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A Quality Assurance Framework for the Copernicus Climate Change Service

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In support of the Climate Change Service of EU’s Copernicus programme (C3S), the Quality Assurance for Essential Climate Variables (QA4ECV) project prototyped a generic system for the implementation and evaluation of quality assurance (QA) measures for satellite-derived climate data records. The project demonstrated the QA system on six new long-term climate quality data records for atmospheric nitrogen dioxide (NO2), formaldehyde (HCHO) and carbon monoxide (CO), and for surface albedo, leaf area index, and fraction of absorbed photosynthetically active radiation.
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The need for a data quality assurance framework

Climate change understanding, mitigation and adaptation require systematic observation of the climate system and identification of its natural and/or human causes of change. Key to this is the derivation of Essential Climate Variables (ECV) describing the chemical and physical properties of the biosphere, using reliable data from multiple sources.

Currently 54 ECVs have been identified for the Global Climate Observing System, spanning the atmospheric, cryospheric, oceanic and terrestrial domains.  In recent projects supported by the European Space Agency and the European Commission (EC), emphasis has been placed on the generation of climate data records (CDRs) to assess long-term (multi-decadal) trends, patterns and fluctuations, based on:

  • measurements from satellites
  • monitoring networks
  • complementary data sources

Fundamental to the scientific understanding of the climate system and to informed policy making, are the reliable documentation of the generation process and the rigorous quantification of the accuracy and validity of these CDRs.  Nevertheless, comprehensive and fully traceable quality information is rarely available. Harmonisation among the different domains is also critically needed by data users.

Generic QA System for climate data records

Developed at the normalization institute NPL (UK) with BIRA-IASB expertise for the atmospheric domain and in remote sensing metrology, the QA4ECV Quality Assurance system has been applied to the generation of multi-decadal CDRs for six pilot ECVs of the atmospheric and terrestrial domains:

  1. NO2
  2. HCHO
  3. CO
  4. surface albedo
  5. leaf area index
  6. fraction of absorbed photosynthetically active radiation

Building on international standards in metrology, terminology and system engineering, this generic QA system provides guidance on how to assure, evaluate and document ECV data quality, e.g., through traceability chains describing the data generation process, along which error propagation can be calculated to obtain uncertainty estimates.

This system contributes now to the Evaluation and Quality Control function of the Copernicus Climate Change Service (C3S) coordinated by the European Center for Medium- range Weather Forecasts (ECMWF).

Atmospheric ECV Validation Server

As a practical and direct application for the atmospheric domain, BIRA-IASB has developed the detailed processing model for an Atmospheric ECV Validation Server, virtually applicable to any atmospheric ECV. The latter has been prototyped and applied to the validation of NO2, HCHO and CO climate data records produced from different satellites within the project.

Following this successful demonstration, the QA4ECV prototype has been approved by the European Space Agency for implementation in the operational validation facility of its Mission Performance Centre for the Sentinel-5p TROPOMI mission, the first atmospheric Sentinel of EU’s Earth Observation programme Copernicus.


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The QA4ECV quality assurance framework for Essential Climate Variables. © Credit EC FP7 QA4ECV project, 2014-2018.
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The traceability chain describes how the climate data record is derived from satellite measurements. © Credit EC FP7 QA4ECV project, 2014-2018.
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Figure 4 caption (legend)
The Atmospheric ECV Validation Server compares satellite-derived climate data records to ground-based reference measurements and outputs quality indicators. © Credit EC FP7 QA4ECV project, 2014-2018.
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