The INTENSE project: using observations and models to understand the past, present and future of sub-daily rainfall extremes.

Blenkinsop, S., H.J. Fowler, R. Barbero, S.C. Chan, S.B. Guerreiro, E. Kendon, G. Lenderink, E. Lewis, X.-F.Li, S. Westra, L. Alexander, R. Allan, P. Berg, R.J. Dunn, M. Ekstrom, J.P. Evans, G. Holland, R. Jones, E. Kjellstrom, A. Klein-Tank, D. Lettenmaier, V. Mishra, A.F. Prein, J. Sheffield, M.R. Tye
Advances in Science and Research, 15, 117-126, doi: 10.5194/asr-15-117-2018, 2018.

Abstract

Historical in situ sub-daily rainfall observations are essential for the understanding of short-duration rainfall extremes but records are typically not readily accessible and data are often subject to errors and inho- mogeneities. Furthermore, these events are poorly quantified in projections of future climate change making adaptation to the risk of flash flooding problematic. Consequently, knowledge of the processes contributing to intense, short-duration rainfall is less complete compared with those on daily timescales. The INTENSE project is addressing this global challenge by undertaking a data collection initiative that is coupled with advances in high-resolution climate modelling to better understand key processes and likely future change. The project has so far acquired data from over 23 000 rain gauges for its global sub-daily rainfall dataset (GSDR) and has provided evidence of an intensification of hourly extremes over the US. Studies of these observations, combined with model simulations, will continue to advance our understanding of the role of local-scale thermodynamics and large-scale atmospheric circulation in the generation of these events and how these might change in the future.

Key Figure


Figure 1. INTENSE project research themes, information flows and outcomes. The collection of in situ sub-daily rain gauge data represents a core project activity (blue arrows). Thermodynamic and atmospheric/ocean processes are considered independently (red and green arrows) but also in an integrated manner (yellow arrows). These data and knowledge will be used to evaluate model simulations of extreme rainfall across different timescales and locations. Model outputs will then be used for the development of process-based downscaling methods and provide guidance on the use of projections (black arrow). Data in dashed boxes denotes externally produced data used in the project.


UNSW    This page is maintained by Jason Evans | Last updated 23 January 2018