Abstract
Abstract Current seasonal prediction of rainfall typically focuses on 3-month rainfall totals at regional scale. This temporal summation reduces the noise related to smaller-scale weather variability but also implicitly emphasizes the peak of the climatological seasonal cycle of rainfall. This approach may hide potentially predictable signals when rainfall is lower: for example, near the onset or cessation of the rainy season. The authors illustrate such a case for the East African long rains (March–May) on a network of 36 stations in Kenya and north Tanzania from 1961 to 2001. Spatial coherence and potential predictability of seasonal rainfall anomalies associated with tropical sea surface temperature (SST) anomalies clearly peak during the early stage of the rainy season (in March), while the largest rainfall (in April and May) is far less spatially coherent; the latter is shown to contain a large noise component at the station scale that characterizes interannual variability of the March–May seasonal total amounts. Combining the empirical orthogonal function of both interannual and subseasonal variations with a fuzzy k-means clustering is shown to capture the most spatially coherent subseasonal “scenarios” that tend to filter out the noisier variations of the rainfall field and emphasize the most consistent signals in both time and space. This approach is shown to provide insight into the seasonal predictability of long dry spells and heavy daily rainfall events at local scale and their subseasonal modulation.
Highlights
Seasonal forecasts of tropical rainfall are issued routinely by global centers using general circulation models (GCMs; e.g., Kumar et al 1996; Livezey et al 1996; Goddard et al 2001, 2003; Barnston et al 2003, 2010; Friederichs and Paeth 2005; Saha et al 2006; Batteand Deque 2011)
The canonical correlation analysis (CCA) is cross validated with one year left out at each turn and the predictors and predictands are prefiltered with empirical orthogonal function (EOF)
We have presented a conceptual analysis of the seasonal predictability from a rather new perspective
Summary
Seasonal forecasts of tropical rainfall are issued routinely by global centers using general circulation models (GCMs; e.g., Kumar et al 1996; Livezey et al 1996; Goddard et al 2001, 2003; Barnston et al 2003, 2010; Friederichs and Paeth 2005; Saha et al 2006; Batteand Deque 2011). Negative rainfall anomalies are widespread during the onset stage of the monsoon over Indonesia in September–December of El Nino years (Haylock and McBride 2001; Moron et al 2009b, 2010) but less coherent during the core of the rainy season in December–March (Chang et al 2005; Moron et al 2009b, 2010). These rainfall anomalies tend to become positive over mountainous parts of Java (Qian et al 2010). Reducing the length of the time average such as using fixed calendar months would adversely enhance the noise and may artificially cut consistent periods during a given season
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