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Subseasonal prediction performance for austral summer South American rainfall

Klingaman, N. P. ORCID:, Young, M., Chevuturi, A. ORCID:, Guimaraes, B., Guo, L., Woolnough, S. ORCID:, Coelho, C. A. S., Kubota, P. Y. and Holloway, C. E. ORCID: (2021) Subseasonal prediction performance for austral summer South American rainfall. Weather and Forecasting, 36 (1). pp. 147-169. ISSN 0882-8156

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To link to this item DOI: 10.1175/WAF-D-19-0203.1


Skilful 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 the El Nino--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.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:94704
Publisher:American Meteorological Society


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