Editorial board

Editors of this journal work on a purely voluntary basis without remuneration in line with the not-for-profit philosophy of the EGU.
Executive editors

Christian Franzke

Pusan National University
Center for Climate Physics, Institute for Basic Science
Climate System
Korea, Republic Of

Subject areas

Subject areas

Time series, machine learning, networks, stochastic processes, extreme events

Ana M. Mancho

Consejo Superior de Investigaciones Científicas
ICMAT
Spain

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation

Daniel Schertzer

Ecole des Ponts ParisTech
Hydrology Meteorology and Complexity (HM&Co)
France

Subject areas

Subject areas

Scaling, multifractals, turbulence, complex systems, self-organized criticality

Olivier Talagrand

École Normale Supérieure
Géosciences, Laboratoire de Météorologie Dynamique
France

Subject areas

Subject areas

Predictability, probabilistic forecasts, data assimilation, inverse problems

Stéphane Vannitsem

Royal Meteorological Institute of Belgium
Meteorological and Climatological Information Service
Belgium

Subject areas

Subject areas

Time series, machine learning, networks, stochastic processes, extreme events
Editors

Amit Apte

Indian Institute of Science Education and Research, Pune
Data Science
India

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

Rudy Calif

Université des Antilles
UFR SEN
Physics
France

Subject areas

Subject areas

Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Vincenzo Carbone

Università della Calabria
Dipartimento di Fisica
Italy

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Scaling, multifractals, turbulence, complex systems, self-organized criticality

Natale Alberto Carrassi

University of Bologna
Department of Physics
Italy

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems

Mickael D. Chekroun

UCLA
Department of Atmospheric and Oceanic Sciences
United States

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Time series, machine learning, networks, stochastic processes, extreme events

Jezabel Curbelo

Universitat Politècnica de Catalunya
Departament de Matemàtiques
Spain

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Scaling, multifractals, turbulence, complex systems, self-organized criticality

Reik Donner

Magdeburg-Stendal University of Applied Sciences
Water, Environment, Construction & Safety
Germany

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Jinqiao Duan

Illinois Institute of Technology
College of Computing
Department of Applied Mathematics
United States

Subject areas

Subject areas

Predictability, probabilistic forecasts, data assimilation, inverse problems
Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Wansuo Duan

Institute of Atmospheric Physics, Chinese Academy of Sciences
LASG
China

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

Jie Feng

Fudan
Department of Atmospheric and Oceanic Sciences
China

Subject areas

Subject areas

Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

Harindra Joseph Fernando

University of Notre Dame
Department of Civil Engineering and Geological Sciences
United States

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Scaling, multifractals, turbulence, complex systems, self-organized criticality

Ulrike Feudel

University of Oldenburg
Institute for Chemistry and Biology of the Marine Environment
Germany

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Scaling, multifractals, turbulence, complex systems, self-organized criticality

Christian Franzke

Pusan National University
Center for Climate Physics, Institute for Basic Science
Climate System
Korea, Republic Of

Subject areas

Subject areas

Predictability, probabilistic forecasts, data assimilation, inverse problems
Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Behzad Ghanbarian

Kansas State University
Geology Department
United States

Subject areas

Subject areas

Scaling, multifractals, turbulence, complex systems, self-organized criticality

Richard Gloaguen

Helmholtz Institute Freiberg for Resource Technology
Exploration
Germany

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

Allen G. Hunt

Wright State University
Physics and Earth & Environmental Sciences
United States

Subject areas

Subject areas

Scaling, multifractals, turbulence, complex systems, self-organized criticality

Jürgen Kurths

Potsdam Institute for Climate Impact Research
Germany

Subject areas

Subject areas

Time series, machine learning, networks, stochastic processes, extreme events

Giovanni Lapenta

KU Leuven
Center for Mathematical Plasma Astrophysics
Wiskunde
Belgium

Subject areas

Subject areas

Predictability, probabilistic forecasts, data assimilation, inverse problems
Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Shaun Lovejoy

McGill University
Department of Physics
Canada

Subject areas

Subject areas

Predictability, probabilistic forecasts, data assimilation, inverse problems
Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Ana M. Mancho

Consejo Superior de Investigaciones Científicas
ICMAT
Spain

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Scaling, multifractals, turbulence, complex systems, self-organized criticality

Norbert Marwan

Potsdam Institute for Climate Impact Research
Complexity Science
Germany

Subject areas

Subject areas

Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

Takemasa Miyoshi

Japan

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

Juan M Restrepo

Oak Ridge National Laboratory
Mathematics in Computation
United States

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems

Balasubramanya Nadiga

Los Alamos National Laboratory
United States

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

William I. Newman

University of California
Department of Earth and Space Sciences
United States

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Scaling, multifractals, turbulence, complex systems, self-organized criticality

Joachim Peinke

Carl-von-Ossietzky University Oldenburg
Institute of Physics and ForWind - Center for Wind Energy Research
Germany

Subject areas

Subject areas

Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Vicente Perez-Munuzuri

University of Santiago de Compostela
Physics
Spain

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

Stefano Pierini

Università di Napoli Parthenope
Dipartimento di Scienze e Tecnologie
Italy

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Kira Rehfeld

University of Tübingen
Geo- and Environmental Research Center
Department of Geoscience
Germany

Subject areas

Subject areas

Time series, machine learning, networks, stochastic processes, extreme events

Irina I. Rypina

United States

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation

Adarsh Sankaran

APJ Abdul Kalam Technological University
TKM College of Engineering Kollam
Civil Engineering
India

Subject areas

Subject areas

Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Victor Shrira

Keele University
School of Computing andf Mathematics
United Kingdom

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Scaling, multifractals, turbulence, complex systems, self-organized criticality

Olivier Talagrand

École Normale Supérieure
Géosciences, Laboratoire de Météorologie Dynamique
France

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

Pierre Tandeo

IMT Atlantique
Mathematical and Electrical Engineering Department
France

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

Ioulia Tchiguirinskaia

Ecole des Ponts ParisTech, HM&Co
France

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Luciano Telesca

National Research Council
Institute of Methodologies for Environmental Analysis
Italy

Subject areas

Subject areas

Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Zoltan Toth

NOAA Research
Global Systems Laboratory
United States

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events

Bruce Tsurutani

Pasadena Associates
Heliospheric Physics
United States

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Scaling, multifractals, turbulence, complex systems, self-organized criticality
Time series, machine learning, networks, stochastic processes, extreme events

Stéphane Vannitsem

Royal Meteorological Institute of Belgium
Meteorological and Climatological Information Service
Belgium

Subject areas

Subject areas

Bifurcation, dynamical systems, chaos, phase transition, nonlinear waves, pattern formation
Predictability, probabilistic forecasts, data assimilation, inverse problems
Time series, machine learning, networks, stochastic processes, extreme events