Extensive validation of CM SAF surface radiation products over Europe

  1. Urraca, R. 3
  2. Gracia-Amillo, A.M. 4
  3. Koubli, E. 1
  4. Huld, T. 4
  5. Trentmann, J. 2
  6. Riihelä, A. 5
  7. Lindfors, A.V. 5
  8. Palmer, D. 1
  9. Gottschalg, R. 1
  10. Antonanzas-Torres, F. 3
  1. 1 Loughborough University
    info

    Loughborough University

    Loughborough, Reino Unido

    ROR https://ror.org/04vg4w365

  2. 2 Deutscher Wetterdienst, Offenbach, Germany
  3. 3 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  4. 4 Joint Research Centre
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    Joint Research Centre

    Bruselas, Bélgica

  5. 5 Finnish Meteorological Institute
    info

    Finnish Meteorological Institute

    Helsinki, Finlandia

    ROR https://ror.org/05hppb561

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Revista:
Remote Sensing of Environment

ISSN: 0034-4257

Año de publicación: 2017

Volumen: 199

Páginas: 171-186

Tipo: Artículo

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DOI: 10.1016/J.RSE.2017.07.013 SCOPUS: 2-s2.0-85025154982 WoS: WOS:000410469100014 GOOGLE SCHOLAR

Otras publicaciones en: Remote Sensing of Environment

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Resumen

This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 8–13 W/m2, whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRC's accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements. © 2017 The Authors