Syllabus

Module 1:
Atmospheric Observations Basic observational methods, Upper air observations, Surface synoptic observations, Weather Radars, Satellites and Synoptic charts, Analysis of surface and upper-air charts, Station models. [Duration: 6 hours]

Module 2:
Basics of weather models Physical and analytic modelling, Overview of numerical weather prediction, Different spatial and temporal scales in NWP, Basic structure of numerical models and their applications, Basic set of equations used in mesoscale models, Map projections, Horizontal and vertical coordinate system Global models, Regional models, Mesoscale models, Hydrostatic & non-hydrostatic assumption. [Duration: 6 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: 8 hours]

Module 4: Data assimilation initial and boundary conditions Model evaluation Examples of mesoscale models. Data assimilation: Objective analysis schemes, continuous data assimilation techniques - 3D & 4D Variational assimilation initialization. Predictability and Ensemble forecasting.[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]

Educate the students for concept of climate and role of different physics and dynamics for climate forecast.

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.

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 Students are trained for understanding and solving the fundamental equations.
C02 Structure of a numerical model and different components of numerical model
CO3 Students are trained for different energy balance models and 3D climate models, etc.
CO4 Familiarisation of atmospheric observations and concept of objective analysis and data assimilation
CO5 Different types of parameterization schemes that control numerical models performance

James R. Holton, An introduction to dynamic meteorology, Academic Press , Fifth Edition, 201

Roger A. Pielke Sr, Mesoscale meteorological modeling, Academic Press , Second Edition, 2002

Roland Stull, Meteorology (for scientists and engineers), Brooks/Cole Thomson Learning , Second edition, 2000

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