Abstract
Based on an analytic signal theory, the authors have developed an iterative algorithm for climate clustering using a temperature oscillation analysis. Surface temperature is selected as an integrated climate change indicator. Temperature series are studied as modulated signals. The algorithm enables signal grouping on various spatio-temporal scales using the available information on the synchronicity of envelopes of the signals.
Original language | English |
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Article number | 012003 |
Journal | IOP Conference Series: Earth and Environmental Science |
Volume | 211 |
Issue number | 1 |
DOIs | |
Publication status | Published - 17 Dec 2018 |
Event | International Conference and Early Career Scientists School on Environmental Observations, Modeling and Information Systems, ENVIROMIS 2018 - Tomsk, Russian Federation Duration: 5 Jul 2018 → 11 Jul 2018 |
ASJC Scopus subject areas
- Environmental Science(all)
- Earth and Planetary Sciences(all)