Fast retrieval of weather analogues in a multi-petabytes archive using wavelet-based fingerprints

Raoult, B., Di Fatta, G., Pappenberger, F. and Lawrence, B. ORCID: https://orcid.org/0000-0001-9262-7860 (2018) Fast retrieval of weather analogues in a multi-petabytes archive using wavelet-based fingerprints. In: International Conference on Computational Science, 11-13 June 2018, Wuxi, China, pp. 697-710. doi: 10.1007/978-3-319-93701-4_55

Abstract/Summary

Very large climate data repositories provide a consistent view of weather conditions over long time periods. In some applications and studies, given a current weather pattern (e.g. today’s weather), it is useful to identify similar ones (weather analogues) in the past. Looking for similar patterns in an archive using a brute force approach requires data to be retrieved from the archive and then compared to the query, using a chosen similarity measure. Such operation would be very long and costly. In this work, a wavelet-based fingerprinting scheme is proposed to index all weather patterns from the archive. The scheme allows to answer queries by computing the fingerprint of the query pattern, then comparing them to the index of all fingerprints more efficiently, in order to then retrieve only the corresponding selected data from the archive. The experimental analysis is carried out on the ECMWF’s ERA-Interim reanalyses data representing the global state of the atmosphere over several decades. Results shows that 32 bits fingerprints are sufficient to represent meteorological fields over a 1700 km × 1700 km region and allow the quasi instantaneous retrieval of weather analogues.