|
|||||
|
|
Non-stationarity of the signal and noise characteristics of seasonal precipitation anomalies |
|
| Authors: | Ian M Ferguson Philip B Duffy Thomas J Phillips Xu Liang John A Dracup Siegfried Schubert Philip Pegion |
| Institution: | 1. Department of Geology and Geological Engineering, Colorado School of Mines, Golden, CO, USA 2. Climate Central, Inc., Palo Alto, CA, USA 3. Program for Climate Model Diagnostics and Intercomparison, Lawrence Livermore National Laboratory, Livermore, CA, USA 4. Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA, USA 5. Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA 6. Global Modeling and Assimilation Office, National Aeronautics and Space Administration, Goddard Space Flight Center, Greenbelt, MD, USA 7. Earth Systems Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA |
| Abstract: | In order to improve seasonal-to-interannual precipitation forecasts and their application by decision makers, there is a clear need to understand when, where, and to what extent seasonal precipitation anomalies are driven by potentially predictable surface–atmosphere interactions versus to chaotic interannual atmospheric dynamics. Using a simple Monte Carlo approach, interannual variability and linear trends in the SST-forced signal and potential predictability of boreal winter precipitation anomalies is examined in an ensemble of twentieth century AGCM simulations. Signal and potential predictability are shown to be non-stationary over more than 80% of the globe, while chaotic noise is shown to be stationary over most of the globe. Correlation analysis with respect to magnitudes of the four leading modes of global SST variability suggests that interannual variability and trends in signal and potential predictability over 35% of the globe is associated with ENSO-related SST variability; signal and potential predictability are not significantly associated with SST modes characterized by a global SST trend, North Atlantic SST variability, and North Pacific SST variability, respectively. Results suggest that mechanisms other than SST variability contribute to the non-stationarity of signal and noise characteristics of hydroclimatic variability over mid- and high-latitude regions. |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ | |