ACROSS is composed of the following four sub-schemes.
Details of the sub-schemes are provided below.
Clouds are an integral part of monsoon convection and precipitation. Current understanding of the coupling of monsoon dynamics to convection and cloud processes is limited due to the lack of observations and inadequate representation of cloud processes in climate models.
The MC4 scheme was envisioned to improve the observational database and climate models for enhanced predictive understanding of monsoonal precipitation changes and their impacts in a warming environment. The overarching goal of MC4 is to describe better and quantify interactions among monsoon dynamics, clouds, aerosols, precipitation and water cycle in a changing climate. It will be accomplished by climate modelling and observational studies and would enable improved prediction of climatic variations and regional impacts over south Asia.
Objectives of MC4
To achieve these objectives, MC4 has the following four sub-programmes.
1. Centre For Climate Change Research (CCCR) including virtual water centre
A state-of-the-art CCCR was established at the Indian Institute of Tropical Meteorology (IITM), Pune, to improve the understanding of climate change in the tropics and to enable improved assessments of regional climate responses to global climate change.
Achievements of CCCR
2. Physics and Dynamics of TropicalClouds (PDTC)
PDTC aims to advance the understanding of tropical clouds and their interaction with the environment. Thisis required for better prediction of monsoon, and to establish a scientific rationale for cloud seeding operations to increase rainfall efficiency. It has the following four sub-projects.
Achievements of PDTC
3. Atmospheric Research Testbeds (ART) for process studies and National Climate Reference Network (NCRN)
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.
In the first phase, an ART would be set up in central India to study convection, land-atmosphere interactions and precipitation processes. It is expected to provide a sound basis for other research testbed programs in climatologically interesting and important areas. In the second phase, ART is to be set up in the northeast/eastern part of the country to study severe thunderstorm processes.
The NCRN will comprise of a network of ~25 climate reference stations commissioned in several parts of the country, equipped to provide long-term, accurate, and unbiased observations. Such observations are essential to define the state of the integrated Earth system, its history, and its future variability and change. Most historical in situ observations of surface climate variables have been undertaken for real-time applications such as weather forecasting, hydrology, and agro-meteorology. Changes during the time of observation, instrumentation, and operators also contribute to uncertainty. Historically, undocumented or inadequate metadata that describes changes in meteorological measurements has been all too common. The NCRN will make it possible to validate the climate projections from ESMs using accurate and reliable ground truth verifications.
Achievements of ART and NCRN
4. Metro Air Quality and Weather Service (MAQWS)
MAQWS is a nearly warning system of air quality of Delhi. It was launched on 15th October 2018 and was developed in collaboration with the National Center for Atmospheric Research (NCAR), USA. The system assimilates data from ~36 monitoring stations which are run by the Central Pollution Control Board (CPCB), Delhi Pollution Control Committee (DPCC), and the System of Air Quality and Weather Forecasting and Research (SAFAR). The system provides location-specific information on air quality in near real-time and its forecast with a lead time of 1 to 3 days. Data from satellites on stubble burning in northwest India or dust storms along with the prevalent meteorological factors helps to improve the initial conditions of the dynamical chemistry transport model. This enables accurate prediction of air-quality, which aids in planning of mitigation strategies. The scientific outcome of MAQWS will allow the implementation of a graded response action plan well in advance. Such an approach could lead to more targeted and cost-effective action on weather information and clean air, focused on public health.
Achievements
MoES is mandated to provide the nation with the best possible services of forecasting the monsoons and other weather and climate parameters, ocean state, natural disasters such as earthquakes and tsunamis, and other phenomena related to earth systemnation. Improving these forecasts is a challenging task as it requires solving of complex mathematical equations at a very high spatial resolution across the entire globe. The models to solve these equations need high-performance computational resources, including modern supercomputers with vast parallel computing architecture with support from artificial intelligence and machine learning algorithms.
The existing HPCS resources of 6.8 petaflops (PF) commissioned in 2018 has resulted in improved short-medium scale forecasts with the usage of high-resolution models. For further enhancing weather and climate prediction, high-resolution dynamical models with increased complexity and advanced data assimilation techniques are required, which are highly computationally intensive. Rigorous developmental work has been undertaken at MoES institutes which include following important tasks.
MoES has taken up work to develop the following essential initiatives as part of the HPCS programme.
Adequate computational facilities are also required to enhance training capacity to cater to the enormous need for skilled manpower in the field of Earth System sciences. In addition, real-time weather and climate-related information and services are provided to the SAARC (South Asian Association for Regional Cooperation), IOR-ARC (Indian Ocean Rim Association for Regional Co-operation), RIMES (Regional Integrated Multi-hazard Early Warning System), ASEAN (Association of Southeast Asian Nations) countries for societal benefit.
MoES also hosts and established the Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) Centre for Weather and Climate, the Indo Africa Centre for Medium Range Weather Prediction in Mauritius, and the National Tsunami Early Warning Centre (which has been providing tsunami advisory services to India and IOR-ARC countries). High computational power is required to carry out all activities related to the flagship programs of MoES.
Objectives
Implementing institutions
Achievements
Plans
Agricultural productivity and economy of our country largely depends on the performance of Indian monsoon rainfall. Therefore, prediction of total quantum of Indian summer monsoon rainfall (ISMR) during the months of June to September (also called the seasonal rainfall, which produces about 80% annual rainfall over the country), its intra-seasonal and inter-annual variability, and knowledge of extreme rainfall conditions are very useful for planning and managing agriculture, water resources and disaster management, leading to great benefit to the society and citizens of the country. The ISMR has a global teleconnection with El Nino, which relates to an anomalous warming of Sea Surface Temperature (SST) over East Pacific Ocean and its opposite phase La-Nina, relating to cooling of SST over the same region. This has a predictive value for seasonal prediction of ISMR, as the signal is obtained few months in advance.
In last few decades, many studies have been made on the El Nino and Southern Oscillation (ENSO) phenomenon which is a dominant mode of global inter-annual variability with vast influence on other regional climates. However, till a decade ago (up to 2010), no significant breakthrough had taken place in improving the prediction skill of the ISMR. Historically, statistical models had been used for operational long-range forecasts for the Indian summer monsoon rainfall over the years. But improvement in prediction skill was not appreciable in operational forecasts, in spite of better understanding of monsoon variability, its teleconnection mechanisms and the knowledge that it is a prominent heat source over Indian region that drives the major atmospheric circulations. Moreover, statistical models had constraints in predicting monsoon rainfall in higher spatial and temporal resolutions.
Recent improvements in dynamical numerical models with ocean-atmosphere coupling have shown good prediction skill of ENSO SST with six months lead time. The seasonal mean rainfall hind cast skill, at one season lead time, over the central Pacific is also very good. In recent times, with the dynamical models, several new approaches (high resolution, improved physical parameterization schemes, super parameterizations, data assimilation, etc.) have shown that the variability in tropics can be reasonably resolved, thereby creating optimism for improving the monsoon prediction. Although many centres in the world were using dynamical modelling frameworks to predict seasonal mean climate routinely, in India such a framework was not in place before 2012.
The Ministry of Earth Sciences (MoES), Government of India, launched the National Monsoon Mission (NMM) in 2012 (now referred as Monsoon Mission, MM), with a vision to develop a state-of-the-art dynamical prediction system for Indian monsoon rainfall on different time scales. MoES bestowed the responsibility of execution and coordination of this mission to the Indian Institute of Tropical Meteorology (IITM), Pune in collaboration with the National Centre for Environmental Prediction (NCEP), USA, other MoES organizations (NCMRWF, IMD & INCOIS) and various national and international academic institutions and organizations. Climate Forecast System (CFS) of NCEP was found to be one of the best among the currently available coupled climate models, and its second version (CFSv2) has been implemented at IITM Pune, as the basic modelling system for the above purpose. Scientists of IITM, along with collaborators, made necessary model development works on this base model for improving prediction skill of this model over Indian monsoon region, with decreased model bias. Unified Model (UM) of UK Meteorological Office was implemented at NCMRWF, Noida as the base model for short and medium range weather predictions. NCMRWF scientists and collaborators worked on this model. In addition, CFS & GFS based models were used for extended range prediction and high-resolution short-range prediction at IITM Pune, in collaboration with IMD and NCMRWF. Model data assimilation works were done at NCMRWF, INCOIS and IITM, in collaboration with the University of Maryland, USA. High Performance Super Computing Systems (HPCS), installed at IITM and NCMRWF, provided the modelling infrastructure. Several national and international projects were funded through MM and those were coordinated by the Monsoon Mission Directorate (MMD) at IITM, with guidance of important Committees formed by MoES. There had been many high-level training courses, manpower development works, deputation of young scientists abroad for working with international principal investigators, high-level meetings and events during the MM-I.
In 2017, the first phase of monsoon mission (referred to as MM-I) was completed successfully. The seasonal prediction system with improved hind cast skill (retrospective forecast of seasonal monsoon) was handed over to IMD for operational forecasting and this modified model is referred as Monsoon Mission CFS (MMCFS). The extended range prediction system was also handed over to IMD for operational forecasting of active/break spells of monsoon and other weather events, up to 4 weeks in advance. The success of MM-I led to its continuance, as the second phase.
The second phase of monsoon mission (MM-II), which began in September 2017, focuses on predicting weather/climate extremes and development of climatic applications based on monsoon forecasts, especially in the field of agriculture, hydrology and energy sector, while continuing model development activities. In MM-II, focus has been given to high-resolution short-range predictions, predicting extremes, and using forecasts to develop applications for agriculture, hydrology, disaster management, energy sector, etc. As a new initiative to predict extremes, dynamical prediction of thunderstorm and lightning has been initiated. Model development, through enhancement in resolution and improvement in physical processes in the model, is continuing for increasing prediction skill of Indian monsoon and minimizing model biases.
Objectives
Implementing institutions
Achievements
Plans
The scheme Atmospheric Observations Network of IMD is a continuing scheme primarily encompassing ongoing programs in an integrated manner aimed at sustenance of observational network. This scheme
is a part of the umbrella scheme Atmosphere & Climate Research-Modelling Observing Systems & Services (ACROSS) programme of MoES.
The meteorological services have significant societal impact. Public/private/government sectors demand for accurate prediction of weather and climate at various temporal and spatial scales is increasing due to possible impacts of global climate variability and change. Improved and reliable forecast of weather and climate requires high resolution dynamical models backed by comprehensive data assimilation systems. Thus, intensive monitoring of various weather systems through different platform based observing systems provide not only the necessary information about current weather systems, their effective assimilation in numerical models provide important guidance for skillful forecasts generation.
The current observations need to be sustained and continued as per WMO procedures and standards for all times to come. The measurement of various atmospheric parameters through surface, upper air, aircraft is a prime requirement for operating the meteorological services. Several major advanced technology based equipments have been installed over the years. The maintenance and augmentation of these equipments is essential so that the benefit of technology upgradation is available on continuous basis. IMD needs upgradation & sustenance of observational network in order to achieve accelerated progress for providing top quality meteorological services to the society. IMD has been operating and sustaining several types of observational networks all over the country for monitoring the meteorological conditions and providing the meteorological data to weather forecasting and other uses. Sustenance of integrated observation system will be the major strategy of the scheme.
Objectives
The scheme Weather & Climate Services of IMD is a continuing Scheme primarily encompassing ongoing programs in an integrated manner aimed at providing efficient weather and climate services across
IMD provides services to weather-sensitive sectors viz. agriculture, irrigation, shipping, aviation, offshore oil explorations, etc. Over the years, specialized services have also been built for state-of-the-art Monitoring, Detection and Early Warning of extreme weather phenomena including tropical cyclones, severe thunderstorms, dust storms, heavy rains and snowfall events, cold and heat waves, etc. The meteorological services have significant societal impact. Public/private/government sectors demand for accurate prediction of weather and climate at various temporal and spatial scales is increasing due to possible impacts of global climate variability and change. The weather services are dependent on the sustained investments in Research and Development (R&D) and capacity building so that advances in weather and climate sciences get inducted in to service through a focused performance evaluation in a semi-operational environment. Further improvement of current services requires effective conversion of R&D results into fully operational products, services and effective means to develop linkages with decision-makers and users. Especially, effective use of public weather services to communicate through tools, products and services that are useful for decision-making is the need of the hour.
Major components of the scheme “Weather and Climate Services” are:
Objectives
The scheme Upgradation of Forecast System of IMD is a continuing Scheme primarily encompassing ongoing programs in an integrated manner aimed at providing efficient weather and climate services across the country in various sectors. This scheme is a part of the umbrella scheme “Atmosphere & Climate Research-Modelling Observing Systems & Services (ACROSS)” of MoES.
The proposed scheme Upgradation of Forecast System is aimed at improving the accuracy of weather forecasts to bring it at par with the international standards which will help many sectors like army operations, air operation, agriculture, tourism, mountaineering, aviation, roads and communications, power generation, water management, environmental studies, Sports & Adventure, Transport, Government Authorities, NGOs and Public in general.
Objectives
IMD presently operates a radar network most of which comprises of very old technology and are based on conventional analog systems, and therefore it is becoming obsolete with respect to the current and future generation DWRs. Moreover, the conventional radar products are incompatible with present day requirements of digital data on different parameters which can be directly used as inputs to weather prediction models.
Induction of an adequate number of DWRs in the network would facilitate plugging the existing gaps in the meteorological observational network of radars, desirable for effective and efficient analysis and consequent forecasting, in particular at the mesoscale. The availability of countrywide weather radar coverage and its integration, including overlapping regions of the proposed network would provide adequate warning in the event of approach of Cyclonic Storms, Monsoon Depressions, etc. It would also provide vital information for nowcasting purposes on mesoscale convective weather developments anywhere in the country. Radar observations would also stimulate research on the dynamics and microphysics of convective weather phenomena. The data from these DWRs would also help in understanding key as well as major differences between super cell storms and ordinary storms. Besides, it is desirable to have a dual polarimetric facility to obtain additional information on hydrometeors and their quantification in clouds, classification of precipitating clouds, etc.
Continuing the efforts of induction of the polarimetric DWRs with an aim of creating multiple overlapping configuration of the modern DWR network in the country, a total of another Eleven DWRs are being proposed by the IMD
Objectives
These proposed set of new DWRs would be of immense use in better Nowcasting and mesoscale forecasting. Using both NWP and conventional approaches, the objectives of other ongoing programmes are also in sync with the current proposal’s objectives.