Abstract
This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled control run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño-Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.
Original language | English |
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Pages (from-to) | 8517-8537 |
Number of pages | 21 |
Journal | Journal of Climate |
Volume | 30 |
Issue number | 21 |
DOIs | |
State | Published - Nov 1 2017 |
Funding
Acknowledgments. This work is funded by U.S. Department of Energy (DOE) Regional and Global Climate Modeling (RGCM) Program (Grant PRJ88SM) and National Science Foundation (NSF) Climate and Large-Scale Dynamics (CLD) Program (Grant 1343904). Computer resources are provided by DOE National Energy Research Scientific Computing Center (NERSC) and National Science Foundation Computational Information Systems Laboratory Yellowstone (NSF/ CISL/Yellowstone). We also acknowledge the CESM Large Ensemble Community Project. We also thank two anonymous reviewers for their excellent suggestions and comments.
Funders | Funder number |
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DOE National Energy Research Scientific Computing Center | |
NERSC | |
National Science Foundation Computational Information Systems Laboratory Yellowstone | NSF/ CISL/Yellowstone |
National Science Foundation | |
U.S. Department of Energy | PRJ88SM |
Directorate for Geosciences | 1343904 |
Keywords
- Africa
- Atmosphere
- General circulation models
- Interannual variability
- Ocean