Abstract
AbstractSkillful and reliable predictions of week-to-week rainfall variations in South America, two to three weeks ahead, are essential to protect lives, livelihoods, and ecosystems. We evaluate forecast performance for weekly rainfall in extended austral summer (November–March) in four contemporary subseasonal systems, including a new Brazilian model, at 1–5-week leads for 1999–2010. We measure performance by the correlation coefficient (in time) between predicted and observed rainfall; we measure skill by the Brier skill score for rainfall terciles against a climatological reference forecast. We assess unconditional performance (i.e., regardless of initial condition) and conditional performance based on the initial phase of the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO). All models display substantial mean rainfall biases, including dry biases in Amazonia and wet biases near the Andes, which are established by week 1 and vary little thereafter. Unconditional performance extends to week 2 in all regions except for Amazonia and the Andes, but to week 3 only over northern, northeastern, and southeastern South America. Skill for upper- and lower-tercile rainfall extends only to week 1. Conditional performance is not systematically or significantly higher than unconditional performance; ENSO and MJO events provide limited “windows of opportunity” for improved S2S predictions that are region and model dependent. Conditional performance may be degraded by errors in predicted ENSO and MJO teleconnections to regional rainfall, even at short lead times.
Highlights
Subseasonal to seasonal (S2S) variations in local- and regional-scale rainfall present considerable hazards in the tropics, through floods and meteorological droughts that reduce agricultural yields, limit hydropower generation, and degrade human and ecosystem health
We investigate S2S prediction quality for South American weekly rainfall in four recent forecast models, including conditional performance evaluation based on Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO) phases to understand whether large-scale variability improves S2S forecasts
To understand the potential for conditional prediction of rainfall based on largescale tropical variability, we compute mean biases, errors and performance conditioned on the phases of ENSO and the MJO
Summary
Subseasonal to seasonal (S2S) variations in local- and regional-scale rainfall present considerable hazards in the tropics, through floods and meteorological droughts that reduce agricultural yields, limit hydropower generation, and degrade human and ecosystem health. In monsoonal regions where the seasonal cycle is strong and assumed to be predictable, crop sowing dates are tied to climatological rainfall onset. ‘‘false onsets’’ in which breaks in the rains immediately follows onset, cause seeds to fail to germinate and lead to substantial agricultural losses (e.g., Marteau et al 2011). Flooding after planting substantially reduces yields; heavy rain during harvest can delay harvests or damage crops (e.g., Coomes et al 2016). The perceived lack of Denotes content that is immediately available upon publication as open access
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