Geometry in Meteorology and Climatology

The atmosphere is a highly non-linear dynamic system, where equations can present some solutions known as strange attractors since they have non-integer dimensions, or in other words,  fractional volumes. The fractality in meteorology and climatology is reflected in the self-similarity at different spatial and temporal scales. For instance, atmospheric patterns present quasiperiodic oscillations that are reproduced at all spatial scales (from the eddy and the polar vortex to the Quasi-Biennial Oscillation and the Arctic Oscillation). Other examples are the disaggregation methods of sub-daily rainfall and the distribution of dry spells within a drought, which closely resemble the gaps in the Cantor set. Therefore, this Special Issue aims to review the state of the art and boost cutting-edge methods in “Geometry in Meteorology and Climatology” by collecting original contributions covering transdisciplinary approaches. Due to the strong link between atmospheric sciences and mathematics, this Special Issue will be focused on geometrical methods applied to characterize, analyze, predict or attribute physical phenomena linked to atmospheric dynamics and the effects. This includes characterization by geometrical approaches such as multifractal cascading, time scaling, rainfall concentration and drought lacunarity, as well as an empirical orthogonal basis of atmospheric patterns, principal components, compound events and extreme value theory of atmospheric variables. This Special Issue also accepts advanced methods for climate change attribution analysis, forensic meteorology and hindcast or operational forecasting that use geometrical perspectives such as performance metrics in supervised learning algorithms, similarity measures and analogue stratification, among others. Finally, the geometrical interpretation of time series analysis (breaking points, transitivity, information power, entropy, and Lyapunov and Hurst exponents) should also be adjusted to the scope when atmospheric variables are a key part of the papers.

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