Abstract submition until 30th of September 2026
Invited Gests
Francisco Taveira Pinto (FEUP)
Roger Randriamampianina ( Norwegian Meteorological Institute,NO)
Program
In this third workshop on Numerical Weather Prediction in Portugal, abstract submission should focus primarily on the main subjects, but other relevant contributions will be considered.
Subjects
Atmospheric/ocean and land observations and their applications
Advances and challenges in applying data from various observation platforms to evaluate and improve high-resolution simulations and forecasting.
Wind Power Generation Modeling
Wind power generation forecasting analysis. Wind forecasting at altitude, generation ramps. Modeling of onshore and offshore wind farm productivity.
Solar Power Generation Modeling
Irradiance and solar power forecasting analysis. Cloudiness, aerosols, and their propagation in high-resolution models for photovoltaic forecasting.
Hydro Power Generation Modeling
Hydro generation productivity forecasting analysis. Floods, droughts, and their impact on generation and grid resilience.
Ocean Energy Generation Modeling
Electricity generation productivity forecasting analysis using tides, waves, and currents.
Model validation
Verification of model physics and forecast against observations. Ensemble of forecasts or climate change projections, including strategies in ensemble construction
High-resolution dynamic modeling from mesoscale to convective permitting scales
Forecasting and simulating high impact weather/climate events over the ocean and land, including urban areas. Research on high resolution simulations of severe weather events, such as winter storms and severe mesoscale convective storms and droughts.
Wildfire modeling and analysis
Research on wildfire spread, fire induced atmospheric phenomena. Wildfire modeling.
Statistical and artificial intelligence methods.
Research on using advanced artificial intelligence and machine learning techniques to improve numerical weather model prediction of severe weather events over the earth's surface, from the ocean to rural and urban landscapes. Including Digital Twins projects and emerging technologies like machine learning for short term forecasts to climate projections.
Abstract format
The abstract should not be greater than one page and should be submitted as pdf or docx
The name of the author which will present should be underlined and in bold
The abstract can be written in English or Portuguese
Location:
Biblioteca do Instituto Dom Luiz
Faculdade de Ciências da Universidade de Lisboa
Edifício C1, piso 1