Policy Update
Prashail Tripathi
Background
The Monsoon Convection, Clouds, and Climate Change (MC4) scheme is one of seven sub-schemes that make up the Atmosphere & Climate Research-Modelling Observing Systems & Services (ACROSS) scheme. It aims to improve our understanding of the monsoon, clouds, and climate change. It was previously an autonomous sub-scheme, however it has now been integrated into the ACROSS scheme, which also includes two new sub-schemes, namely – the Physics and Dynamics of Tropical Clouds (PDTC) and the Centre for Climate Change Research.
The MC4 scheme was formally implemented as a component of ACROSS during the 12th and 13th Five-Year Plans, with significant expansion occurring in 2017-2021 and beyond. It is carried out by INCOIS (Indian National Centre for Ocean Information Services), a significant institute under MoES. The total outlay, as per the Union Budget 2024-25, for the whole of the ACROSS scheme is approximately 500 crores INR, of which the MC4 scheme is an integral part.
Clouds are necessary for monsoon convection and precipitation. The current understanding of the relationship between monsoon dynamics, convection, and cloud processes is limited due to a paucity of observations and inadequate depiction of cloud activities in climate models. The MC4 scheme seeks to improve the empirical dataset and climate models in order to enhance the understanding of monsoonal precipitation fluctuations and their effects in a warming world. The major goal of MC4 is to have a better understanding of, and quantify the relationships between monsoon interactions, clouds, particles, precipitation, and the water cycle in a changing climate. The scheme is implemented using climate models and observational studies, allowing for better prediction of climatic changes and regional effects across South Asia.
Source: https://shorturl.at/bsMYV
Functioning
The Monsoon Convection, Clouds, and Climate Change (MC4) scheme aims to address the sizeable scientific challenges of quantifying the interactions between monsoon dynamics, clouds, aerosols, precipitation, and the water cycle under changing climate, which is critical for better prediction of regional climatic variations and their impacts on South Asia, in a warming world.
This system includes five targeted project components that prioritise scientific deliverables and promote cross-fertilization of creative research ideas through interconnected components. MC4’s subcomponents are interconnected, with each having distinct aims that contribute to the overall goal.
The five sub-components are as follows –
1. Centre for Climate Change Research (CCCR)
2. Physics & Dynamics of Tropical Clouds (PDTC)
3. Atmospheric Research Testbeds (ARTs)
4. Metro Air Quality and WeatherService (MAQWS)
5. Climate Variability and decadal Prediction (CVP)
The combined objectives are as follows –
I. Modelling global and regional climate variability and change, as well as assessing its effects, with Earth System Models and excellent quality climate models.
II. Undertake observational research, computer simulations, and laboratory tests on monsoon cloud dynamics and microphysics.
III. Examine ground-based data on greenhouse gas (GHG) concentrations and fluxes, chemical trace gases, and climatic variables.
IV. Reconstruct historical changes in the Asian monsoon that span back thousands of years.
V. Outreach, training, and dissemination of credible climate data.
VI. Increase in-house capabilities for global and regional climate modelling and observation.
VII. Set up an “Atmospheric Research Testbed in Central India” (ART-CI).
VIII. Establish a “National Climate Reference Network” (NCRN).
Source: https://lnk.ink/9eIU7
Performance
The Monsoon Convection, Clouds, and Climate Change (MC4) scheme was formally adopted around the year 2017-2018, under the ACROSS framework. It is operated through the collaboration between
1. Indian Institute of Tropical Meteorology (IITM), Pune
2. National Centre for Medium Range Weather Forecasting (NCMRWF)
3. India Meteorological Department (IMD)
And, it also works in synergy with global efforts such as CMIP6, GEWEX, and CLIVAR Contribution so far,
1. Several field campaigns, such as CLOUD-ACT, ICARB, and MISO-BOB, were launched to examine cloud dynamics and air-sea interactions.
2. Convection-permitting models (CPMs) have been developed as enhanced parameterizations for monsoon cloud systems.
3. Significant contributions to climate projections in India’s NDCs.
The MC4 scheme has also assisted the IMD and other allied departments to explain trends like:
(a.) Shift in monsoon rainfall patterns (with more short-duration, intense rainfall events).
(b.) Decline in low-rainfall days and increase in extreme rainfall events.
(c.) Regional changes in cloud cover and atmospheric stability due to warming.
Source: https://lnk.ink/8TXXN
Achievements
The achievements of the MC4 programme can be bifurcated and listed under the four sub-programmes (mentioned earlier) that it incorporated, to achieve an overall success.
The sub-programme-wise achievements are as follows:
1. Achievements of CCCR (to improve the understanding of climate change in the tropics)
(a.) For the first time, India contributed to CMIP6 (Coupled Model Intercomparison Project) experiments and the IPCC’s sixth assessment report (AR6) using the IITM Earth System Model (IITM-ESM).
(b.) Several DECK (Diagnostic, Evaluation, and Characterisation of Klima) CMIP6 simulations have been completed. These include a 300-year spin-up, 500-year pre-industrial control runs, historical (~150 years) simulations, AMIP (Atmospheric Model Intercomparison Project) experiments, and simulations involving transient and abrupt CO2 increases.
(c.) Developed and tested a 27-kilometer global model of the IITM-ESM’s atmospheric-only component for future downscaling investigations
2. Achievements of PDTC ( aims to advance the understanding of tropical clouds and their interaction with the environment.
(a.) Launched a three-year cloud seeding research program, including physical and statistical evaluation. A total of 234 randomised samples were collected to develop cloud seeding procedures.
(b.) Airborne observations were made of seeded and unseeded clouds, as well as their microphysical alterations.
(c.) Built a cloud and precipitation observation facility in the rain shadow region of the Western Ghats for weather modification research purposes.
(d.) Established a cutting-edge lightning location network across India, with over 75 sensors installed in various states. IITM integrates all sensors with the central CPU. The network will be enhanced with a few more sensors added in the future.
3. Achievements of ARTs (The ART program is a highly focused observational and analytical research effort that will use collocated observations from advanced measurement systems to understand various atmospheric processes, particularly cloud, land-atmosphere interactions and radiative processes, testing parameterisations of these processes for use in atmospheric models.)
Acquisition of 100 acres of land at Silkheda, tehsil Shyampur, Sehore, Madhya Pradesh (a core monsoon zone) to build an ART. Planning and development of physical and equipment infrastructure are now underway.
4. Achievements of MAQWS (MAQWS is a near-real-time warning system for Delhi air quality. It was introduced on October 15, 2018. Created in collaboration with the National Centre for Atmospheric Research (NCAR) in the United States, the system collects data from approximately 36 monitoring stations operated by the Central Pollution Control Board (CPCB), Delhi Pollution Control Committee (DPCC), and System of Air Quality and Weather Forecasting and Research (SAFAR).
(a.) Designed an advanced version of the Fine Dust Model with multiple dust schemes for large-scale dust storms and transport paths to forecast extreme events in northwest India, including Delhi. It was augmented with SAFAR
(b.) The first indigenous investigation of the impact of air pollution on health to better understand exposure to particulate matter pollution and its implications on disease burden and life expectancy in each Indian state.
(c.) Built a dynamic gridded emission inventory of Kharif crop residue burning in the north Indian states of Punjab and Haryana by combining three satellite datasets (INSAT-3D, INSAT-3DR, and MODIS data) with ground-truth observations. Estimated the contribution of stubble burning in Punjab and Haryana to Delhi’s air quality.
The achievements of the MC4 programme, listed above, are not restricted to only these points, but have been an exponential catalyst for the IMD to amp up its research and training facilities and provide the most accurate data retrieved from each of these sub-schemes, and employ it for fruitful use.
Source: https://www.tropmet.res.in/Project%20Structure-83-Page
Impact
Initial Phase (2012-2017)
The scheme’s primary purpose was to gain a better understanding of monsoon convection and cloud microphysics, as well as how climate change influences these processes. Early research was led by IITM-Pune, NCMRWF, and IMD, with support from supercomputing initiatives and monsoon missions.
During its early stages, the MC4 program launched field campaigns such as CLOUD-ACT (Cloud Aerosol Interaction and Convection Transition) and MISO-BOB (Monsoon Intra-seasonal Oscillations in the Bay of Bengal).
Consolidation and Integration Phase (2017-22)
MC4 was designated as a sub-scheme under ACROSS, resulting in increased budgetary and institutional assistance.
High-resolution convection-permitting models have been developed to simulate monsoon cloud systems.
Research findings have resulted in more accurate monsoon beginning and withdrawal projections. The scheme has assisted in recognising shifts in cloud patterns and excessive rainfall as a result of global warming. The approach enabled India to contribute to IPCC reports and national climate assessments (for example, the MoES’s 2020 Climate Assessment Report).
Expansion and Research Phase (2022- Present)
Amping up the collaboration with foreign partners (e.g., UK Met Office, NCAR, and WCRP-GEWEX).
The MC4 achieved success in data generation and began providing insights on:
1. Seasonal rainfall warnings for agricultural and water resource planning.
2. Climate-smart rainfall trends at the district level.
Field campaign support was enhanced through programs such as ORCA (Ocean-Atmosphere Interactions in the Bay of Bengal). It was integrated into Phase II of the National Monsoon Mission and linked to climatic services provided by IMD.
Future Directions For Wider Adoption
1. Combining MC4 results with sectoral models (e.g., agricultural, water, and urban flooding).
2. Improving modelling infrastructure to enable operational-scale convection-resolving simulations.
3. Academic institutions are expanding their monsoon cloud modelling training programs.
4. Improve state-level applications for local climate adaptation planning.
Emerging Challenges
1. The intricate nature of monsoon systems necessitates high resolution simulations and tremendous processing capacity.
2. Lack of high quality, long-term observational information, particularly across oceans and rugged terrain.
3. Because MC4 is primarily a research tool, its real-world applicability (such as farming or urban planning) is limited unless it is combined with sectoral models. For example, The MC4 scheme improves seasonal and sub-seasonal monsoon forecasts, which are critical for:
(a.) Crop selection and sowing decisions
(b.) Input planning (fertilizer, seeds, labor)
(c.) Irrigation scheduling and water storage. It also helps reduce crop failure risks due to delayed or erratic rainfall.
4. Integration with hydrology, urban planning, and disaster risk reduction needs improvement.Urban cities, today, are rightfully called Urban Jungles of Concrete, as due to mass deforestation and infrastructure development, the urban cities, today, are prone to natural calamities. The role of MC4 comes handy in these situations as long term climate projections would enable the planners, to better plan the cities, keeping in mind the calamities like floods as they would be in a better situation, being informed beforehand, and would accurately risk zone the areas that have the chances of being hit by such calamities.
5. There is a shortage of trained scientists in cloud dynamics and monsoon modeling.
6. Precise simulation of monsoon cloud microphysics and convection needs high resolution (HR) cloud-permitting models, which are computationally expensive and currently in development. This could have an impact on operational forecasts, which often oversimplify convective processes, compromising reliability, particularly for short-term and local-scale rainfall prediction.
7. Even modern models struggle to capture the Indian monsoon’s increasingly nonlinear behaviour due to global warming (e.g., unpredictable bursts, monsoon breaks, intense localised rain). In turn, it tests the forecasting ability of MC4-based models in extreme conditions, reducing user confidence
8. Last, but not the least, lack of a defined institutional structure for incorporating MC4 outputs into climate resilience planning, particularly at the state and district levels.
Source: https://www.insightsonindia.com/wp-content/uploads/2022/09/grim.jpg
Way Forward
To make communities immune against climate change and help people make wise decisions regarding the same, we need to create user-friendly digital platforms that enable the creation of valuable tools such as farming suggestions and flood warning maps.
In addition, we should invest in improved technology and current methodologies such as using strong computer models, merging diverse weather forecasts, and utilising artificial intelligence to improve predictions. To obtain better and more reliable data, we must also establish more weather stations, use more satellites, and improve our ocean monitoring methods.
The MC4 scheme’s findings will be integrated into national and state climate missions, as well as disaster management plans, ensuring that scientific insights become actionable solutions. Finally, creating multi-model ensembles and strong uncertainty quantification processes will result in more trustworthy forecasts, allowing for informed sector-wide planning.
References
1.Centre for Science and Environment. (2016). Poleward drift [PDF]. Down To Earth. https://cdn.downtoearth.org.in/pdf/poleward-drift-20160831.pdf
2. Ministry of Earth Sciences. (n.d.). Home. Government of India. https://moes.gov.in
3.Ministry of Earth Sciences. (2020). Assessment of climate change over the Indian region. Government of India.
4. Indian Institute of Tropical Meteorology. (n.d.). Home. IITM Pune. https://www.tropmet.res.in
5. India Meteorological Department. (n.d.). Mausam. IMD. https://mausam.imd.gov.in
6.National Centre for Medium Range Weather Forecasting. (n.d.). Home. NCMRWF. https://www.ncmrwf.gov.in
7.Intergovernmental Panel on Climate Change. (2014). Climate Change 2014: Synthesis Report.
Contribution of Working Groups I, II and III to the Fifth Assessment Report (AR5). IPCC.
Intergovernmental Panel on Climate Change. (2021). Climate Change 2021: The Physical Science Basis. Sixth Assessment Report (AR6). IPCC.
8. Indian Meteorological Department. (n.d.). Schemes. IMD. https://indianmeteorologicaldepartment-userinfo.com/schemes/
9. Ministry of Earth Sciences. (n.d.). Project information. https://lnk.ink/BWAn6
10.Indian Institute of Tropical Meteorology. (n.d.). Project structure. IITM Pune. https://www.tropmet.res.in/Project%20Structure-83-Page
About the contributor
Prashail Tripathi has completed his post graduation (M.A) in National Security Studies from the Central University of Jammu. He has been affiliated with IMPRI as a Policy Research Intern since June 2025. His core interests include understanding current geopolitical scenarios, civil-military relations of India’s neighbouring countries, energy security and International Relations.
Acknowledgment
The author extends sincere gratitude to Ms. Aasthaba Jadeja for her invaluable guidance and mentorship throughout the research process.
Disclaimer: All views expressed in the article belong solely to the author and not necessarily to the organisation.
