Publications associées à Assimilation de données

Good enough: Intermediate complexity atmospheric models improve the representation of processes affecting seasonal snow

Snow plays a crucial role in processes regulating ecosystems, the climate, and human development. Mountain snowpack in particular has great relevance for downstream communities. Knowledge about the distribution and properties of the snowpack thus help in p ...

EPFL2024

Spatiotemporal Dynamics of Flow and Hydrochemistry in Drainage Networks

Izabela Bujak-Ozga

Despite their high ecological value, non-perennial streams have received less attention than their perennial counterparts. This doctoral thesis addresses this disparity by advancing knowledge on the dynamics of the drainage density and hydrologic processes ...

EPFL2024

Machine Learning Security Against Data Poisoning: Are We There Yet?

Kathrin Grosse

Poisoning attacks compromise the training data utilized to train machine learning (ML) models, diminishing their overall performance, manipulating predictions on specific test samples, and implanting backdoors. This article thoughtfully explores these atta ...

Ieee Computer Soc2024

Assessing the simulation of snowfall at Dumont d'Urville, Antarctica, during the YOPP-SH special observing campaign

Alexis Berne, Etienne Gabriel Henri Vignon

The performance of a set of atmospheric models and meteorological reanalyses in the representation of precipitation days in Antarctica is assessed using ground-based observations such as a precipitation gauge and a Micro Rain Radar during the Year Of Polar ...

WILEY2023

Combining Weather Station Data and Short-Term LiDAR Deployment to Estimate Wind Energy Potential with Machine Learning: A Case Study from the Swiss Alps

Michael Lehning, Wolf Hendrik Huwald, Jérôme François Sylvain Dujardin, Franziska Gerber, Fanny Kristianti

Wind energy potential in complex terrain is still poorly understood and difficult to quantify. With Switzerland’s current efforts to shift to renewable energy resources, it is now becoming even more crucial to investigate the hidden potential of wind energ ...

2023

Evaluation of 30 urban land surface models in the Urban-PLUMBER project: Phase 1 results

Gabriele Manoli, Matthias Roth

Accurately predicting weather and climate in cities is critical for safeguarding human health and strengthening urban resilience. Multimodel evaluations can lead to model improvements; however, there have been no major intercomparisons of urban-focussed la ...

Wiley2023

An evaluation of new particle formation events in Helsinki during a Baltic Sea cyanobacterial summer bloom

Lubna Dada, Marjan Marbouti

Several studies have investigated new particle formation (NPF) events from various sites ranging from pristine locations, including forest sites, to urban areas. However, there is still a dearth of studies investigating NPF processes and subsequent aerosol ...

Copernicus GmbH2022

A Bayesian data assimilation framework for lake 3D hydrodynamic models with a physics-preserving particle filtering method using SPUX-MITgcm v1

Damien Bouffard, Camille Roland Marie Minaudo, Cintia Luz Ramon Casanas, Firat Ozdemir

We present a Bayesian inference for a three-dimensional hydrodynamic model of Lake Geneva with stochastic weather forcing and high-frequency observational datasets. This is achieved by coupling a Bayesian inference package, SPUX, with a hydrodynamics packa ...

COPERNICUS GESELLSCHAFT MBH2022

Reinforcement Learning for the occupant-centric operation of building energy systems: Theoretical and experimental investigations

Amirreza Heidari

Occupant behavior, defined as the presence and energy-related actions of occupants, is today known as a key driver of building energy use. Closing the gap between what is provided by building energy systems and what is actually needed by occupants requires ...

EPFL2022

Learning Decoupled Representations for Human Pose Forecasting

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan, Yuejiang Liu, Behnam Parsaeifard

Human pose forecasting involves complex spatiotemporal interactions between body parts (e.g., arms, legs, spine). State-of-the-art approaches use Long Short-Term Memories (LSTMs) or Variational AutoEncoders (VAEs) to solve the problem. Yet, they do not eff ...

IEEE2021