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Impact of Sea Surface Temperature Forcing on Weeks 3 and 4 Forecast Skill in the NCEP Global Ensemble Forecasting System.
- Source :
-
Weather & Forecasting . Dec2017, Vol. 32 Issue 6, p2159-2174. 16p. - Publication Year :
- 2017
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Abstract
- The Global Ensemble Forecasting System (GEFS) is being extended from 16 to 35 days to cover the subseasonal period, bridging weather and seasonal forecasts. In this study, the impact of SST forcing on the extended-range land-only global 2-m temperature, continental United States (CONUS) accumulated precipitation, and MJO skill are explored with version 11 of the GEFS (GEFSv11) under various SST forcing configurations. The configurations consist of 1) the operational GEFS 90-day e-folding time of the observed real-time global SST (RTG-SST) anomaly relaxed to climatology, 2) an optimal AMIP configuration using the observed daily RTG-SST analysis, 3) a two-tier approach using the CFSv2-predicted daily SST, and 4) a two-tier approach using bias-corrected CFSv2-predicted SST, updated every 24 h. The experimental period covers the fall of 2013 and the winter of 2013/14. The results indicate that there are small differences in the ranked probability skill scores (RPSSs) between the various SST forcing experiments.The improvements in forecast skill of the Northern Hemisphere 2-m temperature and precipitation for weeks 3 and 4 are marginal, especially for North America. The bias-corrected CFSv2-predicted SST experiment generally delivers superior performance with statistically significant improvement in spatially and temporally aggregated 2-m temperature RPSSs over North America. Improved representation of the SST forcing (AMIP) increased the forecast skill for MJO indices up through week 2, but there is no significant improvement of theMJO forecast skill for weeks 3 and 4. These results are obtained over a short period with weak MJO activity and are also subject to internal model weaknesses in representing the MJO. Additional studies covering longer periods with upgraded model physics are warranted. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 08828156
- Volume :
- 32
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Weather & Forecasting
- Publication Type :
- Academic Journal
- Accession number :
- 127914523
- Full Text :
- https://doi.org/10.1175/WAF-D-17-0093.1