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.
|Journal||IOP Conference Series: Earth and Environmental Science|
|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)