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Article

Hourly and Sub-Hourly Rainfall under Synoptic Patterns during the Anomalous Meiyu Season 2020

by
Liye Li
1,2 and
Fan Zhang
1,*
1
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
2
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Atmosphere 2023, 14(4), 727; https://doi.org/10.3390/atmos14040727
Submission received: 28 February 2023 / Revised: 3 April 2023 / Accepted: 7 April 2023 / Published: 18 April 2023
(This article belongs to the Special Issue Monsoon and Typhoon Precipitation in Asia: Observation and Prediction)
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Abstract

:
The 2020 Meiyu season has received extensive attention due to its record-breaking rainfall in the Yangtze–River Huai Basin (YHRB) region of China. Although its rainfall features have been well studied on various time scales, the sub-hourly/hourly rainfall features are unknown. In this study, a wavelet analysis was applied to 1 min rainfall data from 480 national rain gauges across the YHRB, and hourly synoptic patterns during the Meiyu season were grouped using an obliquely rotated principal component analysis in T-mode (PCT). The results suggest that variances on the sub-hourly and hourly scales contributed 63.4% of the 2020 Meiyu rainfall. The hourly synoptic variations in the Meiyu season can be categorized into three major patterns: weak synoptic forcing (P1), a convergence line (P2), and a vortex (P3). The rainfalls under P1 were spatially dispersed over the YHRB and on the shortest time scale, with a 70.4% variance from sub-hourly to hourly rainfalls. P2 had a peak wavelet variance around 30 min–1 h, with rainfalls concentrated to the south of the convergent line. The rainfalls under P3 were locally distributed with a longer duration of around 1–4 h. Compared with the climate mean, hourly rainfall frequencies are indispensable to understanding the 2020 accumulated Meiyu rainfall anomaly. This research highlights the dominant role of synoptic patterns on the temporal and spatial features of the Meiyu rainfall.

1. Introduction

During the months of June and July every year, a southwesterly monsoonal airstream brings a substantial amount of moisture into Eastern China, producing a sizeable portion of annual rainfalls, known as the Meiyu season, over the Yangtze–Huaihe River Basin (YHRB) [1,2,3,4,5]. Most rainfalls are generated along an elongated rainbelt hundreds of kilometers in length, which is referred to as the Meiyu front and is often defined by a high horizontal equivalent potential temperature (θe) gradient [4,5]. In some years, in the YHRB, Meiyu rainfalls accounts for more than half of the annual precipitation [6], and floods triggered by the concentrated regional rainstorms cause major disasters [7]. Given the typical nature of heavy convective rainfalls, flash floods, landslides, and urban inundation are often related to short-duration rainfalls, such as hourly and sub-hourly rainfalls [8,9,10]. Thus, the temporal and spatial features of hourly rainfalls during the rainy season and the associated climate trends have been studied in Eastern China, covering the YHRB [7,11,12,13]; however, rainfall features on the sub-hourly scale are seldom studied, and the contribution from rainfalls on the hourly and sub-hourly scale compared with other scales is not quantitatively presented, especially during the abnormal Meiyu season.
The most recent abnormal Meiyu season was that of 2020, during which the YHRB received the heaviest rainfall since 1961 [14,15]. As many as 124 rain gauges within the YHRB recorded an accumulated rainfall of over 800 mm, with the maximum accumulated rainfall being 1719.5 mm in the Huang mountains (S1 at Figure 1) and the maximum hourly rate being 88.7 mm at the lower reach of the Yangtze River (S4 in Figure 1). The 2020 Meiyu season affected 63.46 million people over the YHRB and resulted in direct economic losses of over CNY 178.96 billion (http://www.gov.cn/xinwen/2020-08/13/content_5534534.htm, accessed on 1 September 2020).
Numerous studies have been conducted on the generation of this record-breaking and high-social-impact Meiyu season. The results show that the interdecadal [16] and interannual variations in Sea Surface Temperature (SST) in the Indian, Pacific, and Atlantic oceans [14,17,18] facilitated the development of anomalous large-scale circulations, such as an extremely strong Western Pacific Subtropical High (WPSH), excessive atmospheric blocking over East Siberia, an upper-level westerly jet, and a low-level southwesterly jet [15,19,20]. The anomalously strong WPSH and the southwesterly flows to its west advected warm and moist air from the Arabian Sea, the Bay of Bengal, and the South China Sea to the YHRB [15,19,21,22]. Moreover, quasi-stationary blocking highs promoted active cold air intrusion to the south. Thus, mass convergence and uplifting in the lower troposphere was increased over the YHRB [15,19,20]. In addition, upper-level divergence and ascending motions over the YHRB were enhanced by a periodically strengthened upper-level westerly jet [15]. As a result, stagnant rainbelts with heavy precipitation could be maintained over the YHRB during the 2020 Meiyu season.
In addition to the total rainfall anomaly, rainfall features on the synoptic and diurnal scales during the 2020 Meiyu season have also been investigated, together with the associated circulation patterns. The synoptic variations were related to a mid-latitude trough, eastward-propagated low-level cyclonic vortices, and a WPSH that shifted northwest–southeast [23,24]. Diurnal variation in the low-level southerlies favored nocturnal low-level jets (NLLJs) and the development of nocturnal rainbelts [25]. Those superimposed synoptic and diurnal variations led to the temporal and spatial heterogeneity of rainfalls, so that the 2020 Meiyu rainfall included several intense multi-day rainfall episodes [15,24,25,26] and presented localized features over the YHRB (Figure 1).
However, little work has been done on the sub-hourly and hourly characteristics of the 2020 Meiyu rainfall events and their associated large-scale circulations. In addition, the high seasonal rainfall amounts in the 2020 Meiyu season could be partly attributed to heavy rainfall rates and partly to the unusually long duration of the 2020 Meiyu season, (62 days) (Table 1). It is unclear if intensity or frequency potentially contributed to the 2020 Meiyu rainfall anomaly. More work is needed to examine the sub-hourly and hourly rainfall features and the favorable larger-scale circulations that could account for the accumulated heavy rainfall.
To this end, the objectives of this study were to (i) explore the hourly and sub-hourly characteristics of the 2020 Meiyu rainfalls; (ii) investigate the types of larger-scale circulations that led to the distinct sub-hourly and hourly rainfall features; and (iii) compare the hourly rainfall features of the 2020 Meiyu season with other years. The next section describes the data and methodology used in this study. Section 3 presents the sub-hourly and hourly characteristics of the 2020 Meiyu rainfall events. Section 4 shows the representative circulations during the 2020 Meiyu season and hourly variations in circulations. Section 5 explores the features of sub-hourly and hourly rainfalls under different synoptic patterns during the 2020 Meiyu season. The features of the hourly 2020 Meiyu rainfalls are compared with historical data in Section 6. A summary and concluding remarks are given in the final section.

2. Data and Methods

2.1. Data

In this study, two sets of observed rainfall data (referred to as R1m and R1h) from 480 national operational rain gauges over the YHRB, released by the National Meteorological Information Center of the China Meteorological Administration, are used. R1m and R1h have the same spatial resolution of 15–20 km but different temporal resolutions. R1m, with a temporal resolution of 1 min, was used to explore the high-frequency characteristics of the 2020 Meiyu rainfalls using a wavelet analysis. R1h comprises hourly rainfall data during the years 1980–2020. In total, 367 of 480 national operational rain gauges produced continuous records for those years, which were used to conduct the year-to-year comparisons in Section 6.
To better characterize the spatial distribution of the observed rainfalls, R1m during the year 2020 was interpolated into 0.1° × 0.1° horizontal grids using the Cressman [27] analysis. The fifth generation of the European Center for Medium-Range Forecasts (ECMWF) atmospheric hourly reanalysis data (ERA5) [28] with a 0.25° horizontal resolution was used for synoptic analysis and pattern classification.

2.2. Wavelet Analysis

To identify the rainfall features on various time scales, especially the sub-daily scale, a wavelet analysis was used on the R1m dataset in this study, because a wavelet analysis is suitable for local time-frequency decomposition and is flexible on non-stationary signals with short-lived high-frequency phenomena, such as abrupt variations or singularities [29,30,31,32]. In particular, a discrete wavelet transform (DWT) scheme, which follows the Parseval’s theorem and conservatively decomposes the energy in a dyadic time series (an integer multiple of 2) across scales [33], was selected for this paper, so that the distribution of energy could be used to indicate the contribution from rainfalls on individual time scales and the maximum component of periodicity could be identified [34,35].
Hereafter, a rainfall episode is defined as a sequence of rainfall records, which is roughly continuous and has considerable wavelet variance on the time scale of its duration. Therefore, the sequence is regarded as an episode related to a rainfall system with physical consistency.

2.3. Obliquely Rotated Principal Component Analysis in T-Mode (PCT)

To help gain insights into the sub-daily variation in heavy rainfalls during the 2020 Meiyu season, their associated major circulation patterns were clustered using an objective classification method, i.e., an obliquely rotated principal component analysis in T-mode (PCT) [36]. This classification method is capable of simplifying an immense variety of regional circulation patterns by identifying a small number of representative ones and capturing the underlying physical structures. Moreover, this method is less dependent on the choice of pre-set parameters [37].
The PCT analysis is used in many studies to identify the dominating circulation patterns [38,39]. In the present study, the PCT method was applied to hourly geopotential heights at 850 hPa during the Meiyu seasons of 2018–2021. That is, each hourly circulation pattern was objectively classified into one representative type, and the evolution of hourly variations could be interpreted by alternations between the major circulation patterns. The data affected by the passage of a tropical cyclone were excluded.

3. Sub-Hourly to Hourly Rainfall in the 2020 Meiyu Season

3.1. Meiyu Rainfall in 2020 and Synoptic Background

Figure 1 presents the spatial distribution of the accumulated rainfall in the 2020 Meiyu season. As many as 92% rain gauges over the YHRB region recorded an accumulated rainfall of over 400 mm. An accumulated rainfall of over 800 mm was recorded in the middle to lower reaches of the Yangtze River, which is near and to the south of the averaged Meiyu front at around 31–32° N, defined as the maximum equatorial gradient of the equivalent potential temperature hereafter. Two rainfall centers at over 1000 mm were located around Mts. Dabie and Huang, whose peaks are on average 1000–1800 m above the sea level. The highest three accumulated rainfalls of over 1500 mm (S1, S2, and S3) were also recorded on the mountain top and slope of Mt. Dabie and Mt. Huang.
The anomalous rainfall events were associated with anomalous large scale environmental conditions, and the large-scale background during June–July 2020 in Eastern China is shown in Figure 2, including a deviation of 500 hPa geopotential height compared with the climate mean. The positive anomaly in ~15–31° N exceeded 20 gpm, which is in excess of two standard deviations, indicating the anomalously strong WPSH in June–July 2020. Moreover, as denoted by the 5880 gpm isobaric line, the WPSH extended northwestward, with the western apex of the ridge axis shifting from its climate mean location of 130° E to 108° E in June–July 2020. The YHRB was to the north of the strengthened and westward-extended WPSH, thus the meridional pressure gradient aloft was enhanced. Correspondingly, the low-level southwesterly wind along the northwest rim of the WPSH was enhanced, with a mean speed greater than 8 m s−1, transporting abundant moisture into the YHRB. Supported by the steady and moist southwesterlies, the Meiyu front had an average location of around 31–32° N, crossing the YHRB in June–July 2020. In the warm sector of the Meiyu front, the YHRB was mostly covered by an enhanced low-level southwesterly and abnormally high precipitable water. The total precipitation over the YHRB was more than the climate mean, exceeding it by two standard deviations from the ERA5. The accumulated Meiyu rainfall according to national rain gauges was distributed over a similar area in the middle reach of the Yangtze River (Figure 1).
Normally, the onset and retreat of the Meiyu season corresponds to significant northward jumps of the WPSH around mid-June and mid-July, respectively [40,41]. On average, the Meiyu seasons over the YHRB lasted for 41 days (i.e., from 8 June to 19 July) during 1980–2019 (see Table 1). In contrast, as suggested by the white dashed and dash-dotted lines in Figure 2, the WPSH ridge axis jumped to the north of 20° N on 1 June and swung within the YHRB until 2 August, resulting in the extra-long duration of the 2020 Meiyu season.

3.2. Sub-Hourly and Hourly Rainfall Features

To obtain an overview of the contribution of rainfall variation to the Meiyu rainfalls in 2020 on different time scales, including sub-hourly and hourly rainfalls, the energy distribution of the 1 min rainfalls in June–July 2020 was calculated by a wavelet analysis (Figure 3a). Overall, 63.4% of the rainfall expectation was from a time scale shorter than or around 1 h, with the maximum amplitude around 30 min, implying the important contribution of sub-hourly to hourly rainfalls in the 2020 Meiyu season. The wavelet variance results emphasize the necessity to investigate the sub-hourly and hourly rainfall features and various synoptic disturbances when assessing such rainfall features.
Figure 3b shows the spatial distribution of the hourly rainfall frequency over the YHRB in June–July 2020. In general, the 480 rain gauges over the YHRB recorded an average hourly rainfall frequency of 273 h in June–July 2020, which is equal to 4.5 h per day on average. The hourly rainfall frequency had a similar spatial distribution as the accumulated rainfall, with two maximum rainfall centers above the terrain. The stations of S1, S2, and S3, which had the top three accumulated rainfalls, also recorded hourly rainfall frequencies of over 400 counts, indicating the contribution of hourly rainfall frequency to the accumulated rainfall anomaly. Among all the hourly records by rain gauges within the YHRB in June–July 2020, the intensity of hourly rainfall over the 97% threshold ranged from 15 mm to 88.7 mm. Therefore, 15 mm per hour is used as the threshold for hourly heavy rainfalls hereafter. Figure 3b shows the hourly heavy rainfall frequency for the rain gauges at different thresholds during June–July 2020, i.e., 10 to 20 times, greater than 20 times, and the top two maximum counts of 26 times. Two stations at the Huang mountains recorded the highest hourly rainfall occurrence and five stations at and near the Dabie mountains recorded an occurrence of over 20 counts. These were also the centers of the accumulated rainfall (Figure 1) and the hourly rainfall frequency (Figure 3b). In addition, 32.1% of the 480 rain gauges with over 10 counts of hourly heavy rainfalls were widely distributed in the warm sector to the south of the Meiyu front, not only near the Meiyu front, but also far to the south of 30° N, indicating possible rainfall systems producing hourly heavy rainfalls away from the average location of the Meiyu front, but with less contributions to the accumulated rainfall. Moreover, the maximum hourly rain rates according to the 480 rain gauges are shown in the box and whisker chart (Figure 3c), showing that an hourly rainfall over 28 mm h−1 was observed by more than 75% of the rain gauges within the YHRB. In addition, the maximum hourly rainfall records ranged from 6.6 mm h−1 to the largest of 88.7 mm h−1, implying the possibility of the rainfall system producing spatially localized heavy rainfalls. The variations in hourly rainfall frequency relative to the location of the Meiyu front and the maximum hourly rain rates according to the rain gauges require further analysis in relation to the synoptic variations produced.

4. Regional Flow Regimes and Hourly Rainfall Features

The rainfall episodes with different temporal features, as shown in Figure 3a, could form sequences of organized convection, such as squall lines, meso-scale convective systems, and meso-scale convective complexes, subject to the influence of their synoptic environments [42,43]. Under weak-forcing conditions, the cloud/rainfall episodes could occur in short durations [44,45]. During the 2020 Meiyu season, synoptic disturbances included a mid-latitude trough with active cold air intrusions and generated southwest vortices (SWVs) [15,23], which are conducive to record rainfalls. To establish how synoptic patterns affect the spatial and temporal features of sub-hourly and hourly Meiyu rainfalls, first, the hourly circulation patterns needed to be objectively grouped into major types for the Meiyu seasons using the PCT method.

4.1. Clustered Flow Regimes

The hourly synoptic patterns in Central and East China during the Meiyu season without typhoon days from 2018–2021 were objectively classified into four types using the PCT method, with a cumulative variance of 95% calculated by the principal component analysis. The frequency of the four patterns in 2020 was 56.3%, 30.6%, 7.5%, and 4.5%, respectively. The composite patterns of the clustered flow regimes and the accumulated rainfall under each during June–July 2020 are presented in Figure 4. The accumulated rainfall under P1 was widely distributed, with a maximum center over 1000 mm around the Dabie mountains and the surrounding areas, near the average maximum equatorial gradient of the equivalent potential temperature around 30–32° N. The WPSH 5880 m isoline extended northward to 29° N. Along the west rim of the WPSH, low-level southerlies crossing the horizontal isothermal line brought a substantial amount of moisture into the YHRB, which is the major energy source in the form of latent heat for the development and maintenance of the disturbances in the Meiyu rainbelt [46,47,48]. The YHRB was generally under the warm sector, with relatively uniform dynamic and thermal-dynamic conditions with few synoptic disturbances from the mid-latitudes and southwest.
In contrast to the weak-forcing environment of P1, the synoptic patterns of P2 (Figure 4b) and P4 (Figure 4d) both have distinct mid-latitude disturbances of high- and low-pressure centers in a sequence, but the differences between P2 and P4 are noticeable as well. Firstly, the northern YHRB was covered by the post-frontal northerly wind related to a low-pressure center under P2. Moreover, it was under the descending region of a high-pressure center under P4. Secondly, the WPSH under P2 extended northwestward but retreated southward under P4. Thus, the meridional pressure gradient under P2 was enhanced and the average wind speed was greater than 10 m s−1. Thirdly, P2 had distinct wind convergence between the dry northerly and moist southwesterly regions within the YHRB, and a rainbelt over 400 mm was observed to the south of the mean Meiyu front around 31° N, with a maximum center over 800 mm near the Huang mountains. By contrast, P4 had a lower pressure and equivalent pressure gradient and thus weaker convergence in the YHRB, contributing only 3.25% to the Meiyu rainfalls over the YHRB in 2020. Therefore, we chose not to focus on P4 in this paper.
P3 (Figure 4c) only had a frequency of 7.5% during 2020, but it caused intense and localized rainfalls, with a maximum record over 150 mm in the southern YHRB. The frequency of P3 was only comparable to 13.8%, but the maximum cumulative rainfall reached 27.9% of that under P1 in June–July 2020. The synoptic pattern of P3 featured a vortex in the YHRB. Such meso-scale cyclonic circulations within the YHRB can develop from eastward-moving SWVs, which occurred in the eastern and southeastern flanks of the Tibetan Plateau and were identified at 700 hPa. The east-moving SWVs may become the quasi-stationary cyclone center for the Meiyu front and produce heavy rainfalls [43,49,50,51,52]. In the composite synoptic pattern of P3, the horizontal wind shear was at ~30° N, with southwesterly winds to the south and easterly winds to the north. The equivalent potential temperature had a maximum gradient in the northern part of the vortex around 31° N, while precipitation accumulated to the south of the shear line. The WPSH under P3 retreated southward and the low-level southerly wind was strong, with a wind speed of over 10 m s−1, favoring the conveyance of moisture.

4.2. Vertical Cross Section

Figure 5, Figure 6 and Figure 7 present the mean vertical cross sections in the north–south direction under the major synoptic patterns of P1, P2, and P3 (Figure 5a, Figure 6a, and Figure 7a), including the equatorial gradient of the equivalent potential temperature, the distribution of relative humidity, and the in-plane wind vectors. The cross section is located along the longitude of the maximum accumulated rainfall center under each synoptic pattern. In addition, the zonally averaged rainfall within the longitudinal boundary of the YHRB is also shown along the latitudes (Figure 5b, Figure 6b, and Figure 7b).
The In-plane winds under P1 (Figure 5a) were steady southerlies, promoting the movement of moisture northward, with a low-level relative humidity over 80% in the YHRB. The belt of the maximum equatorial equivalent potential temperature over 3 K (deg lat−1) was around 31 to 34° N, and it tilted northward along with the height, indicating the average location of the Meiyu front. The steady southerlies crossing the dense isotherm lines of the equivalent potential temperature indicate the warm advection favoring the upward motion along the Meiyu front [5]. In addition, impinging airflow towards the terrain caused upslope lifting, and moisture was piled up on the upslope and above the mountains, suggesting a possible orographic effect. The zonal mean accumulated rainfall under P1 in the YHRB (Figure 5b) at latitudes from 28 to 34° N was over 100 mm, and the maximum was around 32° N, under the high gradient of the equivalent potential temperature.
Apart from warm advection from the southerlies similar to that observed under P1, the synoptic pattern of P2 (Figure 6a) has a noticeable convergence line around 32° N with a dry northerly from the mid-latitude and increased upward motion around 30° N. The strong convergence intensified, and the gradient was over 5 K (deg lat−1) around 30–32° N. The external forcing under P2 triggered a convection by lifting air parcels, and the upward motion was further reinforced by the convective instability and the resultant diabatic heating. Therefore, the convection–circulation feedback intensified the Meiyu front [5,53,54] and the accumulated rainfall was produced to the south of the convergence line around 30° N (Figure 6b).
In terms of P3 (Figure 4c and Figure 7a) with a vortex average center around 30° N, the equivalent potential temperature decreased rapidly to the north of the horizontal shear line, leading to a high gradient zone around 32° N with a core above from 1 to 4 km, which was more intense than those of the other patterns. In addition, a localized and intense rainfall was generated to the south of the horizontal shear line (Figure 7b), where the surface moisture was confined with a maximum of over 90% and spread upwards to the upper level, and the southerly wind turned into an upward motion.

4.3. Hovmöller Diagram of Hourly Rainfall Clusters

Under the effect of the strength and variation of synoptic disturbances, the circulation patterns change and bring rainfall with different features. To check the impact of the hourly synoptic variations on sub-hourly and hourly rainfalls, representative synoptic patterns for each hour were labeled using different color blocks along the timeline for June–July 2020 (Figure 8b,d and Figure 9). The time series of the hourly rainfall frequency in the YHRB is plotted in Figure 8a,c. The hourly rainfall is presented in Hovmöller space to exhibit the meridional (Figure 8b,d) and zonal (Figure 9) propagating characteristics of rainfall clusters. In particular, to identify the impacts from mid-latitude disturbances and eastward-moving SWVs, the locations and trajectories of any closed vortex at 850 hPa within 112–120° E and 27–34° N are marked with the letter L and a dashed line, and SWVs with its center entering the YHRB are emphasized in red (Figure 9).
Meridionally, the Meiyu front stayed in the YHRB region with several north–south swings after its first northward movement in early June (Figure 8b,d). Zonally, the YHRB was affected by strong and weak synoptic disturbances, including 12 sets of eastward-moving meso-vortices with four sets across the YHRB, and weak-forcing breaks between the sets of vortices, such as those seen in mid-June and the end of July (Figure 9). Overall, the location of the hourly rainfall clusters varies in relation to the meridional shifting Meiyu front and the eastward-moving disturbance. In addition, the synoptic patterns altered between P1 and P2 with occasional interludes of P3 (Figure 8 and Figure 9).
During the breaks of the eastward-moving vortices, without strong synoptic forcing from mid-latitude or southwest China, the synoptic pattern was often classified as P1 (Figure 9). In addition, the Meiyu front either stayed stationary at around 31–32° N (e.g., 15–17 June, 27–31 July) or moved northward under the promotion of the steady southwesterly (e.g., 7–8 June, 20–23 June, 26–28 June) (Figure 8b,d). While the Meiyu front moved northward, the rainfall clusters were weak and widely spread in the warm sector with little longitudinal migration (Figure 9), and the hourly rainfall frequency was enhanced within the YHRB (Figure 8a,c).
When the vortices were moving eastward from ~105° E to the north of the YHRB (Figure 9), the post-trough dry northerly was enhanced to favor its convergence with the moist southwesterly at a low level. In addition, the Meiyu front retreated southward after a rapid swing (Figure 8b,d) and P1 turning to P2 can be observed, such as on 21–24 June, 27–30 June, 2–3 July, 11–12 July, and 17–20 July. The rapid switch between P1 and P2 reveals the intense collision between the dry northerly and moist southerly within the YHRB, producing aggregated hourly rainfall clusters near the Meiyu front in latitude (Figure 8b,d) and displacing eastward in longitude with time (Figure 9). Once the YHRB was largely occupied by the dry air mass from the north under P2, the rainfall diminished (Figure 8b,d) and the hourly rainfall frequency decreased (Figure 8a,c) under the dry sector, such as on 17–19 June and 23–24 July.
When the vortices were moving eastward and entering the YHRB (Figure 9), as shown in the case of 5–6 June, 8–10 June, 25–26 June, and 7–9 July, the synoptic patterns were mostly clustered as for P3, except for the case of 25–26 June, during which the SWV was weak and the flow pattern was close to a shear line rather than a vortex (not shown); thus, the pattern is classified as P2. The SWVs on 7–9 July were the strongest and stayed the longest in eastern China from the aforementioned cases, causing continuous heavy rainfall in the southern quadrant of the vortex. During this rainfall event, the maximum 6 h rainfall during the 2020 Meiyu season was recorded at 212.6 mm at 0100-0600 LST, on 8 July.
In summary, the hourly variation in synoptic patterns features an evolution of the mid-latitude ridge/trough, eastward-moving SWVs, and a steady southwesterly, which together affect the location of the Meiyu front and the rainfall distribution. The classification of P1–P3 can show the hourly synoptic variations that produced rainfalls during the 2020 Meiyu season.

4.4. Hourly and Sub-Hourly Rainfall under Synoptic Patterns

To quantitatively capture the rainfall features under each synoptic pattern, a similar wavelet analysis to that shown in Figure 3a was applied on the R1m data under P1, P2, and P3 (Figure 10). As shown in the results, the energy distribution of the wavelet variance under each pattern exhibited a different distribution on a range of time scales. The rainfall episodes under P1 had the shortest time scale, with a 70.4% rainfall expectation from sub-hourly to hourly rainfalls, suggesting that the rainfall episodes under P1, produced by warm and steady southerlies without significant synoptic disturbance, were the shortest in duration but made the largest contribution to the accumulated rainfall compared with the other patterns. In addition, with the frequent occurrence of P1 (56.3%), the accumulated rainfall under P1 was 57.6% of the total 2020 Meiyu rainfall, indicating that weak/no forcing days can accumulate considerable rainfall via short-term rainfall episodes with a high frequency.
P2 has a wavelet variance maximum around 30 min–1 h and 59.8% of the rainfall expectation is from the sub-hourly to hourly scales, implying that the external forcing of the convergence line prolonged the duration of rainfall episodes. In contrast to P1 and P2, the rainfall episodes under P3 lasted longer with a maximum wavelet variance of 1–4 h; thus, the percentage of the sub-hourly to hourly rainfalls was reduced to 50.1%, which is related to the quasi-stationary vortex in the YHRB. Overall, the sub-hourly and hourly rainfalls contributed more than half of the total Meiyu rainfall under each synoptic pattern.
To separate the effect of the hourly rainfall frequency under different synoptic patterns on shaping the spatial distribution of the 2020 Meiyu rainfall, the hourly rainfall (≥0.1 mm h−1) frequency and the center of the hourly heavy rainfall (≥15 mm h−1) frequency are spatially shown in Figure 11a–c. In addition, a box and whisker plot of the maximum hourly rain rates at the 480 rain gauges within the YHRB under P1, P2, and P3 are presented (Figure 11d). Rain gauges that recorded the hourly rainfall over the 25th quantile and the maximum outlier are labeled in Figure 11a,c, so that the spread of the most intense rainfalls under each synoptic pattern are illustrated.
In general, the hourly rainfall frequency (Figure 11) exhibited a similar distribution to the accumulated rainfall under each pattern (Figure 4). Rain gauges within the YHRB under P1 (Figure 11a) widely observed an hourly rainfall frequency of more than 90 counts, with the maximum frequency reaching 300 counts around the Dabie mountains. The hourly heavy rainfall was also more frequent near the average location of the Meiyu front and over terrain, indicating a possible orographic enhancement under steady impinging southwesterlies. Moreover, 75% of the rain gauges had a maximum hourly rain rate (Figure 11d) of over 20 mm h−1 and intense hourly rainfalls over the 25th quantile, and the maximum outlier was widely observed in the warm sector of the YHRB under P1, suggesting that the rainfall system producing hourly rainfalls was also widely dispersed to the south of the Meiyu front under P1.
The hourly rainfall frequency and the center of the hourly heavy rainfall frequency were concentrated to the south of the Meiyu front under P2, along the convergence line. In addition, they were enhanced on the upslopes and mountaintop of the Huang mountains (Figure 11b). Compared with P1, less rain gauges under P2 recorded the maximum hourly rainfall over the threshold of hourly heavy rainfalls (≥15 mm h−1), due to the less frequent rainfalls in the dry sector to the north of the convergence line. Rain gauges that observed hourly rainfalls over the 25th quantile were concentrated to the south of the convergence line, along with the steady southwesterlies.
The hourly rainfall under P3 was further limited to the south of the vortex within the YHRB, and the maximum hourly rainfall frequency was on the slope of the Huang mountains (Figure 11c). Abundant moisture supplied by the strong southerlies was restricted to the south of the horizonal shearline (Figure 7a), producing a localized rainfall distribution. In addition, P3 had the lowest portion of rain gauges, recording a maximum hourly rainfall over 15 mm h−1, but had the most records beyond the maximum outliers, which were distributed in the southeast quadrant of the average location of the vortex. The maximum hourly rain rate under P3 was 82.1 mm h−1, close to that of 88.7 mm h−1 under P1. The hourly rainfall feature under P3 indicated that the quasi-stationary meso-vortex not only extended the duration of rainfall episodes (Figure 10) but also increased the hourly rainfall frequency and produced localized intense rainfalls.

5. Contribution from Hourly Rainfall to Meiyu Anomaly

Rain intensity or rainfall frequency may have both contributed to the 2020 Meiyu rainfall anomaly and are analyzed in this section. Because historical rainfall data at a 1m interval (R1m) were not available, and considering the sub-hourly rainfall occurrences were included in the hourly rainfall occurrence, the analysis in this section is based on R1h, and the deviation was calculated using the 2020 Meiyu season from the climate mean of 1980–2019. The probability density distributions were calculated using the accumulated rainfall (Figure 12a), the hourly rainfall frequency (Figure 12b), the hourly heavy rainfall frequency (Figure 12c), and the maximum hourly rainfall rates (Figure 12d).
As presented in Figure 12a, the accumulated rainfall records from the national rain gauges in the YHRB during June–July 2020 deviated significantly from the climate mean of the Meiyu seasons in 1980–2019, with 93.9% of the rain gauges recording an accumulated rainfall over one standard deviation and 52.2% over three standard deviations higher than the mean. Similarly, a large percentage of rain gauges recorded much more frequent hourly rainfalls than the historical data show (Figure 12b). Overall, 93.1% of the rain gauges exhibited an hourly frequency deviation over one standard deviation and 56.1% over three standard deviations (Figure 12b) higher than the climate mean. The increase in the hourly rainfall frequency also enhanced the probability of hourly heavy rainfalls (Figure 12c), with 80.1% of the rain gauges in June–July 2020, exceeding one standard deviation of the historical mean data. In comparison, the maximum hourly rainfall intensity was not as anomalous as the rainfall frequency (Figure 12d), with a smaller portion of the rain gauges recording similar levels of deviation, i.e., 49.7% of the rain gauges recorded maximum hourly rainfall rates over one standard deviation higher than the mean and only 8.6% over three standard deviations higher (Figure 12c). The above comparison emphasizes the contribution of the hourly rainfall frequency to the 2020 Meiyu rainfall anomaly.
The spatial correlation between anomalies of the accumulated rainfall and the hourly rainfall frequency is demonstrated in Figure 13. The deviation of the accumulated rainfall (shading) and the sub-hourly frequency (red contours) both depict large values in the middle and lower reaches of the Yangtze River and the two maximum centers at the Huang and Dabie mountains. This pattern almost overlaps with that of the accumulated rainfall distribution over the YHRB (Fig 1), that is to say, the accumulated rainfall centers in the 2020 Meiyu season were the areas with more frequent hourly rainfalls than shown in the historical data, suggesting that hourly rainfall frequency contributed to the total rainfall anomaly.
In addition, the rain gauges with an hourly rainfall intensity exceeding two standard deviations (18.0%) and an hourly rainfall frequency exceeding four standard deviations (30.6%) are marked in Figure 13. These thresholds of standard deviation were selected so that sufficient samples with relatively extreme values in each group were included. The rain gauges with a large hourly rainfall frequency (grey crosses) were distributed in areas that experienced an abundant accumulated rainfall anomaly. Moreover, the records of maximum hourly rainfall (grey squares) were widely dispersed in the YHRB, with no significant spatial correlation with the accumulated rainfall distribution. The maximum hourly rainfall records may have been produced by individual rainfall events and may lack universality in contributing to the accumulated Meiyu rainfall in 2020. In summary, the hourly rainfall frequency is indispensable to understanding the accumulated rainfall in 2020.

6. Summary and Conclusions

A record-breaking abundant rainfall was observed in the YHRB during the extra-long 2020 Meiyu season. Firstly, the features of hourly and sub-hourly rainfalls and their contribution to the Meiyu rainfall in 2020 were investigated. The accumulated rainfall and the hourly rainfall frequency overlapped significantly in spatial distribution, intuitively suggesting the importance of hourly rainfall frequency to the total anomaly. The role of sub-hourly and hourly rainfalls was further quantitatively confirmed via the energy decomposition of R1m over the YHRB., i.e., 63.4% of the Meiyu rainfall expectation in 2020 was from sub-hourly and hourly rainfalls.
Distinct rainfall features on the sub-hourly and hourly scales were associated with hourly synoptic variations, such as steady southwesterlies, mid-latitude disturbance, and eastward-moving southwest vortices. Using the PCT method, representative synoptic patterns of P1, P2, and P3 were objectively summarized, and rainfall features under each were analyzed.
When the YHRB was mostly under steady southwesterlies without a strong synoptic disturbance (trough/vortex), the circulation patterns were likely to be categorized as P1. Under P1, the Meiyu front was around 31–32° N, the WPSH extended northwestward, and sufficient moisture was conveyed into the YHRB by a low-level wind. The relatively uniform dynamic and thermal-dynamic environment of P1 produced short-term and dispersed rainfalls within the YHRB. Compared with the others, these rainfall episodes had the shortest time scale, with a 70.4% expectation from the sub-hourly to hourly scale. The accumulated rainfall and hourly rainfall frequency were widely distributed in the warm sector of P1 and enhanced near the dense isothermal line of the equivalent potential temperature and terrain. With the highest frequency of P1 being 56.3%, the accumulation of short-term rainfalls significantly contributed to the total rainfall in the 2020 Meiyu season.
In addition to the weak-forcing hours of P1, the YHRB was frequently affected by sets of eastward-moving disturbances in the mid-latitude and from southwest during the 2020 Meiyu season. If the approaching trough/vortices were to the north of the YHRB, the region was affected by the post-trough northerly. The dry northerly and moist southwesterly converged near 31° N on average, and the Meiyu front intensified with a stronger horizontal gradient of the equivalent potential temperature. This pattern had an occurrence of 30.6% in June–July 2020 and was classified as P2. The strong synoptic forcing under P2 favored the upward motion and brought concentrated rainfall clusters along the convergence line. The duration of rainfall episodes was extended under P2 compared to P1, and the percentage of sub-hourly and hourly rainfalls in the energy analysis was reduced to 59.8%, with most rainfall expectations within the time scale of ~30 min–1 h.
Once the eastward-moving southwest vortices entered the YHRB, the area was occupied by a quasi-stationary cyclonic wind flow at a low level and significant vertical lifting. This distinct pattern was classified as P3, which was the least frequent type (7.5%) from those studied. Nevertheless, it generated intense and localized rainfalls in the southern quadrant of the horizontal shear line, where the moisture was strongly confined. In terms of duration, rainfall episodes under P3 were elongated, with a maximum variance of 1–4 h, which is distinctively longer than those under P1 or P2.
The time series of hourly synoptic variations during the 2020 Meiyu season can be interpreted via the alternation between the major patterns. Scattered short-term rainfalls were mostly observed under the warm sector of P1. Heavy rainfalls were likely to occur under P3 or during the quick alternation between P1 and P2. Overall, more than half of the rainfall expectations under each pattern were from the sub-hourly and hourly scales. In addition, the role of short-term rainfalls was examined in relation to the 2020 accumulated rainfall anomaly. In comparison with the climate mean of the Meiyu seasons in 1980–2019, the 2020 season exhibited a positive deviation above one sigma for the hourly rainfall frequency and the hourly heavy rainfall frequency, as recorded by more than 80% of the rain gauges within the YHRB. This result emphasizes the indispensable role of hourly rainfall frequency in understanding the accumulated rainfall anomaly in 2020.
The sub-hourly and hourly rainfalls during the 2020 Meiyu season can be further analyzed in association with the meso-scale convective process. The features and occurrence of convective cells, meso-scale convective systems, and the mechanism of convective initiation under each synoptic pattern, can be investigated in detail. In addition, the effect of the terrain in terms of rainfall enhancement or orographic blocking is worth examining in the future.

Author Contributions

Conceptualization, L.L.; methodology, L.L. and F.Z.; software, L.L. and F.Z.; validation, L.L.; formal analysis, L.L.; resources, L.L. and F.Z.; writing—original draft preparation, L.L.; writing—review and editing, L.L. and F.Z.; visualization, L.L. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (Grant 42205005 and 42030607) and the Open Research Program of the State Key Laboratory of Severe Weather (Grant 2022LASW-A05).

Data Availability Statement

The fifth generation of the European Center for Medium-Range Forecasts (ECMWF) atmospheric hourly reanalysis data (ERA5) [28] with 0.25° horizontal resolution for the synoptic analysis and pattern classification are available at ERA5 hourly data on single levels from 1959 to the present (copernicus.eu).

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Tao, S.Y.; Chen, L. A review of recent research on the East Asian summer monsoon in China. Monsoon Meteorol. 1987, 60–92. [Google Scholar]
  2. Liu, Y.Y.; Li, W.J.; Ai, W.X.; Li, Q.Q. Reconstruction and application of the monthly western Pacific subtropical high indices. J. Appl. Meteorol. Climatol. 2012, 23, 414–423, (In Chinese with English abstract). [Google Scholar]
  3. Yao, X.; Ma, J.; Zhang, D.-L.; Yan, L. A 33-yr Mei-Yu-Season Climatology of Shear Lines over the Yangtze–Huai River Basin in Eastern China. J. Appl. Meteorol. Climatol. 2020, 59, 1125–1137. [Google Scholar] [CrossRef]
  4. Ninomiya, K. Characteristics of Baiu Front as a Predominant Subtropical Front in the Summer Northern Hemisphere. J. Meteorol. 1984, 62, 880–894. [Google Scholar]
  5. Sampe, T.; Xie, S.-P. Large-Scale Dynamics of the Meiyu-Baiu Rainband: Environmental Forcing by the Westerly Jet. J. Clim. 2010, 23, 113–134. [Google Scholar] [CrossRef]
  6. Ding, Y. Summer Monsoon Rainfalls in China. J. Meteorol. Soc. Jpn. 1992, 70, 373–396. [Google Scholar] [CrossRef]
  7. Zhang, H.; Zhai, P. Temporal and spatial characteristics of extreme hourly precipitation over eastern China in the warm season. Adv. Atmos. Sci. 2011, 28, 1177–1183. [Google Scholar] [CrossRef]
  8. Lewis, E.; Fowler, H.; Alexander, L.; Dunn, R.; McClean, F.; Barbero, R.; Guerreiro, S.; Li, X.-F.; Blenkinsop, S. GSDR: A Global Sub-Daily Rainfall Dataset. J. Clim. 2019, 32, 4715–4729. [Google Scholar] [CrossRef]
  9. Georgakakos, K.P. On the Design of National, Real-Time Warning Systems with Capability for Site-Specific, Flash-Flood Forecasts. Bull. Am. Meteorol. Soc. 1986, 67, 1233–1239. [Google Scholar] [CrossRef]
  10. Archer, D.; Fowler, H. Characterising flash flood response to intense rainfall and impacts using historical information and gauged data in Britain. J. Flood Risk Manag. 2018, 11, S121–S133. [Google Scholar] [CrossRef]
  11. Ng, C.; Zhang, Q.; Li, W. Changes in Hourly Extreme Precipitation Over Eastern China from 1970 to 2019 Dominated by Synoptic-Scale Precipitation. Geophys. Res. Lett. 2021, 48, e2020GL090620. [Google Scholar] [CrossRef]
  12. Yu, R.; Li, J.; Yuan, W.; Chen, H. Changes in Characteristics of Late-Summer Precipitation over Eastern China in the Past 40 Years Revealed by Hourly Precipitation Data. J. Clim. 2010, 23, 3390–3396. [Google Scholar] [CrossRef]
  13. Luo, Y.; Qian, W.; Zhang, R.; Zhang, D.-L. Gridded Hourly Precipitation Analysis from High-Density Rain Gauge Network over the Yangtze–Huai Rivers Basin during the 2007 Mei-Yu Season and Comparison with CMORPH. J. Hydrometeorol. 2013, 14, 1243–1258. [Google Scholar] [CrossRef]
  14. Zhou, Z.-Q.; Xie, S.-P.; Zhang, R. Historic Yangtze flooding of 2020 tied to extreme Indian Ocean conditions. Proc. Natl. Acad. Sci. USA 2021, 118, e2022255118. [Google Scholar] [CrossRef] [PubMed]
  15. Ding, Y.; Liu, Y.; Hu, Z.-Z. The Record-breaking Mei-yu in 2020 and Associated Atmospheric Circulation and Tropical SST Anomalies. Adv. Atmos. Sci. 2021, 38, 1980–1993. [Google Scholar] [CrossRef] [PubMed]
  16. Guo, Y.; Zhang, R.; Wen, Z.; Li, J.; Zhang, C.; Zhou, Z. Understanding the role of SST anomaly in extreme rainfall of 2020 Meiyu season from an interdecadal perspective. Sci. China Earth Sci. 2021, 64, 1619–1632. [Google Scholar] [CrossRef]
  17. Takaya, Y.; Ishikawa, I.; Kobayashi, C.; Endo, H.; Ose, T. Enhanced Meiyu-Baiu Rainfall in Early Summer 2020: Aftermath of the 2019 Super IOD Event. Geophys. Res. Lett. 2020, 47, e2020GL090671. [Google Scholar] [CrossRef]
  18. Zheng, J.; Wang, C. Influences of three oceans on record-breaking rainfall over the Yangtze River Valley in June 2020. Sci. China Earth Sci. 2021, 64, 1607–1618. [Google Scholar] [CrossRef]
  19. Pan, X.; Li, T.; Sun, Y.; Zhu, Z. Cause of Extreme Heavy and Persistent Rainfall over Yangtze River in Summer 2020. Adv. Atmos. Sci. 2021, 38, 1994–2009. [Google Scholar] [CrossRef]
  20. Chen, X.; Dai, A.; Wen, Z.; Song, Y. Contributions of Arctic Sea-Ice Loss and East Siberian Atmospheric Blocking to 2020 Record-Breaking Meiyu-Baiu Rainfall. Geophys. Res. Lett. 2021, 48, e2021GL092748. [Google Scholar] [CrossRef]
  21. Zhang, L.; Zhao, D.; Zhou, T.; Peng, D.; Xiao, C. Moisture Origins and Transport Processes for the 2020 Yangtze River Valley Record-Breaking Mei-yu Rainfall. Adv. Atmos. Sci. 2021, 38, 2125–2136. [Google Scholar] [CrossRef]
  22. Wang, T.; Wei, K.; Ma, J. Atmospheric Rivers and Mei-yu Rainfall in China: A Case Study of Summer 2020. Adv. Atmos. Sci. 2021, 38, 2137–2152. [Google Scholar] [CrossRef]
  23. Li, L.; Zhu, C.; Zhang, R.; Liu, B. Roles of the Tibetan Plateau vortices in the record Meiyu rainfall in 2020. Atmos. Sci. Lett. 2021, 22, e1017. [Google Scholar] [CrossRef]
  24. Ding, L.; Li, T.; Sun, Y. Subseasonal and Synoptic Variabilities of Precipitation over the Yangtze River Basin in the Summer of 2020. Adv. Atmos. Sci. 2021, 38, 2108–2124. [Google Scholar] [CrossRef]
  25. Zeng, W.; Chen, G.; Bai, L.; Liu, Q.; Wen, Z. Multiscale processes of heavy rainfall over East er 2020: Diurnal cycle in response to synoptic disturbances. Mon. Weather Rev. 2022, 150, 1355–1376. [Google Scholar]
  26. Qian, W.; Ai, Y.; Leung, J.C.-H.; Zhang, B. Anomaly-based synoptic analysis and model product application for 2020 summer southern China rainfall events. Atmos. Res. 2021, 258, 105631. [Google Scholar] [CrossRef]
  27. Cressman, G.P. An operational objective analysis system. Mon. Weather Rev. 1959, 87, 367–374. [Google Scholar] [CrossRef]
  28. Hersbach, H.; Bell, B.; Berrisford, P.; Hirahara, S.; Horanyi, A.; Muñoz-Sabater, J.; Nicolas, J.; Peubey, C.; Radu, R.; Schepers, D.; et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 2020, 146, 1999–2049. [Google Scholar] [CrossRef]
  29. Torrence, C.; Compo, G.P. A Practical Guide to Wavelet Analysis. Bull. Am. Meteorol. Soc. 1998, 79, 61–78. [Google Scholar] [CrossRef]
  30. Liu, Y.; Liang, X.S.; Weisberg, R.H. Rectification of the Bias in the Wavelet Power Spectrum. J. Atmos. Ocean. Technol. 2007, 24, 2093–2102. [Google Scholar] [CrossRef]
  31. Shimomai, T.; Yamanaka, M.; Fukao, S. Application of wavelet analysis to wind disturbances observed with MST radar techniques. J. Atmos. Sol. Terr. Phys. 1996, 58, 683–696. [Google Scholar] [CrossRef]
  32. Daubechies, I. Ten Lectures on Wavelets; Society for Industrial and Applied Mathematics (SIAM): Philadelphia, PA, USA, 1992; p. 61. [Google Scholar]
  33. Percival, D.; Walden, A. Wavelet Methods for Time Series Analysis; Cambridge Series in Statistical and Probabilistic Mathematics; Cambridge University Press: Cambridge, UK, 2000. [Google Scholar] [CrossRef]
  34. Wen, Q.; He, K.; Sun, L.; Zhang, Y.; Ke, M.; Xu, H. Robust period: Robust time-frequency mining for multiple periodicity detection. In Proceedings of the 2021 International Conference on Managementof Data (SIGMOD ’21), Virtual Event, China, 18–27 June 2021; ACM: New York, NY, USA, 2021. [Google Scholar] [CrossRef]
  35. Pando, J.; Fang, L.-Z. Discrete wavelet transform power spectrum estimator. Phys. Rev. E 1998, 57, 3593–3601. [Google Scholar] [CrossRef]
  36. Huth, R. Properties of the circulation classification scheme based on the rotated principal component analysis. Meteorol. Atmos. Phys. 1996, 59, 217–233. [Google Scholar] [CrossRef]
  37. Huth, R. An intercomparison of computer-assisted circulation classification methods. Int. J. Climatol. 1996, 16, 893–922. [Google Scholar] [CrossRef]
  38. Wang, C.; Zhao, K.; Huang, A.; Chen, X.; Rao, X. The crucial role of synoptic pattern in determining the spatial distribution and diurnal cycle of heavy rainfall over the South China coast. J. Clim. 2021, 34, 2441–2458. [Google Scholar] [CrossRef]
  39. Xu, J.; Zhang, Q.; Bi, B.; Chen, Y. Spring Extreme Precipitation Days in North China and Their Reliance on Atmospheric Circulation Patterns during 1979–2019. J. Clim. 2022, 35, 2253–2267. [Google Scholar] [CrossRef]
  40. Tao, S.Y.; Wei, J. The westward, northward advance of the subtropical high over the west Pacific in summer. J. Appl. Meteor. Sci. 2006, 17, 513–525, (In Chinese with English abstract). [Google Scholar]
  41. Ong-Hua, S.; Feng, X. Two Northward Jumps of the Summertime Western Pacific Subtropical High and Their Associations with the Tropical SST Anomalies. Atmos. Ocean. Sci. Lett. 2011, 4, 98–102. [Google Scholar] [CrossRef]
  42. Carbone, R.E.; Tuttle, J.D.; Ahijevych, D.; Trier, S.B. Inferences of predictability associated with warm season precipitation episodes. J. Atmos. Sci. 2002, 59, 2033–2056. [Google Scholar] [CrossRef]
  43. Wang, B.; Orlanski, I. Study of a Heavy Rain Vortex Formed over the Eastern Flank of the Tibetan Plateau. Mon. Weather Rev. 1987, 115, 1370–1393. [Google Scholar] [CrossRef]
  44. Tuttle, J.D.; Carbone, R.E. Coherent Regeneration and the Role of Water Vapor and Shear in a Long-Lived Convective Episode. Mon. Weather Rev. 2004, 132, 192–208. [Google Scholar] [CrossRef]
  45. Wang, C.-C.; Chen, G.T.-J.; Huang, H.-L.; Carbone, R.E.; Chang, S.-W. Synoptic Conditions Associated with Propagating and Nonpropagating Cloud/Rainfall Episodes during the Warm Season over the East Asian Continent. Mon. Weather Rev. 2012, 140, 721–747. [Google Scholar] [CrossRef]
  46. Ninomiya, K.; Murakami, T. The early summer rainy season (Baiu) over Japan. In Monsoon Meteorology; Chang, C.-P., Krishnamurti, T.N., Eds.; Oxford University Press: Oxford, UK, 1987; pp. 93–121. [Google Scholar]
  47. Kuo, Y.-H.; Cheng, L.; Anthes, R.A. Mesocale analyses of the Sichuan flood catastrophe, 11–15 July 1981. Mon. Weather Rev. 1986, 114, 1984–2003. [Google Scholar] [CrossRef]
  48. Wang, W.; Kuo, Y.-H.; Warner, T.T. A Diabatically Driven Mesoscale Vortex in the Lee of the Tibetan Plateau. Mon. Weather Rev. 1993, 121, 2542–2561. [Google Scholar] [CrossRef]
  49. Tao, S.Y. Torrential Rain in China; Science Press: Beijing, China, 1980. [Google Scholar]
  50. Ninomiya, K.; Akiyama, T. Multi-scale Features of Baiu, the Summer Monsoon over Japan and the East Asia. J. Meteorol. 1992, 70, 467–495. [Google Scholar]
  51. Chang, C.-P.; Hou, S.C.; Kuo, H.C.; Chen, T.-J.G. The development of an intense East Asian summer monsoon disturbance with strong vertical coupling. Mon. Weather Rev. 1998, 126, 2692–2712. [Google Scholar] [CrossRef]
  52. Lu, J.H. Introduction to the Southwest Vortex; China Meteorological Press: Beijing, China, 1986. [Google Scholar]
  53. Cho, H.-R.; Chen, T.-J.G. Mei-Yu frontogenesis. J. Atmos. Sci. 1995, 52, 2109–2120. [Google Scholar] [CrossRef]
  54. Chen, T.-J.G.; Wang, C.-C.; Liu, S.C.-S. Potential vorticity diagnostics of a Mei-Yu front case. Mon. Weather Rev. 2003, 131, 2680–2696. [Google Scholar] [CrossRef]
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Figure 1. The accumulated rainfall (mm; shadings) from national rain gauges over YHRB and 850 hPa mean wind vectors from ERA5 (full data description in Section 2.1). The location of national rain gauges receiving an accumulated rainfall of over 1500 mm in June–July 2020 are marked by white triangles (S1: 1719.5 mm; S2: 1667.5 mm; S3: 1581.6 mm). The locations of national rain gauges that recorded maximum hourly rain rates (S4) during June–July 2020 are marked by red triangles. The Dabie, Huang, and Wuyi mountains are labeled by the abbreviations DBM, HM, WYM, respectively. The thick purple dash-dotted line denotes the distribution of the mean Meiyu front in June–July 2020, determined by the maximum gradient of the equivalent potential temperature at 850 hPa from ERA5. The gray contours show terrain heights at altitudes of 250 m and 500 m.
Figure 1. The accumulated rainfall (mm; shadings) from national rain gauges over YHRB and 850 hPa mean wind vectors from ERA5 (full data description in Section 2.1). The location of national rain gauges receiving an accumulated rainfall of over 1500 mm in June–July 2020 are marked by white triangles (S1: 1719.5 mm; S2: 1667.5 mm; S3: 1581.6 mm). The locations of national rain gauges that recorded maximum hourly rain rates (S4) during June–July 2020 are marked by red triangles. The Dabie, Huang, and Wuyi mountains are labeled by the abbreviations DBM, HM, WYM, respectively. The thick purple dash-dotted line denotes the distribution of the mean Meiyu front in June–July 2020, determined by the maximum gradient of the equivalent potential temperature at 850 hPa from ERA5. The gray contours show terrain heights at altitudes of 250 m and 500 m.
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Figure 2. The mean geopotential height in June–July 2020 (gray contour, unit: gpm), its deviation from the climate mean in 1980–2019 (shading), the level of standard deviations (red dashed contours), and the mean horizontal wind at 850 hPa exceeding 8 m s−1. Defined by 5880 gpm at 500 hPa, the white-solid line denotes the mean ridge axis of the subtropical high during June–July 2020, the white dashed and dash-dotted lines mark the location of the WPSH in the onset (1 June) and the end day (2 August) of the 2020 Meiyu season, and the green dashed line denotes the climate mean location of the WPSH in 1980–2019. The blue dots mark the areas with no less than two standard deviations of the total rainfall in June–July 2020 from the climate mean in 1980–2019. The yellow dashed lines denote the location of a mean Meiyu front, determined by the maximum gradient of the equivalent potential temperature at 850 hPa. The purple rectangle represents the study area used for this study, i.e., 27° to 34° N in latitude and 111° to 120° E in longitude.
Figure 2. The mean geopotential height in June–July 2020 (gray contour, unit: gpm), its deviation from the climate mean in 1980–2019 (shading), the level of standard deviations (red dashed contours), and the mean horizontal wind at 850 hPa exceeding 8 m s−1. Defined by 5880 gpm at 500 hPa, the white-solid line denotes the mean ridge axis of the subtropical high during June–July 2020, the white dashed and dash-dotted lines mark the location of the WPSH in the onset (1 June) and the end day (2 August) of the 2020 Meiyu season, and the green dashed line denotes the climate mean location of the WPSH in 1980–2019. The blue dots mark the areas with no less than two standard deviations of the total rainfall in June–July 2020 from the climate mean in 1980–2019. The yellow dashed lines denote the location of a mean Meiyu front, determined by the maximum gradient of the equivalent potential temperature at 850 hPa. The purple rectangle represents the study area used for this study, i.e., 27° to 34° N in latitude and 111° to 120° E in longitude.
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Figure 3. (a) Wavelet spectrum using the DWT method on 1 min Meiyu rainfalls in June–July 2020, standardized by the number of Meiyu days. The accumulated contribution from wavelet variance in the sub-hourly and hourly periods (2 min to 1 h) is 63.41% as labeled by the red line. The X-axis represents the range of time scales from minutes to 32 days. The Y-axis is the wavelet variance at each time scale. (b) This is similar to Figure 1, but for the hourly rainfall frequency (shading; unit: num) during the months of June and July 2020. National rain gauges observed heavy hourly rainfalls (≥15 mm h−1) in the frequency of the top two in 26 counts, more than 20 counts, and 10–20 counts in June–July 2020, which are labeled by white triangles, white squares, and purple crosses, respectively. (c) The box and whisker plot of the maximum hourly rainfall recorded by each of the 480 rain gauges’ stations over the YHRB in June–July 2020. The blue box’s upper and lower boundaries show the 25th and 75th interquartile range. The horizontal line in the box indicates the median value. The upper and lower black lines are the maximum and minimum outliers, which are calculated by q 1 + 1.5 × ( q 3 − q 1 ) and q 3 − 1.5 × ( q 3 − q 1 ) , respectively, where q 1 and q 3 are the 25th and 75th quantile. The values greater than the maximum outliers are labeled by a red cross.
Figure 3. (a) Wavelet spectrum using the DWT method on 1 min Meiyu rainfalls in June–July 2020, standardized by the number of Meiyu days. The accumulated contribution from wavelet variance in the sub-hourly and hourly periods (2 min to 1 h) is 63.41% as labeled by the red line. The X-axis represents the range of time scales from minutes to 32 days. The Y-axis is the wavelet variance at each time scale. (b) This is similar to Figure 1, but for the hourly rainfall frequency (shading; unit: num) during the months of June and July 2020. National rain gauges observed heavy hourly rainfalls (≥15 mm h−1) in the frequency of the top two in 26 counts, more than 20 counts, and 10–20 counts in June–July 2020, which are labeled by white triangles, white squares, and purple crosses, respectively. (c) The box and whisker plot of the maximum hourly rainfall recorded by each of the 480 rain gauges’ stations over the YHRB in June–July 2020. The blue box’s upper and lower boundaries show the 25th and 75th interquartile range. The horizontal line in the box indicates the median value. The upper and lower black lines are the maximum and minimum outliers, which are calculated by q 1 + 1.5 × ( q 3 − q 1 ) and q 3 − 1.5 × ( q 3 − q 1 ) , respectively, where q 1 and q 3 are the 25th and 75th quantile. The values greater than the maximum outliers are labeled by a red cross.
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Figure 4. The composite synoptic patterns under the PCT classifications (P1–P4), including the accumulated rainfall (shading, unit: mm) interpolated from the R1m dataset, the mean equivalent potential temperature (purple contours), the mean geopotential height (black dashed contours), and the mean horizontal wind vectors at 850 hPa (a full barb is 4 m s−1 and a triangle is 20 m s−1). The yellow lines denote the ridge axis of a subtropical high, defined by 5880-gpm at 500 hPa. The black dots denote the area with the maximum gradient of the equivalent potential temperature at 850 hPa greater than 3 K (deg lat−1). The black rectangle represents the study area used for this study, similar to that in Figure 2. The centers of high and low pressures in mid-latitudes are marked by red letters, i.e., H and L. The axis of the trough is denoted by a red solid-line. The black dash lines along the N–S in (a–c) are cross lines for Figure 5. The frequencies of P1–P4 during the Meiyu seasons in 2018–2021 are 1873, 781, 449, and 174 in number of hours and 52.39%, 21.85%, 12.56%, and 4.84% in percentages, respectively.
Figure 4. The composite synoptic patterns under the PCT classifications (P1–P4), including the accumulated rainfall (shading, unit: mm) interpolated from the R1m dataset, the mean equivalent potential temperature (purple contours), the mean geopotential height (black dashed contours), and the mean horizontal wind vectors at 850 hPa (a full barb is 4 m s−1 and a triangle is 20 m s−1). The yellow lines denote the ridge axis of a subtropical high, defined by 5880-gpm at 500 hPa. The black dots denote the area with the maximum gradient of the equivalent potential temperature at 850 hPa greater than 3 K (deg lat−1). The black rectangle represents the study area used for this study, similar to that in Figure 2. The centers of high and low pressures in mid-latitudes are marked by red letters, i.e., H and L. The axis of the trough is denoted by a red solid-line. The black dash lines along the N–S in (a–c) are cross lines for Figure 5. The frequencies of P1–P4 during the Meiyu seasons in 2018–2021 are 1873, 781, 449, and 174 in number of hours and 52.39%, 21.85%, 12.56%, and 4.84% in percentages, respectively.
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Figure 5. (a) The meridional-height (y, z) cross sections in the N–S direction of the equivalent potential temperature (black contours) and its equatorial gradient (shading; units: K (deg lat−1)) in-plane flow vectors (units: m s−1), and the red contours of relative humidity in 80% and 90% along 116.25° E within the YHRB under the synoptic patterns of P1. The vertical purple dashed line at 27° N and 34° N denotes the latitudinal boundary of the study area in this paper. (b) The zonally averaged accumulated rainfall within the longitudinal boundary of the YHRB (111° E to 122° E) under the synoptic patterns of P1 along latitudes from 22° N to 38° N.
Figure 5. (a) The meridional-height (y, z) cross sections in the N–S direction of the equivalent potential temperature (black contours) and its equatorial gradient (shading; units: K (deg lat−1)) in-plane flow vectors (units: m s−1), and the red contours of relative humidity in 80% and 90% along 116.25° E within the YHRB under the synoptic patterns of P1. The vertical purple dashed line at 27° N and 34° N denotes the latitudinal boundary of the study area in this paper. (b) The zonally averaged accumulated rainfall within the longitudinal boundary of the YHRB (111° E to 122° E) under the synoptic patterns of P1 along latitudes from 22° N to 38° N.
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Figure 6. This is similar to Figure 5 but along 117.75° E under synoptic pattern of P2.
Figure 6. This is similar to Figure 5 but along 117.75° E under synoptic pattern of P2.
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Figure 7. This is similar to Figure 5 but along 117° E under synoptic pattern of P3.
Figure 7. This is similar to Figure 5 but along 117° E under synoptic pattern of P3.
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Figure 8. The time series of rainfall clusters under the four synoptic patterns during June–July 2020. (a,c) are the time series of the hourly rainfall frequency recorded by rain gauge stations over the YHRB in June and July 2020, respectively. (b,d) are Hovmöller (latitude–time) plots of hourly rainfalls (mm) averaged within 111–122° E. The black dashed lines denote the distribution of the Meiyu front at hourly intervals, defined by the maximum gradient of the equivalent potential temperature at 850 hPa. The horizontal red dotted lines denote the latitudinal boundaries of our study area (27–34° N). The colored blocks at the bottom frame of (b,d) denote the synoptic patterns (P1 is in blue, P2 is in yellow, P3 is in pink, and P4 is in green) at hourly intervals. The time and latitude of the maximum hourly rain rates (S4) and maximum hour rain rates for June–July 2020, recorded by national rain gauges, are marked by black squares.
Figure 8. The time series of rainfall clusters under the four synoptic patterns during June–July 2020. (a,c) are the time series of the hourly rainfall frequency recorded by rain gauge stations over the YHRB in June and July 2020, respectively. (b,d) are Hovmöller (latitude–time) plots of hourly rainfalls (mm) averaged within 111–122° E. The black dashed lines denote the distribution of the Meiyu front at hourly intervals, defined by the maximum gradient of the equivalent potential temperature at 850 hPa. The horizontal red dotted lines denote the latitudinal boundaries of our study area (27–34° N). The colored blocks at the bottom frame of (b,d) denote the synoptic patterns (P1 is in blue, P2 is in yellow, P3 is in pink, and P4 is in green) at hourly intervals. The time and latitude of the maximum hourly rain rates (S4) and maximum hour rain rates for June–July 2020, recorded by national rain gauges, are marked by black squares.
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Figure 9. This is similar to Figure 6b,d but for Hovmöller (longitude–time) plots with the hourly rainfall averaged within 28–34° N. The colored blocks on the left frame of (a,b) denote the synoptic patterns (P1 is in blue, P2 is in yellow, P3 is in pink, and P4 is in green) at hourly intervals. The vertical red dotted lines denote the longitudinal range of our study area (111–122° E). The dashed lines are used to trace the temporal evolution of vortices, with their longitudinal location of the low-pressure center marked by the letter L. Vortices crossing the study area of the YHRB are marked in red and others are marked in gray. The time and longitude of national rain gauges that recorded the maximum hourly rain rates (S4) during June–July 2020 are marked by black squares.
Figure 9. This is similar to Figure 6b,d but for Hovmöller (longitude–time) plots with the hourly rainfall averaged within 28–34° N. The colored blocks on the left frame of (a,b) denote the synoptic patterns (P1 is in blue, P2 is in yellow, P3 is in pink, and P4 is in green) at hourly intervals. The vertical red dotted lines denote the longitudinal range of our study area (111–122° E). The dashed lines are used to trace the temporal evolution of vortices, with their longitudinal location of the low-pressure center marked by the letter L. Vortices crossing the study area of the YHRB are marked in red and others are marked in gray. The time and longitude of national rain gauges that recorded the maximum hourly rain rates (S4) during June–July 2020 are marked by black squares.
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Figure 10. This is similar to Figure 3a but for 1 min rainfalls under the synoptic patterns of P1, P2, and P3. The X-axis represents the range of time scales from minutes to 32 days. The Y-axis is the wavelet variance at each time scale in percentages of the accumulated rainfall expectation.
Figure 10. This is similar to Figure 3a but for 1 min rainfalls under the synoptic patterns of P1, P2, and P3. The X-axis represents the range of time scales from minutes to 32 days. The Y-axis is the wavelet variance at each time scale in percentages of the accumulated rainfall expectation.
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Figure 11. The hourly rainfall frequency (shadings; unit: num) obtained from the R1m dataset, the mean horizontal wind vectors, and the mean location of the Meiyu front, marked by purple dashed lines, as defined by the maximum gradient of the equivalent potential temperature at 850 hPa, under the synoptic patterns of (a) P1; (b) P2; and (c) P3 during June–July 2020. The white solid contours indicate centers of heavy hourly rainfall frequency (≥15 mm h−1) with a value of 10 counts, 8 counts, and 5 counts under P1, P2, and P3, respectively. Rain gauges that record hourly rainfall rates over the threshold of the 25th quantile and the maximum outlier under each pattern are labeled by purple crosses and red triangles, respectively. (d) This is similar to Figure 3c but for the maximum hourly rainfall at national rain gauges under the synoptic patterns of P1, P2, and P3.
Figure 11. The hourly rainfall frequency (shadings; unit: num) obtained from the R1m dataset, the mean horizontal wind vectors, and the mean location of the Meiyu front, marked by purple dashed lines, as defined by the maximum gradient of the equivalent potential temperature at 850 hPa, under the synoptic patterns of (a) P1; (b) P2; and (c) P3 during June–July 2020. The white solid contours indicate centers of heavy hourly rainfall frequency (≥15 mm h−1) with a value of 10 counts, 8 counts, and 5 counts under P1, P2, and P3, respectively. Rain gauges that record hourly rainfall rates over the threshold of the 25th quantile and the maximum outlier under each pattern are labeled by purple crosses and red triangles, respectively. (d) This is similar to Figure 3c but for the maximum hourly rainfall at national rain gauges under the synoptic patterns of P1, P2, and P3.
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Figure 12. (a) The probability density distribution of the accumulated rainfall at national rain gauges over the YHRB during June–July 2020 (orange bars) and the historical Meiyu seasons in 1980–2019 (blue bars). The blue dashed lines mark the thresholds of a positive standard deviation of 1 to 4 from that of the historical mean, corresponding to the top 68%, 95%, 99.7%, and 99.9% of the historical distribution. (b–d) This is similar to (a) but for the hourly rainfall frequency, the hourly heavy rainfall (≥15 mm h−1) frequency, and maximum hourly rain rates. The hourly rainfall frequency is counted as the number of records at 1 h intervals with rainfalls of no less than 0.1 mm.
Figure 12. (a) The probability density distribution of the accumulated rainfall at national rain gauges over the YHRB during June–July 2020 (orange bars) and the historical Meiyu seasons in 1980–2019 (blue bars). The blue dashed lines mark the thresholds of a positive standard deviation of 1 to 4 from that of the historical mean, corresponding to the top 68%, 95%, 99.7%, and 99.9% of the historical distribution. (b–d) This is similar to (a) but for the hourly rainfall frequency, the hourly heavy rainfall (≥15 mm h−1) frequency, and maximum hourly rain rates. The hourly rainfall frequency is counted as the number of records at 1 h intervals with rainfalls of no less than 0.1 mm.
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Figure 13. The accumulated rainfall deviation (shading) and hourly rainfall frequency deviation (red dashed contours) during June–July 2020, from the climate mean of the Meiyu seasons in 1980–2019. The rain gauge stations that recorded the hourly rainfall frequency exceeding 4 standard deviations in June–July 2020 are marked by grey crosses, and those that recorded a maximum hourly rainfall deviation exceeding 2 standard deviations are marked by grey squares. The location of national rain gauges receiving an accumulated rainfall over 1500 mm in June–July 2020 are marked by white crosses (S1: 1719.5 mm; S2: 1667.5 mm; and S3: 1581.6 mm), and all of them had a standard deviation greater than 4. The location of rain gauges with maximum hourly rain rates (S4) during June–July 2020 are marked by red triangles.
Figure 13. The accumulated rainfall deviation (shading) and hourly rainfall frequency deviation (red dashed contours) during June–July 2020, from the climate mean of the Meiyu seasons in 1980–2019. The rain gauge stations that recorded the hourly rainfall frequency exceeding 4 standard deviations in June–July 2020 are marked by grey crosses, and those that recorded a maximum hourly rainfall deviation exceeding 2 standard deviations are marked by grey squares. The location of national rain gauges receiving an accumulated rainfall over 1500 mm in June–July 2020 are marked by white crosses (S1: 1719.5 mm; S2: 1667.5 mm; and S3: 1581.6 mm), and all of them had a standard deviation greater than 4. The location of rain gauges with maximum hourly rain rates (S4) during June–July 2020 are marked by red triangles.
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Table
Table 1. The duration of the Meiyu season from 1980 to 2021, as determined by the National Climate Center of the China Meteorological Administration, in accordance with the Meiyu monitoring indices (GB/T 33671-2017) over the middle- and lower-reaches of the Yangtze River.
Table 1. The duration of the Meiyu season from 1980 to 2021, as determined by the National Climate Center of the China Meteorological Administration, in accordance with the Meiyu monitoring indices (GB/T 33671-2017) over the middle- and lower-reaches of the Yangtze River.
YearOnsetEndDaysYearOnsetEndDays
198006-Jun07-Aug62200102-Jun28-Jun26
198122-Jun26-Jul34200210-Jun09-Jul29
198211-Jun26-Jul45200321-Jun23-Jul32
198309-Jun25-Jul46200414-Jun21-Jul37
198404-Jun23-Jul49200504-Jul23-Jul19
198504-Jun08-Jul34200631-May29-Jul59
198610-Jun25-Jul45200710-Jun27-Jul47
198719-Jun01-Aug43200807-Jun14-Jul37
198810-Jun23-Jun13200917-Jun08-Jul21
198903-Jun16-Jul43201017-Jun26-Jul39
199029-May21-Jul53201103-Jun21-Jul48
199102-Jun16-Jul44201204-Jun21-Jul47
199213-Jun23-Jul40201306-Jun01-Jul25
199312-Jun08-Aug57201416-Jun20-Jul34
199405-Jun18-Jul43201526-May27-Jul62
199525-May08-Jul44201625-May21-Jul57
199630-May22-Jul53201704-Jun11-Jul37
199718-Jun24-Jul36201819-Jun13-Jul24
199808-Jun04-Aug57201916-Jun17-Jul31
199907-Jun31-Jul54202001-Jun02-Aug62
200029-May30-Jun32202110-Jun10-Jul30
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Li, L.; Zhang, F. Hourly and Sub-Hourly Rainfall under Synoptic Patterns during the Anomalous Meiyu Season 2020. Atmosphere 2023, 14, 727. https://doi.org/10.3390/atmos14040727

AMA Style

Li L, Zhang F. Hourly and Sub-Hourly Rainfall under Synoptic Patterns during the Anomalous Meiyu Season 2020. Atmosphere. 2023; 14(4):727. https://doi.org/10.3390/atmos14040727

Chicago/Turabian Style

Li, Liye, and Fan Zhang. 2023. "Hourly and Sub-Hourly Rainfall under Synoptic Patterns during the Anomalous Meiyu Season 2020" Atmosphere 14, no. 4: 727. https://doi.org/10.3390/atmos14040727

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