Events

Tropical cyclones (TCs) are among the most devastating weather phenomena on Earth, frequently causing numerous fatalities and leading to extensive and costly damage. Effective evacuation planning and the implementation of precautionary measures depend on forecasts that are both highly accurate and available with sufficient lead time. Furthermore, TCs are of particular interest to operational forecasting centres, as they are characterized by extreme deviations from the mean atmospheric state. As such, they pose a significant challenge to numerical weather prediction systems and serve as a rigorous stress test for any forecasting model, making their evaluation a key focus area.
 
While speculation persisted until not long ago that the predictability limit for TC track forecasts had been reached, dedicated research efforts were launched to pool resources and advance intensity forecasts in physics-based models. With the advent of data-driven weather forecasting, however, previously assumed forecast limits have been exceeded in certain aspects of TC prediction, while others have deteriorated. Current model developments aim to fuse both worlds into a hybrid modelling approach, which has shown promising results.
 
In this presentation, I will give an overview of the latest research and developments in TC forecasting with ECWMF’s physics-based and data-driven models.

Results from PhD Thesis
 

This presentation explores how CO₂ fluxes can be inferred from the atmospheric perspective. Both biogenic and anthropogenic fluxes cause measurable signals in CO2 concentration, which can be interpreted using atmospheric transport models. Across continental regions, satellite observations capture broad atmospheric signatures of ecosystem activity. When interpreted with vegetation models, these signals reveal how carbon-water dynamics shape biogenic fluxes. The same principle applies in cities, but at much finer scales: dense sensor networks can record urban enhancements that high-resolution models translate into spatially resolved emissions. The presentation covers optimal sensor network design and first results from the mid-cost CO₂ network in Heidelberg–Mannheim. The results demonstrate how atmospheric signals can be translated into estimates of both biogenic and urban emissions.

(1) The contribution of haboobs to the dust direct radiative effect (2) Doppler Lidar Volume Flux Observations in a Broad Alpine Valley (3) Singular Vectors in data-driven NWP models (4) Lightning Characteristics Along Radar-detected Hail Tracks

(1) Sensitivity of weather forecasts in tropical Africa to available observations – an idealized study using the TEEMLEAP testbed (2) tbd (3) tbd (4) tbd

TBD

(1) Data management topics (2) tbd (3) EnVar Data Assimilation for ICON-LAM (4) tbd

In mid-latitudes, almost every raindrop that reaches the surface, starts as an ice particle in the cloud aloft. Ice microphysical processes are thus key for realistically forecasting the evolution of clouds and precipitation. Besides in-situ observations and laboratory experiments, remote sensing methods, such as modern cloud radars, provide a wealth of information about processes, such as aggregation, riming, and secondary ice production. This talk will provide a compact overview of the measurement principles and application examples of how we can use cloud radars in combination with modern modelling tools to improve our understanding of ice microphysical processes in clouds.

TBD

tbd

(1) tbd (2) Idealized Urban Simulations in ICON-CLM (3) Interplay of orography, aerosol concentration and secondary ice formation in contrasting island environments (4) tbd

(1) tbd (2) Assessing the representation of tropical-extratropical teleconnections in machine learning (ML) and numerical weather prediction (NWP) models for improving the S2S forecast skill (3) Coupling MieAI with RTTOV: Enhancing Radiative Transfer Simulations with AI-Derived Aerosol Properties (4) tbd