MET 2104 Numerical Methods in Meteorology (3CU)
Description
This course looks at numerical techniques and their applications to solving different problems
including interpolation, differentiation, integration and their application to numerical weather
prediction.
Objectives
The course will help the students to achieve the following objectives
 Describe the different errors used in measurements
 Understand the concept of finite differences and its applications in numerical techniques
 Describe the different differential equations and their applications to numerical weather
prediction
Learning outcomes
By the end of the course students should be able to:
 Calculate the different errors involved in numerical problems and their propagation
 interpolate different polynomials using numerical techniques
 Use numerical techniques in differentiation and integration.
 Use numerical techniques to solve ordinary and partial differential equations
Intellectual, Practical and transferable skills
 Problem solving
 Analytical
 communication
Teaching and learning patterns
The mode of learning involves direct contact with students in form of lectures, Tutorials and
assignments
Indicative content
 Errors: Errors and their comparatives, absolute, relative and percentage errors.
 Finite and Divided Differences: Finite difference operators, tables and interpolating
polynomials. Divided differences and divided difference interpolating polynomials.
 Numerical Differentiation and Integration:
Taylor series and finite difference
differentiation.
 Numerical Solution of ordinary differential Equations: Taylor Series, Euler’s and Runge
Kutta Methods.
 Numerical techniques for partial differential Equations: Classification of P.D.Es. Finite
difference techniques for parabolic, hyperbolic and elliptic problems. The Crank
Nicolson method.
 Applications to Numerical weather prediction
Assessment Method
The assessment method is structured to include course work, and final examination. Course work
consists of assignments, reports and tests and accounts for 30% of the final grade. The final
examination will account for 70% of the final grading
Core Reference materials


Sastry S.S (2002): Introductory Methods of Numerical Analysis, 3rd Edition Prentice –
Hall.
Richard L. Burden and J. Douglas Faires (2008): Numerical Analysis 8th Edition.,
Thomson Brooks/Cole