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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.

In early 2018, Cape Town (population ~3.7 million) was at risk of being one of the first major metropolitan areas in the world to run out of water. This was due to a severe multi-year drought that led to the levels of supply dams falling to an unprecedented low. Here we analyze rainfall data from the city catchment areas, including rare centennial records from the surrounding region, to assess the severity of the 2015–2017 drought. We find that there has been a long-term decline in the number of winter rainfall days, but this trend has been generally masked by fluctuations in rainfall intensity. The recent drought is unprecedented in the centennial record and represents a combination of the long-term decline in rainfall days and a more recent decline in rainfall intensity. Cold fronts during the winter months are responsible for most of the rainfall reaching Cape Town and our analysis shows no robust regional trend in the number of fronts over the last 40 years. Rather, the observed multidecadal decline in rainfall days, which threatens to increase the occurrence of severe drought, appears to be linked to a decrease in the duration of rainfall events associated with cold fronts. This change in rainfall characteristics associated with fronts appears to be linked to Hadley Cell expansion seen across the Southern Hemisphere and an increasing trend in post-frontal high-pressure conditions that suppress orographically enhanced rainfall.

Tropical cyclone (TC) landfalls over the U.S. mid-Atlantic region, which include the so-called Sandy-like, or westward-curving, tracks, are among the most infrequent landfalls along the U.S. East Coast. However, when these events do occur, the resulting economic and societal consequences can be devastating. A recent example is Hurricane Sandy in 2012. Multimodel ensemble seasonal hindcasts conducted with a high-atmospheric-resolution coupled prediction system based on the ECMWF operational model (Project Minerva) are used here to compile the statistics of these rare events. Minerva hindcasts are found to exhibit skill in reproducing climatological characteristics of the mid-Atlantic TC landfalls particularly at the highest atmospheric horizontal spectral resolution of T1279 (16-km grid spacing). Historical forecasts are further interrogated to identify regional and large-scale environmental conditions associated with these rare TC tracks to better quantify their predictability on synoptic time scales, and their dependence on model resolution. Evolution of the large-scale atmospheric flow patterns leading to mid-Atlantic TC landfalls is analyzed using local finite-amplitude wave activity (LWA). We have identified large-amplitude quasi-stationary features in the LWA and sea surface temperature (SST) anomaly distributions that persist up to about a week leading to these land-falling events. A statistical model utilizing indices based on the LWA and SST anomalies as predictors is developed that exhibits skill (mostly at T1279) in predicting mid-Atlantic TC landfalls several days in advance. Implications of these results for longer time-scale predictions of mid-Atlantic TC landfalls including climate change projections are discussed.