Predictable and Unpredictable Components of Cape Town Winter Rainfall

Abstract

Abstract In early 2018, due in part to a severe and extended meteorological drought, Cape Town was at risk of being one of the first major metropolitan areas in the world to run out of water. The magnitude of the crisis was exacerbated by the fact that such a prolonged and severe drought was both unanticipated and unpredicted. In this work, we analyze data from both observations and seasonal forecasts made as part of the North American Multimodel Ensemble (NMME) to better understand the predictability of rainfall in the Cape Town (CT) region. We find that there are statistically significant correlations between observed CT rainfall and sea surface temperatures in the tropical Atlantic (∼0.45) as well as a pattern of 200-mb geopotential height (z200) anomalies resembling the Southern Annular Mode (SAM; ∼0.4). Examination of hindcasts from the NMME demonstrates that the models accurately reproduce the observed correlation between CT rainfall and z200 anomalies. However, they fail to reproduce correlations between CT rainfall and the tropical South Atlantic. Decomposition of the correlations into contributions from predictable and unpredictable components indicates that CT rainfall in the models is dominated by unpredicted atmospheric variability (correlation ∼ 0.84) relative to predicted (correlation ∼ 0.14), which may be related to the failure to simulate the connection with the tropical Atlantic. Significance Statement Water crises are occurring with increasing severity and frequency around the globe. The ability to accurately forecast wet season rainfall would be invaluable to water managers and other decision-makers. Here, we explore the reasons behind the failure of a suite of operational seasonal forecast models to accurately predict rainfall in the Cape Town region of South Africa.