Multidecadal Regime Shifts in U.S. Streamflow, Precipitation, and Temperature at the End of the Twentieth Century

Abstract

Intra-to multidecadal variation in annual streamflow, precipitation, and temperature over the continental United States are evaluated here through the calculation of Mann-Whitney U statistics over running-time windows of 6-30-yr duration. When this method is demonstrated on time series of nationally averaged annual precipitation and mean temperature during 1896-2001, it reveals that 8 of the 10 wettest years occurred during the last 29 yr of that 106-yr period, and 6 of the 10 warmest years during the last 16. Both of these results indicate highly significant departures from long-term stationarity in U.S. climate at the end of the twentieth century. The effects of increased wetness are primarily evident in the central and eastern United States, while evidence of warmth is found throughout the Rocky Mountain region and in the West. Analysis of annual streamflow records across the United States during 1939-98 shows broadly consistent effects. Initial evidence of the recent wet regime is most apparent in eastern streamflow, which shows a clear pattern of high-ranked mean annual values during the 1970s. Over the midwestern states, a coherent pattern of high-ranked annual flow is found during multidecadal periods beginning during the late 1960s and early 1970s and ending in either 1997 or 1998. During the late 1980s and early 1990s, a significant incidence of low-ranked annual flow conditions throughout the West was roughly coincident with the onset of western warmth during the mid-1980s. Evidence of highly significant transitions to wetter and warmer conditions nationally, and consistent variation in streamflow analyses, suggests that increased hydrological surplus in the central and eastern United States and increased hydrological deficit in the West may be representative of the initial stages of climate change over the continental United States.

Ecological thresholds and regime shifts: approaches to identification

“…This calls for sequential tests where the existence of a regime shift is tested for at every point in time, and which must be characterized by higher critical values of the test statistic than in classical statistical methods (cf. Box 2) Critical values at different significance levels are tabularized for regularly observed data points, typically time series [38] The most commonly investigated regime shift hypothesis is a step change in mean level using parametric [40,42,43] or non-parametric [44] methods. Regime shift detection methods involving changing variance, shift in the frequencies of fluctuations, or even simultaneous interrelated shifts in several ecosystem components at a particular point have also been proposed [45], but their application to practical data analysis has so far been limited.…”

Using paleoclimate reconstructions to analyse hydrological epochs associated with Pacific Decadal Variability

“…Panels (a1) and (b1) show that the unconditional run length distributions are different using 12 different window widths with the difference greater for a greater difference in window width. 13 However, panels (a3) and (b3) show that the conditional distributions for the longer runs are very 14 similar. This shows that both the short and long window widths extract the longer runs in a largely 15 consistent manner.…”

“…This study will use the Mann-Whitney test method (Mauget, 2003) with a given window 7 width w and confidence level α to identify the step-change points. However, other methods can be 8 used.…”

Nonstationarity of low flows and their timing in the eastern United States

“…However, our understanding of these low flow generating mechanisms is limited (Smakhtin, 2001), and is further compounded by the sensitivity of low flows to changes in climate, land use and human impacts on stream flow (Rolls et al, 2012). For example, large-scale teleconnections may play an important role in driving inter-annual to multi-decadal changes in streamflow (e.g., Mauget, 2003) and low flows (e.g., Giuntoli et al, 2013). Regulation generally introduces nonstationarity into low flow time series that impedes the development of regional or at-site frequency analysis models.…”