Variations in the correlation between teleconnections and Taiwan's streamflow

Abstract

Abstract. Interannual variations in catchment streamflow represent an integrated response to anomalies in regional moisture transport and atmospheric circulations and are ultimately linked to large-scale climate oscillations. This study conducts correlation analysis to calculate how summertime (July–September, JAS) streamflow data derived at 28 upstream and 13 downstream gauges in Taiwan correlate with 14 teleconnection indices in the current or preceding seasons. We find that the western Pacific (WP) and Pacific–Japan (PJ) patterns, both of which play a critical role in determining cyclonic activity in the western North Pacific basin, exhibit the highest concurrent correlations (most significant r = 0. 50) with the JAS flows in Taiwan. Alternatively, the Quasi-Biennial Oscillation (QBO) averaged over the period from the previous October to June of the current year is significantly correlated with the JAS flows (most significant r = −0. 66), indicating some forecasting utility. By further examining the correlation results using a 20-year moving window, peculiar temporal variations and possible climate regime shifts (CRSs) can be revealed. A CRS test is employed to identify suspicious and abrupt changes in the correlation. The late 1970s and 1990s are identified as two significant change points. During the intermediate period, Taiwan's streamflow and the PJ index exhibit a marked in-phase relationship (r > 0. 8). It is verified that the two shifts are in concordance with the alteration of large-scale circulations in the Pacific basin by investigating the changes in pattern correlation and composite maps before and after the change point. Our results suggest that empirical forecasting techniques should take into account the effect of CRSs on predictor screening.

Space- and time-varying associations between Bangladesh's seasonal rainfall and large-scale climate oscillations

“…Additional teleconnection patterns to those adopted in this study could potentially yield significant associations with Bangladesh's seasonal rainfall as well, so incorporating more climate indices in the analysis is one of the top priorities in the future. Further, from both correlation and WC analyses, we found the time-varying, multi-time-scale relationship between the climate indices and seasonal rainfall; such findings imply that it is essential to establish a nonstationary forecasting model of seasonal rainfall able to account for the regime shift in the predictor-predictand relationship [17]. Such forecasting model should be sensitive enough to automatically detect and select most contributing predictors based on preceding conditions of the large-scale environment.…”

“…In addition to concurrent correlations, we also performed moving-window correlation analysis [17] to identify non-stationary characteristics of the association between seasonal rains and teleconnections. A temporal window of 20 years was used to compute correlation over that time period, and the computation swept over the entire data set, moving from the first 20-year window (1965)(1966)(1967)(1968)(1969)(1970)(1971)(1972)(1973)(1974)(1975)(1976)(1977)(1978)(1979)(1980)(1981)(1982)(1983)(1984) to the last (1998-2017) at a 1-year time step.…”

“…Using conventional composite or correlation analysis for teleconnection studies poses another concern for the incapability of addressing non-stationarity and multi-scale relationships between teleconnection patterns and hydro-climatic variables [75,17], which should be accounted for owing to the nonlinear nature of climate systems [68,40,37]. Therefore, the better understanding of nonstationarity underneath teleconnections relies on more adequate techniques, such as moving-window correlation and wavelet analysis [14].…”

Meaningful Trend in Climate Time Series: A Discussion Based On Linear and Smoothing Techniques for Drought Analysis in Taiwan

“…Due to various conditions (e.g., wind directions and topography), the seasonal pattern of rainfall resembles a uniform distribution in northern and eastern Taiwan, but exhibits a unimodal summer peak in central and southern Taiwan. Because of such high spatiotemporal variability, in company with the influence of climate oscillations [19], multiple historical drought events have still been witnessed. In fact, people in Taiwan just experienced an unprecedented drought event in nearly 60 years from late 2020 to middle 2021.…”

Long-term forecasting of appearance dates of ice phenomena and freeze-up at the Dnipro Cascade reservoirs by teleconnection indicators

“…In papers (Shimaraev, 2007;Sizova et al, 2013;Sutyrina, 2017;Khrystiuk and Gorbachova, 2022) the teleconnection indices were used for the long-term forecasting of the water bodies ice regime and acceptable results were obtained. In the world, the use of the teleconnection indices and patterns is a well-known methodological approach in the hydroclimatic forecasting, which allows forecasting weeks to months in advance (van den Dool, 2007;Chen and Georgakakos, 2014;Chen and Lee, 2017). For the first time, the concept of using teleconnections was proposed by Ångström (1935) who described the correlations between remote oscillations of the atmospheric circulation and anomalies.…”