Quality Management Framework for Climate Datasets

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http://urn.fi/URN:NBN:fi-fe2022040727481 http://hdl.handle.net/10138/342592
Title: Quality Management Framework for Climate Datasets
Author: Lacagnina, Carlo; Doblas-Reyes, Francisco; Larnicol, Gilles; Buontempo, Carlo; Obregón, André; Costa-Surós, Montserrat; San-Martín, Daniel; Bretonnière, Pierre-Antoine; Polade, Suraj D.; Romanova, Vanya; Putero, Davide; Serva, Federico; Llabrés-Brustenga, Alba; Pérez, Antonio; Cavaliere, Davide; Membrive, Olivier; Steger, Christian; Pérez-Zanón, Núria; Cristofanelli, Paolo; Madonna, Fabio; Rosoldi, Marco; Riihelä, Aku; Díez, Markel García
Contributor organization: Ilmatieteen laitos
Finnish Meteorological Institute
Publisher: Ubiquity Press, Ltd.
Date: 2022
Language: en
Belongs to series: Data Science Journal
ISSN: 1683-1470
DOI: https://doi.org/10.5334/dsj-2022-010
URI: http://urn.fi/URN:NBN:fi-fe2022040727481
http://hdl.handle.net/10138/342592
Abstract: Data from a variety of research programmes are increasingly used by policy makers, researchers, and private sectors to make data-driven decisions related to climate change and variability. Climate services are emerging as the link to narrow the gap between climate science and downstream users. The Global Framework for Climate Services (GFCS) of the World Meteorological Organization (WMO) offers an umbrella for the development of climate services and has identified the quality assessment, along with its use in user guidance, as a key aspect of the service provision. This offers an extra stimulus for discussing what type of quality information to focus on and how to present it to downstream users. Quality has become an important keyword for those working on data in both the private and public sectors and significant resources are now devoted to quality management of processes and products. Quality management guarantees reliability and usability of the product served, it is a key element to build trust between consumers and suppliers. Untrustworthy data could lead to a negative economic impact at best and a safety hazard at worst. In a progressive commitment to establish this relation of trust, as well as providing sufficient guidance for users, the Copernicus Climate Change Service (C3S) has made significant investments in the development of an Evaluation and Quality Control (EQC) function. This function offers a homogeneous user-driven service for the quality of the C3S Climate Data Store (CDS). Here we focus on the EQC component targeting the assessment of the CDS datasets, which include satellite and in-situ observations, reanalysis, climate projections, and seasonal forecasts. The EQC function is characterised by a two-tier review system designed to guarantee the quality of the dataset information. While the need of assessing the quality of climate data is well recognised, the methodologies, the metrics, the evaluation framework, and how to present all this information to the users have never been developed before in an operational service, encompassing all the main climate dataset categories. Building the underlying technical solutions poses unprecedented challenges and makes the C3S EQC approach unique. This paper describes the development and the implementation of the operational EQC function providing an overarching quality management service for the whole CDS data.
Subject: data quality
trust
FAIR
climate services
scalability
Rights: CC BY 4.0


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