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Ten years of ENVISAT observations at ECMWF: A review of activities and lessons learnt

Journal

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY
Volume 141, Issue 687, Pages 598-610

Publisher

WILEY-BLACKWELL
DOI: 10.1002/qj.2380

Keywords

ENVISAT; NWP; satellite data; atmospheric composition; reanalysis; ocean waves

Funding

  1. European Space Agency [21519/08/I-OL]
  2. MACC-II project - European Commission under the EU [283576]

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In 2002, the European Space Agency (ESA) launched the ENVIromental SATellite (ENVISAT), which carried ten instruments to provide continuous observation of Earth's land, atmosphere, oceans and ice caps. During the satellite's lifetime, the European Centre for Medium Range Weather Forecasts (ECMWF) has routinely monitored a variety of products from many of its instruments. A subset of these data has also been assimilated in the ECMWF operational system, along with two of its applications: the reanalysis and the Monitoring Atmospheric Composition and Climate (MACC) systems. This article reviews those activities and summarizes the lessons learnt in monitoring and assimilating data from a research satellite within a numerical weather prediction system. The value of continuous data monitoring and the benefits that a close collaboration between data provider and data user can bring to both parties are highlighted. For observations that were assimilated, impact assessments on the ECMWF products have been performed periodically. Two cases are presented in this article. The first one shows that the assimilation of ocean wave information can reduce the wave-height model random error by up to 8% at the analysis time, with benefits at later forecast times extending to up to 5 days in the Tropics. The second example shows that the assimilation of two ENVISAT ozone products improves the agreement of the ozone analyses with independent ozone observations obtained from sondes and the Microwave Limb Sounder. Finally, the use of ENVISAT reprocessed data is presented, with an emphasis on the importance of data reprocessing and long-term data preservation as key activities to ensure the future usage of these datasets.

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