0000000000773333
AUTHOR
Lucas Cuadra
Long-term persistence, invariant time scales and on-off intermittency of fog events
Abstract In this work we study different characteristics of fog long-term persistence, in events with different physical formation mechanisms. Specifically, we focus on the characterization of fog long-term persistence from observational data, by means of a Detrended Fluctuation Analysis (DFA) of its associated low-visibility time series. We analyze fog events with radiation and orographic underlying physical formation mechanisms, and identify a two-range pattern of long-term persistence. Our analysis leads to the emergence of a characteristic time, τ∗, at the crossover point between different scaling exponents in the DFA, independent of the time scale at which the fog event is studied. We …
Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources
This paper reviews the most important information fusion data-driven algorithms based on Machine Learning (ML) techniques for problems in Earth observation. Nowadays we observe and model the Earth with a wealth of observations, from a plethora of different sensors, measuring states, fluxes, processes and variables, at unprecedented spatial and temporal resolutions. Earth observation is well equipped with remote sensing systems, mounted on satellites and airborne platforms, but it also involves in-situ observations, numerical models and social media data streams, among other data sources. Data-driven approaches, and ML techniques in particular, are the natural choice to extract significant i…