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Evaluation of MJO Predictive Skill in Multiphysics and Multimodel Global Ensembles.
- Source :
- Monthly Weather Review; Jul2017, Vol. 145 Issue 7, p2555-2574, 20p, 1 Chart, 8 Graphs, 4 Maps
- Publication Year :
- 2017
-
Abstract
- Monthlong hindcasts of the Madden-Julian oscillation (MJO) from the atmospheric Flow-following Icosahedral Model coupled with an icosahedral-grid version of the Hybrid Coordinate Ocean Model (FIM-iHYCOM), and from the coupled Climate Forecast System, version 2 (CFSv2), are evaluated over the 12-yr period 1999-2010. Two sets of FIM-iHYCOM hindcasts are run to test the impact of using Grell-Freitas (FIM-CGF) versus simplified Arakawa-Schubert (FIM-SAS) deep convection parameterizations. Each hindcast set consists of four time-lagged ensemble members initialized weekly every 6 h from 1200 UTC Tuesday to 0600 UTC Wednesday. The ensemble means of FIM-CGF, FIM-SAS, and CFSv2 produce skillful forecasts of a variant of the Real-time Multivariate MJO (RMM) index out to 19, 17, and 17 days, respectively; this is consistent with FIM-CGF having the lowest root-mean-square errors (RMSEs) for zonal winds at both 850 and 200 hPa. FIM-CGF and CFSv2 exhibit similar RMSEs in RMM, and their multimodel ensemble mean extends skillful RMM prediction out to 21 days. Conversely, adding FIM-SAS-with much higher RMSEs-to CFSv2 (as a multimodel ensemble) or FIM-CGF (as a multiphysics ensemble) yields either little benefit, or even a degradation, compared to the better single-model ensemble mean. This suggests that multiphysics/multimodel ensemble mean forecasts may only add value when the individual models possess similar skill and error. An atmosphere-only version of FIM-CGF loses skill after 11 days, highlighting the importance of ocean coupling. Further examination reveals some sensitivity in skill and error metrics to the choice of MJO index. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00270644
- Volume :
- 145
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Monthly Weather Review
- Publication Type :
- Academic Journal
- Accession number :
- 126890156
- Full Text :
- https://doi.org/10.1175/MWR-D-16-0419.1