Wavelet transforms originated in geophysics in the early 1980s for the analysis of seismic
signals. Since then, significant mathematical advances in wavelet theory have enabled a …

In this paper, the wavelet transform methods were briefly introduced, and present
researches and applications of them in hydrology were summarized and reviewed from six …

This paper introduces Prec‐DWARF (Precipitation Downscaling With Adaptable Random
Forests), a novel machine‐learning based method for statistical downscaling of precipitation …

This contribution provides a review of the most recent wavelet applications in the field of
earth sciences and is devoted to introducing and illustrating new wavelet analysis methods …

An ensemble‐based probabilistic precipitation forecasting scheme has been developed that
blends an extrapolation nowcast with a downscaled NWP forecast, known as STEPS: Short …

The wavelet variance decomposes the variance of a time series into components associated
with different scales. We consider two estimators of the wavelet variance: the first based …

Karstic watersheds appear as highly non-linear and non-stationary systems. The main focus
of this paper is a heuristic study of this non-stationarity using a time-scale localisation …

Applications of wavelet analysis to the geophysical sciences grew from Jean Morlet's work
on seismic signals in the 1980s. Used to detect signals against noise, wavelet analysis …

An exploration of the wavelet transform as applied to daily river discharge records
demonstrates its strong potential for quantifying stream flow variability. Both periodic and …

A space‐time multifractal analysis on radar rainfall sequences selected from the Global
Atmospheric Research Program Atlantic Tropical Experiment database is presented. It is …