1. Introduction
During boreal summer, the geographical distribution of land and ocean, the pattern of land and sea surface temperature (SST), and the location of topographic features contribute to driving regional patterns of intense precipitation over southern and eastern Asia and the surrounding oceans. Figure 1a shows the climatological precipitation rate for July, as estimated by the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) (Huffman et al. 2007). In the Eastern Hemisphere, three major precipitation centers are associated with the Asian monsoon: over the west coast of India, the eastern Bay of Bengal, and the Philippines. Smaller regions of intense precipitation are also found in Southeast Asia and along the southern margin of the Himalayan front. Less intense precipitation covers a large area over the western Pacific warm pool that lies at the western end of the intertropical convergence zone (ITCZ). This area extends southeastward across the equator and connects with the South Pacific convergence zone (SPCZ). By contrast, the major precipitation areas in the Western Hemisphere are located closer to the equator in the equatorial Pacific and Atlantic ITCZs, Central America, and northern South America.
(a) TMPA July climatological precipitation rate (color). (b) ERA-Interim July climatological zonal wind u at 370 K (red: u > 0; blue: u < 0; gray: u = 0; interval: 5 m s−1). ERA-Interim July climatological Montgomery streamfunction Ψ at 370 K (black solid contours; interval: 0.5 kJ kg−1). The location of the global maximum of Ψ along the zero-wind lines (u = 0) is indicated by red crosshairs. Climatological positions of the Asian and North American monsoon anticyclones, midoceanic troughs, and westerly ducts are labeled and indicated by arrows.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
The regional precipitation patterns drive two large-scale anticyclonic circulations (Fig. 1) in the Northern Hemisphere upper troposphere and lower stratosphere (UTLS): the Asian monsoon anticyclone (AMA) and the North American monsoon anticyclone (NAMA). In a simple framework these circulations can be understood as the linear steady Rossby wave response to the latent heat released by monsoon precipitation (Gill 1980; Hoskins and Rodwell 1995; Highwood and Hoskins 1998; Siu and Bowman 2019). The AMA is also referred to as the South Asian high (SAH) or Tibetan anticyclone in the literature. The AMA circulation is flanked by the tropical easterly jet to the south and the subtropical westerly jet to the north (Fig. 1b). Siu and Bowman (2019) showed that the NAMA circulation, which is much weaker than its Asian counterpart, is mainly forced by the less intense subtropical precipitation over Mexico and the southern United States, not by the tropical precipitation in the Western Hemisphere. Two midoceanic troughs over the Pacific and the Atlantic (Fig. 1a), which are associated with the westerly ducts (Fig. 1b), separate these two anticyclones (Krishnamurti 1971; Webster and Holton 1982). The intraseasonal variabilities of the Asian monsoon are usually dominated by 10–20- and 30–60-day time scales (Ortega et al. 2017). The former one, also known as the quasi-biweekly oscillation, represents a large amount of the regional precipitation variabilities and has been shown to correlate with the evolution of the AMA at the similar time scale (Krishnamurti and Bhalme 1976; Ortega et al. 2017; Wei et al. 2019).
The discovery of the AMA closely follows the development of upper-air observations. Early studies (e.g., Flohn 1950; Dao and Chen 1957; Koteswaram 1958) noticed a high pressure system in the middle and upper troposphere above the Tibetan Plateau from sparse aerological data. Additional research was catalyzed by the International Geophysical Year (IGY) of 1957–58. The World Meteorological Organization (WMO) made considerable efforts during the IGY to expand the global radiosonde network, standardize the observation times, and improve the data quality with better sounding techniques (van Mieghem 1956). The existence of the AMA was first verified through synoptic upper-air weather maps compiled from IGY radiosonde data (Koteswaram and Rao 1963; Mason and Anderson 1963; Rangarajan 1963). Since then, the AMA has been regarded as an integral component of the Asian summer monsoon system (Krishnamurti and Bhalme 1976). Apart from routine radiosonde launches and satellite measurements (e.g., Santee et al. 2017; Luo et al. 2018), the structure and composition of the AMA have been investigated by several field campaigns in the past decade (e.g., Baker et al. 2011; Brunamonti et al. 2018; Gottschaldt et al. 2018; Vernier et al. 2018).
The AMA circulation can be identified on a map by closed contours of high values of Montgomery streamfunction Ψ (black contours in Fig. 1), high geopotential height Z, or low potential vorticity (PV). Figure 2 shows the seasonal evolution of the climatological Ψ and PV in the Eastern Hemisphere (Hovmöller 1949). A 32-day ideal low-pass Fourier filter has been applied to the original 6-hourly time series of both fields and a smaller contour interval (0.1 kJ kg−1) is used for Ψ > 357 kJ kg−1. The AMA circulation emerges in May and dissipates in September, persisting through much of the warm season. The location of the maximum of Ψ (thick black line) shows that in general the circulation center lies between ~60° and ~100°E. Both fields are rather flat in the interior of the anticyclone during July and early August. In the climatology there is a jump in the location of the center of the AMA circulation (as defined by Ψ), that occurs in mid-July. Toward the end of the warm season, a downstream development of the circulation east of 120°E is indicated by an arrow.
Hovmöller plot of ERA-Interim climatological Montgomery streamfunction Ψ (solid contours for Ψ ≤ 357 kJ kg−1, interval: 0.5 kJ kg−1; dashed contours for Ψ > 357 kJ kg−1, interval: 0.1 kJ kg−1) and PV (colors) at 370 K. The original time series of Ψ and PV at each longitude are the latitudinal averages between 25° and 35°N. A 32-day ideal low-pass Fourier filter has been applied to smooth the time series. The time series of the maximum of Ψ and a downstream development of the circulation are indicated by the thick black line and the black arrow, respectively. A similar plot for the year of 2017 is shown in Fig. 7.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
Synoptic analysis of the AMA reveals more complicated space–time variations (Fig. 3). Our current understanding of the underlying mechanisms is rather limited (Randel and Jensen 2013). Early studies noticed a zonal movement of the AMA on synoptic maps and termed it the east–west oscillation (e.g., Mason and Anderson 1963; Dao and Chu 1964). Using a pentad-mean reanalysis dataset, Zhang et al. (2002) first suggested that the longitudinal distribution of the AMA is bimodal. That is, the AMA has two preferred circulation center locations, one over Iran (~60°E) and one above the Tibetan Plateau (~90°E). These are referred to as the Iranian high (Fig. 3a) and Tibetan high (Fig. 3b), respectively. A number of studies have focused on the bimodality issue (e.g., Zarrin et al. 2010; Yan et al. 2011; Garny and Randel 2013; Ploeger et al. 2015; Nützel et al. 2016; Yang and Li 2016; Amemiya and Sato 2018; Wei et al. 2019; Honomichl and Pan 2020). See Nützel et al. (2016) for a detailed review.
Snapshots showcasing the intraseasonal variabilities of the Asian monsoon anticyclone in 2018. Notable vortex centers are indicated by yellow crosshairs. ERA-Interim PV (color). One-vortex cases: (a) Tibetan, (b) Iranian, and (c) Bonin highs. (d) Two and (e) three subvortices. Frequencies of one, two, and three persistent subvortices present at each analysis time for the period of 1979–2018 are labeled on the left (see also Table 2).
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
This interpretation of the AMA as having a single circulation center with two preferred locations is misleading. As we will show, most of the time there are two or three distinct circulation centers present within the AMA. We refer to these as subvortices (Dunkerton 1995; Dethof et al. 1999). Most previous analyses of the AMA explicitly assume that the AMA has only a single center; Zarrin et al. (2010) is the only geopotential height–based study listed in Nützel et al. (2016) that detects multiple centers. For example, to find the AMA center Zhang et al. (2002) first identify the boundary between the tropical easterlies and subtropical westerlies at a specified vertical level [i.e., the zero-wind line (u = 0) on a pressure or isentropic surface]. The AMA center is then defined to be the location of the maximum geopotential height along that line on the pressure surface or the maximum Montgomery streamfunction on the isentropic surface. Other local maxima along the zero-wind line are ignored. Examples of multiple subvortices are shown in Figs. 3d and 3e. If the single-center method of Zhang et al. (2002) is used, the “center” of the AMA would jump between the subvortices as their relative strength varies.
The single-center assumption is also at odds with observed transient behavior. Eddy-shedding episodes in the AMA have been documented in several observational studies (e.g., Hsu and Plumb 2000; Popovic and Plumb 2001; Vogel et al. 2014; Ploeger et al. 2015; Ungermann et al. 2016; Vogel et al. 2016; Fadnavis et al. 2018). Hsu and Plumb (2000) showed that by imposing sufficient asymmetries in a shallow-water model, an anticyclonic vortex could become unstable, split, and shed eddies from the main vortex. By its nature, a method that detects only the strongest vortex center is unable to diagnose this kind of behavior. It is also not clear whether eddy shedding operates through a simple pinching-off process, as shown schematically in Fig. 4.
Schematic of one possible mode by which fluid is expelled from the anticyclone through pinching off a compact mass of fluid. The arrow between (b) and (c) indicates the source of the fluid in the detached blob of fluid moving to the right.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
Besides the single-center assumption, the existence of bimodality (or lack thereof) is also influenced by other factors. For example, previous studies usually used time-averaged and/or spatially smoothed reanalysis data. Most found that a bimodal distribution exists in pentad-mean, monthly mean, and seasonal-mean data (e.g., Qian et al. 2002; Zhang et al. 2002; Wei et al. 2014), but the results for daily mean data are mixed (e.g., Garny and Randel 2013; Nützel et al. 2016; Yang and Li 2016). It may also be an artifact of the chosen dataset because only two reanalysis datasets, including National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis (NCEP–NCAR; Kalnay et al. 1996) and NCEP–Department of Energy reanalysis (NCEP–DOE; Kanamitsu et al. 2002), have clearly shown bimodality (Nützel et al. 2016).
Understanding the transient behavior of the AMA is important because of its potential impact on the composition of the UTLS (Holton et al. 1995; Dethof et al. 1999). Coupled with deep convection, boundary layer pollutants can be effectively transported into the UTLS (Randel and Park 2006; Bergman et al. 2013). Once within the AMA, these trace gases may be confined inside the circulation (Ploeger et al. 2015), but mass and trace gas exchanges between the upper troposphere and lower stratosphere can occur along isentropic surfaces (Chen 1995; Dethof et al. 1999; Homeyer et al. 2011; Homeyer and Bowman 2013). The fluid within the AMA may also be exported via eddy shedding.
In this study we modify the method used by Zhang et al. (2002) to detect multiple simultaneous circulation centers within the AMA. The instantaneous analyses, which use minimal spatial and no temporal smoothing, are linked in time to diagnose subvortex behavior. We find that most of the time multiple anticyclonic subvortices are present within the AMA. These subvortices display a variety of behaviors including splitting and merger as well as eastward and westward eddy shedding. Lagrangian diagnostics are used to show that the behavior of the subvortices plays an important role in stirring of air within the AMA and export of air from the AMA to global atmosphere.
2. Data
a. ERA-Interim
The primary data source for this study is the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim; Dee et al. 2011). We use 40 years (1979–2018) of ERA-Interim data obtained from the NCAR Research Data Archive (RDA) (ECMWF 2009). Analyses are available at 6-h intervals (0000, 0600, 1200, and 1800 UTC) on the N128 global reduced-Gaussian grid with a latitude–longitude grid spacing of ~0.7° × ~0.7° (~80 km × ~80 km). Here we use ERA-Interim variables that have been interpolated from the original 60-level η-coordinate model grid to 15 irregularly spaced isentropic surfaces from 265 to 850 K. Daily and monthly averages are computed as a simple arithmetic average of the 6-hourly data for the period from 1979 to 2018. Climatological monthly averages are computed in a similar method from the monthly averages. Comparisons of selected cases with the newer ERA5 (Copernicus Climate Change Service 2017; Hersbach et al. 2020) show little difference, so all of the results presented here use ERA-Interim data.
b. TMPA
Precipitation estimates come from version 7 of the TMPA (Huffman et al. 2007; Huffman and Bolvin 2018). This analysis is also referred to as the 3B42 product. We use 19 years (1998–2016) of TMPA obtained from the National Aeronautics and Space Administration (NASA) Precipitation Measurement Missions (PMM) data archive (TRMM 2011). The TMPA is based primarily on measurements from microwave imaging radiometers on multiple satellites. The TMPA data cover the latitude zone from 50°S to 50°N. Data consist of area-averaged precipitation rates for 0.25° × 0.25° longitude–latitude grid boxes at 3-h intervals centered on the nominal observing times of 0000, 0300, …, 2100 UTC. Within each 3-h window, if observations are available for a grid box from multiple microwave instruments, the values are averaged using simple arithmetic averaging. Monthly and climatological averages are computed in a similar method from the 3-hourly data and monthly averages, respectively.
3. Methods
a. Eulerian diagnostics
Here we present an improved method based on the single-center method of Zhang et al. (2002) to identify and track multiple monsoon subvortices in three steps. This is referred to here as the multiple-center method. The ERA-Interim variables used to locate vortices include the Montgomery streamfunction Ψ, zonal wind u, and relative vorticity ζ.
1) Marching squares algorithm
The first step is to identify zonal zero-wind lines for the specified domain at a given analysis time. In a smooth flow field, such as the time-averaged flow in Fig. 1b, the zero-wind line is nearly zonal inside the AMA. In instantaneous analyses, however, the flow field may be more complex; and several zero-wind lines may appear.
While numerical analysis software packages generally include procedures for contouring gridded data, the underlying algorithms vary and can give different results for the same input data. To ensure the replicability of this study (Irving 2016), we implement the marching squares algorithm to find isopleths of u = 0 (Rajon and Bolch 2003; Mantz et al. 2008). This algorithm is the two-dimensional analog of the original marching cubes algorithm used to find three-dimensional isosurfaces (Lorensen and Cline 1987; Lorensen 2020). A family of variants has been proposed to improve both algorithms since their introduction. Examples of using this algorithm family to visualize three-dimensional atmospheric features include radar echoes (Fujiyoshi et al. 1991), jet streams (Kern et al. 2018), and fronts (Kern et al. 2019).
In this study we follow the algorithm outlined in Mantz et al. (2008). In brief, the algorithm first partitions the instantaneous two-dimensional zonal wind field u into multiple marching squares (each with 2 × 2 grid points) and then uses a divide-and-conquer approach to find the intersection points of a selected value (in this case u = 0) on the edges of each marching square (see Fig. 6 of Mantz et al. 2008). The location of these intersection points is determined by linear interpolation from the two closest grid points along the same meridian or parallel. For example, the open circle in Fig. 5 indicates an intersection point because the zonal wind changes from easterlies to westerlies along the meridian. The exact position is then linearly interpolated according to the values of zonal wind of the two closest grid points (red and black dots).
Illustration of the criteria of filtering spurious vortex centers found by the marching squares algorithm. A potential vortex center (open circle) is located at a maximum in Ψ along a u = 0 contour (thick black line). The closest ERA-Interim grid point to this vortex center is indicated by the black dot. The first criterion requires that the relative vorticity ζ at this grid point (black dot) and its four nearest neighbors (black crosses) is anticyclonic (ζ < 0 in the Northern Hemisphere and ζ > 0 in the Southern Hemisphere). The second criterion requires that the three grid points poleward (equatorward) of this closest grid point must be westerlies (easterlies), which are indicated by red (blue) dots. The figure gives an example on how the second criterion is applied in the Northern Hemisphere.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
Multiple distinct isopleths may be extracted by connecting these intersection points (see Fig. 1 of Rajon and Bolch 2003). Isopleths either end at the boundary of the domain or close upon themselves. The algorithm can be implemented in a simple and efficient manner using common programming languages.1
The output of the algorithm is n sets of continuous piecewise-linear contours. For each set of contours, there are m segments and m + 1 nodes (segment endpoints). The coordinates (xi, yi) of these nodes are identified by subscript i, where i = 0, …, m. Note that by nature of the algorithm, all nodes (xi, yi) lie along the meridians or parallels that define the original ERA-Interim grid.
2) Vortex identification
After finding one or more sets of zero-wind (u = 0) contours within the analysis domain, the second step is to locate vortex centers (if any) along the zero-wind contours and filter out vortices that may arise from very small-scale features or from noise in the gridded data. For each set of zero-wind contours the Montgomery streamfunction Ψ is linearly interpolated to the nodes (xi, yi) using the two closest ERA-Interim grid points. The Montgomery streamfunction at the nodes Ψ(xi, yi) can be more conveniently expressed as
For each set of contours, the one-dimensional function
Two criteria used to filter out spurious peaks are shown schematically in Fig. 5. For each identified peak at sk that is indicated as an open circle, the closest ERA-Interim grid point is located and defined as the central grid point (black dot). Note that since all vortex centers are either along the meridians or parallels of the ERA-Interim grid, the maximum distance between the vortex center and the nearest ERA-Interim central grid point is ~0.35°.
The first criterion requires that the relative vorticity ζ of the central grid point (black dot) and its four nearest neighbors (black crosses) be anticyclonic (ζ < 0 in the Northern Hemisphere or ζ > 0 in the Southern Hemisphere). Note that some studies have used the meridional gradient of zonal wind ∂u/∂y (e.g., Zarrin et al. 2010), which ignores the contribution of the zonal gradient of meridional wind ∂υ/∂x to the relative vorticity. The second criterion requires that the three nearest grid points poleward and equatorward of the central grid point must be westerlies (u > 0) and easterlies (u < 0), respectively.
To illustrate, Fig. 6a shows the ERA-Interim zonal wind u and Montgomery streamfunction Ψ on the 370 K isentropic surface for 0000 UTC 19 August 2017. Blue and red colors indicate easterlies and westerlies, respectively. Purple contours (Figs. 6a–c) indicate three zero-wind (u = 0) contours found by the marching squares algorithm. Figure 6c shows
Illustration of the method used to identify vortices within the Asian monsoon anticyclone. Data are for 0000 UTC 19 Aug 2017 at 370 K. (a) Zonal wind u (red: u > 0; blue: u < 0; purple: u = 0; interval: 10 m s−1) and Montgomery streamfunction Ψ (contours; interval: 0.5 kJ kg−1). (b) M for τ = 5 days (grayscale), Ψ (blue contours; interval: 0.5 kJ kg−1), and zero-wind lines u = 0 (purple). Large and small M values are light and dark, respectively. Some hyperbolic regions are indicated by red arrows. (c)
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
3) Vortex tracking
The final step is to track the persistence and movement of subvortices through time by repeating the vortex analysis at a sequence of analysis times. Vortices are defined to be persistent if, from one time step to the next, the location of a vortex center does not change by more than 10° of great-circle distance, and the vortex center is continuous for at least four analysis periods (18 h). The remaining vortices are defined to be transient. As will be shown, by applying these definitions it is relatively easy to track vortex motion and to identify possible vortex splitting, merger, and dissolution. Sensitivity tests show that doubling the persistence criterion, horizontally smoothing the data, and using daily mean data do not significantly change the results presented below (see S1 in the supplemental material).
b. Lagrangian methods
1) Trajectories
2) M diagnostic
Figure 6b shows the corresponding M field in the example of vortex identification discussed in section 3a. An initial grid of particles with a horizontal spacing of 0.25° × 0.25° (1440 × 321 particles) is integrated forward and backward from the reference time for 15 days. In this example M is computed using τ = 5 days, so M represents the length of 10-day trajectories. Large values of M, which represent long particle trajectories, are shown as light shades of gray. Small values of M are dark. The instantaneous Montgomery streamfunction Ψ is plotted in blue. Red crosshairs show the centers of the subvortices within the main anticyclone and red arrows indicate the locations of prominent hyperbolic regions in the flow field associated with the AMA. Hyperbolic (saddle) regions play a crucial role in fluid transport and stirring (Wiggins 1992).
The importance of hyperbolic regions in stirring is illustrated in Fig. 1 of de la Cámara et al. (2013), which shows stirring by a periodically perturbed cat’s-eye flow. (Here we use stirring to mean the creation of fine structure in fluid tracers by the resolved flow and mixing to mean the mixing of fluid at the molecular level.) A hyperbolic region is the local region around a hyperbolic (saddle) point where v = 0. Trajectories near hyperbolic points in the instantaneous flow field resemble hyperbolas. The combination of fluid convergence toward hyperbolic points along the stable manifolds and divergence along the unstable manifolds can lead to rapid filamentation, the creation of small-scale structures, and exchange of patches of fluid (called lobes) between the inside and outside of the cat’s-eyes. Hyperbolic regions can be identified by intersecting curvilinear features in the M field [Fig. 1d of de la Cámara et al. (2013) or Fig. 6b herein]. Kinematically, the AMA can be considered to consist of one or more time-dependent cat’s-eyes.
Figure 6b reveals a relationship between the M field and the instantaneous Montgomery streamfunction Ψ, although the relationship is not one-to-one or monotonic. The largest values of M (i.e., the largest average Lagrangian speeds and longest particle trajectories) lie in a ring around the AMA. Intermediate values of M lie largely in the subtropical jet, while in the tropics weak easterlies lead to short trajectories. Air is at least partially confined within the AMA, as the small values of M within the two subvortices show. The principal hyperbolic regions in the flow associated with the AMA are identified by red arrows. The layering of the M field in these regions indicates the boundaries of the lobes. These often occur near saddle points in Ψ, where the instantaneous flow is hyperbolic, but this is not always the case, as M integrates the Lagrangian behavior of the fluid over an extended time, during which hyperbolic (saddle) points and associated hyperbolic regions can appear, disappear, or move with the flow.
4. Results
a. Eulerian vortex properties
Using the multiple-center method described in section 3a, the longitudes, latitudes, and Montgomery streamfunction of subvortices within the AMA are computed for each 6-hourly ERA-Interim for 0000 UTC 1 May through 1800 UTC 30 September for the 40-yr period from 1979 to 2018. This comprises a total of 24 460 analysis times. The analysis domain extends from 0° to 60°N and from 180°W to 180°E, but the Eulerian vortex statistics are computed only for the region from 15° to 45°N and from 0° to 180°E. The total number of individual vortices for the entire analysis period is 66 312 (Table 1).
Count and frequency of the number of vortices in each month of the warm season for the entire analysis period (1979–2018).
1) Vortex evolution
The evolution of monsoon subvortices for 2017 is shown in Fig. 7. Dots represent each identified vortex center; persistent and transient subvortices are colored in red and blue, respectively, according to the definitions in section 3a. Persistent subvortices are connected by black lines. Persistent vortices account for 77.1% and 77.5% of the population for 2017 and the whole analysis period, respectively (Table 1).
(a) Longitude–time plot of all identified vortex centers (dots) in the region 15°–45°N, 0°–180°E at 370 K for May through September of 2017. Persistent and transient vortices are colored in red and blue, respectively. Persistent vortices are also connected by black lines. The total number of persistent and transient vortices in 2017 are 1387 and 413, respectively. Hovmöller plot of ERA-Interim Montgomery streamfunction Ψ of 2017 (green contours; interval: 0.5 kJ kg−1). The time series of Ψ is averaged and smoothed using the same procedure as in Fig. 2. (b) As in (a), but a latitude–time plot. The colored bars along the left edge indicate the number of vortices present at each analysis time, while the colored bars along the right edges indicate the number of persistent vortices present at each analysis time (orange for 0, dark gray for 1, light gray for ≥2). Statistics of the number of vortex centers are summarized in Table 2.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
Figure 7a is overlaid with the Montgomery streamfunction Ψ (green contours), which is smoothed as in Fig. 2. The life cycle of the AMA in 2017 is similar to the climatology. For example, weak vortices occur during the onset of the AMA in May or away from the main vortex throughout the warm season. The spinup of the AMA during May and June and its dissipation during late September occur more rapidly than in the climatology, which is smoothed by averaging out the interannual variations. During the mature stage in July and August, persistent vortices are found near 60° and 90°E, where Ψ is largest, but multiple persistent vortices are found at other longitudes as well. Over the course of the warm season, the locations of vortices and the latitude of the overall AMA center first shift poleward and then equatorward (Fig. 7b).
The colored bars along the left and right edges of the plot indicate the number of individual vortices and the number of persistent vortices, respectively, that are present at each analysis time (orange for zero, dark gray for one, and light gray for two or more vortices). Two occasions of zero persistent vortices happen in May only. One persistent vortex usually occurs at the beginning and end of the warm season. Transient vortices are seen intermittently at various times in different parts of the domain. Some groups of vortices that appear to be closely clustered in space and time are not identified as persistent. Examples can be seen near 60°E in the second half of May. These clusters are not tagged as persistent vortices because they do not meet the criterion for four sequential analysis times.
Table 2 shows the frequency distribution of the number of persistent vortices present at each analysis time for 2017 and for the entire analysis period. In 2017 most of the time there are two or more vortices (73.5%). Cases of zero (0.3%) and one (26.1%) vortex are less frequent and occur most often in May and September. Because vortices of similar strength often occur at the same analysis time, as shown in Fig. 7a, selecting only the strongest vortex misses much of the interior structure of the overall AMA circulation. For the entire analysis period there is one vortex 23.3% of the time, but more often two and three vortices are present (69.4% combined). Rarely are there either zero (1.9%) or four or more (5.4%) vortices.
Count and frequency of the number of persistent vortices present at each analysis time.
Figure 8 shows that climatologically the number of all subvortices increases over the course of the warm season. The average number of all vortices present is 2.71. But persistent and transient vortices show opposite trends. While there are more transient vortices toward the beginning and the end of the warm season, the number of persistent vortices peaks in August.
Climatological averages of the instantaneous number of vortices for the analysis period 1979–2018 (black: all; red: persistent only; blue: transient only). To reduce the noise, instantaneous values are averaged into 9-day intervals. The overall time average for all vortices is 2.71.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
Similar plots to Fig. 7 for other years are included in the supplemental material file S2. As expected, there are significant variations in the vortex behavior from year to year. The average instantaneous number of all subvortices ranges from 2.17 in 1982 to 3.14 in 2015. In some years, such as 1994, the longitudes of vortices are relatively stationary. In other years, such as 2010, long-lived vortices repeatedly form near 90°E and drift westward. The tracks of the persistent subvortices show that most years have several vortex splitting and merger events throughout the warm season, two clear-cut examples of which will be discussed in section 4b.
2) Geographical distribution of subvortices
Most of the time there are two or more vortices in the domain simultaneously, so it is of interest to see the geographical distributions of the vortex centers. Figure 9 shows the frequency distribution of persistent and transient vortices for the entire period grouped into 2° × 2° bins. Note that the area of a bin centered at 45°N is ~73% of a bin centered at 15°N.
Two-dimensional frequency distributions of the vortex centers for the analysis period (1979–2018). (a) Persistent vortices. (b) Transient vortices. Bin size is 2° × 2°. Bins with zero occurrence of vortex centers throughout the analysis period are colored gray. The total number of persistent and transient vortices are 51 372 and 14 940, respectively. Corresponding one-dimensional frequency distributions for longitude and latitude of persistent vortices are plotted in Figs. 10a and 10b, respectively.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
For the persistent vortices, Fig. 9a bears similarities to Fig. 1 in Nützel et al. (2016), which uses the ERA-Interim daily geopotential height field at 100 hPa for 1979–2014 from June to August. As in Nützel et al. (2016) higher occurrence frequencies are concentrated in the region 25°–35°N, 45°–100°E, but unlike that analysis we find an expansive area of frequent occurrence between 120°E and 180°. Because these vortices tend to be weaker than those over the Asian continent, they are often not detected by the single-center method used in Nützel et al. (2016). This area also extends to a wider range of latitudes compared to vortices over the continent. Figure 9b shows that the transient vortices occur more frequently at lower latitudes than the persistent vortices and are uncommon east of 150°E.
Figure 10a displays histograms of the longitudes of persistent vortex centers for the entire period. There are two broad peaks. A broad peak between about 40° and 100°E is associated with what have previously been labeled as the Iranian and Tibetan highs. In the aggregate plot (black curve) those two modes are not clearly separated. The second peak near 150°E represents the Bonin high, which has received much less attention than the Iranian and Tibetan highs in the literature (e.g., Neyama 1968; Murakami 1978; Enomoto et al. 2003).
Overall and conditional histograms of the (left) longitude and (right) latitude of persistent vortices for the analysis period (1979–2018). Each bin is 2°. (a),(b) All months. (c),(d) May. (e),(f) June. (g),(h) July. (i),(j) August. (k),(l) September. Total number of persistent vortices is labeled for each period (see also Table 1). Line colors indicate overall histograms (black), conditional histograms when one vortex is present (red), two vortices present (green), three vortices present (blue), and four or more vortices present (magenta).
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
Because we identify multiple simultaneous vortices, additional analysis is possible. The histograms in Fig. 10 are stratified by the instantaneous number of persistent vortices present. When a single vortex is present (red), the AMA is most likely to be centered between 60° and 100°E and is rarely found west of 40°E and east of 120°E. Only when two or more vortices are present does the Bonin high peak emerge. Therefore, any method that assumes the existence of a single center is unlikely to detect the Bonin high. For example, although the eastern end of the domain in Nützel et al. (2016) is 140°E, the occurrence of centers clearly drops east of 120°E. We interpret the results differently from Zhang et al. (2002) and Nützel et al. (2016). Rather than seesawing between the Iranian mode near 90°E and the Tibetan mode near 60°E, the main variation is between states with multiple (mainly two or three) persistent vortices within the main AMA circulation.
The peaks representing the Tibetan and Iranian highs are easier to distinguish in some months. In May, most of the time there are either one or two vortices. The Tibetan high starts off as the dominant peak (Fig. 10c), especially when only one peak is present (red). As the AMA strengthens in June, both the Tibetan and Iranian highs stand out when there are two to three vortices (Fig. 10e). In contrast to Enomoto et al. (2003), we find that the Bonin high manifests itself in June, usually appearing when there are also one or two vortices over the continent. In July, the Iranian and Tibetan highs are still the dominant peaks (Fig. 10g). When there are three vortices, there are three distinct peaks in the distribution. Also, the primary peak shifts to the Iranian high (~60°E) when there are two vortices. In August and September single-vortex states become rare and no distinct peak is seen (Figs. 10i,k). The peaks of the Tibetan and Iranian highs are difficult to distinguish, but the peak of the Bonin high becomes much sharper. The total number of persistent vortices increases from May, peaks in August, and slightly drops in September (Table 1). These results reveal details of the time series in Fig. 8b. The increasing number of vortices throughout the season is mainly due to the appearance of the Bonin high, which corroborates the downstream development shown in Fig. 2.
The panels in the right-hand column of Fig. 10b show the latitudinal distributions of the vortex centers. In the meridional direction a single peak is found near 30°N. All months exhibit a single peak independent of the number of vortices present. The latitude of the peak is also independent of the number of vortices present but does depend on month. As the AMA spins up in May, vortices are primarily located equatorward of 25°N (Fig. 10d). Once the AMA is at the mature stage, there is a single peak near 30°N (Figs. 10h,j). In the interim as the AMA strengthens in June and weakens in September, the peak broadens (Figs. 10f,l). Applying the single-center method to the 6-hourly data, the broad peak associated with the Bonin high disappears (not shown), similar to the results using the ERA-Interim daily mean data in Nützel et al. (2016). The overall and conditional histograms for only the summer months (June, July, and August) are included in the supplemental material file S1.
b. Vortex behavior
Using the trajectories and M diagnostic described in section 3b, we present case studies of vortex behavior that are commonly observed within the AMA. These include vortex splitting and merger, and eastward and westward eddy shedding. Note that in the current method there is no objective way to differentiate between vortex splitting and eddy shedding. Drawing a distinction between the two may also depend on how the extent of the AMA circulation is defined.
Figure 1 shows that the outermost closed contour of the Montgomery streamfunction covers a longitude sector of ~180°, but other definitions are possible. For example, Garny and Randel (2013) used two PV thresholds of 0.3 and 1 potential vorticity unit (PVU; 1 PVU ≡ 106 K kg−1 m2 s−1) at 360 K and Ploeger et al. (2015) computed a transport barrier at 380 K, which is defined as the PV contour with a local maximum of the PV gradient, to separate the anticyclone core region from its surroundings. In the former the extent of the 0.3-PVU contour generally agrees with Fig. 1 (see Fig. 6 of Garny and Randel 2013) while in the latter the transport barrier usually ranges from 3 to 4 PVU during summer months (see Fig. 12 of Ploeger et al. 2015).
In other contexts, such as flow past an obstacle, “eddy shedding” is conventionally used to refer to the (quasi-)periodic generation of coherent vortices (Kundu et al. 2016). Given the enormous size of the AMA circulation in Fig. 1, however, it is difficult to determine whether an eddy and its parent vortex are separated. In practice, we define a westward-shedding (eastward shedding) event when an eddy is separated from the AMA circulation, crosses 0° moving west (180° moving east), and persists for more than a great-circle distance aδσ, where the central angle δσ = 30°. The detached eddy also does not recirculate into the AMA circulation at a later time. Sensitivity tests show that the result is not very sensitive to the choice of the longitude boundaries in both eastward and westward shedding cases.
1) Vortex splitting and merger
Subvortices within the AMA usually undergo multiple split-merger cycles during the warm season (see, e.g., June, July, and August in Fig. 7). The details of the flow evolution vary each year, but there are two identifiable types of vortex split-merger events. The first occurs between 30° and 120°E and does not involve the Bonin high. The evolution of one such event during June and July of 2009 is highlighted with a gray background in Fig. 11a. Analyses of Montgomery streamfunction Ψ and PV for selected times are given in Figs. 11b–g. The time of each analysis is indicated by dashed lines in Fig. 11a. Similar analyses of Ψ and PV for other types of vortex behavior are included in the supplemental material file S3 due to space limitations.
An example of the first kind of vortex split–merger event. (a) Evolution of this event during late June and early July 2009, which is highlighted with a gray background. Persistent vortex centers are colored in red and connected with black lines. Transient vortex centers are colored in blue. (b)–(g) Snapshots of this event are labeled and indicated by dashed lines in (a). Montgomery streamfunction Ψ (black contours; interval: 0.5 kJ kg−1) and PV (color) are plotted on the 370 K isentropic surface. Vortex centers are indicated by yellow crosshairs. For clarity, only those vortex centers that are highlighted in (a) are shown.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
Between 25 and 29 June, a single persistent vortex is present near 90°E (Figs. 11a,b). The main vortex with low PV expands eastward and then splits into two subvortices around 1 July (Fig. 11c). The two subvortices continue to separate, reaching their maximum separation around 4 July (Fig. 11d). Two distinct low-PV regions are associated with the two subvortices. Thereafter, the distance of separation decreases (Fig. 11a). Eastward and westward advection of low-PV air is also observed to the south and north of the vortex centers, respectively (Figs. 11e,f). The vortices finally merge around 10 July (Fig. 11g). The entire process takes about 2 weeks, which may be related to the quasi-biweekly oscillation of the Asian monsoon precipitation (Ortega et al. 2017). Another vortex splitting event occurs shortly after 11 July (Fig. 11a).
Fluid motions during this vortex split-merger event are illustrated in Fig. 12 through the use of trajectories. The M field is displayed in grayscale in the background. Contours of Ψ are overlaid in blue. Two patches of fluid marking the two subvortices (Ψ ≥ 356.85 kJ kg−1) are selected at the time of maximum separation of the subvortices, 1200 UTC 4 July 2009 (Fig. 12c). Fluid in the western and eastern vortices is colored cyan and red, respectively. Backward and forward trajectories are used to determine where the fluid in the subvortices came from and how it was stirred together when the vortices merged. The M values within the subvortex interiors are comparatively low (dark gray), indicating the fluid does not move large distances.
Snapshots of trajectories during the first type of vortex split–merger event shown in Fig. 11. Montgomery streamfunction Ψ (blue contours; interval: 0.5 kJ kg−1) and M (grayscale) are plotted on the 370 K isentropic surface. Particle positions (red and cyan) are obtained from forward and backward trajectories initialized at (c) 1200 UTC 4 Jul 2009. Particles are colored the same in all panels based on which of the subvortices they are located in (c). Vortex centers are indicated by yellow crosshairs. For clarity, only those vortex centers that are highlighted in Fig. 11a are shown. Some hyperbolic regions are indicated by red arrows.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
At the beginning of the splitting event, the fluid that will form the western subvortex is located on the north side of the AMA, while the fluid that forms the eastern subvortex is located to the south (Fig. 12a). These patches rotate around each other in the primary AMA flow. The two patches of fluid separate around 1 July as the single vortex splits into two distinct subvortices (Fig. 12b) and a new hyperbolic region emerges between them (middle arrow; cf. Fig. 1 of de la Cámara et al. 2013). Each patch moves into the core of its respective vortex (Figs. 12b,c). Subsequently, the hyperbolic region in the interior of the AMA disappears as the two subvortices weaken. In the absence of the hyperbolic region, the fluid from the two subvortices rotates slowly around the single primary AMA vortex (Fig. 12d). During the merger (4–10 July), the fluid within each subvortex makes one complete revolution around the main AMA circulation. An animation of 6-hourly analyses of this splitting event is included in the supplemental material file S4, which shows that the hyperbolic regions between subvortices can effectively stir the fluid in the interior of the larger AMA.
The second type of vortex split-merger event is associated with the Bonin high. An example of the evolution of this type during late August and early September of 2004 is highlighted by the gray background in Fig. 13a. Several snapshots with contours of Ψ are shown in Figs. 13b–g. In late August, the AMA circulation is in the mature stage, extending over 180° in longitude (Fig. 13b). East of 120°E, two subvortices consecutively break off from the Tibetan and Iranian highs, which are indicated by black arrows in Fig. 13a. This can be confirmed from the consistent eastward movement of the low-PV air (supplemental material file S3). West of 120°E, two persistent vortex centers that can be identified as the Tibetan and Iranian highs persist until they merge around 6 September (Figs. 13b–f). That merger belongs to the first type of vortex split-merger events. Therefore, two kinds of vortex split-merger events can take place simultaneously.
An example of the second kind of vortex split–merger event. (a) Evolution during late August and early September 2004, which is highlighted with a gray background. Persistent vortex centers are colored in red and connected with black lines. Transient vortex centers are colored in blue. Movements of two splitting events east of 120°E are indicated by black arrows. (b)–(g) Snapshots of this event are labeled and indicated by dashed lines in (a). Montgomery streamfunction Ψ (blue contours; interval: 0.5 kJ kg−1) and M (grayscale) are plotted on the 370 K isentropic surface. Particle positions (red and cyan) are obtained from forward and backward trajectories initialized at (d) 1200 UTC 2 Sep 2004. Particles are colored the same in (b)–(g) based on which of the subvortices they are found in (d). Vortex centers are indicated by yellow crosshairs. For clarity, only those vortex centers that are highlighted in (a) are shown. Some hyperbolic regions are indicated by red arrows.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
Fluid motions for both kinds of vortex split-merger events are shown through the use of trajectories in Figs. 13b–g. Two patches of fluid within the AMA are selected from the analysis time 1200 UTC 2 September 2004 (Fig. 13d). The first (Ψ ≥ 356.75 kJ kg−1), representing the core part of the Tibetan and Iranian highs, is colored red; the second (Ψ ≥ 356.5 kJ kg−1), representing the core part of the Bonin high, is colored cyan.
Backward trajectories show that the cyan and red particles are intermingled within the main AMA circulation on 26 August (Fig. 13b). Note the hyperbolic region between the two persistent subvortices (middle arrow). The cyan particles move along the northern side of the AMA circulation (Figs. 13b,c). By 2 September, the cyan and red particles lie within distinct subvortices separated by the emergence of another hyperbolic region near 130°E (Fig. 13d). The subvortex of the Bonin high persists for around a week. As the Bonin high dissipates (Fig. 13e), the low-PV fluid (supplemental material file S3) within is advected westward around the southern side of the primary AMA, where it is stretched and entrained back into the main AMA (Figs. 13f,g). It is then wrapped all the way around the western side and into the interior. The poleward advection of the low-PV fluid is accompanied by the equatorward advection of the high-PV air from the midoceanic trough near 180° (Ortega et al. 2018). While this is happening, the separate Tibetan and Iranian highs merge into one subvortex. An animation of this splitting event is included in the supplemental material file S5.
2) Eastward eddy shedding
Figure 7a shows that for 2017, most of the identified vortices near 180° are weak and transient (blue). Exceptions are seen for some persistent vortices (red) in late August and early September. In this period of time two eastward eddy-shedding events can be clearly identified, one of which is shown in detail in Fig. 14a. The black arrow highlights the motion of the vortex in question. Several snapshots with contours of Montgomery streamfunction Ψ are shown in Figs. 14b–g. A patch of fluid within the AMA (Ψ ≥ 356.5 kJ kg−1) is selected from the analysis time 0000 UTC 23 August 2017 (Fig. 14c). There are two subvortices within this patch of fluid, one being relatively stronger and covering a larger area near 100°E. Note the hyperbolic region between these two vortices (arrow). To examine the validity of the “pinch off” process illustrated in Fig. 4, the particles inside the core region of the stronger vortex (Ψ ≥ 357 kJ kg−1) are tagged in red, while the outer region is tagged in cyan.
As in Fig. 13, but for an eastward eddy-shedding event during August and early September 2017. Particle positions (red and cyan) are obtained from forward and backward trajectories initialized at (c) 0000 UTC 23 Aug 2017. (a) The evolution of this event is highlighted with a gray background. Movements of the eastward shedding eddy are indicated by the black arrow. (b)–(g) For clarity, only those vortex centers that are highlighted in (a) are shown.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
Backward trajectories show that the red particles come from two subvortices of similar strength in the previous split-merger event as shown in Fig. 14b. The red patch of air is brought together by the converging flow near the hyperbolic region (reverse filamentation) seen in Figs. 14b and 14c. Forward trajectories show that the stronger vortex (red) becomes elongated around 25 August (Fig. 14d). A hyperbolic region emerges (right arrow) and then a new subvortex center forms east of the original vortex near 135°E shortly after 25 August. Most of the air comes from the core of the original eastern vortex (red), with filaments (cyan) from the outer region (Figs. 14e,f). This fluid organizes to form a Bonin high (Fig. 14e). At the same time, a deep trough forms east of the Bonin high and high-PV air associated with this trough is stretched southwestward (supplemental material file S3), which would lead to Rossby wave breaking and PV mixing in the deep tropics (Ortega et al. 2018).
The early flow evolution is similar to the second identifiable type of vortex split-merger event (Fig. 13). But unlike the previous split-merger case, this subvortex does not dissipate and recirculate into the main AMA circulation. The low-PV eddy maintains its identity (supplemental material file S3), propagates eastward along the southern flank of the subtropical jet, and enters the Western Hemisphere around 28 August (Figs. 14e,f). The circulation is maintained for several more days before merging with the NAMA. The red particles are entrained into the core of the NAMA circulation and arrive at the west coast of the United States around 1 September (Fig. 14g). The entire eddy-shedding process takes about 10 days. A second eastward eddy-shedding event happens east of the date line at the same time (Fig. 14g). Note that most of the cyan particles that form this second eddy were located on the western side of the AMA a few days earlier (Fig. 14d). This illustrates the complex history of the air contained within eddies pinched off from the main AMA circulation. An animation of this eastward eddy-shedding event is included in the supplemental material file S6.
3) Westward eddy shedding
As can be seen in Fig. 10, vortices occur infrequently west of 30°E, which implies that westward eddy-shedding events are not common. One particularly coherent and long-lived event, shown in Fig. 15, occurred during 1999. The steady westward propagation is indicated by the black arrow in Fig. 15a. Snapshots of corresponding fluid motion are provided in Figs. 15b–g. Two patches of fluid (Ψ ≥ 356.3 kJ kg−1) within the subvortices are selected from the analysis time 0000 UTC 15 July 1999 as shown in Fig. 15e.
As in Fig. 13, but for a westward eddy-shedding event during July 1999. Particle positions (red and cyan) are obtained from forward and backward trajectories initialized at (e) 0000 UTC 15 Jul 1999. (a) The evolution of this event is highlighted with a gray background. Movements of the westward shedding eddy are indicated by the black arrow. (b)–(g) For clarity, only those vortex centers that are highlighted in (a) are shown.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
This eddy-shedding event is preceded by a complete vortex split–merger cycle in early July. A single persistent vortex splits into two subvortices that merge back into a single vortex between 4 and 8 July (Figs. 15a–c). After that, the vortex splits again and forms two subvortices around 12 July (Fig. 15d). The western vortex persists and slowly moves across the prime meridian around 18 July (Figs. 15e,f), which can be confirmed from the westward propagation of the low-PV air in the vortex (see supplemental material file S3).
Backward trajectories show that the fluid that forms the two vortices in Fig. 15e was previously intermingled (Fig. 15b). The red patch forming the core part of the western vortex in Fig. 15c rotates and moves eastward around the north side of the AMA as the two subvortices in Fig. 15b start to merge. Thereafter, a hyperbolic region (red arrow) emerges near 60°E (Fig. 15d). The red particles organize and form a new vortex over Tibet around 12 July and similarly cyan particles form another vortex near 30°E (Fig. 15d). Over the next 2 weeks the new western vortex (cyan) drifts westward as far as 45°W. Some of the air originally in the western vortex is pulled through the hyperbolic region between the two vortices, filamented, and entrained into the eastern vortex (Figs. 15f,g). At this point the westward motion of shed vortex stops, and the eddy weakens and dissipates few days later (Fig. 15a). An animation of this westward eddy-shedding event is included in the supplemental material file S7.
4) Interannual variability
Statistically the plot in Fig. 7 is typical of the vortex behavior for each year. The earlier stage of an eddy-shedding event resembles a vortex split, which makes the identification process less straightforward. All years show both kinds of vortex split-merger events. On average, around five and seven events occur per year for the first and second types of split-merger events, respectively, which represent the bulk of the intraseasonal variations of the AMA circulation. The total number of split-merger events ranges from 8 to 16 times a year, which normally increases with the number of instantaneous subvortices in the domain. Eddy-shedding events do not occur every year. Eastward eddy-shedding events happen in 31 years only and the total number is 61. Westward eddy-shedding events happen in 16 years only and the total number is 34.
5. Discussion and conclusions
Previous interpretations of the behavior of the Asian monsoon anticyclone typically assume a priori that the anticyclone has only one, single, well-defined center at a given time and that the center coincides with the maximum of the Montgomery streamfunction or geopotential height (e.g., Zhang et al. 2002). This approach gives the impression that the AMA center has two preferred locations, over Iran or the Tibetan Plateau, which is referred to as a bimodal distribution. Pan et al. (2016) suggested that two new modes should be included: a double-center mode and a longitudinally elongated mode. However, this does not allow for other transient behavior such as eddy shedding.
We have implemented an improved method that allows the detection and tracking of multiple simultaneous subvortices within the AMA. The analysis presented here reveals that two or more distinct persistent subvortices exist simultaneously within the AMA ~75% of the time. These subvortices often have similar strength. Therefore, choosing the strongest of these subvortices as the location of the AMA gives a misleading impression of both the average state and the variability of the circulation structure.
There is an important conceptual difference between 1) an AMA with a single center that has two preferred locations (and presumably some jumping back and forth between those locations) and 2) an AMA that contains multiple subvortices of similar strength that have preferred locations. Bimodality inherently refers to the first case. Our analysis reveals that there are two preferred regions for the location of subvortex centers that exhibit two distinct life cycles (Fig. 10). The first covers both Iran and the Tibetan Plateau. The associated Iranian and Tibetan highs often exist simultaneously and drift eastward or westward, so the two distinct modes that usually appear in a single-center analysis merge into a broad peak in this analysis. The coexistence of the Iranian and Tibetan highs may also complicate the result from composites of either mode in the literature. The second represents the Bonin high but is shown to be located at a much broader area east of 120°E. It is also clearly revealed as an individual anticyclonic circulation center but is rarely identified under the single-center assumption because it is normally weaker than continental circulation centers.
Time–longitude plots of subvortex locations reveal several types of behavior (Fig. 7), including 1) splitting of a single vortex into two vortices; 2) merger of two vortices into a single vortex; 3) vortex shedding in the eastward direction; 4) vortex shedding in the westward direction; and 5) formation, movement, and dissipation of a vortex. The number and location of subvortices evolve continuously on synoptic time scales. Unlike tropical cyclones, binary interactions such as the Fujiwhara effect (i.e., mutual orbiting of two vortices; Fujiwhara 1921, 1923, 1931) have not been observed in the Asian monsoon. This may be due to the strong confinement of the AMA between the subtropical jet and the tropical easterly jet and the limited space for two subvortices to rotate around each other.
There are limits to the present analysis determined by the resolution and quality of the meteorological analysis and the fundamental scales (smoothness) of the atmospheric flow. Additionally, the analysis method uses the Montgomery streamfunction Ψ to locate vortex centers, but the flow is not in exact balance, so Ψ is not a perfect indicator of where the instantaneous center of rotation is located. The half-width of the search window also sets a lower limit on the size of subvortices that can be detected. This means that it is not possible to observe vortex splitting, merger, or other interactions when vortices are very close to one another, but only after they have separated sufficiently to be distinguished from each other. The instantaneous flow field is quite complex and multiple types of behavior may happen at the same time, which makes rigorous classification difficult.
Since vortex splitting and eddy shedding are not clearly differentiated in the literature, we define an eddy-shedding event for the AMA to be when an eddy crosses 0° or 180° and travels more than 30° along the great-circle arc. Eddy-shedding events occur but are not common under the current definition. Eastward eddy-shedding events are more common than westward eddy-shedding events, as indicated by the low frequency of vortex centers west of the 30°E. Note that the current definition may be relatively strict compared to other definitions that may give different results. For example, Fadnavis et al. (2018) defined a shedding event to be the separation of low PV area (<1 PVU) from the main circulation. They found that it occurs more frequently over western Africa (~68%) than the western Pacific (~25%).
The transitions between states with one to three (or more) subvortices within the AMA play an important role in stirring the air in the interior of the anticyclone. These transitions are associated with the appearance and disappearance of cat’s-eye structures and hyperbolic regions between the subvortices. When a single vortex splits into two temporarily isolated vortices that then remerge, air that was originally in compact patches is stretched and stirred into extended filaments (Figs. 12, 13). The result is efficient stirring of the air inside the anticyclone, which is similar to the stirring seen in the idealized model of Aref (1984) and the tracer simulation of Gottschaldt et al. (2018). As was shown in Figs. 14 and 15, patches of air exiting the vortex do so through lobes associated with hyperbolic regions. In the eastward eddy-shedding case described here, air that forms a coherent eastward propagating eddy is not pinched off the eastern end of the AMA, as was suggested in the Eulerian view of Fig. 4, but instead comes from filaments exported from the anticyclone via the lobes associated with the hyperbolic region between the two subvortices. This eddy moves across the Pacific and reaches the Pacific coast of the United States in around 10 days, which may serve as a possible pathway of long-range transport of Asian pollutants to North America. Westward-shedding events are less common, but the example in Fig. 15 is also associated with the development of a hyperbolic region. These Lagrangian transport pathways are illustrated schematically in Fig. 16.
Transport pathways for air leaving the anticyclone when two vortices are present. Thin black lines represent instantaneous streamlines. Thin gray arrows indicate the direction of the flow. Heavy black arrows show the paths taken by air exiting the hyperbolic region between the two vortices.
Citation: Journal of the Atmospheric Sciences 77, 12; 10.1175/JAS-D-19-0349.1
This study is fundamentally kinematic and, as such, does not directly address the dynamical reasons for the unsteady behavior of the Asian monsoon anticyclone. While the formation of the Tibetan and Iranian highs are driven by the localized thermal forcing and to some extent the orographic forcing (Liu et al. 2007), there is no such consensus for the Bonin high. Besides the localized heating, the emergence of the Bonin high is associated with some teleconnection due to Rossby wave propagation [e.g., Silk Road pattern (Enomoto et al. 2003) and Pacific–Japan pattern (Nitta 1987; Kosaka and Nakamura 2006)]. Note that these teleconnection patterns may also be induced by remote latent heat release due to precipitation and multiple patterns can exist in tandem. Using a simplified model, Enomoto et al. (2003) showed that the Bonin high still exists if the western Pacific heating is not present. However, using another simplified model, Lu and Lin (2009) showed that latent heating associated with subtropical and tropical precipitation anomalies induces strong circulation response in the western Pacific and East Asia, therefore maintaining a meridional tropical–extratropical teleconnection pattern. Ueda et al. (1995) showed that abrupt changes of convective activities over the subtropical western Pacific are associated with the Bonin high.
The eddy shedding may be due to spatial or temporal variability of the latent heat release, to internal nonlinearity of the flow within the anticyclone, or to the instability of the subtropical jet. Hsu and Plumb (2000) studied the effect of asymmetry by imposing a mean wind or PV gradient to a thermally forced anticyclonic circulation in a shallow-water model and showed that eddies can be periodically shed under sufficiently strong asymmetry. Amemiya and Sato (2018) modified a nonlinear β-plane shallow-water model by including a latitude-dependent mean depth. Realistic vortex behaviors can be seen even when the forcing is time invariant. Rupp and Haynes (2020) found that westward eddy-shedding events happen when the flow field becomes absolutely unstable in a single-layer quasigeostrophic flow. However, these models could not explain other behavior, such as eastward eddy shedding. Additional studies are needed to understand the dynamics driving the different types of the vortex behavior.
Acknowledgments
We gratefully acknowledge the organizing committee and participants of the workshop on “Dynamics, Transport and Chemistry of the UTLS Asian Monsoon,” held at the National Center for Atmospheric Research (NCAR) Foothills Laboratory in March 2016. The lively discussion provided the original impetus for this research. We are appreciative of three anonymous reviewers for their insightful comments that helped improve the manuscript. We thank Ping Chang, Andrew Dessler, Ramalingam Saravanan, Alvaro de la Cámara, and Stephen Colucci for their comments and suggestions. We thank Kai-Wei Chang for his assistance with the trajectory model calculations. We thank ECMWF for producing the ERA-Interim and ERA5 data and NASA for producing the TMPA data. We thank Texas A&M University Libraries for offering access to various hard-to-find historical documents. Funding for this work is provided by the National Science Foundation Grant AGS-1550611 and National Aeronautics and Space Administration Grant 80NSSC19K0341 to Texas A&M University. LWS is partly supported by the National Science Foundation through Grant AGS-1840979 to Cornell University.
Data availability statement
The ERA-Interim data were downloaded from the NCAR Research Data Archive (RDA) (https://rda.ucar.edu/datasets/ds627.0/). The ERA5 data were downloaded from the Copernicus Climate Change Service (C3S) Climate Data Store (CDS) (https://cds.climate.copernicus.eu/cdsapp#!/home). The TMPA product were downloaded from the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) (https://disc.gsfc.nasa.gov/datasets/TRMM_3B42_7/summary).
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