As a cornerstone project, the students will develop skills in experimentation, modelling, and data analytics, and will be able to work in teams in association with CAS faculty members.

Summer internship project.

MTech major project part I.

Major project part II for MTech students at CAS.

It's a core major project for MSR students. The students will work under the supervision of faculty members.

Elements of FORTRAN programming; initial and boundary value problems; second order ordinary differential equations, variation of parameters, orthogonal functions; partial differential equations and their classification, method of separation of variables; Euler and Runge-Kutta methods for ODE; spatial and temporal finite differencing schemes of various orders, comparison with exact solutions, accuracy and numerical stability, limitation of finite difference methods; numerical solution of linear advection equation, advection‐diffusion equation, and shallow water equation.

Structure of the atmosphere; hydrostatic equilibrium, geopotential, hypsometric equation and scale height, altimetry; adiabatic processes, lapse rates, static stability, dynamic stability; atmospheric boundary layer structure and evolution, turbulence etc. Atmospheric thermodynamics: thermodynamic laws; thermodynamics of water vapor and moist air: moisture parameters, saturated adiabatic and pseudo adiabatic processes, conditional and convective instability, free and forced convection; thermodynamic diagrams; phase change and Clausius‐Clapeyron equation; clouds: formation and classification, precipitation; atmospheric visibility: dew, frost and fog, smog etc. The fundamental physics of radiation: solar and terrestrial radiation, radiation laws; absorption, emission and scattering in the atmosphere, Schwarzschild’s equation; radiation in the earth‐atmosphere system: geographical and seasonal distribution, radiative heating and cooling of the atmosphere, surface energy budget, energy balance of the earth-atmosphere system.

Fundamental forces; basic laws of conservation; hydrodynamic equations in rotating frame of reference; dimensional analysis; geostrophic and hydrostatic approximations; atmospheric stability; isobaric coordinate system; gradient wind approximation; thermal wind; vertical motion; barotropic and baroclinic atmospheres; circulation and vorticity; vorticity equation; potential vorticity conservation. Boussinesq approximation; Reynolds averaging; mixing length hypothesis; Ekman layer; acoustic, gravity, Poincare, Rossby and kelvin waves. Atmospheric general circulation.

Atmospheric composition and air pollutants, geochemical cycles: evolution of the atmosphere and geochemical cycling of elements, atmospheric photochemistry; chemistry of the troposphere: basic photochemical cycle, atmospheric chemistry dealing with various pollutant species and photochemical smog; oxidising power of the troposphere and the Hydroxyl radical, global budgets of precursor species; stratospheric chemistry and ozone: overview, Chapman mechanism, reservoir species and catalytic cycles, ozone hole and polar stratospheric clouds, arctic ozone loss, ozone depletion potential; aqueous phase atmospheric chemistry and acid rain; atmospheric aerosols: sources and characteristics, radiative effects and perturbation to climate; atmospheric air pollutants: sources, impacts and standards; air pollution meteorology: sources of air pollutants, classification and air quality standards, stability conditions, wind velocity profile, turbulence, mixing depth, characteristics of stack plumes; dispersion of pollutants in the atmosphere: A Gaussian dispersion model, dispersion parameters and effective stack height.

Description of the climate system (general circulation, hydrological cycle, carbon cycle). Natural greenhouse effect and the effect of trace gases and aerosols. Forcings (natural and anthropogenic), fast and slow feedbacks, equilibrium climate sensitivity, transient climate response. Climates of the past (ice ages, proxy records, abrupt climate change, instrumental record of climate). Climate variability and time-scales; Madden-Julian Oscillation (MJO), El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation ( PDO), Milankovic cycles. Modeling climate: simple Energy Balance Models (EBMs), coupled climate models. Natural and anthropogenic climate change. Future climate projections.

Properties of sea water; temperature and salinity distributions; stratification and stability of oceanic water column; equation of state of seawater; oceanic mixed layer processes; governing equations for oceanic motions; inertial and geostrophic currents; wind driven circulation; thermohaline circulation; barotropic and baroclinic transports; western boundary intensification; gyres and mesoscale eddies; gyre systems, major currents in world oceans; Indian ocean circulation; physics and dynamics of ocean wind waves, internal waves and tides; coastal ocean processes; upwelling and downwelling in coastal and equatorial oceans; Rossby and Kelvin waves, biological productivity of oceans; heat and salt budget of oceans; observational methods in oceans; storm surges, ENSO and IOD phenomenon.

Introduction to weather and climate models, numerical modeling versus other modeling approaches, examples of atmospheric and oceanic simulations, model hierarchy (simple, intermediate, complex); governing equations in cartesian, isobaric and sigma coordinate systems; numerical discretization (finite difference, finite volume, spectral) and integration, stability, Courant-Friedrichs-Lewy (CFL) criterion, unconditionally stable numerical scheme; model components, dynamical core, physical parameterization, tracers, coupling of components; global and regional models used in weather forecasting and climate simulations.

Introduction to the boundary layer, definition and qualitative description of temporal evolution and vertical structure; Fourier series and turbulence spectra, Reynold’s averaging, interpreting variance/ covariance as turbulent kinetic energy and fluxes, tensors and Einstein summation notation; prognostic equations for mean variables in a turbulent flow, simplifications; prognostic equations for turbulent fluxes and variances; TKE equation, static and dynamic instability, Reynold’s number, Richardson number, Obukhov length, stability parameter relationships, closure problem in turbulent flow, first-order local closure; surface boundary conditions, surface momentum, energy and moisture budgets, fluxes at surface and entrainment zone, drag and Bowen ratio methods; surface layer similarity theory, Buckingham pi method, applications to wind profiles; stable and convective mixed layer phenomena including nocturnal jets, thermals, dust devils; boundary layer clouds, fair-weather cumulus, fog; geographically generated local circulations like slope and valley winds, sea/lake breeze, geographically modified flow, fetch, internal boundary layer.

Introduction to atmospheric aerosols; characterization of aerosols; physical and optical properties of aerosols, size distribution, refractive indices of aerosols, absorption and scattering of radiation by aerosols; single scattering albedo, aerosol optical depth, aerosol phase function, hygroscopic growth; mixing state, vertical distribution in the atmosphere; aerosol chemical composition; mixing state of aerosols; new particle formation; volatile chemical compounds and gas‐to‐particle conversion processes; observations and measurements of aerosols; climatology of tropospheric aerosols; stratospheric aerosols; dynamics of single aerosol particle and aerosol population; transport and transformation of aerosols; removal of aerosols; thermodynamics of aerosols; role in nucleation; role in cloud physics; interaction of aerosols with radiation; direct, indirect, and semi‐direct effects of aerosols and their influence on climate; aerosol effects on human health and air quality; aerosols in chemistry transport models; aerosols in climate models; latest trends in aerosol research and future directions.

The course covers cloud classification and formation, including the types of clouds, thermodynamic and dynamical conditions for their development, and the role of atmospheric stability and lifting mechanisms. It examines cloud dynamics such as entrainment, detrainment, downdraft initiation in cumulus clouds, large-scale convergence, and mesoscale convective systems (MCS). Nucleation processes are discussed through Köhler theory, cloud condensation nuclei (CCN) and ice nuclei (IN), and both homogeneous and heterogeneous nucleation mechanisms. The course introduces the fundamental thermodynamic and dynamical equations governing cloud formation and evolution, followed by detailed discussions on warm cloud microphysics, including diffusional growth, droplet size distribution evolution, collision–coalescence, and radiative cooling. Cold and ice cloud microphysics are explored in terms of ice nucleation pathways, multiplication mechanisms, growth through deposition, aggregation, and riming, as well as melting and precipitation formation. It also covers hydrometeors, their classification, and the interaction of microphysical processes with cloud dynamics. Additional topics include cloud chemistry, focusing on the composition of cloud water and ice, aqueous-phase reactions, and atmospheric oxidation processes. The course further addresses aerosol–cloud interactions, including direct, indirect, and semi-direct effects on cloud properties, precipitation, and radiation balance, as well as the representation of cloud microphysics in numerical weather prediction and climate models. Finally, it explores cloud–climate interactions, emphasizing the role of clouds in earth’s radiation budget, feedback mechanisms, and climate sensitivity.

Basics of satellite remote sensing: satellite orbits, sensor characteristics, view angle, passive and active remote sensing; atmospheric radiative transfer application in retrievals of geophysical parameters; aerosol remote sensing using ground‐based (passive radiometer and lidar) and satellite platforms, retrieval algorithm, vertical distribution, application of aerosol products in climate studies; cloud remote sensing, cloud detection using multi‐spectral technique, issues in cloud‐masking, CO2 slice technique; trace gas retrievals; ocean colour remote sensing, SST retrieval, wind scatterometry, altimetry; microwave remote sensing: soil moisture retrieval, passive (brightness temperature) and active (radar) microwave remote sensing for precipitation, sounding, remote sensing of cryosphere; satellite meteorology for extreme weather events (for example cyclone, thunderstorms etc.); land‐use/land‐cover change; hydrological application using gravity anomaly from satellites.

Overview; structure of the tropical atmosphere; role of the tropics in the global mass, momentum, and energy balance; tropical circulation and mean precipitation distribution; ITCZ (inter‐tropical convergence zone); tropical waves and tropical variability (intra‐seasonal: MJO (Madden‐Julian oscillation), CCEWs (convectively coupled equatorial waves), inter‐annual: ENSO (El Niño southern oscillation), QBO (quasi‐biennial oscillation), decadal: PDO (pacific decadal oscillation), AMO (atlantic multi‐decadal oscillation), NAO (north atlantic oscillation)); monsoons (mean and variability); tropical cyclones; modeling of the tropical climate and weather.

State of matter near the air‐sea interface, marine boundary layer, transfer properties between atmosphere and ocean, solar and terrestrial radiation, sea surface radiation budget, surface wind waves, air‐sea interaction processes using examples of ENSO, hurricane, Indian monsoon, turbulent transfer near the interface, bubbles and spray, transport of trace gases across the interface; latent, sensible, and momentum fluxes in the surface boundary layer over the sea, bulk parameterizations, large‐scale forcing by sea surface buoyancy fluxes, spatio‐ temporal variability of ocean surface fluxes with reference to Indian ocean.

Fundamentals of climate change and weather extremes. Interpretation of climate change and weather extreme in the context of human exposure. Geohealth. Environmental health pathway. Exposure, dose, and risk assessment. Health burden indicators. Heat stress. Environmental conditions for transmission of water and vector-borne diseases. Air pollution epidemiology. Confounders in health burden estimates. Health impact assessment tools. Impacts of climate change and air pollution on mental health. Ozone layer, UV radiation and health impacts. Food security and malnutrition. Disease forecasting. Climate-health co-benefits. Climate-resilient health infrastructure. Health early-warning system.

Overview and scope of deep learning for weather and climate; types of meteorological data; perceptrons; feedforward neural networks; optimization; evaluation matrics; weather classification using CNN; RNNs and sequence models for time series prediction; U-net for spatial data segmentation; GANs for data augmentation; physics informed deep learning; uncertainty quantification in predictions; interpretability of deep learning models; societal applications of weather and climate forecast.

This course covers foundational principles of climate science communication, including how to interpret and summarize peer-reviewed research for broader audiences and effectively visualize scientific data. Students will learn core techniques for presenting complex climate concepts clearly and accurately, with an emphasis on structured scientific writing, oral presentation skills, and basic data representation.

Decided by the course coordinator.

To be given by the interested faculty.

Students are expected to assist with teaching that includes preparing course materials, managing class activities and examination, providing support to student engagement, grading assignments. They are also expected to help with practical, tutorials, class projects (depending on the course content) and other administrative tasks related to the course and the centre.

Introduction to UNIX/LINUX, basic commands, file management; introduction to MATLAB, using Mathworks resources; MATLAB I/O with NetCDF, HDF and GRIB2; plotting 1, 2 and 3 dimensional weather/climate data and animations with MATLAB; univariate and bivariate statistics, mean/median/mode, variance/standard deviation, correlation, errors, regression; probability and distributions, how to frame and test a hypothesis, principles of statistical significance, using MATLAB functions to test hypotheses and estimate statistical significance; working with spatial weather/climate data, regridding meteorological station data, interpolation, map overlays; working with time‐series, interpolation, estimating trend in weather/climate variables.

Review of statistics and statistical inference, correlation and teleconnection, regression based approaches, simple linear and multiple, ridge and lasso, analyzing trends in climate data, and determining if they are statistically significant (Mann‐Kendall test etc.). Compositing patterns, standard diagnostics and skill scores to evaluate weather forecast, extreme events analysis, analysis of time series, autocorrelation and spectral analysis, isolating patterns using EOF/PC, applications of EOF/PC analysis, introduction to neural networks and DNN, application of AI/ML in weather and climate data analysis.