Alberto Carrassi

Alberto Carrassi

University of Reading

H-index: 28

Europe-United Kingdom

About Alberto Carrassi

Alberto Carrassi, With an exceptional h-index of 28 and a recent h-index of 24 (since 2020), a distinguished researcher at University of Reading, specializes in the field of Data assimilation, Dynamical Systems, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

A data-driven sea-ice model with generative deep learning

Investigating ecosystem connections in the shelf sea environment using complex networks

Generative diffusion for regional surrogate models from sea-ice simulations

Parameter sensitivity analysis of a sea ice melt pond parametrisation and its emulation using neural networks

Multivariate state and parameter estimation using data assimilation in a Maxwell-Elasto-Brittle sea ice model

Replacing parametrisations of melt ponds on sea ice with machine learning emulators

Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review

Tailoring data assimilation to discontinuous Galerkin models

Alberto Carrassi Information

University

Position

and University of Utrecht

Citations(all)

2629

Citations(since 2020)

2062

Cited By

1276

hIndex(all)

28

hIndex(since 2020)

24

i10Index(all)

47

i10Index(since 2020)

39

Email

University Profile Page

University of Reading

Google Scholar

View Google Scholar Profile

Alberto Carrassi Skills & Research Interests

Data assimilation

Dynamical Systems

Machine Learning

Top articles of Alberto Carrassi

Title

Journal

Author(s)

Publication Date

A data-driven sea-ice model with generative deep learning

Tobias Sebastian Finn

Charlotte Durand

Flavia Porro

Alban Farchi

Marc Bocquet

...

2024/3/7

Investigating ecosystem connections in the shelf sea environment using complex networks

Biogeosciences

Ieuan Higgs

Jozef Skákala

Ross Bannister

Alberto Carrassi

Stefano Ciavatta

2024/2/8

Generative diffusion for regional surrogate models from sea-ice simulations

Tobias Sebastian Finn

Charlotte Durand

Alban Farchi

Marc Bocquet

Pierre Rampal

...

2024/4/23

Parameter sensitivity analysis of a sea ice melt pond parametrisation and its emulation using neural networks

Journal of Computational Science

Simon Driscoll

Alberto Carrassi

Julien Brajard

Laurent Bertino

Marc Bocquet

...

2024/3/16

Multivariate state and parameter estimation using data assimilation in a Maxwell-Elasto-Brittle sea ice model

Yumeng Chen

Polly Smith

Alberto Carrassi

Ivo Pasmans

Laurent Bertino

...

2024/3/7

Replacing parametrisations of melt ponds on sea ice with machine learning emulators

Simon Driscoll

Alberto Carrassi

Julien Brajard

Laurent Bertino

Marc Bocquet

...

2024/3/7

Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review

Sibo Cheng

César Quilodrán-Casas

Said Ouala

Alban Farchi

Che Liu

...

2023/5/31

Tailoring data assimilation to discontinuous Galerkin models

arXiv preprint arXiv:2305.02950

Ivo Pasmans

Yumeng Chen

Alberto Carrassi

Chris KRT Jones

2023/5/4

Assimilation of Sentinel-1 backscatter into a land surface model with river routing and its impact on streamflow simulations in two Belgian catchments

Journal of Hydrometeorology

Michel Bechtold

Sara Modanesi

Hans Lievens

Pierre Baguis

Isis Brangers

...

2023/12

Arctic sea ice data assimilation combining an ensemble Kalman filter with a novel Lagrangian sea ice model for the winter 2019–2020

The Cryosphere

Sukun Cheng

Yumeng Chen

Ali Aydoğdu

Laurent Bertino

Alberto Carrassi

...

2023/4/25

Multivariate state and parameter estimation with data assimilation on sea-ice models using a Maxwell-Elasto-Brittle rheology

EGUsphere

Yumeng Chen

Polly Smith

Alberto Carrassi

Ivo Pasmans

Laurent Bertino

...

2023/10/16

Ecosystem connections in the shelf sea environment using complex networks

EGUsphere

Ieuan Higgs

Jozef Skákala

Ross Bannister

Alberto Carrassi

Stefano Ciavatta

2023/4/17

Supermodeling: improving predictions with an ensemble of interacting models

Bulletin of the American Meteorological Society

Francine Schevenhoven

Noel Keenlyside

François Counillon

Alberto Carrassi

William E Chapman

...

2023/9

Supervised machine learning to estimate instabilities in chaotic systems: estimation of local Lyapunov exponents

Quarterly Journal of the Royal Meteorological Society

Daniel Ayers

Jack Lau

Javier Amezcua

Alberto Carrassi

Varun Ojha

2023/4

Deep learning subgrid-scale parametrisations for short-term forecasting of sea-ice dynamics with a Maxwell elasto-brittle rheology

The Cryosphere

Tobias Sebastian Finn

Charlotte Durand

Alban Farchi

Marc Bocquet

Yumeng Chen

...

2023/7/21

Data assimilation for chaotic dynamics

Alberto Carrassi

Marc Bocquet

Jonathan Demaeyer

Colin Grudzien

Patrick Raanes

...

2022

Dynamical effects of inflation in ensemble‐based data assimilation under the presence of model error

Quarterly Journal of the Royal Meteorological Society

Guillermo Scheffler

Alberto Carrassi

Juan Ruiz

Manuel Pulido

2022/7

Improving streamflow simulation by assimilating Sentinel-1 backscatter into a land surface model with river routing

Michel Bechtold

Sara Modanesi

Hans Lievens

Pierre Baguis

Isis Brangers

...

2022/12/2

Training a supermodel with noisy and sparse observations: a case study with CPT and the synch rule on SPEEDO–v. 1

Geoscientific Model Development

Francine Schevenhoven

Alberto Carrassi

2022/5/12

Sensitivity Analysis and Machine Learning of a Sea Ice Melt Pond Parametrisation

AGU Fall Meeting Abstracts

Simon Driscoll

Alberto Carrassi

Marc Bocquet

Laurent Bertino

Julien Brajard

...

2022/12

See List of Professors in Alberto Carrassi University(University of Reading)

Co-Authors

H-index: 87
Michael Ghil

Michael Ghil

University of California, Los Angeles

H-index: 79
Eugenia Kalnay

Eugenia Kalnay

University of Maryland, Baltimore

H-index: 50
Marc Bocquet

Marc Bocquet

École des Ponts ParisTech

H-index: 6
Colin James Grudzien

Colin James Grudzien

University of Nevada, Reno

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