Details of Award
NERC Reference : NE/G018499/1
AMMA Further Analysis: Convective life-cycles over African continental surfaces
Grant Award
- Principal Investigator:
- Professor D Parker, University of Leeds, School of Earth and Environment
- Co-Investigator:
- Professor MJ Evans, University of York, Chemistry
- Co-Investigator:
- Professor J Peakall, University of Leeds, School of Earth and Environment
- Co-Investigator:
- Dr AN Ross, University of Leeds, School of Earth and Environment
- Grant held at:
- University of Leeds, School of Earth and Environment
- Science Area:
- Atmospheric
- Overall Classification:
- Atmospheric
- ENRIs:
- Global Change
- Environmental Risks and Hazards
- Science Topics:
- Land - Atmosphere Interactions
- Boundary Layer Meteorology
- Regional & Extreme Weather
- Climate & Climate Change
- Abstract:
- The population of West Africa rely on rainfall for their survival, since rainfall in most areas is the most important limit on agricultural production. Rainfall is also important in the availability of water for human consumption and for hydroelectric power generation, while the seasonal rainfall influences certain diseases such as malaria. Currently, our ability to predict rainfall in this region is extremely poor. This project aims to improve our understanding of the rain-bringing storms of West Africa, and improve our ability to forecast them. Through a knowledge-exchange programme with weather forecasters from the UK and West Africa, we will feed the new scientific understanding into daily and longer-term predictions. In the Sahel region during the monsoon season, most of the rain is delivered by large thunderstorm clouds, known as cumulonimbus, which can extend 20 kilometres upwards into the atmosphere. These cumulonimbus clouds band together into large, organised storms, several hundred km in extent, that produce intense rain, leading to patches of very wet soil. Often, after a storm, patches of wet soil lie adjacent to soil which remains extremely dry. In turn, the soil moisture patterns lie on top of a mixed distribution of vegetation, from forest to agriculture, savanna and desert. We know that such patterns in the land surface can interact with storms on the following days, and it is important to understand these processes for accurate weather forecasting. In the past, a major problem in quantifying this interaction between the land surface and cloud has been a lack of useful measurements from this remote region. Following the successful NERC-funded AMMA (African Monsoon Multidisciplinary Analysis) study, we now have unprecedented observational data for this region of the continental tropics. Using this dataset, we will analyse cases in which storms interact with the land surface, and therefore improve weather prediction models. The West African Monsoon is an airflow which brings humid air from the Atlantic Ocean into the continent: this humidity feeds the rain-bringing storms. However, moisture is also transported out of the low level, humid monsoon layer by smaller clouds, known as cumulus congestus. The rate at which moisture is mixed upwards by congestus clouds influences the water budget of the entire West African region, so we need to assess their effects if we are to get the forecast right. We will make use of chemical tracers measured during AMMA, to understand and evaluate the rates of congestus mixing, in reality and in models. We will use the UK Met Office weather and climate prediction model - the 'Unified Model' (UM). The UM is excellent for this kind of study because it can be used to describe a wide range of phenomena in the atmosphere, from small clouds a kilometre or so across, or the whole global atmosphere. Advances made in a sister project (Cascade) mean that now we have a version of the UM which can resolve clouds right across the continent, and assess the interactions between these clouds. Such interactions are just as important as the land surface state in setting off new storms -a big thunderstorm sets of patterns of waves in the atmosphere which move thousands of km across the continent and may commonly set off a new storm at a remote location. By resolving these processes in the Cascade version of the UM, we aim to understand what is needed to get them right in a weather prediction version of the UM. The UM is also used as a climate prediction model: currently, climate predictions for West Africa disagree on projections of future rainfall, which hinders effective mitigation strategies that could help in planning for local and international governments. The knowledge gained from this project will help not only in the day-to-day prediction of storm events but also in prediction of future rainfall trends.
- Period of Award:
- 1 Jun 2010 - 30 Nov 2013
- Value:
- £375,068 Lead Split Award
Authorised funds only
- NERC Reference:
- NE/G018499/1
- Grant Stage:
- Completed
- Scheme:
- Standard Grant (FEC)
- Grant Status:
- Closed
- Programme:
- Standard Grant
This grant award has a total value of £375,068
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Staff | DA - Other Directly Allocated | DI - T&S |
|---|---|---|---|---|---|---|
| £36,804 | £122,171 | £32,603 | £37,785 | £118,220 | £2,141 | £25,346 |
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