Assessment of a climate model to reproduce rainfall variability and extremes over southern Africa

Williams, C J R, Kniveton, D R and Layberry, R (2007) Assessment of a climate model to reproduce rainfall variability and extremes over southern Africa. In: EGU General Assembly 2007., Vienna, Austria.

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Abstract

It is increasingly accepted that any possible climate
change will not only have an influence on mean climate but
may also significantly alter climatic variability. A change in
the distribution and magnitude of extreme rainfall events
(associated with changing variability), such as droughts or
flooding, may have a far greater impact on human and natural
systems than a changing mean. This issue is of particular
importance for environmentally vulnerable regions such as
southern Africa. The sub-continent is considered especially
vulnerable to and ill-equipped (in terms of adaptation) for
extreme events, due to a number of factors including extensive
poverty, famine, disease and political instability. Rainfall
variability and the identification of rainfall extremes is a
function of scale, so high spatial and temporal resolution data
are preferred to identify extreme events and accurately predict
future variability. The majority of previous climate model
verification studies have compared model output with
observational data at monthly timescales. In this research,
the assessment of ability of a state of the art climate model to
simulate climate at daily timescales is carried out using
satellite-derived rainfall data from the Microwave Infrared
Rainfall Algorithm (MIRA). This dataset covers the period
from 1993 to 2002 and the whole of southern Africa at a
spatial resolution of 0.1° longitude/latitude. This paper
concentrates primarily on the ability of the model to simulate
the spatial and temporal patterns of present-day rainfall
variability over southern Africa and is not intended to discuss
possible future changes in climate as these have been
documented elsewhere. Simulations of current climate from
the UK Meteorological Office Hadley Centre’s climate model,
in both regional and global mode, are firstly compared to the
MIRA dataset at daily timescales. Secondly, the ability of the
model to reproduce daily rainfall extremes is assessed, again
by a comparison with extremes from the MIRA dataset. The
results suggest that the model reproduces the number and
spatial distribution of rainfall extremes with some accuracy,
but that mean rainfall and rainfall variability is underestimated (over-estimated) over wet (dry) regions of southern
Africa

Item Type: Conference or Workshop Item (Paper)
Additional Information: Poster presentation
Schools and Departments: School of Global Studies > Geography
Depositing User: Dominic Kniveton
Date Deposited: 06 Feb 2012 15:12
Last Modified: 11 Apr 2012 13:44
URI: http://sro.sussex.ac.uk/id/eprint/11104
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