Relationships between subseasonal‐to‐seasonal predictability and spatial scales in tropical rainfall
Résumé
Subseasonal to seasonal (S2S) tropical rainfall predictability is assessed both from an analysis of the spatial scales of observed rainfall variability data, as well as from an S2S model reforecast skill. Observed spatial scales are quantified from gridded observed daily rainfall data, in terms of the size (area) of daily contiguous wet grid-points (referred to as 'wet patches'), as well as from the spatial autocorrelations of 7-91-day running averages of rainfall. Model S2S reforecast skill is measured using the anomaly correlation coefficient between observed and simulated weekly and monthly rainfall from an 11-member ensemble of European Centre for Medium-Range Weather Forecasts (ECMWF) reforecasts (1998-2017). Both measures of S2S predictability are found to be systematically lower over land than sea, usually peaking at the start or end of the rainy season and decreasing during the core. Small spatial scales and low skill over equatorial/northern tropical Africa and western Amazonia coincide with small daily rainfall patch size and strong synoptic-scale (≤7 days) variability there. Over most of South and SE Asia, daily wet patches are larger and strongly modulated by intraseasonal oscillations, boosting S2S rainfall predictability, while this is offset by large daily mean rainfall intensities that increase the noise. In consequence, S2S rainfall skill here generally remains low. Several land areas (as around Maritime Continent from the Philippines to Northern Australia, Eastern and Southern Africa, Eastern South America) exhibit larger spatial scales and skill, especially where the relative amplitude of SST-forced interannual variations is strong. Most of the Maritime Continent illustrates such behaviour, but even here, the time-averaged spatial scales and skill drop during the core of the rainy season.