Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS)

Lead Research Organisation: NERC Centre for Ecology and Hydrology
Department Name: Hydro-climate Risks


The monsoon supplies the majority of water for agriculture and industry in South Asia, and is therefore critical to the well-being of a billion people. Active and break periods in the monsoon have a major influence on the success of farming, while year-to-year variations in the rainfall have economic consequences on an international scale. The growing population and developing economy mean that understanding and predicting the monsoon is therefore vital. Despite this, our capability to model the monsoon, and to make forecasts on scales from days to the season ahead is limited by large errors that develop quickly. The relatively poor performance of weather prediction models over India is due to a very strong and complex relationship between the land, ocean and atmosphere, which are linked by the process of convection, in the form of the rain-bringing cumulonimbus clouds. Forecast errors occur primarily because the convective clouds are not accurately linked to the large-scale circulation or to the surface conditions, and these errors persist to long time scales. Worldwide, weather and climate forecast models are gaining resolution, and yet the errors in monsoon rainfall are not diminishing. A lack of detailed observations of the land, ocean and atmospheric parts of the monsoon system, on a range of temporal and spatial scales, is preventing a more thorough understanding of processes in monsoon convective clouds and at the land surface, and their interaction with the large-scale circulation.
This project will use a programme of new measurements over India and the adjacent oceans to advance monsoon forecasting capability in the Indo-UK community. The first detachment of the FAAM research aircraft to India, in combination with an intensive ground-based observation campaign, will gather new observations of the land surface, the boundary layer structure over land and ocean, and atmospheric profiles. We will institute a new long-term series of measurements of energy and water exchanges at the land surface. Research measurements from one monsoon season will be combined with long-term observations on the Indian operational networks. Observations will be focused on two transects: in the northern plains of India, covering a range of surface types from irrigated to rain-fed agriculture, and wet to dry climatic zones; and across the Western Ghats, with transitions from land to ocean and across orography. The observational analysis will represent a unique and unprecedented characterization of monsoon processes linking the land, ocean and atmospheric patterns which control the rainfall. Long-term measurements will allow the computation of statistical relationships between the various factors.
The observational analysis will feed directly into improved forecasting at the Met Office and NCMRWF. The Met Office Unified Model, which is used for weather forecasting at both institutions, will be set up in a range of different ways for the observational period. In particular, we will pioneer the test development of a new 100m-resolution atmospheric model, which we expect to greatly improve the representation of land-ocean-atmosphere interactions. Another priority will be to improve land surface modelling in monsoon forecasts. By comparing the results of the very high resolution models on small domains with lower-resolution models representing the global weather patterns, it will be possible to describe the key processes controlling monsoon rainfall, and to indicate how these need to be represented in different applications, such as weather predictions or climate predictions. Through model evaluation at a range of scales, the development of simple theoretical understanding of the rainfall processes, and working with groups responsible for operational model improvement, the project will lead directly to improvements in monsoon forecasts. By improving rainfall prediction, we expect the work to have an economic impact in India and internationally.

Planned Impact

The primary impacts of our research will be delivered through our partners, the Met Office, National Centre for Medium Range Weather Forecasting (NCMRWF) and the India Meteorological Department (IMD). The effectiveness of these public weather forecasting and climate prediction services will be enhanced by better understanding of existing and new processes affecting monsoon predictability. The primary goal of the project is to improve the performance of the weather and climate forecast models used by these centres. Furthermore, improved understanding of the key processes in the monsoon will have knock-on scientific benefits, for instance in the improved conceptual understanding which can be taught to forecasters, improved ability to give strategic advice on issues such as land management, and better-informed strategies for model development. Improved monsoon modelling and forecasting capability in the medium-to-long term will raise the profile and performance of these organisations nationally and internationally, increasing their reputation (the current status of monsoon prediction is currently regarded as poor) and saleability of their products. These organisations would also benefit from our quantitative assessment of the value of new observations demonstrated by the proposed field campaign, and generally greater awareness of the uses of such data.

Our weather-service partners will convey impacts of our research to national and state government ministries in India. These organisations will be provided with quantitative evidence to inform new policies of investment in the monsoon observing system, given the improvements to forecasting and analysis that we expect our new and additional observations will initiate. New interpretations of the effect of contrasts between different surface types on weather over India should also influence policies on agriculture and extraction of groundwater (both related to irrigation).

As a result of improved weather and climate predictions, there is an opportunity for planners and governors at the state and district level to benefit from improved protection against extremes, and associated impact reductions (of flooding, drought, delayed monsoon onset), if the intended improvements to understanding of monsoon variability and forecasting can be effectively communicated to society. For instance, the IMD are already communicating forecast information to millions of farmers via new electronic media.

Technical staff undertaking in situ measurements in India will benefit from improved skills and knowledge in measurement of surface fluxes, the relative merits of the different techniques involved and improvement in their quality control procedures. This will make their data products more reliable and useful.

Finally, the public will benefit through greater awareness of monsoon forecasting and its inherent limitations, and its effect on society. The public will also become engaged more directly with the process of science.
Description We have demonstrated the importance of the rapid transitions of the land over India during the monsoon for prediction of weather. When the monsoon rains begin, the soil wets up rapidly. This provides a source of moisture for evaporation back into the atmosphere, which effectively cools the air. We have measured the changes in evaporation over a year in multiple locations and shown the importance of irrigation for evaporation in many parts of India. We have also shown how the wetness of the soil can influence new rain events, providing an important feedback mechanism.
Exploitation Route The data and findings can help Met Services in India and elsewhere to evaluate and improve their weather forecasts
Sectors Environment

Title High temporal resolution meteorology and soil physics observations from INCOMPASS land surface stations in India, 2016 to 2018 
Description The dataset contains time series observations of meteorological and soil physics variables logged at one minute time resolution at three Land Surface Stations in India. The three INCOMPASS Land Surface Stations were located at: (1) agricultural land in Southern Karnataka (Berambadi); (2) the University of Agricultural Sciences in Dharwad in northern Karnataka; and (3) a semi-natural grassland at the Indian Institute of Technology in Kanpur (IITK), Uttar Pradesh. Observations were collected under the Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) Project between January 2016 and January 2019. 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? Yes