Walker, DP orcid.org/0000-0003-1687-0599, Birch, CE orcid.org/0000-0001-9384-2810, Marsham, JH orcid.org/0000-0003-3219-8472 et al. (3 more authors) (2019) Skill of dynamical and GHACOF consensus seasonal forecasts of East African rainfall. Climate Dynamics, 53 (7-8). pp. 4911-4935. ISSN 0930-7575
Abstract
Seasonal forecasts of rainfall are considered the priority timescale by many users in the tropics. In East Africa, the primary operational seasonal forecast for the region is produced by the Greater Horn of Africa Climate Outlook Forum (GHACOF), and issued ahead of each rainfall season. This study evaluates and compares the GHACOF consensus forecasts with dynamical model forecasts from the UK Met Office GloSea5 seasonal prediction system for the two rainy seasons. GloSea demonstrates positive skill (r = 0.69) for the short rains at 1 month lead. In contrast, skill is low for the long rains due to lack of predictability of driving factors. For both seasons GHACOF forecasts show generally lower levels of skill than GloSea. Several systematic errors within the GHACOF forecasts are identified; the largest being the tendency to over-estimate the likelihood of near normal rainfall, with over 70% (80%) of forecasts giving this category the highest probability in the short (long) rains. In a more detailed evaluation of GloSea, a large wet bias, increasing with forecast lead time, is identified in the short rains. This bias is attributed to a developing cold SST bias in the eastern Indian Ocean, driving an easterly wind bias across the equatorial Indian Ocean. These biases affect the mean state moisture availability, and could act to reduce the ability of the dynamical model in predicting interannual variability, which may also be relevant to predictions from coupled models on longer timescales.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Keywords: | seasonal climate forecasts; consensus outlooks; East Africa; Precipitation; Probabilistic verification |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) |
Funding Information: | Funder Grant number NERC NE/M02038X/1 NERC NE/P021077/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Jun 2019 13:41 |
Last Modified: | 25 Jun 2023 21:51 |
Status: | Published |
Publisher: | Springer Berlin Heidelberg |
Identification Number: | 10.1007/s00382-019-04835-9 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:146837 |
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