Journal of Climate
Oscillations, Climate Classification/regimes, Changepoint Analysis, Pattern Detection, Ranking Methods, Time Series
Atmospheric Sciences | Climate | Meteorology
In Part I of this paper, the optimal ranking regime (ORR) method was used to identify intradecadal to multidecadal (IMD) regimes in U.S. climate division temperature data during 1896–2012. Here, the method is used to test for annual and seasonal precipitation regimes during that same period. Water-year mean streamflow rankings at 125 U.S. Hydro-Climatic Data Network gauge stations are also evaluated during 1939–2011. The precipitation and streamflow regimes identified are compared with ORR-derived regimes in the Pacific decadal oscillation (PDO), the Atlantic multidecadal oscillation (AMO), and indices derived from gridded SST anomaly (SSTA) analysis data. Using a graphic display approach that allows for the comparison of IMD climate regimes in multiple time series, an interdecadal cycle in western precipitation is apparent after 1980, as is a similar cycle in northwestern streamflow. Before 1980, IMD regimes in northwestern streamflow and annual precipitation are in approximate antiphase with the PDO. One of the clearest IMD climate signals found in this analysis are post-1970 wet regimes in eastern U.S streamflow and annual precipitation, as well as in fall [September–November (SON)] precipitation. Pearson correlations between time series of annual and seasonal precipitation averaged over the eastern United States and SSTA analysis data show relatively extensive positive correlations between warming tropical SSTA and increasing fall precipitation. The possible Pacific and northern Atlantic roots of the recent eastern U.S. wet regime, as well as the general characteristics of U.S. climate variability in recent decades that emerge from this analysis and that of Part I, are discussed.
Steven A. Mauget and Eugene C. Cordero. "Optimal Ranking Regime Analysis of Intra- to Multidecadal U.S. Climate Variability. Part II: Precipitation and Streamflow" Journal of Climate (2014): 9027-9049. https://doi.org/10.1175/JCLI-D-14-00041.1