Urban Meteorology, Air Pollution and Health, Aerosol-Climate Interactions, Heat Island Effect and Fog Prediction, Air Quality Studies.
Aerosols influence the Earth’s climate by scattering and/or absorbing solar radiation, altering cloud characteristics and hydrological cycle, and impacting land and ocean biogeochemistry, atmospheric chemistry, and cryosphere. Urban meteorology and the fog life cycle are also influenced by aerosol radiative and microphysical feedback processes. Therefore, understanding aerosol-climate interaction via diverse pathways is critical to reducing uncertainty in climate projections.
When we breathe, these tiny particles enter our respiratory tract, and causes damage to our health. Exposure to aerosols is the second largest health risk in India and the sixth largest globally. High levels of air pollution can damage crops. Cleaning the air by reducing emissions of aerosols to protect the health may have diverse consequences for the climate depending on aerosol characteristics and the feedback processes.
At CAS, we are involved in cutting-edge research on advancing fundamental understanding of the complex interactions between aerosols, hydrosphere, biosphere, atmosphere, and cryosphere using ground-based and satellite observations and models. The strategic knowledge generated by the CAS researchers in this field has been instrumental in various past and recent national and international programs. CAS researchers play a major role in shaping environmental policies and producing skilled manpower. Addressing air pollution by achieving climate and health co-benefits is essential for sustainable development.
Prof. Dilip Ganguly, Prof. Manju Mohan, Prof. Ravi Kumar Kunchala, Prof. Sagnik Dey, Prof. Sajeev Philip, Prof. Shahzad Gani
Climate Dynamics, Climate Variability and Changes, Climate Change, Detection & Attribution, Global and Regional Climate Modeling, Climate Projections, Climate Change Impacts.
Climate Research at the Centre for Atmospheric Sciences aim to address fundamental questions about climate such as: How has the climate changed in the past at timescales ranging from intraseasonal, annual to millennial and longer? How will the climate change in future due to anthropogenic warming? What controls the surface temperatures and rainfall patterns globally and over India? What is the uncertainty in projected future surface air temperature and precipitation over India? Answers to these fundamental questions allow better forecasts of regional impacts of the projected global climate change.
To answer such questions, research conducted at CAS focuses on understanding climate variability and changes using observational data and modelling of past and modern climates, with a particular focus on the climate of the Indian subcontinent. Understanding past climate involves reconstructing rainfall and temperature using various proxies recorded in natural climate archives. Detection and attribution of climate change involves assessing the causes of observed changes in the climate system through systematic comparison of climate models and observations using various statistical methods. Climate research at CAS overall work towards contributing to improved models for weather forecasting and climate prediction.
Prof Krishna AchutaRao, Prof Sandeep Sukumaran, Prof. Saroj Kanta Mishra, Prof. Sarvesh Kumar Dubey, Prof. Saurabh Rathore, Prof Yama Dixit,
Numerical Modeling of the Atmosphere, General Circulation, Tropical Meteorology and Indian Monsoon, Land-Surface Process Modeling, Land-Atmosphere Interaction.
Numerical models of the atmosphere are powerful tools for simulating and forecasting the state of the atmosphere. A core research activity at CAS is to build better models and conduct numerical experiments with these models to understand and predict the behaviour of the atmosphere and its interactions with the land surface and oceans. CAS researchers have actively contributed to developing cutting-edge general circulation models that can simulate the atmospheres of the earth and other planets like Mars and Venus.
The main focus of numerical modeling at CAS is the Indian summer monsoon. Even though the monsoon is often considered the lifeline of the Indian economy, accurately forecasting the monsoon is still an open challenge. The major reason for the slow progress in the monsoon prediction is that we lack a complete understanding of the fundamental processes associated with the monsoon. To fill this gap, researchers at CAS are working on understanding various aspects of the Indian summer monsoon, including aerosol-cloud-precipitation interaction, the energetics of the monsoon, and the genesis mechanisms of monsoon low-pressure systems. Further, CAS researchers also use the latest AI/ML techniques to predict monsoon synoptic and intraseasonal activities. In addition to monsoon, organised convection and tropical cyclones are the other major high-impact weather systems that affect tropical regions like India. Therefore, we also investigate the mechanisms of organised convection and work on improving tropical cyclone prediction.
Land surface characteristics play a crucial role in modulating the regional climate. Many human activities change land use and land cover patterns that can affect regional weather and climate. An important area of research at CAS is to build models and conduct numerical experiments to simulate land-surface processes and land-atmosphere interaction. CAS faculty have significantly contributed to improving our understanding of changes in regional weather and climate due to agriculture, large-scale deforestation, and urbanization.
Prof. Dilip Ganguly, Prof. Krishna AchutaRao, Prof. Manju Mohan, Prof. Sandeep Sukumaran, Prof. Saroj Kanta Mishra, Prof. Sarvesh Kumar Dubey, Prof. Saurabh Rathore, Prof. Somnath Baidya Roy,
Renewable Energy Meteorology, Resource Assessment, Forecasting.
Renewable energy is widely acknowledged to be a part of the solution to the climate change, air quality, and energy security problems. That is why India, and the world are rapidly moving away from conventional fossil fuels to renewables like wind, solar, hydro, wave, tidal, and biomass energy. Developing and operating renewable energy systems require a thorough understanding of atmospheric and oceanic dynamics because, after all, the atmosphere and the oceans are the sources of most renewables. CAS researchers are blending fundamental concepts, cutting-edge techniques, and latest data to explore problems in atmospheric and oceanic sciences that are relevant for renewable energy. Some examples of these problems include assessing wind, solar, and tidal resources and the effect of air pollution and climate change on these resources; forecasting renewable power generation to improve grid integration of renewable power plants; energy replenishment in wind farms; and effects of renewable energy systems on the environment. Addressing these and other emerging questions is absolutely critical for the growth of the new energy sector.
Prof. Dilip Ganguly, Prof. Sagnik Dey, Prof. Somnath Baidya Roy
Numerical Methods, Data Assimilation and Adjoint Modeling, Inverse Modeling, GPU Computing.
Accurate prediction of weather and climate require a comprehensive understanding of the behaviour and the complex interactions between the atmosphere, oceans, land and other components of the Earth System. Many of these processes, including the conservation equations of mass, momentum, and energy, are well known to us. However, these equations are highly non-linear partial differential equations that cannot be solved by hand. Hence, we need numerical models that are computer programs capable of solving these equations. A well-designed model running on a fast supercomputer like the IITD HPC Padum can easily solve these equations at a pace that allows us to predict weather and climate ahead of time. CAS researchers develop efficient numerical methods to discretize these equations having compatibility with cutting-edge computer architectures (e.g., distributed memory, GPU, etc.) to enhance the overall performance and skill of climate models.
An accurate initial condition describing the best possible state of the system is needed to initialize these models and ensure their stability. We employ advanced data assimilation techniques, which optimally combine the outputs from these models and observations to estimate the accurate state of the system. At CAS, we explore the role of advanced data assimilation techniques in improving monsoon and extreme event predictions and modify these techniques to enhance the skill of models.
Researchers at CAS employ adjoint and inverse modeling approaches for parameter estimation, stability, and sensitivity analysis. In addition to rigorous numerical methods, we are also exploring how to use soft computing, Machine Learning, and data-driven approaches to improve climate models and climate model projections.
Prof. Maithili Sharan, Prof. A D. Rao, Prof. Krishna AchutaRao, Prof. Somnath Baidya Roy, Prof. Saroj Kanta Mishra, Prof. Sandeep Sukumaran and Prof. Sarvesh Kumar Dubey, Prof. Saurabh Rathore
Ocean Modelling, Coastal Processes, Ocean State Simulations and Forecasting, Storm Surges and Inundation.
Oceans cover more than 70% of the Earth’s surface and plays a crucial role in influencing the climate system and its variability in many ways including heat storage and meridional heat transport through ocean currents. The genesis and propagation of tropical cyclones, Indian Ocean Dipole (IOD), and El-Niño Southern Oscillations (ENSO) are examples of strong atmosphere-ocean coupling that influence weather/climate at different time scales. For the past four decades, CAS has been spearheading the research in ocean sciences in the country with particular emphasis on numerical simulation of oceanic and air-sea interaction processes at different time scales to understand their impacts on weather/climate and provide information of societal importance to protect lives, ecosystems, and infrastructure.
Oceanic research at CAS involves the implementation of regional and global ocean models in 1-D, 2-D, and 3-D space and the analysis of observational and climate models data. CAS faculty developed the first model to predict storm surges and associated inundation along the Indian coastline. The CAS faculty use a variety of ocean models to study ocean processes such as coastal upwelling, generation and propagation of internal waves, river plume dynamics, marine biogeochemistry, etc. Coupled atmosphere-ocean models are also being used to understand the air-sea interaction during the passage of tropical cyclones over the Bay of Bengal and the Arabian Sea, as well as the impacts of IOD and ENSO on regional ocean processes. Recent research on sea-ice dynamics and its variability in the polar ocean (the Arctic Ocean and coastal Antarctic regions) has been initiated. The spatio-temporal variations in sea-ice parameters and ocean physical and biological parameters are being studied using numerical models and available observations over the polar oceanic regions.
Alongside the foregoing research areas, the ocean fraternity of CAS has spread its wings to understand the high-resolution coastal ocean circulation features and dynamical processes at multiple spatial (mesoscale, 10-100 km; sub-mesoscale, < 10 km) and temporal (tidal to seasonal) scales in the northern Indian Ocean using the state-of-the-art observational platforms, like, the HF Radars, drifters, and Argos. The CAS faculty also investigates the drivers and dynamics of marine heatwaves in the northern Indian Ocean and within the maritime continents to understand their impacts on marine productivity and tropical cyclones.
Prof. A. D. Rao, Prof. Vimlesh Pant, Prof. Samiran Mandal, Prof. Krishna AchutaRao, Prof. Saurabh Rathore