Changes In Growing-season Rainfall Characteristics And Downscaled Scenarios Of Change Over Southern Africa: Implications For Growing Maize

Author: Mark Tadross, Pablo Suarez, Alex Lotsch, Sepo Hachigonta, Marshall Mdoka, Leonard Unganai, Filipe Lucio, Donald Kamdonyo, and Maurice Muchinda

Year: Unknown

Category: Corporate Reports

Abstract

Global climate change is a detectable and attributable phenomenon, yet its manifestation at the regional scale, especially within the rainfall record, can be difficult to characterize due to the high degree of variability. At the same time, an understanding of historical change is essential in order to provide context for climate change projections, as well as a credible basis for adaptation. Over southern Africa this task is complicated by particularly erratic rainfall, the presence of multidecadal trends, and limited data with sparse spatial coverage. Furthermore, climate models suggest that competing responses (such as increasing numbers of dry days, coupled with increases in rainfall intensity), working at different timescales, will serve to additionally mask any signals in the time-averaged total rainfall. Ideally, the changes in the secondary attributes can then be compared with equivalent attributes from downscaled climate scenarios to assess agreement and contribute to confidence in projected downscaled data. However, downscaled scenarios may suffer from varied biases and limitations due to their methodological approach, e.g. rainfall parameterisations within RCMs and neglected land-climate interactions within empirically derived scenarios. These limitations may lead to inconsistencies between different sources of information. The comparisons described earlier, based on secondary attributes and sub-seasonal timescales, facilitate highlighting areas of weakness in each downscaling, which may not be readily manifest in the more commonly used time-averaged products. These issues are explored using data from southern Africa; station observations of daily rainfall, dynamical scenarios from 2 regional climate models and empirical scenarios from 6 general circulation models. The observations are analysed for detectable trends in the start, end, and duration of the rainfall season, as well as number of dry days, length of dry spells and measures of rainfall intensity during critical periods for agriculture. Correlations with the Southern Oscillation Index (SOI) and Antarctic Oscillation (AAO) are used to infer how large-scale climate variability affects these attributes of rainfall and highlight where (and when) trends may contribute to more frequent crossings of critical thresholds. Trends are also compared with and discussed in relation to changes projected in the downscaled scenarios, highlighting inconsistencies, which may be due to systematic biases in each methodology. The implications for agricultural adaptation are examined and discussed. The paper suggests that when building scenarios of climate change, a wide range of models and methodologies should be interrogated and their interpretation relies heavily on understanding the methods and underlying physical processes. Furthermore, such processes act across political boundaries and collaboration across institutions, as highlighted here, is needed to confidently make regional assessments.

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