Preservation and harmonization of historical AVHRR LAC data to serve the needs of users in climate research

Stefan Wunderle, Christoph Neuhaus, Andrew Brooks, Fabia Hüsler, Neil Lonie, Mirko Albani, Sergio Folco, Rosemarie Leone

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Abstract

Historical satellite data are of high value for climate research as an independent source to validate the output of climate models. Of special interest are data from the AVHRR sensor in 1km spatial resolution (LAC), which are available from 1981 until 2017 (2022). The data archived at different centers in Europe need consolidation (filling data gaps, removing redundant orbits etc.) and harmonization (generating the same format and meta-files) before transferred to ESA facilities to make a long time series accessible for scientific use. In the frame of ESA's Long Term Data Preservation program the archived AVHRR data will be stored and maintained for the next +50 years. We will present the different parts of the ESA-UniBern AVHRR-LTDP project and recommendations for the next processing steps needed to generate essential climate variables (e.g. snow extent, lake surface water temperature).
Original languageEnglish
Title of host publicationProceedings of the 2017 conference on Big Data from Space (BIDS' 2017)
PublisherESA Publications Division
Pages154
Number of pages157
ISBN (Electronic)978-92-79-73527-1
DOIs
Publication statusPublished - Nov 2017
Event2017 Conference on Big Data from Space
- Centre de Congrès Pierre Baudis, Toulouse, France
Duration: 28 Nov 201730 Nov 2017
http://www.bigdatafromspace2017.org/

Conference

Conference2017 Conference on Big Data from Space
Abbreviated titleBiDS'17
CountryFrance
CityToulouse
Period28/11/1730/11/17
Internet address

Keywords

  • AVHRR-LAC data
  • ESA Long Term Data Preservation (LTDP)
  • data consolidation and harmonization

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    Wunderle, S., Neuhaus, C., Brooks, A., Hüsler, F., Lonie, N., Albani, M., Folco, S., & Leone, R. (2017). Preservation and harmonization of historical AVHRR LAC data to serve the needs of users in climate research. In Proceedings of the 2017 conference on Big Data from Space (BIDS' 2017) (pp. 154). ESA Publications Division. https://doi.org/10.2760/383579