@article{dec6770c12f14c8493a27dd46ddd8060,
title = "Tropical rainfall predictions from multiple seasonal forecast systems",
abstract = "We quantify seasonal prediction skill of tropical winter rainfall in 14 climate forecast systems. High levels of seasonal prediction skill exist for year-to-year rainfall variability in all tropical ocean basins. The tropical East Pacific is the most skilful region, with very high correlation scores, and the tropical West Pacific is also highly skilful. Predictions of tropical Atlantic and Indian Ocean rainfall show lower but statistically significant scores. We compare prediction skill (measured against observed variability) with model predictability (using single forecasts as surrogate observations). Model predictability matches prediction skill in some regions but it is generally greater, especially over the Indian Ocean. We also find significant inter-basin connections in both observed and predicted rainfall. Teleconnections between basins due to El Ni{\~n}o–Southern Oscillation (ENSO) appear to be reproduced in multi-model predictions and are responsible for much of the prediction skill. They also explain the relative magnitude of inter-annual variability, the relative magnitude of predictable rainfall signals and the ranking of prediction skill across different basins. These seasonal tropical rainfall predictions exhibit a severe wet bias, often in excess of 20% of mean rainfall. However, we find little direct relationship between bias and prediction skill. Our results suggest that future prediction systems would be best improved through better model representation of inter-basin rainfall connections as these are strongly related to prediction skill, particularly in the Indian and West Pacific regions. Finally, we show that predictions of tropical rainfall alone can generate highly skilful forecasts of the main modes of extratropical circulation via linear relationships that might provide a useful tool to interpret real-time forecasts.",
keywords = "ENSO, NAO, PNA, ensemble, seasona prediction, tropical rainfall",
author = "Scaife, {Adam A.} and Laura Ferranti and Oscar Alves and Panos Athanasiadis and Johanna Baehr and Michel Dequ{\'e} and Tina Dippe and Nick Dunstone and David Fereday and Gudgel, {Richard G.} and Greatbatch, {Richard J.} and Leon Hermanson and Yukiko Imada and Shipra Jain and Arun Kumar and Craig MacLachlan and William Merryfield and M{\"u}ller, {Wolfgang A.} and Ren, {Hong Li} and Doug Smith and Yuhei Takaya and Vecchi, {Gabriel Andres} and Xiaosong Yang",
note = "Funding Information: information Joint DECC/Defra Met Office Hadley Centre Climate Programme, Grant/Award Number: GA01101; UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund; European Union 7th Framework Programme (FP7 2007–2013), Grant/Award Number: 603521; German Ministry of Education and Science, Grant/Award Numbers: 03G0837A, 01LP1517D; Universit{\"a}t Hamburg; Cluster of Excellence CliSAP, Grant/Award Number: EXC177; Ministry of Education and Research, Grant/Award Number: 01LP1519AThis work was supported by the UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund and the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). This paper is also an outcome of the “Interaction/teleconnection between tropics and extratropics” initiative of the World Climate Research Programme's Working Group on Subseasonal to Seasonal Prediction (WGSIP). We thank the WMO-WCRP for supporting this work and coordinating the CHFP database through the WGSIP. W.A.M. was supported by the German Ministry of Education and Research (BMBF) under the MiKlip project FLEXFORDEC (Grant No. 01LP1519A). J.B. was supported by the Cluster of Excellence CliSAP (EXC177), Universit{\"a}t Hamburg, funded through the German Science Foundation (DFG). T.C. and R.J.G. acknowledge support from the German Ministry of Education and Science (BMBF) through MiKlip2 subproject ATMOS-MODIN (Grant No. 01LP1517D) and SACUS (Grant No. 03G0837A) and by the European Union 7th Framework Programme (FP7 2007–2013) under Grant agreement 603521 PREFACE project. Funding Information: Joint DECC/Defra Met Office Hadley Centre Climate Programme, Grant/Award Number: GA01101; UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund; European Union 7th Framework Programme (FP7 2007–2013), Grant/ Award Number: 603521; German Ministry of Education and Science, Grant/Award Numbers: 03G0837A, 01LP1517D; Universit{\"a}t Hamburg; Cluster of Excellence CliSAP, Grant/Award Number: EXC177; Ministry of Education and Research, Grant/Award Number: 01LP1519A Funding Information: This work was supported by the UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund and the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). This paper is also an outcome of the “Interaction/teleconnection between tropics and extratropics” initiative of the World Climate Research Programme{\textquoteright}s Working Group on Subseasonal to Seasonal Prediction (WGSIP). We thank the WMO-WCRP for supporting this work and coordinating the CHFP database through the WGSIP. W.A.M. was supported by the German Ministry of Education and Research (BMBF) under the MiKlip project FLEXFORDEC (Grant No. 01LP1519A). J.B. was supported by the Cluster of Excellence CliSAP (EXC177), Universit{\"a}t Hamburg, funded through the German Science Foundation (DFG). T.C. and R.J.G. acknowledge support from the German Ministry of Education and Science (BMBF) through MiKlip2 subproject ATMOS-MODIN (Grant No. 01LP1517D) and SACUS (Grant No. 03G0837A) and by the European Union 7th Framework Programme (FP7 2007–2013) under Grant agreement 603521 PREFACE project. Publisher Copyright: {\textcopyright} 2018 Crown copyright, Met Office Weather {\textcopyright} 2018 Royal Meteorological Society This article is published with the permission of the Controller of HMSO and the Queen\u2019s Printer for Scotland",
year = "2019",
month = feb,
day = "1",
doi = "10.1002/joc.5855",
language = "English (US)",
volume = "39",
pages = "974--988",
journal = "International Journal of Climatology",
issn = "0899-8418",
publisher = "John Wiley and Sons Ltd",
number = "2",
}