Dominant patterns of US warm season precipitation variability in a fine resolution observational record, with focus on the southwest

Abstract

Spatial patterns of interannual variability in US precipitation and their forcing mechanisms are very different between the cool and warm seasons, as determined by the recent observational record. In this work, the dominant continental scale patterns of warm season precipitation variability, in the form of the standardized precipitation index (SPI), are related to their large-scale atmospheric teleconnection forcing patterns. To account for intraseasonal differences in atmospheric teleconnection patterns, the 2-month SPI is considered for the separate periods of early, June-July (JJ), and late, August-September (AS), periods, as well as the 6-month SPI for the cool season (November-April). Rotated empirical orthogonal function analysis and canonical correlation analysis are applied to determine the dominant spatial modes of SPI, their relationship to large-scale teleconnection patterns, and their possible forcing mechanisms, as seen in anomalies of 500-mb geopotential height, sea surface temperature (SST), and outgoing longwave radiation (OLR). Two dominant quasi-stationary Rossby wavetrain teleconnections appear to govern US warm season precipitation variability: (1) a mode that reflects the well-known out-of-phase relationship in summer precipitation between the central United States and southwest, which is related to Pacific SST forcing in early summer and Indian monsoon convection in later summer, and (2) Two phases of the Circumglobal Teleconnection pattern that are more related to precipitation variability in the south central and eastern United States The southwest United States region relating to the variability of the North American Monsoon is considered within the continental scale variability patterns associated with the warm season. This work is a subset of a larger project to determine if tree-ring records from the southwest United States are reliable proxies for extending the warm season climate record. It also provides a benchmark for assessing how US warm season climate patterns may be assessed in regional climate models used for seasonal forecast or climate change projection purposes.

Low‐frequency variability of precipitation in the North American monsoon region as diagnosed through earlywood and latewood tree‐ring chronologies in the southwestern US

“…To establish the linkage between Pacific‐SST forcing and its atmospheric teleconnection response with the tree‐ring network dominant modes of EW and LW adj , networks of tree‐ring chronologies are correlated with the corresponding SSTA and 500‐mb GPHA. The relationships with EW tree‐ring chronologies in Figure (a) and (b) show a clear winter ENSO‐PDV signature, just as in Figure (b) and in a similar analysis by Ciancarelli et al (). A well‐defined wave train from the western Pacific into the southern hemisphere is also observed.…”

“…The most predominant of these is the aforementioned ENSO-PDV response in early summer that accounts for the anti-phase relationship in warm season precipitation anomalies between the central United States and the Southwest (Higgins et al, 1997;Barlow et al, 1998;Castro et al, 2001Castro et al, , 2007Castro et al, , 2009Castro et al, , 2012Ciancarelli et al, 2013). In their analysis of LW adj tree-ring data from a subset of the southwestern tree-ring network, Ciancarelli et al (2013) showed a relationship to the aforementioned ENSO-PDV signal that is consistent with the instrumental record. However, the simultaneous effect of winter and summer was not addressed nor how this might be important in dual-season droughts.…”

“…Other work has investigated the relationships between monsoon precipitation in the Southwest and ocean/atmospheric circulation, and the manifestation of this relationship in a preliminary version of the monsoon tree‐ring network. Ciancarelli et al () identified several distinct warm season atmospheric teleconnection responses (quasi‐stationary Rossby wave trains) that control the continental‐scale spatial variability of US warm season precipitation. The most predominant of these is the aforementioned ENSO‐PDV response in early summer that accounts for the anti‐phase relationship in warm season precipitation anomalies between the central United States and the Southwest (Higgins et al , ; Barlow et al , ; Castro et al , , , , ; Ciancarelli et al , ).…”

“…Ciancarelli et al (2013) identified several distinct warm season atmospheric teleconnection responses (quasi-stationary Rossby wave trains) that control the continental-scale spatial variability of US warm season precipitation. The most predominant of these is the aforementioned ENSO-PDV response in early summer that accounts for the anti-phase relationship in warm season precipitation anomalies between the central United States and the Southwest (Higgins et al, 1997;Barlow et al, 1998;Castro et al, 2001Castro et al, , 2007Castro et al, , 2009Castro et al, , 2012Ciancarelli et al, 2013). In their analysis of LW adj tree-ring data from a subset of the southwestern tree-ring network, Ciancarelli et al (2013) showed a relationship to the aforementioned ENSO-PDV signal that is consistent with the instrumental record.…”

The more extreme nature of U.S. warm season climate in the recent observational record and two “well‐performing” dynamically downscaled CMIP3 models

“…Like the Indian monsoon, the NAMS is also strongly modulated by natural climate variability on interannual and intraseasonal time scales, complicating any assessment of how anthropogenic climate change may potentially influencing the monsoon [e.g., Arriaga-Ramirez and Cavazos, 2010]. NAMS interannual variability is partly controlled by warm season atmospheric teleconnections (i.e., quasi-stationary Rossby wave trains) emanating from the western tropical Pacific, related to the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Variability (PDV) [e.g., Castro et al, 2007aCastro et al, , 2007bGrantz et al, 2007;Ciancarelli et al, 2014]. By modulating the position of the monsoon ridge, a positive (negative) phase of ENSO-PDV is associated with a dry and delayed (wet and early) monsoon.…”