replace the EOR at the above DOI when it is published
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