Numerical Weather Forecast

Course Information
TitleΑριθμητική Πρόγνωση Καιρού / Numerical Weather Forecast
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter
CoordinatorIoannis Pytharoulis
Course ID40001944

Class Information
Academic Year2017 – 2018
Class PeriodWinter
Weekly Hours2
Total Hours26
Class ID
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction)
General Prerequisites
familiarity on the use of computers
Learning Outcomes
Upon successful completion of this course, students will be able to: 1) Understand the usefulness and the operation of a numerical weather prediction model 2) Design the appropriate numerical experiments/simulations for weather forecast/analysis 3) Write programs in Fortran language for representing the trasport of atmospheric waves / disturbances by applying appropriate numerical methods. 4) Understand and identify the errors of numerical weather prediction models and know the methods of dealing with them
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Work autonomously
Course Content (Syllabus)
Introduction: general characteristics of atmospheric numerical models, historical aspects, applications. Equations: The primitive equations, prognostic and diagnostic equations. Numerical Methods: Round off and truncation errors, finite difference schemes, linear advection equation, diffusion equation, non-linear advection equation, stability, aliasing and non-linear instability, spectral methods, time differencing. Grids: Horizontal grids, horizontal differencing, staggered grids of Arakawa, Gaussian grids, boundary conditions, choice of a grid, nesting (oneway, 2-way), vertical coordinates (sigma, Eta, isentropic), boundary conditions over land/sea surface (land/sea mask, topography, vegetation, land use). Physical parameterizations: Surface energy balance, soil schemes, moisture and heat fluxes in the soil, microphysical schemes, convection schemes, treatment of snow, air/sea interaction, viscous sublayer. Ensemble Weather Prediction: Analyses, operational numerical weather prediction, data assimilation, forecast errors, ensemble foreacasting methods (poor man’s ensemble, LAF, Ensemble Prediction System), singular vectors, available forecast parameters.
Numerical weather prediction, meteorological numerical models, model stability, grids, physical parameterizations, model errors, ensemble weather forecasting
Educational Material Types
  • Notes
  • Slide presentations
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Lectures using Powerpoint and the internet, use of computers and the Fortran language to write programs, contact by email
Course Organization
Laboratory Work60.2
Student Assessment
Written exams, assignments (at home), presentations
Student Assessment methods
  • Written Exam with Short Answer Questions (Formative)
  • Written Assignment (Formative)
  • Written Exam with Problem Solving (Formative)
Additional bibliography for study
“Mesoscale Meteorological Modeling”. Roger Pielke Sr. “Numerical Prediction and Dynamic Meteorology”. G.Haltiner and R.T.Williams “Numerical Recipes in Fortran. The Art of Scientific Computing”. W.H.Press, S.A.Teukolsky, W.T.Vetterling, B.P.Flannery “An Introduction to Dynamic Meteorology”. J.R.Holton
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