Christian Lessig
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View article: RainShift: A Benchmark for Precipitation Downscaling Across Geographies
RainShift: A Benchmark for Precipitation Downscaling Across Geographies Open
Earth System Models (ESM) are our main tool for projecting the impacts of climate change. However, running these models at sufficient resolution for local-scale risk-assessments is not computationally feasible. Deep learning-based super-re…
View article: A GPU parallelization of the neXtSIM-DG dynamical core (v0.3.1)
A GPU parallelization of the neXtSIM-DG dynamical core (v0.3.1) Open
The cryosphere plays a crucial role in the Earth's climate system, making accurate sea-ice simulation essential for improving climate projections. To achieve higher-resolution simulations, graphics processing units (GPUs) have become incre…
View article: RAINA - High-resolution nowcasting of precipitation and wind extremes with a foundation model for the atmosphere
RAINA - High-resolution nowcasting of precipitation and wind extremes with a foundation model for the atmosphere Open
Data-driven weather prediction models based on deep learning have been on the rise for several years and have outperformed traditional physics-based numerical models in various benchmark forecasting scores. However, a significant challenge…
View article: Analysis of optimal atmospheric predictability using machine learning-based forecasting models
Analysis of optimal atmospheric predictability using machine learning-based forecasting models Open
With the development of highly skillful, machine learning-based weather prediction models over the last 2-3 years, many new possibilities have emerged. These include applications, such as downscaling, temporal interpolation, or generating …
View article: OceanRep: A Foundation Model for Ocean Dynamics
OceanRep: A Foundation Model for Ocean Dynamics Open
OceanRep proposes a novel AI foundation model for ocean dynamics, a cornerstone for understanding and predicting climate change. Inspired by the success of AtmoRep, a deep learning model for atmospheric dynamics, OceanRep seeks to extend t…
View article: Towards next generation machine learning-based Earth system models that exploit a wide range of datasets
Towards next generation machine learning-based Earth system models that exploit a wide range of datasets Open
The training of machine learning models for weather and climate on multiple datasets, including local high-resolution reanalyses and level-1 observations, is one of the frontiers of the field. It promises to allow for models that are no lo…
View article: Towards machine learning-based Earth system models
Towards machine learning-based Earth system models Open
Large scale machine learning is currently revolutionizing Earth system modeling and the next generation of models will likely be machine learning-based or contain substantial machine learning components. The lack of a complete equation-bas…
View article: Global Location Transferability of Generative Deep Learning Models for Precipitation Downscaling
Global Location Transferability of Generative Deep Learning Models for Precipitation Downscaling Open
Generative deep learning models have shown remarkable skill in the probabilistic downscaling of climate and weather forecasts, with generative adversarial networks (GANs) as a particularly effective approach for precipitation downscaling. …
View article: Development of a GPU-accelerated, Finite Element based Dynamical Core for Sea Ice
Development of a GPU-accelerated, Finite Element based Dynamical Core for Sea Ice Open
Sea ice is an import part of Earth's climate system. Yet, an accurate, highly resolved simulation of sea ice dynamics remains challenging. As the development of faster processors has slowed down, a turn to more specialized hardware is need…
View article: SIGGRAPH: G: Improved Projective Dynamics Global Using Snapshots-based Reduced Bases
SIGGRAPH: G: Improved Projective Dynamics Global Using Snapshots-based Reduced Bases Open
We propose a snapshots-based method to compute reduction subspaces for physics-based simulations. Our method is applicable to any mesh with some artistic prior knowledge of the solution and only requires a record of existing solutions duri…
View article: ArchesWeather & ArchesWeatherGen: a deterministic and generative model for efficient ML weather forecasting
ArchesWeather & ArchesWeatherGen: a deterministic and generative model for efficient ML weather forecasting Open
Weather forecasting plays a vital role in today's society, from agriculture and logistics to predicting the output of renewable energies, and preparing for extreme weather events. Deep learning weather forecasting models trained with the n…
View article: Robustness of AI-based weather forecasts in a changing climate
Robustness of AI-based weather forecasts in a changing climate Open
Data-driven machine learning models for weather forecasting have made transformational progress in the last 1-2 years, with state-of-the-art ones now outperforming the best physics-based models for a wide range of skill scores. Given the s…
View article: A GPU-parallelization of the neXtSIM-DG dynamical core (v0.3.1)
A GPU-parallelization of the neXtSIM-DG dynamical core (v0.3.1) Open
The cryosphere plays a crucial role in Earth’s climate system, making accurate sea ice simulation essential for improving climate projections. To achieve higher resolution simulations, graphics processing units (GPUs) have become increasin…
View article: Machine Learning for the Physics of Climate
Machine Learning for the Physics of Climate Open
An exponential growth in computing power, which has brought more sophisticated and higher resolution simulations of the climate system, and an exponential increase in observations since the first weather satellite was put in orbit, are rev…
View article: Data driven weather forecasts trained and initialised directly from observations
Data driven weather forecasts trained and initialised directly from observations Open
Skilful Machine Learned weather forecasts have challenged our approach to numerical weather prediction, demonstrating competitive performance compared to traditional physics-based approaches. Data-driven systems have been trained to foreca…
View article: Emerging AI-based weather prediction models as downscaling tools
Emerging AI-based weather prediction models as downscaling tools Open
The demand for high-resolution information on climate change is critical for accurate projections and decision-making. Presently, this need is addressed through high-resolution climate models or downscaling. High-resolution models are comp…
View article: AIFS -- ECMWF's data-driven forecasting system
AIFS -- ECMWF's data-driven forecasting system Open
Machine learning-based weather forecasting models have quickly emerged as a promising methodology for accurate medium-range global weather forecasting. Here, we introduce the Artificial Intelligence Forecasting System (AIFS), a data driven…
View article: ArchesWeather: An efficient AI weather forecasting model at 1.5° resolution
ArchesWeather: An efficient AI weather forecasting model at 1.5° resolution Open
One of the guiding principles for designing AI-based weather forecasting systems is to embed physical constraints as inductive priors in the neural network architecture. A popular prior is locality, where the atmospheric data is processed …
View article: Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core
Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core Open
The cryosphere plays a significant role in Earth's climate system. Therefore, an accurate simulation of sea ice is of great importance to improve climate projections. To enable higher resolution simulations, graphics processing units (GPUs…
View article: An adaptive finite element multigrid solver using GPU acceleration
An adaptive finite element multigrid solver using GPU acceleration Open
Adaptive finite elements combined with geometric multigrid solvers are one of the most efficient numerical methods for problems such as the instationary Navier-Stokes equations. Yet despite their efficiency, computations remain expensive a…
View article: Earth Virtualization Engines (EVE)
Earth Virtualization Engines (EVE) Open
To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all …
View article: Downscaling with the foundation model AtmoRep
Downscaling with the foundation model AtmoRep Open
In recent years, deep neural networks (DNN) to enhance the resolution of meteorological data, known as statistical downscaling, have surpassed classical statistical methods that have been developed previously with respect to several valida…
View article: AIFS – ECMWF’s Data-Driven Probabilistic Forecasting 
AIFS – ECMWF’s Data-Driven Probabilistic Forecasting  Open
In just two years, the idea of an operational data-driven system for medium-range weather forecasting has been transformed from dream to very real possibility. This has occurred through a series of publications from innovators, which have …
View article: Towards a machine learning model for data assimilation and forecasting directly trained from observations
Towards a machine learning model for data assimilation and forecasting directly trained from observations Open
State-of-the-art data assimilation systems, such as the 4DVar system of the European Centre for Medium-Range Weather Forecasts (ECMWF), are highly successful in producing state estimates of the atmosphere constrained by millions of observa…
View article: AtmoRep: large scale representation learning for atmospheric dynamics
AtmoRep: large scale representation learning for atmospheric dynamics Open
The atmosphere affects humans in a multitude of ways, from loss of lives due to adverse weather effects to long-term social and economic impacts. Very recently, AI-based models have shown tremendous potential in reducing the computational …
View article: Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core
Towards a GPU-Parallelization of the neXtSIM-DG Dynamical Core Open
The cryosphere plays a significant role in Earth's climate system. Therefore, an accurate simulation of sea ice is of great importance to improve climate projections. To enable higher resolution simulations, graphics processing units (GPUs…
View article: DNN-MG: A hybrid neural network/finite element method with applications to 3D simulations of the Navier–Stokes equations
DNN-MG: A hybrid neural network/finite element method with applications to 3D simulations of the Navier–Stokes equations Open
We extend and analyze the deep neural network multigrid solver (DNN-MG) for the Navier–Stokes equations in three dimensions. The idea of the method is to augment a finite element simulation on coarse grids with fine scale information obtai…
View article: Comment on essd-2023-376
Comment on essd-2023-376 Open
Abstract. To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines are proposed as international federation of centers of excellence to empo…
View article: Comment on essd-2023-376
Comment on essd-2023-376 Open
Abstract. To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines are proposed as international federation of centers of excellence to empo…
View article: Earth Virtualization Engines (EVE)
Earth Virtualization Engines (EVE) Open
To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines are proposed as international federation of centers of excellence to empower all pe…