edu.ucar.opensky::articles:22383 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-25T15:48:18.442813 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7w380br Tropical rainfall predictions from multiple seasonal forecast systems 2018-10-07T00:00:00Z publication https://n2t.org/ark:/85065/d7w380br https://doi.org/10.1002/joc.5855 Scaife, A. A. author Ferranti, L. author Alves, O. author Athanasiadis, P. author Baehr, J. author Dequé, M. author Dippe, T. author Dunstone, N. author Fereday, D. author Gudgel, R. G. author Greatbatch, R. J. author Hermanson, L. author Imada, Y. author Jain, S. author Kumar, A. author MacLachlan, C. author Merryfield, W. author Müller, W. A. author Ren, H. author Smith, D. author Takaya, Y. author Vecchi, G. author Yang, Xiaosong author UCAR/NCAR - Library publisher 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 Nino-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. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright 2018 Crown copyright, Met Office Weather Copyright 2018 Royal Meteorological Society. This work is licensed as open access under a Creative Commons Attribution 4.0 International license. None eng geoscientificInformation