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  The importance of land-atmosphere interactions for future changes in extreme rainfall in convection permitting models


   NERC Doctoral Training Centre Studentships with CENTA

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  Dr M Widmann, Dr X Cai  No more applications being accepted  Competition Funded PhD Project (European/UK Students Only)

About the Project

Anthropogenic climate change is expected to lead to substantial increase in extreme precipitation with impact on flooding. However, simulating precipitation and how it may change in the future is still a major challenge, and associated with large uncertainties. One of the main problems is the important role of convection in generating precipitation. Until recently the spatial resolution of climate models was too coarse to resolve convection, and it was instead only approximately represented by so-called parameterisations. Over the last few years very high-resolution regional climate models, below 4km resolution, have been developed that resolve large storms and meso-scale organisation of convection explicitly. Simulations with such Convection-Permitting Models (CPMs) have shown much more realistic precipitation fields (Figure 1, Prein et al 2015; Chan et al 2014) and substantially stronger future changes in short-duration precipitation extremes compared to standard regional climate models (Kendon et al. 2014).

For reducing the uncertainties in regional climate change projections it is crucial to understand the processes that cause the climate change signal (Maraun et al. 2017, Maraun and Widmann 2018). CPMs allow for the first time to investigate in sufficient detail how land-atmosphere interactions, for instance related to soil-moisture variations or urban areas, influence precipitation and its future changes.

This project will exploit the first ensemble of CPM simulations over the UK within the UK Climate Projections UKCP18 project, which will feed into the Climate Change Risk Assessment (CCRA3). The aim is to compare the representation of soil moisture and surface hydrology in CPM and standard climate models, and investigate how it impacts on present and future convective rainfall. The ensemble will not only provide a large database for this analysis, but also allow for the first time an estimate of uncertainty in future changes at convection-permitting scale, thus providing UK risk assessment studies with more reliable climate change projections at local and hourly scales.

The student will be hosted jointly by the Met Office and the University of Birmingham, and also have extended visits at CEH and Cranfield University. This will ensure that the work will be undertaken in an efficient way, and will provide experience and networking possibilities in different research environments.

The project will bring together Met Office expertise in climate analysis and convective-scale climate modelling with CEH expertise in representing land surface hydrology in coupled land-atmosphere models, Cranfield University knowledge on soil properties and behaviour, and Birmingham experience with regional climate change, downscaling and urban modelling.

Funding Notes

CENTA studentships are for 3.5 years and are funded by NERC. In addition to the full payment of their tuition fees, successful candidates will receive the following financial support:

Annual stipend, set at £14,777 for 2018/19
Research training support grant (RTSG) of £8,000

References

Chan S.C., E.J. Kendon, H. J. Fowler, et al., 2014: The value of high-resolution Met Office regional climate models in the simulation of multihourly precipitation extremes. J. Climate, 27:6155–6174. doi: 10.1175/JCLI-D-13-00723.1
Kendon, E.J., N.M. Roberts, H.J. Fowler, et al., 2014: Heavier summer downpours with climate change revealed by weather forecast resolution model. Nature Climate Change, 4:570–576. doi: 10.1038/nclimate2258
Maraun, D and M. Widmann, 2018: Statistical downscaling and bias correction in climate research. Cambridge University Press, ISBN 1107066050.
Maraun, D, T. Shepherd, M. Widmann, G. Zappa , D. Walton, J. Gutierrez, S. Hagemann, I. Richter, P. Soares, A. Hall, and l. Mearns, 2017: Towards process-informed bias correction of climate change simulations. Nature Climate Change, 7 (11), 764-773.
Prein, A. F. et al., 2015: A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges, Review of Geophysics., 53, 323–361. doi:10.1002/2014RG000475

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