TY - JOUR
T1 - Generating a missing half of multifractal fields with a blunt extension of discrete cascades
AU - Gires, Auguste
AU - Tchiguirinskaia, Ioulia
AU - Schertzer, Daniel
N1 - Publisher Copyright:
© 2023 IAHS.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Despite strong limitations, discrete random multiplicative cascades are often used to address scale issues that are ubiquitous in geosciences. A blunt extension based on the parsimonious framework of universal multifractals has recently been suggested. It preserves its simplicity and intuitiveness while overcoming its non-stationarity features. It relies on smoothing through a geometrical moving average the increments at each cascade step. Here, a space-time extension is suggested. Theoretically expected multifractal behaviour is retrieved on numerical simulations for typical rainfall parameters. A new algorithm to generate the missing half of multifractal fields in one, two or three dimensions is developed and tested on rainfall fields and numerical simulations. It consists in stochastically generating half of the increments and deterministically iteratively reconstructing the others to retrieve the available data and ensure a smooth transition with the unknown portion while preserving the multifractal behaviour. Potential applications to nowcasting of hydro-meteorological extremes are discussed.
AB - Despite strong limitations, discrete random multiplicative cascades are often used to address scale issues that are ubiquitous in geosciences. A blunt extension based on the parsimonious framework of universal multifractals has recently been suggested. It preserves its simplicity and intuitiveness while overcoming its non-stationarity features. It relies on smoothing through a geometrical moving average the increments at each cascade step. Here, a space-time extension is suggested. Theoretically expected multifractal behaviour is retrieved on numerical simulations for typical rainfall parameters. A new algorithm to generate the missing half of multifractal fields in one, two or three dimensions is developed and tested on rainfall fields and numerical simulations. It consists in stochastically generating half of the increments and deterministically iteratively reconstructing the others to retrieve the available data and ensure a smooth transition with the unknown portion while preserving the multifractal behaviour. Potential applications to nowcasting of hydro-meteorological extremes are discussed.
KW - discrete random multiplicative cascades
KW - multifractals
KW - nowcasting
KW - rainfall
UR - https://www.scopus.com/pages/publications/85146314164
U2 - 10.1080/02626667.2022.2154160
DO - 10.1080/02626667.2022.2154160
M3 - Article
AN - SCOPUS:85146314164
SN - 0262-6667
VL - 68
SP - 261
EP - 275
JO - Hydrological Sciences Journal
JF - Hydrological Sciences Journal
IS - 2
ER -