GEOF321 covers the construction and application of modern models for numerical weather forecasting and climate prediction, including data assimilation, verification and ensemble prediction. In the first part, the elements of numerical models for weather and climate prediction are explained and guidance for their interpretation is given. Weaknesses and caveats associated with numerical schemes, model grid, parameterised processes, boundary and initial conditions are explored and discussed in relation to constraints in operational forecasting. In the second part, the course covers common verification methods, data assimilation procedures, aspects of predictability, and ensemble forecasting.

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student

• knows about the construction of numerical weather prediction and climate models
• knows about the history of numerical weather prediction and climate modelling
• knows common parameterisation schemes for the calculation of turbulent fluxes, cloud properties and moist convection
• knows the concepts of data assimilation, predictability and ensemble forecasting
• knows the numerical, computational and conceptual limitations of numerical weather prediction models
• know the procedures and challenges of operational forecasting

Skills

The student

• can assess uncertainties of weather forecasts
• can relate model uncertainties to relevant atmospheric processes
• can display and analyse numerical weather prediction model output using different software products and programming languages
• can apply common forecast verification methods
• can interpret results from deterministic and ensemble prediction systems

General competence

The student

• is able to prepare basic short and medium-range weather forecasts
• is able to analyse and discuss strategies for improving a forecasting system
• is able to evaluate strategies for numerical weather prediction in an operational context

2 lectures à 2 hours per week

1 exercise à 2 hours per week

2 group discussions