Peter Dueben
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View article: Comment on egusphere-2025-1829
Comment on egusphere-2025-1829 Open
View article: Implementing digital twin technology of the earth system in Destination Earth
Implementing digital twin technology of the earth system in Destination Earth Open
View article: Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4 Open
We report on the first multi-year kilometre-scale global coupled simulations using ECMWF's Integrated Forecasting System (IFS) coupled to both the NEMO and FESOM ocean–sea ice models, as part of the H2020 Next Generation Earth Modelling Sy…
View article: AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score
AIFS-CRPS: Ensemble forecasting using a model trained with a loss function based on the Continuous Ranked Probability Score Open
Over the last three decades, ensemble forecasts have become an integral part of forecasting the weather. They provide users with more complete information than single forecasts as they permit to estimate the probability of weather events b…
View article: The hectometric modelling challenge: Gaps in the current state of the art and ways forward towards the implementation of 100‐m scale weather and climate models
The hectometric modelling challenge: Gaps in the current state of the art and ways forward towards the implementation of 100‐m scale weather and climate models Open
For a number of years research has been carried out in several centres which has demonstrated the potential benefits of 100‐m scale models for a range of meteorological phenomena. More recently, some meteorological services have started to…
View article: Optimising orography for global high-resolution simulations
Optimising orography for global high-resolution simulations Open
The model’s mean orography acts as the boundary condition for the model dynamics and the drag from resolved orographic gravity waves can have a significant impact on the large-scale atmospheric circulation in weather and climate mode…
View article: Comment on egusphere-2024-913
Comment on egusphere-2024-913 Open
Abstract. We report on the first multi-year km-scale global coupled simulations using ECMWF’s Integrated Forecasting System (IFS) coupled to both the NEMO and FESOM ocean-sea ice models, as part of the Horizon 2020 Next Ge…
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: WeatherBench 2: A Benchmark for the Next Generation of Data‐Driven Global Weather Models
WeatherBench 2: A Benchmark for the Next Generation of Data‐Driven Global Weather Models Open
WeatherBench 2 is an update to the global, medium‐range (1–14 days) weather forecasting benchmark proposed by (Rasp et al., 2020, https://doi.org/10.1029/2020ms002203 ), designed with the aim to accelerate progress in data‐driven weather m…
View article: Comment on egusphere-2024-913
Comment on egusphere-2024-913 Open
Abstract. We report on the first multi-year km-scale global coupled simulations using ECMWF’s Integrated Forecasting System (IFS) coupled to both the NEMO and FESOM ocean-sea ice models, as part of the Horizon 2020 Next Ge…
View article: Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5/NEMOv3.4
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5/NEMOv3.4 Open
We report on the first multi-year km-scale global coupled simulations using ECMWF’s Integrated Forecasting System (IFS) coupled to both the NEMO and FESOM ocean-sea ice models, as part of the Horizon 2020 Next Generation Earth Modelling Sy…
View article: The Global Extremes Digital Twin of Destination Earth: successes and challenges
The Global Extremes Digital Twin of Destination Earth: successes and challenges Open
At the end of the first phase of the Destination Earth initiative in May 2024, ECMWF will deliver a prototype of the global component of the Weather-Induced Extremes Digital Twin (or Global Extremes DT). The Global Extremes DT will monitor…
View article: Towards a global km-scale flood forecasting system
Towards a global km-scale flood forecasting system Open
River discharge has direct influence on the water-food-energy-environment nexus and can have devastating impacts during extreme events with rapid onsets such as floods. Floods often occur after extreme precipitation events, which are chall…
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: The Rise of Data-Driven Weather Forecasting: A First Statistical Assessment of Machine Learning–Based Weather Forecasts in an Operational-Like Context
The Rise of Data-Driven Weather Forecasting: A First Statistical Assessment of Machine Learning–Based Weather Forecasts in an Operational-Like Context Open
Data-driven modeling based on machine learning (ML) is showing enormous potential for weather forecasting. Rapid progress has been made with impressive results for some applications. The uptake of ML methods could be a game changer for the…
View article: DiffDA: a Diffusion Model for Weather-scale Data Assimilation
DiffDA: a Diffusion Model for Weather-scale Data Assimilation Open
The generation of initial conditions via accurate data assimilation is crucial for weather forecasting and climate modeling. We propose DiffDA as a denoising diffusion model capable of assimilating atmospheric variables using predicted sta…
View article: Deep learning for quality control of surface physiographic fields using satellite Earth observations
Deep learning for quality control of surface physiographic fields using satellite Earth observations Open
A purposely built deep learning algorithm for the Verification of Earth System ParametERization (VESPER) is used to assess recent upgrades to the global physiographic datasets underpinning the quality of the Integrated Forecasting System (…
View article: Computing the ecRad radiation scheme with half-precision arithmetic
Computing the ecRad radiation scheme with half-precision arithmetic Open
Numerical simulations of weather and climate models are conventionally carried out using double-precision floating-point numbers throughout the vast majority of the code. At the same time, the urgent need of high-resolution forecasts given…
View article: WeatherBench 2: A benchmark for the next generation of data-driven global weather models
WeatherBench 2: A benchmark for the next generation of data-driven global weather models Open
WeatherBench 2 is an update to the global, medium-range (1-14 day) weather forecasting benchmark proposed by Rasp et al. (2020), designed with the aim to accelerate progress in data-driven weather modeling. WeatherBench 2 consists of an op…
View article: The rise of data-driven weather forecasting
The rise of data-driven weather forecasting Open
Data-driven modeling based on machine learning (ML) is showing enormous potential for weather forecasting. Rapid progress has been made with impressive results for some applications. The uptake of ML methods could be a game-changer for the…
View article: Scalability on pre-exascale EuroHPC systems - Deliverable D1.3
Scalability on pre-exascale EuroHPC systems - Deliverable D1.3 Open
The central objectives of Work Package 1 of ESiWACE2 is to develop and run coupled model simulations at a resolution as high as possible and with a throughput rate of at least one simulated year per day (1 SYPD) producing full model output…
View article: Improving medium-range ensemble weather forecasts with hierarchical ensemble transformers
Improving medium-range ensemble weather forecasts with hierarchical ensemble transformers Open
Statistical post-processing of global ensemble weather forecasts is revisited by leveraging recent developments in machine learning. Verification of past forecasts is exploited to learn systematic deficiencies of numerical weather predicti…
View article: Scalability on pre-exascale EuroHPC systems - Deliverable D1.3
Scalability on pre-exascale EuroHPC systems - Deliverable D1.3 Open
The central objectives of Work Package 1 of ESiWACE2 is to develop and run coupled model simulations at a resolution as high as possible and with a throughput rate of at least one simulated year per day (1 SYPD) producing full model output…
View article: Recent progress and outlook for the ECMWF Integrated Forecasting System
Recent progress and outlook for the ECMWF Integrated Forecasting System Open
ECMWF recent improvements on scientific and technological fronts will be presented. In 2021 two new operational upgrades of the Integrated Forecasting System (IFS), cycles 47r2 and 47r3, have been introduced. In 2022 the ECMWF Hi…
View article: Deep Learning for Verification of Earth's surfaces
Deep Learning for Verification of Earth's surfaces Open
Ever increasing computing capabilities and crave for high-resolution numerical weather prediction and climate information are specially interesting for the representation of Earth surfaces. Knowledge of accurate and up-to-date surface stat…
View article: Emulating radiative transfer in a numerical weather prediction model
Emulating radiative transfer in a numerical weather prediction model Open
Machine learning, and particularly neural networks, have been touted as a valuable accelerator for physical processes. By training on data generated from an existing algorithm a network may theoretically learn a more efficient representati…
View article: Comment on egusphere-2022-1177
Comment on egusphere-2022-1177 Open
Abstract. About 2/3 of all densely populated areas (i.e. at least 300 inhabitants per km2) around the globe are situated within a 9 km radius of a permanent waterbody (i.e. inland water or sea/ocean coast), sinc…
View article: Comment on egusphere-2022-1177
Comment on egusphere-2022-1177 Open
Abstract. About 2/3 of all densely populated areas (i.e. at least 300 inhabitants per km2) around the globe are situated within a 9 km radius of a permanent waterbody (i.e. inland water or sea/ocean coast), sinc…
View article: Comment on egusphere-2022-1177
Comment on egusphere-2022-1177 Open
Abstract. About 2/3 of all densely populated areas (i.e. at least 300 inhabitants per km2) around the globe are situated within a 9 km radius of a permanent waterbody (i.e. inland water or sea/ocean coast), sinc…
View article: Deep Learning for Verification of Earth-System Parametrisation of Water Bodies
Deep Learning for Verification of Earth-System Parametrisation of Water Bodies Open
About 2/3 of all densely populated areas (i.e. at least 300 inhabitants per km2) around the globe are situated within a 9 km radius of a permanent waterbody (i.e. inland water or sea/ocean coast), since inland water sustains the vast major…