Syllabus

Module 1:
Basics of weather models Different spatial and temporal scales in NWP, Basic structure of numerical models and their applications, Governing equations, Map projections, Vertical coordinate system Global models, Regional models, Mesoscale models, Hydrostatic & non-hydrostatic assumption. [Duration: 6 hours]

Module 2:
Data assimilation Basic observational methods, Upper air observations, Surface synoptic observations, Weather Radars, Satellites and Synoptic charts, Analysis of surface and upper-air charts, Station models. Objective analysis schemes, data assimilation techniques, Initialization, Predictability and Ensemble forecasting. [Duration: 8 hours]

Module 3: Numerical Solutions Finite difference method-Forward and centered finite difference methods, Semi – implicit method and computational instability Computation of Jacobian and Laplacian Solution of Helmholtz and Poisson equations using relaxation method Spectral method, spherical harmonics [Duration: 6 hours]

Module 4: Atmospheric models Barotropic or Single level primitive model and instability Two level primitive equation model multilevel primitive equation models. Sigma coordinate system [Duration: 8 hours]

Module 5: Parameterization Parameterization of sub-grid scale physical processes: planetary boundary layer, moist microphysics physics, cumulus convection, radiation, air-sea interaction processes, and land surface processes. [Duration: 8 hours]

The course deals with the basic structure of weather models including initial conditions (data assimilation), fundamental equations that represents the dynamics and physical parameterizations, and numerical solutions.

In detail, it educates model details such as map projections, vertical coordinate systems, etc types of observations, instrumentation and different objective analysis techniques to prepare initial conditions.

The application of finite difference methods to solve NWP models is introduced and detailed derivations to understand NWP model stability.

The course delivers hierarchy of atmospheric models starting from single level model to multi-level models and sub-grid scale parameterization that indicates the sole nature of local phenomena.

After the completion of the course, the students will be able
CO1 Structure of a numerical model and different components of numerical model
C02 Current status of atmospheric observations and concept of objective analysis and data assimilation
CO3 Provides detailed understanding of numerical solutions of atmospheric models and their stability
CO4 Familiarisation of hierarchy of atmospheric models starting from single level model to multi-level models
CO5 Different types of parameterization schemes that control numerical models performance

Holton J. R. and G. J. Hakim, An Introduction to Dynamical Meteorology, Academic Press (ELSEVIER) , Fifth Edition, 2013

Lynch A. H. and and J. J. Cassano, Applied Atmospheric Dynamics, John Wiley and Sons Ltd , 2005

Haltiner G.J., Numerical Weather Prediction,, John Wiley & Sons Inc , 1971

Haltiner G. J. and F.L.Martin, Dynamical and Physical Meteorology, McGraw-Hill Publcations , 1957