Meiyu Season Research Articles

Improving ozone estimation during rainy-warm seasons from the perspective of weather systems based on machine learning.

Surface ozone pollution in eastern China is increasingly serious during summer, coinciding with distinct stages of the rainy seasons in this region. This study focuses on the spatiotemporal distribution of ozone concentrations, their synoptic driving factors and estimation during the Meiyu periods from 2015 to 2022. Results show that high ozone levels mainly occur during the interval of Meiyu season (HOP), accounting for 15.1% of the total Meiyu period, with MDA8 O3 concentrations in HOP exceeding those in non-HOP (NHOP) by over 20μgm-3 at >60% of sites. Compared to NHOP, HOP is characterized by lower precipitation (-0.17mm), higher temperatures (0.25K), increased solar radiation (3.16kJm-2), and reduced relative humidity (-8.56%). Using the Lindeman, Merenda, and Gold method, it is found that the meteorological factors with the greatest impact on MDA8 O3 during the 2015-2022 Meiyu season are relative humidity (30.4%), surface 2m temperature (28.6%), and total precipitation (23.2%). These favorable conditions for ozone production are along with specific state synoptic-scale and large-scale atmospheric circulation systems. On a daily scale, the further south the position of the western Pacific subtropical high pressure ridge (72.2%) and the stronger the intensities of El Niño-Southern Oscillation and East Asian summer monsoon (19.0%) will lead to higher O3 concentration in the Meiyu-affected area. The results of machine learning prove that instead of conventional consideration of meteorological conditions, the introduction of daily atmospheric circulation indices can effectively improve the accuracy of ozone concentration estimation (R2: 0.72, NRMSE: 0.15). These findings provide valuable insights for predicting ozone pollution during the rainy interval period.

Land–air interaction maintaining the tripole pattern of anomalous Eurasian blocking activities during the Meiyu season

Land–air interaction maintaining the tripole pattern of anomalous Eurasian blocking activities during the Meiyu season

Seesaw between the westerlies and Asian monsoon regulates vegetation and climate during the last deglaciation in southern Northeast China

The history and drivers of hydroclimate changes during the last deglaciation in Northeast China remain contentious. We present a high-resolution record of vegetation and climate changes from Lake Buridun in southern Northeast China (SNEC), spanning the last ∼16 kyr. Multi-proxy reconstruction reveals a slight increase in precipitation prior to the end of Heinrich Stadial 1 (HS1) and forest development during the middle Bølling warming, indicating that hydrothermal conditions regulated regional vegetation. Significant fluctuations in all millennial-scale climatic events underscore the high sensitivity of SNEC to climate change. Our record aligns with high-resolution data from both SNEC and North China, showing a persistent wetting trend during the Bølling-Allerød period. This trend coincides with changes in East Asian summer monsoon intensity and Indo-Pacific warm pool heat content but contrasts with the Greenland temperature records. During the HS1 and Younger Dryas, records show a cold-dry mode in SNEC, contrasting with the cold-wet pattern in central-eastern China caused by the prolonged Meiyu season, which corresponds to the retreat of the monsoon precipitation belt and an enhanced westerly jet. Our data, along with more comprehensive records from broader regions, suggest that hydroclimate in SNEC was dominated by the low-latitude monsoon and the high-latitude westerlies during the warm and cold phases of the last deglaciation, exhibiting a seesaw-like interaction.

Analysis of a Rainstorm Process in Nanjing Based on Multi-Source Observational Data and Lagrangian Method

Using multi-source observation data including automatic stations, radar, satellite, new detection equipment, and the Fifth Generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA-5) data, along with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) platform, an analysis was conducted on a rainstorm process that occurred in Nanjing on 15 June 2020, with the aim of providing reference for future urban flood control planning and heavy rainfall forecasting and early warning. The results showed that this rainstorm process was generated under the background of an eastward-moving northeast cold vortex and a southward retreat of the Western Pacific Subtropical High. Intense precipitation occurred near the region of large top brightness temperature (TBB) gradient values or the center of low TBB values on the northern side of the convective cloud cluster. During the heavy precipitation period, the differential propagation phase shift rate (KDP), differential reflectivity factor (ZDR), and zero-lag correlation coefficient (ρHV) detected by the S-band dual-polarization radar all increased significantly. The vertical structure of the wind field detected by the wind profile radar provided a good indication of changes in precipitation intensity, showing a strong correspondence between the timing of maximum precipitation and the intrusion of upper-level cold air. The abrupt increase in the integrated liquid water content observed by the microwave radiometer can serve as an important indicator of the onset of stronger precipitation. During the Meiyu season in Nanjing, convective precipitation was mainly composed of small to medium raindrops with diameters less than 3 mm, with falling velocities of raindrops mainly clustering between 2 and 6 m·s−1. The rainstorm process featured four water vapor transport channels: the mid-latitude westerly channel, the Indian Ocean channel, the South China Sea channel, and the Pacific Ocean channel. During heavy rainfall, the Pacific Ocean water vapor channel was the main channel at the middle and lower levels, while the South China Sea water vapor channel was the main channel at the upper level, both accounting for a trajectory proportion of 34.2%.

Where and why do Mei-yu season Heavy-rainfall quantitative precipitation forecasts in Taiwan improve the most using a higher model resolution

Where and why do Mei-yu season Heavy-rainfall quantitative precipitation forecasts in Taiwan improve the most using a higher model resolution

Northeast China Cold Vortex Amplifies Extreme Precipitation Events in the Middle and Lower Reaches Yangtze River Basin

The middle and lower reaches of the Yangtze River (MLYR) frequently experience extreme precipitation events (EPEs) during June and July, the so-called Meiyu season. This study investigated EPEs in the MLYR during Meiyu seasons over 1961–2022, using rain gauge observations and ERA5 reanalysis data. EPEs associated with the Northeast China cold vortex featured more undulating westerlies with a distinct wave train pattern from Europe to Northeast Asia. Due to robust Rossby wave energy, the trough deepened from Northeast China towards the MLYR and was confronted with a westward extension of the western Pacific subtropical high. Such a configuration enhanced the warm and moist monsoon conveyor belt and convergence of water vapor flux from southwestern China to the MLYR. The warm and moist air favored upward motion. The increased rainfall prevailed from southwestern China to the MLYR. In contrast, ordinary EPEs were characterized by zonal westerlies and weaker Rossby wave propagation. The Meiyu trough was comparatively shallow and confined to the MLYR with less westward expansion of the subtropical high. In response, the warm and moist monsoon conveyor belt was more localized, resulting in weaker EPEs in the MLYR.

Contrasting aerosol effects on shallow and deep convections during the Mei-yu season in China

Convective clouds during the Mei-yu season contribute significantly to the total rainfall and related disasters over the middle and lower reaches of the Yangtze River in China. Studying the effects of aerosols on convective clouds is of great importance to weather and climate research. However, there are still many open questions to address. This study investigated the effects of aerosol on convections with different cloud geometrical thickness (CGT) bins during the 2018 Mei-yu season, which lasted for 17 days from 18 June to 5 July. Contrasting aerosol effects on shallow and deep convective clouds were revealed by means of anthropogenic aerosol experiments in the Weather Research and Forecasting model with Chemistry (WRF-Chem). Specifically, increased anthropogenic aerosols lead to a 9% reduction in total rainfall and a 7.17% decrease in convection occurrences during the Mei-yu season. After adopting a methodology that stratifies the convective clouds by fixing the CGT, we found that increasing aerosols suppress shallow convections with CGT <4 km and invigorate deep convections with CGT >4 km. Increased aerosols enhance the scattering of shortwave radiation, resulting in cooling of the surface air and increasing the stability of the regional lower atmosphere, potentially suppressing shallow convection. Meanwhile, in deep convection, with its stronger updraft and more latent heat, convective invigoration occurs under polluted conditions due to the aerosol-related microphysical and dynamical responses. Considering the high-humidity environment during the Mei-yu season, additional relative humidity tests show that the competing aerosol effects come from convective core invigoration and convective periphery processes which enhance evaporation and dissipation, demonstrating relative humidity is a critical factor in maintaining the net aerosol effects on convections. These results contribute to a better understanding of the effects of anthropogenic aerosols on convections during the Mei-yu season and the competing effects of aerosols depending on the ambient environmental conditions.

Evaluation of Precipitation Forecast by the Operational China Meteorological Administration Mesoscale Model During the 2020 Meiyu Period

AbstractThis study evaluated the precipitation forecast produced by the operational China Meteorological Administration Mesoscale model (CMA‐MESO) during the “super violent” Meiyu season of 2020. Generally, CMA‐MESO, which runs with ∼3‐km‐grid resolution, is able to reproduce the distribution and diurnal variation of precipitation. However, the precipitation amount is greatly overestimated, especially in eastern coastal areas of China. Precipitation in that region usually occurs with two peaks: one in the morning that mostly reflects organized precipitation systems, and the other in the afternoon generated mostly by local convection. Analyses showed that overestimation of low‐level wind speed is the main reason for the overestimation of precipitation. CMA‐MESO produces low‐level winds that are overly strong, which greatly enhance the predicted convergence at night, leading to overestimation of precipitation. Additionally, the stronger wind speed increases the estimated transport of water vapor to the eastern coastal area, producing fake convection near the coastal mountains as the perturbed wind direction turns toward the mountain area in the afternoon. In comparison with ERA5, CMA‐MESO tends to overestimate (underestimate) the temperature in the northwest (southeast), and the larger temperature gradient increases the pressure gradient, resulting in the stronger low‐level wind speed.

An Evaluation and Improvement of Microphysical Parameterization for a Heavy Rainfall Process during the Meiyu Season

The present study assesses the simulated precipitation and cloud properties using three microphysics schemes (Morrison, Thompson and MY) implemented in the Weather Research and Forecasting model. The precipitation, differential reflectivity (ZDR), specific differential phase (KDP) and mass-weighted mean diameter of raindrops (Dm) are compared with measurements from a heavy rainfall event that occurred on 27 June 2020 during the Integrative Monsoon Frontal Rainfall Experiment (IMFRE). The results indicate that all three microphysics schemes generally capture the characteristics of rainfall, ZDR, KDP and Dm, but tend to overestimate their intensity. To enhance the model performance, adjustments are made based on the MY scheme, which exhibited the best performance. Specifically, the overall coalescence and collision parameter (Ec) is reduced, which effectively decreases Dm and makes it more consistent with observations. Generally, reducing Ec leads to an increase in the simulated content (Qr) and number concentration (Nr) of raindrops across most time steps and altitudes. With a smaller Ec, the impact of microphysical processes on Nr and Qr varies with time and altitude. Generally, the autoconversion of droplets to raindrops primarily contributes to Nr, while the accretion of cloud droplets by raindrops plays a more significant role in increasing Qr. In this study, it is emphasized that even if the precipitation characteristics could be adequately reproduced, accurately simulating microphysical characteristics remains challenging and it still needs adjustments in the most physically based parameterizations to achieve more accurate simulation.

Two high-impact extreme precipitation events during the Meiyu season: simulations and their sensitivity to a scale-aware convective parameterization scheme

In this study, we investigate the impact of a scale-aware convective parameterization scheme (CPS) on simulating two high-impact extreme precipitation events during the Meiyu season at a 1 km resolution. Compared with explicit resolving simulation, applying scale-aware CPS mostly affects the atmospheric environment before convection is triggered and the regions outside the convective cell (e.g., stratiform regions) by consuming convective available potential energy (CAPE), which further inhibits precipitation. For the 2019 event, since the explicit resolving simulation underestimates precipitation, applying scale-aware CPS further inhibits precipitation and reduces the skill for the heavy rainfall category. In contrast, for the 2020 event, as the explicit resolving simulation overestimates precipitation, using scale-aware CPS inhibits precipitation and improves the skill of the model. When scale-aware CPS is applied, increasing σ1, which represents the effect of horizontal resolution, the CPS precipitation is reduced and the grid-scale precipitation is increased, but the overall effect inhibits the total precipitation. However, with the increase in σ1, although the number of stations with heavy rainfall (≥50 mm) is reduced, the average precipitation among these stations is increased. Further analysis of those stations with the largest 24 h precipitation and cross sections over regions with large radar reflectivity shows that increasing σ1 reduces the CAPE consumed by CPS and provides a more favorable environment for strong convections and strengthens precipitation. The results of this study may provide useful information for operational model application and may be beneficial to society.

Construction and characteristic analysis of background error covariance coupled with land surface temperature

Land surface temperature (LST) is the key variable in land–atmosphere interaction, having an important impact on weather and climate forecasting. However, achieving consistent analysis of LST and the atmosphere in assimilation is quite challenging. This is because there is limited knowledge about the cross-component background error covariance (BEC) between LST and atmospheric state variables. This study aims to clarify whether there is a relationship between the error of LST and atmospheric variables, and whether this relationship varies spatially and temporally. To this end, the BEC coupled with atmospheric variables and LST was constructed (LST-BEC), and its characteristics were analyzed based on the 2023 mei-yu season. The general characteristics of LST-BEC show that the LST is mainly correlated with the atmospheric temperature and the correlation decreases gradually with a rise in atmospheric height, and the error standard deviation of the LST is noticeably larger than that of the low-level atmospheric temperature. The spatiotemporal characteristics of LST-BEC on the heavy-rain day and light-rain day show that the error correlation and error standard deviation of LST and low-level atmospheric temperature and humidity are closely related to the weather background, and also have obvious diurnal variations. These results provide valuable information for strongly coupled land–atmosphere assimilation.摘要地表温度 (LST) 是涉及陆气相互作用的关键变量, 对天气气候预报具有重要影响. 不过在同化中实现LST与大气的协调分析却并不容易. 这是因为目前对跨陆气圈层的背景误差协方差 (BEC) 的了解较少. 本文旨在探究LST与大气的背景误差是否存在联系, 以及这种联系是否存在时空变化. 为此, 本研究构建了耦合大气变量和LST的BEC, 并基于2023年梅雨季分析了其特征. 总体特征表明: LST误差主要与大气温度相关; 随着大气高度的上升, 误差相关性逐渐减小; LST误差的标准差明显大于低层大气温度. “多雨日”和“少雨日”的时空特征表明, LST与低层大气温湿度误差的相关性及标准差均与天气背景密切相关, 且具有明显的昼夜变化. 上述结果可为后续陆气强耦合同化提供参考.

Local Torrential Rainfall Event within a Mei-Yu Season Mesoscale Convective System: Importance of Back-Building Processes

Local Torrential Rainfall Event within a Mei-Yu Season Mesoscale Convective System: Importance of Back-Building Processes

The performance of IMERG near-real-time estimations during the record-breaking Meiyu season in 2020

The extreme Meiyu season, characterized by continuous heavy precipitation, is often leads to numerous flood-related disasters. Accurate and timely monitoring of extreme Meiyu precipitation is crucial for the effective prevention and mitigation of these disasters. The near-real-time (NRT) products from Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), specifically IMERG-E and IMERG-L products, have high potential utility to acquire timely precipitation data. Therefore, it is important to quantify their errors and uncertainties during the extreme Meiyu season. In this study, we assess and compare the performance of IMERG NRT products with Global Satellite Mapping of Precipitation Motion Vector Kalman product (GSMaP-MVK) using hourly gauge observations during the recor-breaking Meiyu event in 2020. The main conclusions are as follows: all three satellite products generally capture the spatial–temporal evolution of Meiyu precipitation, with IMERG-L showing the closest agreement with gauge observations, particularly for the precipitation center. In terms of the statistical and volumetric categorical metrics, IMERG-L performs best among the three products, while IMERG-E does not exhibit superior performance compared to GSMaP-MVK. Regarding the diurnal cycle, IMERG-L generally reproduces the diurnal cycle of observed precipitation amount with a peak time occurring two hours earlier. In contrast, both IMERG-E and GSMaP-MVK exhibit notably poorer performance. When it comes to the diurnal cycle of precipitation frequency and intensity, both IMERG products display bad performance in reproducing their diurnal variations. Furthermore, all three satellite products show a wet biases for light precipitation and a dry biases for heavy precipitation, which is consistent with previous evaluation studies. However, a novel phenomenon is noticed that theses biases tend to worsen significantly in the afternoon compared to the morning. Although this study is limited to a case study, the findings can serve as a valuable reference for the NRT applications of IMERG products during the extreme Meiyu seasons and provide insights for the improvement of IMERG algorithm.

Flash Drought in the South of Yangtze River and the Potential Impact of North Atlantic Sea Surface Temperature

AbstractFlash droughts (FDs), a type of drought with rapid onset, occurred in growing season have damaging impacts on crops, ecosystem and hence livelihoods. However, the associated physical mechanism were not well understood, which prohibits a skillful early warning. Based on the reanalysis data for 1961–2022, we diagnosed the characteristics, antecedent meteorological conditions and large‐scale atmospheric circulation of FDs over the region south of Yangtze River (SYR), a hotspot region of FDs. The FDs tend to occur during the periods before (i.e., from April to mid‐June) and after (i.e., early July–September) Meiyu season (B‐Meiyu and A‐Meiyu periods). Large precipitation deficits and rapid elevated temperature caused by anomalous subsidence and moisture divergence are responsible for the onset of FDs during the two periods. The North Atlantic tripole‐like sea surface temperature anomaly (SSTA) modes have potential impact on the anomalous circulations via modulating Rossby wave trains, but with different locations among the two periods. During B‐Meiyu period, the SSTA mode is characterized by positive SSTA over subtropical North Atlantic and negative SSTAs over the tropical and mid‐latitude ocean, triggering a “+ − + − + −” circulation pattern over North Atlantic–Eurasia, which reinforces the East Asian trough (EAT). Anomalous northeasterly winds dominate the SYR suppressing moisture transport from the tropics. The SSTA mode locates farther to the north during A‐Meiyu period, inducing a “+ − + − +” wave train over mid‐latitude North Atlantic‐Eurasia, leading to the strengthening of the western Pacific subtropical high. The high‐pressure anomalies control the SYR, resulting in anomalous subsidence and hence negative precipitation anomalies.

The Impact of Large-Scale Environments and a Southwest Vortex on Heavy Rainfall in Southern Taiwan in Late May 2020

Abstract This paper investigates the impact of the environmental conditions during the first half of the 2020 mei-yu season (Y20) and the southwest vortex (SWV), as well as their interaction, on heavy precipitation in southern Taiwan during late May 2020, based on a quantitative approach through ensemble simulations. The control experiment successfully replicates observed heavy precipitation in southern and central Taiwan and reveals a positive spatial correlation between precipitation occurrence probabilities and mean accumulated precipitation, emphasizing continuous rainfall accumulation over intermittent extreme events. Comparative analyses with sensitivity experiments elucidate that the Y20, featuring an extended western North Pacific subtropical high, intensify pressure gradients and southwesterly flow near Taiwan, favoring precipitation in windward regions but hindering it in the east. The SWV creates a moist and vortical environment near Taiwan, amplifying moisture supply and westerly winds, promoting precipitation in southern Taiwan, and enhancing frontal activity. The interaction between the SWV and the Y20, though limited in its impact on providing favorable wind and moisture conditions for precipitation southwest of Taiwan, significantly contributes to precipitation in southern Taiwan. The reason is that although the SWV primarily enhances moisture and the Y20 predominantly boost southwesterly flow, creating favorable conditions for rainfall, substantial precipitation occurs only when both factors converge in a nonlinear interaction. The interaction increases frontal activity over the Taiwan Strait and influences the movement and strength of the SWV, enhancing southwesterly flow and moisture flux in southwestern Taiwan.

Seeding invigoration effect of ice-containing clouds on lower convective clouds during MeiYu season in 2020

Cloud seeding is a process that adjusts cloud physical properties and processes, including both natural and human measures. This study aims to assess the effects of natural ice seeding from upper ice-containing clouds on low convective clouds through in-situ aircraft observations during an Integrative Monsoon Frontal Rainfall Experiment (IMFRE-II) in the summer of 2020. We mainly focus on two distinct shallow convective clouds, one with and the other without upper ice-containing layer, namely Cloud A and Cloud D. The in-situ data demonstrate that snowfall from the upper ice-containing layer to the lower Cloud A, leading to significant changes in cloud top height, median value of radar echo as well as vertical velocity. Compared to shallow convective cloud D without upper-level seeding, cloud A had an approximately 84% less concentration of cloud droplets (diameter <100 μm) and had a slightly smaller cloud droplet effective diameter. For drizzle particles and cloud ice particles with sizes larger than 100 μm, cloud A had a concentration one order of magnitude larger than that of cloud D, also with a larger spectral broadening ratio. These findings reveal the influence of “Seeder-Feeder” effects on microphysical properties of cloud A. The physical mechanisms of Bergeron, riming, and coalescence most likely play a role in the rapid formation of large drizzle/precipitation particles. The natural seeding effect of “seeder-feeder” through snow-virga also likely forms local turbulence, accelerates turbulent entrainment mixing, and promotes the development of the seeded shallow convective cloud.

Different impacts of the variations of western and eastern portions of the East Asian westerly jet stream on southern China rainfalls in Meiyu season

Variations of East Asian westerly jet (EAJ) drastically affect the rainfall in southern China (SC) during Meiyu season. Previous studies conventionally focused on the entire EAJ's variations and their impacts. In this study, we find that the variations of EAJ eastern section (EAJE) and western section (EAJW) are mostly independent of each other. Moreover, the independent components of EAJE and EAJW's variations have different impacts on the rainfall in SC. Southward-displaced and intensified EAJE (SI-EAJE) and southward-displaced and weakened EAJW (SW-EAJW), the first two leading modes of EAJ variations, are associated with increased rainfall anomalies centred over central and southern parts of SC, respectively.Associated with the SI-EAJE (SW-EAJW), anomalous cold cyclone is centred around the Japan Sea (central China). The associated anomalous westerly wind and northward-decreasing (northwestward-decreasing) temperature centred over the central (southern) SC together induce midtropospheric warm advection and thus positive rainfall anomalies centred over the central (southern) SC. The anomalous circulations also cause moisture convergences roughly collocated with the anomalous warm advections over the SC, which intensifies the rainfall anomalies.Warm sea surface temperature anomalies in the equatorial central-eastern Pacific during boreal spring induce meridional teleconnection along the coastal East Asia in Meiyu season through suppressing the convective activities in the northwestern Pacific. The resultant SI-EAJE and associated anomalous circulations increase the rainfall over the central SC, and vice versa. Dipole of increased (decreased) spring snow anomalies on the eastern (western) Tibetan Plateau suppresses (intensifies) convective activities in Meiyu season. The resultant SW-EAJW and associated anomalous circulations increase the rainfall in the southern SC.

Characteristics of Warm‐Season Mesoscale Convective Systems Over the Yangtze–Huaihe River Basin (YHR): Comparison Between Radar and Satellite

AbstractMesoscale convective systems (MCSs) are crucial in modifying the water cycle and frequently induce high‐impact weather events over eastern China. Radar and Climate Prediction Center (CPC)‐4 km satellite‐derived infrared cloud top temperature (Tb) data were used to thoroughly analyze the long‐term climatology of MCSs over eastern China, particularly in the Yangtze–Huaihe River Basin (YHR) in the warm season from 2013 to 2018. For the first time, we contrasted the effects of data set selection and threshold setting on research outcomes. The large‐scale environments of MCSs initiation were also investigated using the latest global reanalysis data ERA5. It is found that striction of thresholds, including duration, reflectivity/Tb, area, and linearity, would lead to a greater proportion of early‐morning MCSs. Satellite‐identified MCSs differed from radar‐derived ones, exhibiting afternoon diurnal peaks, faster movement speeds, longer travel distances, and expansive impact areas. The center of MCS and related precipitation shifted northward from Pre‐Meiyu to Post‐Meiyu seasons, contributing to up to 20% of total rainfall, with most MCSs moving along eastward trajectories. MCSs typically had the most substantial impact in the Meiyu season because of the most prolonged duration, largest convective core area, and strongest precipitation intensity. Warm‐season MCSs initiated ahead of midlevel troughs and were related to strong anomalous low‐level convergence and midlevel upward. The circulation anomalies were the strongest in the Pre‐Meiyu season among the three subseasons, with most moisture sourced from the southwest.

Radar Characteristics and Causal Analysis of Two Consecutive Tornado Events Associated with Heavy Precipitation during the Mei-Yu Season

This paper comprehensively analyzed two consecutive tornado events associated with heavy precipitation during the Mei-yu season (a period of continuous rainy weather that occurs in the middle and lower reaches of the Yangtze River in China from mid-June to mid-July each year) and detailed the formation and development process of the tornadoes using Doppler weather radar, wind profiler radar, ERA5 reanalysis data, ground automatic station data and other multi-source data. The results showed that: (1) Small-scale vortices were triggered and developed during the eastward movement of the low vortex, forming two tornadoes successively on the eastern section of the Mei-yu front. (2) The presence of a gap on the front side of the reflectivity factor profile indicated that strong incoming airflow entered the updraft. Mesocyclones were detected with decreasing heights and increasing shear strengths. The bottom height of the tornado vortex signature (TVS) dropped to 0.7 km, and the shear value increased to 55.4 × 10−3 s−1. Tornado debris signatures (TDSs) could be seen with a low cross-correlation coefficient (CC) value area of 0.85–0.9 in the mesocyclone. The difference between the lowest-level difference velocity (LLDV) and the maximum difference velocity (MXDV) reached the largest value when a tornado occurred. (3) The continuously enhanced low-level jet propagated downward to form a super-low-level jet, and the strong wind direction and wind speed convergence in the boundary layer created a warm, moist and unstable atmosphere in Suzhou. With the entrainment of dry air, the northwest dry jet and the southeast moist jet stimulated the formation of a miniature supercell. (4) The low-level vertical wind shear of 0–1 km increased significantly upon tornado occurrence, which was more conducive to the formation and intensification of horizontal vorticity tubes. Encountering updrafts and downdrafts, the vorticity tubes might have been stretched and intensified. The first lightning jumps appeared 15 min and 66 min earlier than the Kunshan Bacheng tornado and the Taicang Liuhe tornado. The Liuhe tornado occurred during the stage when the lightning frequency reached its peak and then fell back.

Spatial Correlations of Regional Tropical Cyclone– and Nontropical Cyclone–Induced Severe Rainstorms during 2000–19

Abstract Severe rainstorms are one of the most devastating disasters in southeast China (SEC). A deep and comprehensive understanding of the spatial correlations of severe rainstorms is important for preventing rainstorm-induced hazards. In this study, tropical cyclone– and nontropical cyclone–induced severe rainstorms (TCSRs and NTCSRs, respectively) over SEC during 2000–19 are discussed. Co-occurrence probability and range values calculated using the semivariogram method are used to measure the spatial correlations of severe rainstorms. The extent to which potential factors [El Niño/La Niña, Indian Ocean dipole (IOD), latitudes, longitudes, temperature, elevation, and radius of maximum wind] affect the spatial structure of severe rainstorms is discussed. The spatial correlation distances for TCSRs (300–700 km) in typhoon season (July, August, and September) are longer than most of those for NTCSRs (150–300 km) in mei-yu season (June and July). The range values of TCSRs at each percentile (except for the minimum range values) tend to be omnidirectional. While NTCSRs tend to have a major direction of northeast–southwest. El Niño tends to increase the average spatial correlation distance of TCSRs in the northeast–southwest and NTCSRs in the north–northeast. La Niña tends to decrease the spatial correlation distance of TCSRs in the northeast–southwest. The occurrence of positive IOD (+IOD) and negative IOD (−IOD) events may increase the spatial correlation distance of TCSRs in the northwest–southeast, and −IOD events may decrease the distance in the northeast–southwest. IOD events, especially −IOD, may change the spatial correlation distance of NTCSRs in the east–northeast. Latitudes, longitudes, temperature, elevation, and radius of maximum wind significantly affect the spatial correlation distance of TCSRs in various directions. Significance Statement Spatial correlation distances of rainfall events, especially severe rainstorms induced by different weather systems such as tropical and nontropical cyclones (TCSR and NTCSR), can provide important information for rain-induced hazard risk mitigation. Moreover, factors that affect the variability of the spatial correlation distance of TCSRs and NTCSRs are also of interest. To this end, co-occurrence probability and semivariogram methods are used to obtain the spatial correlation distances. The spatial correlation distance of TCSRs varies between 300 and 700 km in typhoon season (July, August, and September) while it ranges between 150 and 300 km in mei-yu season (June and July) for NTCSRs over southeast China (SEC). El Niño/La Niña, Indian Ocean dipole (IOD), latitudes, longitudes, temperature, elevation, and radius of maximum wind have significant impacts on the spatial correlation distances of TCSRs. These findings can provide useful information for forecasting the spatial correlation distance of severe rainstorms over SEC.