Clustering of Tibetan Plateau Vortices by 10–30-Day Intraseasonal Oscillation*

Abstract

Tibetan Plateau (TP) vortices and the related 10-30-day intraseasonal oscillation in May-September 1998 are analyzed using the twice-daily 500-hPa synoptic weather maps, multiple reanalysis datasets, and satelliteretrieved brightness temperature. During the analysis period, distinctively active and suppressed periods of TP vortices genesis are noticed. In 1998, nine active periods of TP vortices occurred, which were largely clustered by the cyclonic circulations associated with the intraseasonal oscillation of 500-hPa relative vorticity. In addition to the well-recognized 30-60-day oscillation, the clustering of TP vorticity in the 1998 summer are more likely modulated by the 10-30-day oscillation, because all active periods of TP vortices fall into the positive phase of the 10-30-day oscillation in 1998. Even in the negative (i.e., anticyclonic) phases of the 30-60-day oscillation, the positive (i.e., cyclonic) 500-hPa 10-30-day oscillation can excite the clustering of TP vortices. This result indicates that the 10-30-day oscillation more directly modulates the activities of TP vortices by providing a favorable (unfavorable) cyclonic (anticyclonic) environment. The analysis of the 10-30-day atmospheric oscillation suggests that the westerly trough disturbances, in conjunction with convective instability due to low-level warm advection from the Indian monsoon region, are important in the clustering of TP vortex activities. In particular, the moisture flux from the southwest boundary of TP is essential to the accumulation of convective energy. Thus, a better understanding and prediction of the 10-30-day intraseasonal oscillation is needed to advance the extended-range forecasting of TP vortices and their downstream impacts on the weather and climate over East Asia.

Quasi-Biweekly Oscillation over the Tibetan Plateau and Its Link with the Asian Summer Monsoon*

“…Then the active and break composites of filtered circulation, precipitation, moisture conditions, and diabatic heating are constructed in Fig. Zhang et al (2014) showed similar circulation and moisture conditions by analyzing TP vortices and the related 10-30-day intraseasonal oscillation. When the QBWO signal is active, more precipitation occurs in the CETP and its downstream area, while less occurs in northern India, northern China, and eastern China.…”

“…He et al (2006) found that, in summer, the southeastern TP was the most active ISV area of blackbody temperature. In particular, the ISV modes over the TP, to some extent, can influence local and even large-scale weather systems, including the plateau low vortex (Zhang et al 2014), subtropical high (Li et al 1991), and South Asian high (Liu and Lin 1991), as well as the precipitation anomaly in eastern China (Zhou et al 2000). ISV signals over the TP may originate from either the lower latitudes, such as the Bay of Bengal and the southern rim of the TP (Krishnamurti and Subrahmanyam 1982;Zhang et al 2009) or middle-to-high latitudes (Blackmon et al 1984a,b;Xie et al 1989).…”

Impact of East Asian Summer Monsoon Heating on the Interannual Variation of the South Asian High

“…For the former aspect, the location of the SAH center usually varies in the east-west direction, known as ''bimodality'': the Tibetan type (or eastern pattern) is when the center is located at the southern slope of the TP and the Iranian type (or western pattern) is when the center is located at the Plateau of Iran (IP). These two SAH types are associated with apparently different circulation at multiple time scales ranging from a few days to submonthly and interannual scales (Krishnamurti 1973;Liu et al 2007;Luo et al 1982;Wei et al 2014;Zhang et al 2014;Zhang et al 2002), which has been linked to extreme weather and climate events in Asia (Ye and Gao 1979). For the latter aspect, the SAH intensity is also linked to summer extreme climate events and rainfall anomalies over Asia and over western Africa, the North Pacific, and Central America, especially at interannual scales (Kanamitsu and Krishnamurti 1978;Zhang et al 2005;Zhao et al 2007).…”

Contribution of the North Atlantic subtropical high to regional climate model (RCM) skill in simulating southeastern United States summer precipitation

“…This study used multiple available reanalysis datasets (Table 1) to derive these variables in order to reduce the potential uncertainties introduced by the choice of reanalysis datasets, and thus ensure the robustness of the analysis results. A reanalysis ensemble method was applied, and the ensemble circulation fields were treated as an approximation of observed atmospheric circulation (Li et al 2013b;Zhang et al 2014). These variables simulated by the WRF were compared with the reanalysis ensemble to understand the causes of the precipitation bias in the WRF simulation.…”