Search Results (18)

Intense convection is often accompanied by high-frequency lightning and is highly prone to producing heavy rainfall, strong winds, hail, and tornadoes, frequently resulting in significant damage and loss of life. It is necessary to understand the mechanisms and meteorological conditions of intense convection. This study utilizes the Thunderstorm Feature Dataset from 2010–2018 to analyze the characteristics of thunderstorms with extreme lightning activity (TELAs), defined as thunderstorms whose lightning frequency ranks in the top 1%. Four regions with relatively high thunderstorm activity were selected for analysis: Northeast China (NEC), North China (NC), South China (SC), and the Tibetan Plateau (TP). In NEC, TELAs primarily occur just west of upper-level westerly troughs (UWT), including cold vortices. In NC, TELAs are mainly associated with UWT and subtropical highs (STH). In SC, TELAs are related to frontal systems, easterly waves, tropical cyclones, and STH. In TP, TELAs are generated by TP vortices. Before the TELA process, vertically integrated moisture divergence (VIMD) and convective available potential energy (CAPE) show the most notable anomalies. Except for the TP, TELAs are typically located between centers of anomalies with positive and negative geopotential height (500 hPa) and near centers of anomalies with positive CAPE and negative VIMD, accompanied by notable increases in surface temperature and wind speed. These findings offer a valuable reference for the early warning and forecasting of intense convection. Full article

In order to meet the needs of low-impact development and sustainable development, there is an urgent desire to develop an innovative recycled aggregate pervious concrete (I-RAPC) that is of high strength and permeability. In this study, I-RAPC was prepared based on response surface methodology (RSM) using recycled aggregate, river sand, and different types of pipes as the materials, and the effects of different pipe parameters (number, diameter, material, and distribution form) on the performance of I-RAPC were investigated. In addition, the calculation model of the compressive strength and the permeability coefficient of I-RAPC were proposed. The results showed that the frontal- and lateral-compressive strengths of I-RAPC were 39.8 MPa and 42.5 MPa, respectively, when the pipe material was acrylic, the position was 1EM, and the diameter was 10 mm—at which time the permeability coefficient was 3.02 mm/s, which was the highest in this study. The maximum relative errors of the compressive strength calculation model and the permeability coefficient calculation model were only 7.52% and 4.42%, respectively, as shown by the post hoc test. Therefore, I-RAPC has the advantages of high strength and permeability and is expected to be applied in low-impact development in cities with heavy surface sediment content and rainfall. Full article

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 (Z_DR), specific differential phase (K_DP) 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, Z_DR, K_DP 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. Full article

Warm zone rainstorms and frontal rainstorms are two types of rainstorms that often occur in the rainy season in Jiangxi (located in the eastern part of China). The ability to correctly identify the type of rainstorms is important for accurate forecasting of rainstorms. Two heavy rainstorms took place in Jiangxi province. The first heavy rainstorm occurred from 20:00 BJT (Beijing Time) on 6 June to 20:00 BJT on 9 June (referred to as the “6.9” process) and another heavy rainstorm occurred from 20:00 BJT on 21 June to 20:00 BJT on 22 June (referred to as the “6.9” process), 2019. We analyzed the two rainstorms’ processes by using ground-based observation data, NCEP/FNL reanalysis data, ECMWF and CMA-SH9 numerical forecasting products. The results show that: “6.9” process is a warm area rainstorm, and a strong northeast cold vortex exists at 500 hPa geopotential height. The northwesterly flow behind the northeast cold vortex trough is stronger. The position of the northern edge of the subtropical high pressure is more south than that at “6.22” process. The rainstorm is in the precipitation zone of the warm temperature ridge over 925 hPa geopotential height, and with more convective character than “6.22” process. The process of “6.22” is a frontal rainstorm. The convective character of precipitation is weaker. The rainstorm precipitation zones are in a strong temperature front area at 925 hPa geopotential height and there is a tendency for vertical convection to develop into oblique upward convection in the late stage of the rainstorm. The precipitation location and intensity forecast by CMA-SH9 at the “6.9” process is better than that of ECMWF, while ECMWF’s prediction of the precipitation zone and weather condition of the “6.22” process is better. Full article

The study explores the characteristics of morning extreme precipitation (MEP) during the pre-summer in inland Guangdong. Based on the principal modes, MEP events can be classified into four groups. The first group of MEP (G1) is a typical southeastward-propagating rainfall system originating from the northwestern mountains. This is caused by the strongest accelerated southwesterly winds at night, which bring abundant moist and warm air from the South China Sea (SCS) along with the shear line and the highest convective available potential energy (CAPE). The second group of MEP (G2) is warm-sector heavy rainfall with large-scale warming and higher CAPE. This local rainfall system originates in the south of Nanling mountains at night and reaches its mature stage in the morning. The rainfall system of the third group (G3) originates in central Guangxi and propagates to the southern inland region. The southeasterly winds in Guangxi intensify at night due to the anomalous cyclonic circulation. However, in the morning, the easterly winds shift to the westerlies, favoring eastward propagation. After SCS monsoon onset, cold air intrudes southward, colliding with moist warm air from the SCS, leading to heavy frontal precipitation in the inland region, classified as the fourth group MEP (G4). Full article

In light of the 2020–2021 flood season in Guangdong, we conducted a comprehensive assessment of short-term precipitation forecasts generated by the ensemble prediction system (EPS) based on the China Meteorological Administration Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS). Furthermore, we applied four distinct strategies to cluster the ensemble forecast data produced by the model for precipitation, aiming to enhance our understanding of their applicability in short-term precipitation forecasting for Guangdong. Our key findings were as follows.: Precipitation during the 2020–2021 flood season in Guangdong exhibited distinct characteristics. The impacting areas of frontal and subtropical high-edge rainfall were relatively scattered, predominantly occurring in the evening and nighttime. In contrast, monsoon precipitation and return-flow precipitation were concentrated, with their impacts lasting from early morning to evening. Notably, the errors using the ensemble maximum and minimum values were large, while the errors for the ensemble mean values and medians were small. This indicated that the model’s short-term precipitation forecasts possessed a high degree of stability. The vertical shear of different types of precipitation exerted a noticeable influence on the model’s performance. The model consistently displayed a tendency to underestimate short-term precipitation in Guangdong; however, this bias decreased with longer lead times. Simultaneously, the model’s dispersion increased with longer lead times. In terms of mean absolute error (MAE) test results, there was little difference in the performance of ensemble primary forecasts under various strategies, while the “ward” strategy performed well in sub-primary cluster forecasts. This was particularly true for areas and types of precipitation where the model’s performance was poor. While the clustering approach lagged behind ensemble mean forecasts in predicting rainy conditions, it exhibited improvement in forecasting short-term heavy rainfall events. The “complete” and “single” strategies consistently delivered the most accurate forecasts for such events. Our study sheds light on the effectiveness of clustering methods in improving short-term precipitation forecasts for Guangdong, particularly in regions and conditions where the model initially struggled. These findings contribute to our understanding of precipitation forecasting during flood seasons and can inform strategies for enhancing forecast accuracy in similar contexts. Full article

This study selected three heavy-rainfall events of different types in Taiwan’s Mei-yu season for high-resolution simulations at a grid size of 1 km and assessed the model’s capability to reproduce their morphology and characteristics. The three cases include a pre-frontal squall line, a mesoscale convective system (MCS) embedded in southwesterly flow, and a local convection near the front in southern Taiwan during the South-West Monsoon Experiment (SoWMEX) in 2008, chosen mainly because of the availability of the S-band polarimetric (S-Pol) radar observations, and especially the particle identification results. The simulations using the Cloud-Resolving Storm Simulator (CReSS) could reproduce all three corresponding rainfall systems at roughly the correct time and location, including their kinematic structures such as system-relative flows with minor differences, although the cells appeared to be coarser and wider than the S-Pol observations. The double-moment cold-rain microphysics scheme of the model could also capture the general distributions of hydrometeors, such as heavy rainfall below the updraft core with lighter rainfall farther away below the melting level, and graupel and mixed-phase particles in the upper part of the updraft with snow and ice crystals in stratiform areas between updrafts above the melting level. Near the melting level, the coexistence of rain and snow corresponds to wet snow in the observations. Differences in cloud characteristics in the events are also reflected in the model results to some extent. Overall, the model’s performance in the simulation of hydrometeors exhibits good agreement with the observation and appears reasonable. Full article

Extreme rainfall events cause diverse loss of life and economic losses. These disasters include flooding, landslides, and erosion. For these intense rainfall events, one can statistically estimate the time when a given rainfall volume will occur. Initially, this work estimated rainfall volumes for the mountainous region of Rio de Janeiro, and the frequency with which rainfall events occur. For this, we analyzed daily precipitation data using the ANOBES method and the Gumbel statistical distribution to estimate return times. Extreme prec’ipitation volumes of up to 240 mm per day were identified in some locations, with 100 years or more return periods. On 11 January 2011 precipitation volumes were high, but on 12 January they were extreme, similar to the 100-year return time data. The analysis method presented enables the determination of the return time of heavy rainfall, assisting in the prevention of its effects. Knowledge of the atmospheric configuration enables decision support. The atmospheric systems that combined to cause the event were local circulations (orographic and sea breeze) and large-scale systems (SACZ and frontal systems). Full article

In order to improve the precipitation forecast of the next-generation Global Prediction System with the Finite-Volume Cubed-Sphere Dynamical Core in Taiwan’s Central Weather Bureau, this study modified the convective processes in the New Simplified Arakawa-Schubert scheme based on the methodology of scale-aware parameterization developed in Kwon and Hong (2017) and investigated its impacts on a front event, which propagated across Taiwan and produced heavy rainfall in late May of 2020. Results show that the modified scale-aware parameterization has significantly improved the intensity and the spatial distribution of frontal precipitation forecasts due to the proper definition of convective updraft fraction. However, the synoptic-scale features perform a larger warm bias with the modified scale-aware parameterization. Therefore, further modification of the scale-aware capability of convective cloud water detrainment is proposed to reduce the heating from microphysical processes and result in a better overall performance for the medium-range weather forecasts. Full article

This study analyzes an ensemble of numerical simulations of a heavy rainfall event east of Taiwan on 9 June 2020. Heavy rainfall was produced by quasi-stationary back-building mesoscale convective systems (MCS) associated with a mei-yu front. Global model forecast skill was poor in location and intensity of rainfall. The mesoscale ensemble showed liminal conditions between heavy rainfall or little to no rainfall. The two most accurate and two least accurate ensemble members are selected for analysis via validation against radar-estimated rainfall observations. All members feature moist soundings with low levels of free convection (LFC) and sufficient instability for deep convection. We find that stronger gradients in 100-m ${\theta }_e$ and ${\theta }_v$ in the most accurate members associated with a near-surface frontal boundary focus the lifting mechanism for deep, moist convection and enhanced rainfall. As the simulations progress, stronger southerly winds in the least accurate members advect drier mid-level air into the region of interest and shift the near-surface boundary further north and west. Analysis of the verification ensemble mean analysis reveals a strong near-surface frontal boundary similarly positioned as in the most accurate members and dry air aloft more similar to that in the least accurate members, suggesting that the positioning of the frontal boundary is more critical to accurately reproducing rainfall patterns and intensity in this case. The analyses suggest that subtle details in the simulation of frontal boundaries and mesoscale flow structures can lead to bifurcations in producing extreme or almost no rainfall. Implications for improved probabilistic forecasts of heavy rainfall events will be discussed. Full article

During 6–7 June 2003, a Mei-Yu jet/front system over Southern China is characterized by appreciable horizontal temperature contrast below the 850 hPa level (>8 K), where the cold, dry, postfrontal northeasterlies converge with the warm, moist southwesterly flow, and above the 400–hPa level (>18 K) associated with an upper-level front. The frontal baroclinic zone tilts northward with a slope of ~1/100. During the passage of a midlatitude trough, the upper-level jet/front system advances southeastward. The thermally direct circulation across the subsynoptic low-level jet (SLLJ)/Mei-Yu front system, coupled with dynamic forcing aloft on the equatorial side of the entrance region of a subsynoptic upper-level jet (SULJ), provides a favorable environment for the development of a frontal cyclone over Southern China. A southwesterly marine boundary layer jet (MBLJ) develops between the deepening Mei-Yu frontal cyclone and the West Pacific Subtropical High (WPSH). The MBLJ transports moisture from the northern South China Sea (NSCS) to Southern China. All three jets (SULJ, SLLJ, and MBLJ) interact together during the deepening of the Mei-Yu frontal cyclone with positive feedback effects of latent heat release. On 7 June 2003, as the Mei-Yu front arrives near the Taiwan area, the warm, moist, and unstable air associated with the MBLJ decelerates as it approaches the Central Mountain Range (CMR). The warm, moist, and unstable air is orographically lifted by the CMR and enhances the vertical motion already present with the frontal zone. A region of widespread heavy rainfall develops, with a maximum of more than 350 mm/day, over a region extending from the southwestern coast of Taiwan to the windward slopes of the CMR. Full article

During the early summer rainy season over Taiwan, three types of low-level jets are observed, including a synoptic low-level jet (SLLJ) situated in the 850–700 hPa layer in the frontal zone, a marine boundary layer jet (MBLJ) embedded within the southwesterly monsoon flow over the northern South China Sea at approximately the 925 hPa level, and an orographically induced jet at approximately the 1 km level off the northwestern Taiwan coast (e.g., barrier jet (BJ)). The characteristics and physical processes of the formation of these three types of low-level jets are reviewed, and their roles in the development of heavy rainfall are discussed. Full article

In view of the limited predictability of heavy rainfall (HR) events and the limited understanding of the physical mechanisms governing the initiation and organization of the associated mesoscale convective systems (MCSs), a composite analysis of 58 HR events over the warm sector (i.e., far ahead of the surface cold front), referred to as WSHR events, over South China during the months of April to June 2008~2014 is performed in terms of precipitation, large-scale circulations, pre-storm environmental conditions, and MCS types. Results show that the large-scale circulations of the WSHR events can be categorized into pre-frontal, southwesterly warm and moist ascending airflow, and low-level vortex types, with higher frequency occurrences of the former two types. Their pre-storm environments are characterized by a deep moist layer with >50 mm column-integrated precipitable water, high convective available potential energy with the equivalent potential temperature of ≥340 K at 850 hPa, weak vertical wind shear below 400 hPa, and a low-level jet near 925 hPa with weak warm advection, based on atmospheric parameter composite. Three classes of the corresponding MCSs, exhibiting peak convective activity in the afternoon and the early morning hours, can be identified as linear-shaped, a leading convective line adjoined with trailing stratiform rainfall, and comma-shaped, respectively. It is found that many linear-shaped MCSs in coastal regions are triggered by local topography, enhanced by sea breezes, whereas the latter two classes of MCSs experience isentropic lifting in the southwesterly warm and moist flows. They all develop in large-scale environments with favorable quasi-geostrophic forcing, albeit weak. Conceptual models are finally developed to facilitate our understanding and prediction of the WSHR events over South China. Full article

The electrical state of the surface atmosphere changes significantly under the influence of cloudiness and atmospheric phenomena, including atmospheric precipitation. These features can be used for possible diagnostics of precipitation and improvement of their characteristics based on variations of atmospheric-electrical quantities in the surface layer. Studies of variations of meteorological and atmospheric-electrical quantities in the surface layer were carried out during the heavy rainfall associated with the cumulonimbus (Cb) clouds passage. Meteorological and atmospheric-electrical observations in the Geophysical Observatory of the Institute of Monitoring of Climatic and Ecological Systems are presented in this paper. Precipitation data are used to identify periods of heavy rainfall ≥ 5 mm/h. Information of weather stations and satellites is used to separate the heavy rainfall events by synoptic conditions like thunderstorms and showers of frontal or internal air masses. We find that rains associated with the frontal Cb clouds produce more abrupt changes in negative electrical conductivity in comparison with the Cb clouds in internal air masses. The significant increase in negative electrical conductivity (more than two times vs. normal values) occurs typically during the passage of frontal Cb and heavy rain with droplet size greater than 4 mm. Full article

An impactful and poorly forecasted heavy rainfall event was observed in association with the Meiyu front over the Yangtze River valley of China from 30 June–4 July 2016. Operational global numerical weather prediction models for almost all forecast lead times beyond 24 h incorrectly forecasted the location and intensity of the precipitation associated with this event. This study presents the first examination of this poleward bias in the operational models for the Meiyu front, which has been frequently noted by meteorologists at the Chinese Meteorological Administration, and explores areas of forecast error and uncertainty in the prediction of the position of the primary frontal rainbelt that is crucial to the placement and intensity of the heavy rainfall. A new zonal mean maximum accumulated precipitation index is introduced and utilized to identify members in the European Centre for Medium-Range Forecasts (ECMWF) Ensemble Prediction System (EPS) that either perform well or perform poorly in forecasting the location of the Meiyu front. Using this new precipitation metric, five-member subgroups representing the EPS members that were most accurate and those that incorrectly displace the Meiyu front the furthest north were identified. An analysis of composite mean fields for the EPS subgroups and the correlation between the rain band placement and the 500 hPa heights was performed for several EPS model runs. We showed that a successful prediction of the location of the Meiyu front rainbelt position by the EPS is most sensitive to the intensity of the 500 hPa trough located over eastern China for the event. The ensemble members that had the largest northward error in the location of the rain band were found to have a more intense 500 hPa trough than the members that more accurately predicted the rainbelt. The more intense upper level trough was found to have enhanced the lower tropospheric southerly flow equatorward of the front and led to a less zonal-oriented Meiyu front, resulting in a northward displacement of both the rainbelt and the regions of more intense precipitation rates. Finally, an examination of the evolution of the differences between the subgroups shows that the primary differences in 500 hPa intensity propagate in-phase with the 500 hPa trough. We show that it is the intensity of the trough, rather than the rate of propagation, that is the most important source of forecast dissimilarities between the successful and failed forecasts. Full article