1. Introduction
Southeast Australia (SEA) experienced devastating floods in late March 2021: the Hawkesbury–Nepean catchment in Sydney suffered its most significant flooding in more than 30 years, and the torrential rainfall stretched from central Australia to New South Wales (NSW), resulting in substantial flooding of several inland rivers in SEA [Bureau of Meteorology (BOM); BOM 2021]. Meanwhile, rainfall in February 2021 also was above average for most parts of highly populated SEA; some sites in southeast NSW, northeast Victoria, and Tasmania reported the highest daily rainfall on record for February (Bureau of Meteorology: http://www.bom.gov.au/climate/current/month/aus/archive/202102.summary.shtml). A detailed investigation is warranted to study whether these two monthly climate backgrounds (February and March) share any similarities and are influenced by long-lasting forcing factors leading to variation in atmospheric moisture and favoring the formation of extreme precipitation. The study area along with the main streams and catchments in Australia is displayed in Fig. 1 for reference.
For such extreme precipitation events, it is always worth investigating the responsible moisture fields because an abundant moisture supply is fundamental for heavy precipitation. Therefore, revealing the characteristics of the moisture transport associated with anomalous wet conditions is necessary to better understand the background of extreme precipitation. Moisture transport by atmospheric circulation plays a dominant role and can contribute significantly to precipitation since on a long time scale, the amount of local moisture change is relatively limited (Benton et al. 1950; Budyko 1974; Trenberth et al. 2003). It is estimated that less than one-third of moisture precipitated in the extratropics is from local evaporation, and a large portion of the water vapor is advected into storm systems from other source regions (Trenberth 1998). In previous studies of how atmospheric moisture variation corresponds to extreme events in Australia, results are quite limited compared to other parallel monsoon regions, such as North America and East Asia (e.g., Simmonds et al. 1999; Li et al. 2011; Jiang et al. 2009; Huang et al. 1998). Deng and Ritchie (2019) investigated moisture transport in association with an extreme rainfall event in Canberra and found that moisture advection associated with different weather systems contributed to precipitation from several directions, while the local moisture contribution was close to 0 during the rainfall period. Godfred-Spenning and Reason (2002) illustrated the features of moisture flux associated with the Australian monsoon lifetime on a monthly scale. In other monsoon regions, previous investigation has revealed that the contribution of moisture transport to seasonal or monthly extreme precipitation events is of substantial importance (Trenberth and Branstator 1991; Trenberth and Guillemot 1995; Jiang et al. 2009; Li and Zhou 2012). Hence, it is important to examine the characteristics of moisture transport associated with extreme wet conditions in SEA, which will also lead to improved comprehension of regional climate variation, and of the water balance in the regional and global hydrologic cycle. In this paper, variation in monthly broadscale moisture transport is examined to reveal the impact of moisture transport variation on precipitation anomalies and contribute to better understanding of the mechanisms of extreme precipitation in SEA.
It is suggested by the BOM that the La Niña event of 2020/21 could have been the main external contributor to the extreme precipitation in the austral late summer in SEA (BOM 2021), but how La Niña modulated the moisture transport into the specific region of interest and consequently favored the extreme precipitation in SEA needs detailed analysis. Regarding the linkage between ENSO and Australian rainfall, many previous studies tend to agree that Australia usually experiences decreased precipitation during El Niño events, with the reverse tendency during La Niña events (McBride and Nicholls 1983; Lewis and Karoly 2015; Nicholls and Kariko 1993; Godfred-Spenning and Reason 2002). Yet the association between ENSO and precipitation in SEA has produced some controversial results in previous work: some studies show that ENSO has limited influence on SEA (e.g., McBride and Nicholls 1983; Pepler and Coutts-Smith 2013), while others reveal an evident linkage between ENSO and precipitation at some locations within SEA (e.g., Kiem and Franks 2001; Verdon et al. 2004). Meanwhile, the contribution of ENSO to Australian rainfall is not temporally stationary (Nicholls et al. 1996; Simmonds and Hope 1997). These controversial outcomes may indicate an instability in the relationship of ENSO with Australian rainfall, which could be modulated by other factors (van Rensch et al. 2019). In a study focusing particularly on the variability of precipitation on the eastern seaboard of Australia, which is east of SEA, Twomey and Kiem (2021) demonstrated that the complexity of precipitation variability could be linked to east coast lows synoptically, which in turn could be modulated by southern annular mode (SAM) variation (Risbey et al. 2009).
The SAM is an internal climate mode in the atmosphere that arises from a positive eddy–zonal flow feedback (Lorenz and Hartmann 2001), characterized by changes in zonal wind strength with opposing centers of action near 40° and 65°S and an equivalent barotropic structure (e.g., Lorenz and Hartmann 2001; Hartmann and Lo 1998; Thompson and Wallace 2000). Previous studies have revealed that a positive SAM tends to enhance precipitation in northwest Australia (Feng et al. 2013; Meneghini et al. 2007). Internal atmospheric variability is suggested to be important to long-term rainfall anomalies (Taschetto et al. 2016). For example, Meneghini et al. (2007) focused on comparing the relative roles of SAM and ENSO and suggested that for some specific regions of Australia, such as western and southern Victoria, SAM accounts for more of the winter precipitation variability, while for summer and autumn precipitation, the signals in SEA are not very well organized or apparent. Hendon et al. (2007) documented that the responses of precipitation to SAM from December to February are characterized by positive precipitation anomalies in SEA, while those from March to May are limited, with only some responses in Western Australia. Actually, during these two months (February and March 2021), positive SAM is also salient in the midlatitudes, such that reasonable speculation can be made about the combined impacts of La Niña and a positive SAM on the extreme precipitation. Hendon et al. (2014) examined the contributors to the extreme wet conditions in eastern Australia in austral spring (September to November) in 2010 and emphasized that the predictability of extreme conditions lies with La Niña as well as a positive SAM, but the mechanisms have not yet been sufficiently addressed. Given the importance of external and internal forcing factors, the probable combined contributions of La Niña and positive SAM to extreme late summer precipitation will also be further examined in this study, with a primary focus on the underlying physical mechanisms rather than on predictability; the underlying mechanisms have been less considered in previous studies of extreme Australian precipitation.
In this study, the anomalous wet conditions in February and March 2021 are examined with a particular focus on moisture transport and regional moisture budget analysis, and the contributions of different processes to water vapor convergence are also diagnosed. In addition, the possible combined effects of external and internal forcing factors are also investigated in order to reveal the physical mechanisms of the impacts of ENSO and SAM on precipitation variability in highly populated SEA.
The data and methodology employed are briefly described in section 2. The important role of atmospheric moisture transport in extreme precipitation conditions and the diagnosis results of moisture convergence are illustrated in section 3. The impacts and mechanisms associated with La Niña and positive SAM forcing are described in section 4. Possible orography effects related to moisture transport in different directions are discussed in section 5. A summary of this study is presented in section 6.
2. Data and methodology
To depict the anomalous rainfall conditions during the focus months, February and March, the Global Precipitation Climatology Project (GPCP) version 2.3 monthly precipitation dataset from 1979 to 2021 and GPCP version 2.3 daily precipitation from 1997 to 2021, with a horizontal resolution of 2.5° × 2.5° (Adler et al. 2003), is extracted from NOAA/OAR/ESRL PSL, Boulder, Colorado (https://psl.noaa.gov/). Calculations of water vapor flux are based on 6-hourly specific humidity, horizontal winds at different pressure levels, and surface pressure from the fifth-generation ECMWF reanalysis dataset (ERA5) with a horizontal resolution of 1° × 1° (Hersbach et al. 2020). In addition, large-scale background conditions are also analyzed based on monthly mean parameters from the ERA5 dataset, with the same resolution as the hourly dataset, including geopotential height, omega, mean sea level pressure, and the moisture analysis output of vertically integrated water vapor flux (viz., the vertical integral of the divergence of moisture flux, the vertical integral of the eastward water vapor flux, and the vertical integral of the northward water vapor flux). The Extended Reconstructed SST version 5 (ERSSTv5) produced by the National Oceanic and Atmospheric Administration (NOAA; Huang et al. 2017) with a horizontal resolution of 2° × 2° is adopted to demonstrate the situation of ENSO.
The SAM variation is represented by a SAM index, defined as the zonal pressure difference between 40° and 65°S (Marshall 2003). The SAM mode denotes the internal alternation of atmospheric mass between middle and high latitudes, in association with changes in the north–south location of the westerly jets in the Southern Hemisphere. Meanwhile, the regional mean SST over the Niño-3.4 region (5°S–5°N, 170°–120°W) is calculated to illustrate the state of ENSO events. To ensure that the analysis time scales match, when differentiating different phases of SAM and ENSO, the average indices of the two months are estimated. On the basis of 0.5 standard deviation of each index, positive and negative phases of SAM are identified and used in further composite analysis. Classification of ENSO phases is according to the definition that events with five consecutive 3-month periods above 0.5 (below −0.5) anomaly are identified as El Niño (La Niña) events based on the 3-month running oceanic Niño index (ONI; from https://ggweather.com/enso/oni.htm). Hence, different combinations of SAM and ENSO can be recognized, with results listed in Table 1. Here, in order to focus on the combined impacts of SAM and ENSO when they are both beneficial for precipitation in SEA, the years with in-phase states of SAM and ENSO, positive (negative) SAM coupled with El Niño (La Niña), are ignored in Table 1.
Classification of years when SAM and ENSO occur during February and March. Out-of-phase classification represents years when La Niña (El Niño) co-occurs with a positive (negative) SAM event. Years with in-phase SAM and ENSO are not documented.
To understand the roles of the possible effects of SAM and ENSO, we can make composites under different combinations of SAM and ENSO. For this composite analysis, we employ the bootstrap method to test for statistical significance. The bootstrap is a databased, computer-intensive simulation method for statistical inference that operates by generating random data batches from existing samples (with replacement; Wilks 2005). Resampling with the same sample size is conducted within each of the two composites, and then the difference between these two bootstrapped composites can be calculated. Multiple bootstrap composites are generated a certain number of times (1000 times in this study) to create a distribution of bootstrap difference. The confidence interval is verified based on the upper and lower percentiles of the distribution: the lower boundary at the 2.5th percentile of the bootstrap distribution and the upper boundary at the 97.5th percentile result in the 95% confidence interval of the bootstrap difference. To reject the null hypothesis—the composite difference is 0—the value of zero should be outside the confidence level. This method has been utilized in many climate studies to reveal external forcing effects (e.g., Chu and Wang 1997; Guo et al. 2017; King et al. 2021) as well as to investigate the uncertainty of model simulations (e.g., Yeh et al. 2009). The detailed procedures of bootstrap composite analysis can also be found in King et al. (2021).
According to the flux form of water vapor and its vertically integrated form, the moisture advected through the lateral boundaries of a certain region can be computed as
3. Moisture transport and budget analysis associated with late summer Australian precipitation in 2021
The extreme anomalous precipitation pattern during February and March over Australia is first presented in Figs. 2a and 2b (shading), and the region experiencing catastrophic floods is also highlighted along with the enhanced precipitation in SEA. The year-to-year variations of precipitation anomalies during these two months share similar spatial patterns, especially within the region of interest, where the variations reach a local maximum along the highly populated coastal region and gradually decrease to the west (dashed contours in Figs. 2a,b). The standard deviations are in the range of 0.5–2.5 mm day−1, and the year-to-year variations in February are generally larger than those in March. In February 2021, above-normal precipitation occurs east of SEA, influencing the highly populated coastal region. And this wet condition continues to March, when catastrophic flooding occurs in New South Wales and Victoria. It is noticeable that the responsible anomalous precipitation pattern stretches from the tropical Indian Ocean and largely spreads all over the highlighted region, influencing the main streams of the Murray–Darling River and leading to disastrous floods. Generally, the northwest–southeast distributed precipitation anomalies agree well with the characteristics of continental-scale bands of continuous cloud stretching from northwest to southeast Australia, normally known as Australian northwest cloudbands (Reid et al. 2019).
We also analyzed the number of rainy days and total precipitation amount in SEA (the region highlighted in Figs. 2a,b; 27°–40°S, 142°–155°E) in February and March by showing the distribution of historical observations (Figs. 2c–f). For February 2021, the number of rainy days (19) and total precipitation (75.75 mm) are close to the median. According to the BOM report (http://www.bom.gov.au/climate/current/month/aus/archive/202102.summary.shtml), during February above-average rainfall was observed over much of New South Wales, northeast Victoria, and much of Tasmania; the rainfall amount for the Murray–Darling basin ranks 80th out of the 122 (highest) records. The wet conditions for SEA in March 2021 are quite extreme: the total precipitation amount in this month exceeds the 95th percentile; precipitation in New South Wales ranks as the second wettest March based on historical records for the state (http://www.bom.gov.au/climate/current/month/aus/archive/202103.summary.shtml#extremes). All these characteristics confirm that SEA experienced a wet February and an extremely wet March during 2021, so investigation of the detailed mechanisms associated with these two wet months is warranted to understand the nature of anomalous climate in SEA.
The water vapor supply responsible for the abnormal precipitation during these two months is further investigated to reveal the characteristics of moisture anomalies related to the precipitation. The water vapor input through each lateral boundary of the region of interest as well as the derived total net convergence of the water vapor flux at different levels is first analyzed, with profiles given in Fig. 3. Climatologically (Figs. 3a,b), the effect of moisture transport for this region is approximately negative in these two months, especially for the middle troposphere. For levels above 850 hPa, water vapor loss is attributed mainly to water outflow through all boundaries except the western boundary, while for the near-surface level below 850 hPa, the water vapor is transported into the targeted region mainly through the eastern boundary and secondarily through the northern boundary, but the water vapor output through the other boundaries offsets the water vapor input to some extent, thus leading to a small net convergence of moisture during February. The situation in March is similar to that in February except for the role of water vapor transport through the northern boundary at the lower level, where water vapor mainly flows out of SEA; thus the net convergence of water vapor at all levels in the target region is consistently negative (Fig. 3b). During February 2021 (Fig. 3c), the anomalous convergence of moisture below the 700 hPa level within the region is primarily positive, associated with the wet conditions in SEA (BOM: http://www.bom.gov.au/climate/current/month/aus/archive/202102.summary.shtml), which is contributed mainly by the water vapor input through zonal boundaries; for the meridional boundaries, the water vapor outflow is dominant. The conditions in March vary in the role of the primary contributing boundary; most water vapor comes from the meridional boundaries (Fig. 3d), indicating the leading contribution of water vapor convergence in the meridional direction. Meanwhile, it is also noticeable that the magnitudes of the anomalies in March are greater than those in February, corresponding to the much more severe precipitation in March. Climatologically, the anomalous net convergence of water vapor is positive during both February and March, consequently providing adequate moisture for the wet conditions over SEA (Fig. 3c).
Further investigation of the water vapor supply for the precipitation is based on the water vapor flux and its divergence, as shown in Fig. 4. During February, there is an anomalous cyclonic circulation pattern off the coast of eastern Australia, but the major water vapor convergence appears over the ocean, and the convergence response over land is limited within the region of interest (Fig. 4a). A comparison between the anomalous field (Fig. 4a) and the monthly field without subtracting the climatological mean (Fig. 4b) shows that during this month the westerly water vapor transport to the north of SEA decreases, while the moist air carried by northwesterlies from the tropics apparently increases. As for March, some consistent anomalous patterns can be observed, such as the dominant cyclonic circulation pattern over SEA, as well as the anomalous and stronger northwesterly water vapor transport (Fig. 4c). Furthermore, significant water vapor convergence is evident within the region of interest, related to the shift in the location of the anomalous cyclone just above SEA, along with the anomalous southeastward water vapor flux on its northern flank. Such an anomalous cyclonic system in these two months can benefit the abundant moist air mass propagating not only from the Tasman Sea but also from the tropical Indian Ocean, providing surplus moisture for the extreme precipitation in SEA.
It is also interesting to investigate the relative roles played by the anomalous horizontal wind and the anomalous moisture fields of the water vapor flux, and further partitioning is conducted based on the terms on the right-hand side of Eq. (4). During these two months, the anomalous wind field primarily drives the anomalous water vapor flux, while the anomalous water vapor field plays a secondary role in leading to the anomalous water vapor convergence in the target region (Fig. 5). During February, the dynamic contribution of the anomalous wind field benefits the flow of water vapor flux into SEA through zonal boundaries (Fig. 5a). Meanwhile, the anomalous water vapor convergence is limited to northeast New South Wales, which corresponds mainly to the anomalous water vapor distribution in central Australia and the Coral Sea, and the meridional gradient of the water vapor distribution favors water vapor transport into southern Australia (Fig. 5b). Although the interactive term contributes little to the water vapor flux anomalies, it can still facilitate the convergence of water vapor flux after integration of the anomalies at all levels in SEA (Fig. 5c). During March, the largest difference compared to February is the change in dynamic wind fields: the anomalous cyclonic circulation pattern dominates the southern portion of eastern and central Australia—which is also observed around the Tasman Sea during the last month—and anomalous northwesterly water vapor transport contributes most to the convergence of water vapor in SEA (Fig. 5d). A similar anomalous moisture pattern is also observed in March, but with stronger intensity and a southward-shifted center, better contributing to the moisture convergence in SEA (Fig. 5e). The northwest–southeast distribution of the convergence of water vapor is even salient in the contribution of the third term (Fig. 5f), indicating that in this extreme month, all three terms contribute to the anomalous convergence of water vapor in the region of interest. But overall, in both months, the dynamic contribution from the anomalous cyclonic circulation above the Tasman Sea tends to be dominant for the extreme moisture convergence in SEA. Considering the recent substantial warming SST trend in the Tasman Sea, which can lead to increased evaporation and atmospheric humidity, anomalies above the Tasman Sea could potentially induce more extreme precipitation events in Australia in the future (Sato et al. 2021). In the meantime, the anomalous westerlies originating from the tropical Indian Ocean also transport moist air masses into SEA, sustaining the extreme precipitation. It has been revealed in previous studies that tropical anomalies, such as sea surface pressure and SST anomalies northwest of Australia, can stimulate significant precipitation responses in Australia (Simmonds et al. 1992; Simmonds 1990; Simmonds and Rocha 1991). On average, the contributions of dynamic and thermodynamic processes primarily act in concert to ensure a considerable amount of water vapor for the abnormal precipitation over SEA.
4. The large-scale background circulation anomalies during late summer of 2021
Based on the earlier analysis, the precipitation can be largely attributed to the dynamic anomalous wind field, which also agrees with previous studies (e.g., Wang and Paegle 1996; Li et al. 2012). We further ascertain the important role of the cyclonic circulation pattern around SEA based on the diagnosis of different contributions to the water vapor convergence, while in the following analysis, we can also demonstrate the detailed dynamic process by examining the responsible large-scale circulation pattern at different levels.
Although the precipitation anomalies in March are much more extreme than those in February, some similarities are still evident in the large-scale background circulation around SEA. At the lower level (Figs. 6a,b), negative sea surface pressure anomalies are located above SEA, coupled with the evident cyclonic wind anomalies, which is the important system addressed in the earlier discussion. In the upper troposphere (Figs. 6c,d), similar anomalous cyclonic circulation is also salient, along with the negative geopotential high along southern Australia around 30°S and positive geopotential height anomalies south of SEA. In association with the fact that the anomalous cyclone can also be observed at both the lower and higher levels, the atmospheric circulations can refer to an equivalent-barotropic system. Under the control of such a deep convective system, anomalous rising motion can be expected over SEA. The divergent wind and velocity potential at 200 hPa are also calculated during February and March (Figs. 6e,f); divergence and a negative velocity potential center above the region can be identified in both months, which tends to induce ascending vertical motion. The vertical circulation along the meridional direction also demonstrates that around 30°S anomalous ascending motion predominates along with the upper-level divergence center (Figs. 6g,h). As a result, the importance of the dominant equivalent-barotropic cyclonic system to the extreme precipitation over SEA can be further identified by the upper and lower atmospheric circulation anomalies during both months. Such a dominant role for extreme rainfall events over SEA has also been documented by a previous study (Boschat et al. 2015).
But there are also some obvious dissimilarities during these two months. The prominent differences are the location of the anomalous cyclonic circulation and the magnitudes of the anomalous sea level pressure around the south Indian Ocean (SIO). During February, the center of the anomalous cyclone is located over the sea, exerting limited influence over land. During March, the anomalous cyclone is located just above SEA, leading to severe responses in the atmosphere and benefiting the extreme precipitation. The different location of the anomalous cyclone may be related to different circulation patterns over the Indian Ocean as well as over higher latitudes (Figs. 6b,d). During March, anomalous perturbation occurs at high latitudes, where a strong geopotential height minimum is dominant over the Indian Ocean sector, and two positive geopotential height centers are located on both the west and east sides of SEA, strengthening the cyclonic circulation anomalies above SEA.
Given the commonality in February and March, we want to seek the possible large-scale climate driver of these two wet months for SEA. So further investigations are conducted to reveal the potential mechanisms of climate drivers contributing to the anomalous equivalent-barotropic cyclonic circulation in the next section.
5. The possible combined effects of internal and external forcing
To reveal the possible climate drivers, we can first illustrate the most dominant climate drivers for Australia by examining the SAM index and Niño-3.4 index during February and March, shown in Fig. 7a. Previous studies have suggested that SAM and ENSO tend to interact to some extent (e.g., L’Heureux and Thompson 2006; Fogt and Bromwich 2006), while the correlation coefficient of the SAM and ENSO indices during these two months is only −0.08. Therefore, the conditions in late austral summer 2021 can be identified via the indices as a combination of positive SAM forcing and a La Niña event. Considering the important impacts of these two phenomena as indicated by previous studies, it is worth examining the possible driving roles of these modes in triggering the extreme precipitation in SEA and to find out whether they are responsible for the equivalent-barotropic anomalous cyclone.
As identified by the Niño-3.4 index, La Niña should be expected over the eastern equatorial Pacific during 2021. The cooling pattern in the SST anomaly field (Fig. 7b) can also confirm this fact, as cooling SST can be observed in the central equatorial Pacific as well as off the coast of Peru, with a maximum absolute value above 1°. The cooling SST anomalies also trigger warming responses over the subtropics around 150°W.
In terms of SAM forcing, the index indicates that during these two months, a positive SAM is dominant, characterized by abnormal positive sea level pressure around 60°S and negative anomalies around the subtropics. Such a pattern can be identified in the distribution of mean sea surface pressure, where there are two maximum centers spreading from 120°E to 30°W along 60°S, and negative anomalies dominating the subtropics, especially around Australia (Fig. 7c). As a result, La Niña and positive SAM can be recognized by both the indices and the large-scale distributions of related parameters during these two months.
To determine the possible effects of ENSO and SAM, composite analysis is first conducted based on different situations of these forcings (Table 1), according to the phase of each mode that has a positive effect on Australian precipitation during the warm season. We mainly consider four conditions: SAM-only years; ENSO-only years; positive SAM coupled with La Niña years; and SAM coupled with out-of-phase ENSO years—when positive (negative) SAM co-occurs with La Niña (El Niño). When we analyze the years when SAM occurs with La Niña (Table 1), the composite patterns of the related anomalous parameters in February and March are computed. But for the other three conditions, composite difference patterns between the wet and dry conditions (Table 1) are computed instead. For simplicity, the following analyses refer to the results as only SAM events, only ENSO events, positive SAM along with La Niña events, and out-of-phase SAM and ENSO co-occurrence events, without mentioning whether it is a composite pattern or a composite difference pattern.
When positive SAM occurs alone during late summer (based on the composite difference between positive and negative SAM years, Figs. 8a,b), SEA tends to experience above-normal rainfall, especially in March (Fig. 8b), when most of central and eastern Australia is influenced by more precipitation. But during February, some precipitation deficits can also be observed over northern Australia and Western Australia (Fig. 8a). The composite of precipitation anomalies based on ENSO events shows a tendency consistent with previous studies (based on the composite difference between La Niña and El Niño; McBride and Nicholls 1983; Lewis and Karoly 2015; Nicholls and Kariko 1993; Godfred-Spenning and Reason 2002); La Niña events correspond to more precipitation for most areas of Australia (Figs. 8c,d). But during March, some negative precipitation anomalies are also evident around central Australia (Fig. 8d). The general paradigm is true for the region of interest; that is, La Niña events are likely to favor more precipitation in western SEA during February and in southeast SEA during March. Since both positive SAM and La Niña can lead to above-normal precipitation over SEA, further composite analysis is also performed with a focus on the situations with both positive SAM and La Niña or combined with cases when negative SAM and El Niño occur together.
When positive SAM and La Niña occur jointly, positive precipitation responses over SEA are stimulated during February and March; the abnormal precipitation in February occurs with less significant signals (Fig. 8e), while the precipitation responses are much more significant in March (Fig. 8f). For the composite difference between the years with positive SAM and La Niña and the years with negative SAM and El Niño, similar patterns are shown but with more significant signals. Especially in March, the anomalous precipitation belt is distributed from southeast to northwest Australia (Fig. 8h), which is also the case in the late summer of 2021, further indicating a plausible joint contribution of positive SAM and La Niña to the devastating floods during this year.
Composites of large-scale circulation patterns in association with different situations of SAM and ENSO are also plotted in Fig. 9, in order to reveal the responsible underlying mechanisms whereby these modes influence precipitation in SEA. When only SAM occurs, a belt of characteristic high sea level pressure is dominant around the midlatitudes, to its south, and anomalous enhanced low-level westerlies are also observed. Due to the influence of positive SAM forcing in southern Australia, SEA is also dominated by the high pressure system during February, in parallel with anomalous easterlies over the region of interest (Fig. 9a). In March the areas of the high pressure anomalies shrink and the intensity weakens, and a weak cyclonic circulation establishes above SEA (Fig. 9b). Meanwhile, over the SIO anomalous cyclonic patterns along with negative pressure signals dominate around 20°S during February and March. The pattern indicates the distinctive role of positive SAM in the Mascarene high: positive SAM tends to weaken the Mascarene high relative to ENSO (Figs. 9c,d). Normally a weakened Mascarene high benefits easterly winds around Tasmania, transporting more moisture from the Tasman Sea to Australia (Rehman et al. 2019). When only ENSO occurs, the anomalous responses in the tropics are very salient during February (Fig. 9c), and characteristic equatorial easterlies and an anomalous low pressure center around the Maritime Continent are triggered by the anomalous SST distribution. Influenced by ENSO, negative pressure responses are triggered above Australia during February. During March (Fig. 9d), the signals in the tropics and the negative pressure above Australia associated with ENSO weaken, but some prominent signals show at higher latitudes; however, the location of the maximum response is quite different compared to signals responding to positive SAM or the patterns in 2021. For years when both La Niña and positive SAM occur (Figs. 9e,f), the anomalous pattern in the tropics shows some resemblance to that during La Niña–only years, signifying the strong influence of ENSO on the atmosphere. Nevertheless, negative responses in sea level pressure occur over SIO off the coast of Western Australia, and positive anomalies at higher latitudes are consistent with the composite of SAM-only cases. Similar patterns are also displayed in the composite when considering the situation of the out-of-phase SAM and ENSO (Figs. 9g,h). During February (Fig. 9g), a strong low pressure system is located over Australia, and the significant anomalous cyclonic circulations are distributed over the Tasman Sea and the South Pacific, sharing similarities with the patterns associated with ENSO-only forcing, which indicates that the anomalies are stimulated mainly by external forcing. During March, the anomalous negative pressure is evident in SIO, likely linked to the pattern associated with SAM forcing (Fig. 9h). And to its east, the low pressure anomalies also reach SEA, leading to a weak cyclonic circulation pattern, and favorable structure for the formation of convection.
Responses in the higher troposphere are also examined in Fig. 10 in association with different combinations of ENSO and SAM events. During February, the significant anomalies responding to SAM impacts can be derived based on the composites of SAM-only cases and SAM cases accompanied by ENSO (Figs. 10a,e,g), in which there is a contrast in the geopotential height between higher latitudes and the subtropics with a minimum above SEA, constructing a wavelike pattern stretching from 30° to 60°S. The atmospheric responses at 200 hPa associated with La Niña are stronger over the tropics with or without a SAM event, and direct Gill-type responses (Gill 1980) corresponding to ENSO forcing also initiate an anomalous wave train along the meridional direction intruding into higher latitudes in the Pacific sector, which resembles the Pacific–South American pattern (e.g., Irving and Simmonds 2016; Figs. 10c,e,g). During March, the anomalies associated with SAM forcing vary a little bit: as revealed by the SAM-only cases, the wavelike pattern shifts eastward to the Pacific. Meanwhile, another positive center appears west of 60°E. Combined with the influence of ENSO, the shifted wave pattern due to SAM forcing tends to merge into the signals related to the direct Gill-type response forced by the SST cooling in the eastern Pacific (Figs. 10f,h). And the positive center west of 60°E enhances in the meantime when SAM occurs with an out-of-phase ENSO, which can also lead to a wavelike pattern expanding to the subtropical SIO. The negative geopotential height also corresponds to the negative pressure center near the surface (Figs. 9f,h), indicating that the Mascarene high is expected to weaken due to the SAM forcing. In between the two positive geopotential height anomalies along the 50°–60°S zonal belt, a negative anomaly center is located over southern Australia, modulating the climate in SEA.
During February, according to the conditions in the high troposphere, the responsible atmospheric circulation relative to SAM forcing is recognized as a disturbance originating from higher latitudes, triggering a cyclonic and negative geopotential high above SEA (Figs. 10a,e,g). At the lower level, the anomalous positive values along the zonal belt of 50°–60°S also suggest that the response is associated with SAM and is equivalent-barotropic (Figs. 9a,e,g). However, with SAM forcing only (Fig. 9a), the anomalous wave energy above SEA originating from higher latitudes tends to be relatively weak and cannot propagate downward to a lower level above SEA, resulting in the edge of positive pressure anomalies dominating southern Australia in the lower troposphere. Under the influence of ENSO, the wavelike pattern originating from higher latitudes in the higher troposphere cooperates with the strong low pressure system extending from the tropics due to the ENSO effect, facilitating the formation of the equivalent-barotropic cyclonic circulation. During March, when SAM occurs with an out-of-phase ENSO (Figs. 10f,h), the anomalous circulation in the higher troposphere is also beneficial for the maintenance of the cyclonic circulation pattern. At the lower level (Figs. 9b,f,h), in response to the anomalous wave energy propagating from higher latitudes, the cyclonic circulation anomalies are obvious above SEA in the years when SAM occurs, favoring convection activity.
To directly demonstrate the propagation of anomalous wave energy, wave activity flux propagation associated with SAM and ENSO along the meridional direction for the region between 120° and 140°E is plotted (Fig. 11); because this region is not in the direct pathway of ENSO influence, only the anomalous wave pattern associated with SAM forcing is obvious. It is noticeable that the strong wave energy source associated with SAM is over the subpolar region around 60°–70°S, where the anomalous wave energy can further propagate equatorward, reaching 20°S or much farther north. Such a wave pattern is dominant in February, which may be because from summer to autumn, the influence of SAM gradually weakens (Hendon et al. 2007; Ding et al. 2012). The positive (negative) values of the quasigeostrophic streamfunction at each level correspond to clockwise (counterclockwise) flow. Accompanied by La Niña events, the anomalous wave energy generated by SAM variation is evidently stronger, so it can intrude downward and convey convective wave energy to the surface (Figs. 11c,d). The reinforcement of La Niña to the wave pattern also reflects its longer duration; the wave pattern is still evident in March when SAM co-occurs with ENSO (Figs. 11g,h).
Therefore, based on these large-scale characteristics, a favorable environment is undoubtedly well set up with the collaboration of both internal and external forcing to the atmosphere, when a La Niña–triggered low pressure system dominates the lower troposphere over Australia and a positive SAM-induced anomalous cyclonic disturbance propagating from higher latitudes governs the higher level above southern Australia, leading to the equivalent-barotropic cyclonic circulation just above the region of interest. As revealed in the last section, such an equivalent-barotropic cyclonic circulation pattern is surely the most important system responsible for the extreme wet conditions during late summer of 2021, which proves the potential of ENSO and SAM to contribute to extreme precipitation in SEA by triggering such a dominant equivalent-barotropic cyclonic circulation pattern. The cyclonic circulation is associated with anomalous onshore winds from the Tasman Sea, as well as anomalous northwesterly winds across Australia, and these horizontal winds can transport abundant moisture from the Tasman Sea and tropical Indian Ocean, sustaining the long-term wet conditions.
6. Conclusions and discussion
Investigation of the extreme precipitation in SEA during late austral summer of 2021 is conducted with a particular focus on the responsible characteristics of water vapor transport and the possible joint impacts of internal SAM forcing and external ENSO forcing. In February 2021, above-normal precipitation occurs east of SEA, influencing the highly populated coastal region. These wet conditions continue into March, with the anomalous precipitation belt stretching from the tropical Indian Ocean and largely spreading all over SEA, influencing the main streams of the Murray–Darling River and leading to disastrous floods. A regional analysis of water vapor convergence reveals that anomalous moisture convergence below the 700 hPa level within the region is primarily positive during February, contributed mainly by water vapor input through zonal boundaries; the magnitudes of the anomalies of water vapor convergence are much larger during March, attributed mainly to water vapor convergence in the meridional direction. The horizontal distribution of vertically integrated water vapor flux illustrates an anomalous cyclonic circulation pattern around the Tasman Sea and SEA, which is responsible for the intensified water vapor transport along northwesterlies from the tropical Indian Ocean and along anomalous easterlies from the Tasman Sea during both February and March. This cyclonic circulation can also be identified as the main responsible anomalous wind pattern when examining the relative dynamic and thermodynamic contributions that largely contribute to the water vapor convergence in SEA. Additionally, anomalous water vapor distribution can also contribute to the water vapor convergence in this region, though it plays a secondary role. The presence of upper and lower large-scale atmospheric circulations ascertains that cyclonic water vapor flux is attributed to a dominant equivalent-barotropic cyclonic system over SEA, accompanied by deeply developed beneficial ascending motion, which contributes to the formation of strong rainfall.
The climate forcing conditions during austral late summer 2021 can be confirmed by both the SAM and El Niño indices and the large-scale background. Under the joint influences of La Niña and positive SAM, a general significant precipitation response is evident over SEA, corresponding to an equivalent-barotropic cyclonic circulation pattern around coastal subtropical eastern Australia. Examination of the detailed mechanism shows that La Niña tends to trigger a significant low pressure system and cyclonic wind anomalies over Australia, while SAM stimulates anomalous wave patterns initiating from higher latitudes to subtropical SEA in the higher troposphere. Hence, when these two forcing factors occur together, their impacts can be amplified: the anomalous wave energy generated by SAM variation is enhanced and can propagate to near the surface, conveying the convective wave energy to the surface. Meanwhile, the location of the La Niña–induced low pressure center extends southward, leading to the important barotropic cyclonic system.
One issue regarding the extreme wet conditions and the corresponding water vapor transport during these two months in SEA needs further discussion. Why is precipitation in March much more extreme than that in February under a similar forcing background? Here we want to address this from the perspective of the interaction between beneficial water vapor transport and SEA orography.
Meridional and zonal moisture transport are both examined over SEA along a vertical slice (Fig. 12) with orography. It is noticeable that during February, the dominant responsible moisture convergence comes from the zonal contribution (Fig. 12a), while meridional water vapor convergence is observed only along 25°S near the surface (Fig. 12c). However, the orography of the Great Dividing Range can block moist air masses in the lower troposphere from the eastern ocean, and most moisture is located at the lower level; as a result, zonal water vapor convergence is less efficient for precipitation. To quantitatively view the water vapor input into the targeted region, analysis of the net convergence of water vapor is also useful here. Hence the calculated results, shown in Fig. 12e, in February support the above-mentioned convergence of water vapor in the zonal direction, where a comparable amount of moisture is advected through the western and eastern boundaries of SEA, but quite a bit of moisture is also transported out through the southern boundary due to the blocking of the south–north-oriented Great Dividing Range, resulting in considerably less net moisture input.
During March, water vapor convergence shows a distinctive pattern when extreme flooding occurs, revealing the relatively dominant role of meridional moisture contributions at different levels (Fig. 12d). Zonal water vapor transport displays a weak divergence pattern, with the prevailing eastward and westward transport to the east and west of 150°E (Fig. 12b). In the meridional direction, strong convergence of water vapor flux appears between 30° and 40°S at all levels, providing the necessary abundant moisture for the extreme precipitation during March (Fig. 12d). The meridional water vapor flux can be traced back to the tropical ocean, as revealed by the horizontal distribution of the vertically integrated flux pattern (Fig. 3), and along the passage of water vapor transport, the topography generally consists of the central plains, which favor moisture transport into SEA. In that case, meridional water vapor convergence is revealed to be more efficient in providing moisture supply for precipitation in SEA, and the different features of water vapor transport can be responsible for relatively wetter conditions in March. The regional analysis also agrees with these features, where considerable moisture converges into SEA through the southern and northern boundaries, while only about 30% of the input moisture flows out through the zonal boundaries, which still leads to an extreme net moisture input remaining in the region and contributing to the wetter month (Fig. 12f). Notably, the water vapor analysis in the present study is conducted based on 6-hourly data and therefore excludes the effect of the relevant covariances due to higher-frequency variations, which could be considerable under some intense circumstances.
Acknowledgments.
This work is jointly supported by the National Natural Science Foundation of China Key Project (42120104001), National Natural Science Foundation of China (42005010), and the External Cooperation Program of the Bureau of International Cooperation, Chinese Academy of Sciences (134111KYSB20200020).
Data availability statement.
The reanalysis dataset, ERA5, is obtained from the European Centre for Medium-Range Weather Forecasts (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5). GPCP and ERSSTv5 datasets are extracted from the NOAA/OAR/ESRL PSL, Boulder, Colorado (https://psl.noaa.gov/).
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