Abstract
Abstract. In science, poor quality input data will invariably lead to faulty conclusions, as in the spirit of the saying “garbage in, garbage out”. Atmospheric sciences make no exception and correct data is crucial to obtain a useful representation of the real world in meteorological, climatological and hydrological applications. Titan is a computer program for the automatic quality control of meteorological data that has been designed to serve real-time operational applications that process massive amounts of observations measured by networks of automatic weather stations. The need to quality control third-party data, such as citizen observations, within a station network that is constantly changing was an important motivation that led to the development of Titan. The quality control strategy adopted is a sequence of tests, where several of them utilize the expected spatial consistency between nearby observations. The spatial continuity can also be evaluated against independent data sources, such as numerical model output and remote sensing measurements. Examples of applications of Titan for the quality control of near-surface hourly temperature and precipitation over Scandinavia are presented. In the case of temperature, this specific application has been integrated into the operational production chain of automatic weather forecasts at the Norwegian Meteorological Institute (MET Norway). Titan is an open source project and it is made freely available for public download. One of the objectives of the Titan project is to establish a community working on common tools for automatic quality control, and the Titan program represents a first step in that direction for MET Norway. Further developments are necessary to achieve a solution that satisfies more users, for this reason we are currently working on transforming Titan into a more flexible library of functions.
Highlights
Applications in meteorology, hydrology and climatology are based on different assumptions, serve different needs and have different objectives
The characterization of the uncertainties of meteorological observations depends on the application at hand, and it might happen that the uncertainty of a particular observation is too large for a specific purpose, even when the observation itself is an accurate measurement of the atmospheric state
The Titan project provides a flexible procedure for the automatic quality control of in-situ meteorological data
Summary
Applications in meteorology, hydrology and climatology are based on different assumptions, serve different needs and have different objectives They all share the fundamental working hypothesis that observed data are representative of the atmospheric state. A number of non-conventional observations (e.g. citizen science data (Chapman et al, 2017; De Vos et al, 2017, 2019a; Nipen et al, 2019), and measurement from moving vehicles (Anderson et al, 2012, 2019)) have been stored in the databases of national centres alongside conventional observations. Different quality control approaches with focus on timeseries analysis of meteorological data have been proposed and tested on data from citizen networks.
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