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During 19–21 July 2021, an extreme rainfall event occurred in Henan Province, China, during which a record-breaking maximum hourly rainfall of 201.9 mm was recorded in Zhengzhou at 09 UTC July 20. In this study, the predictability of this extreme rainfall event is investigated using two convection-permitting ensemble forecast systems (CEFSs): one initialized from NCEP GEFS (named CEFS_GEFS) and the other initialized from time-lagged ERA5 data (named CEFS_ERA). Both are able to reproduce the daily heavy rainfall along the Taihang Mountains, but most members have significant position biases for the extreme rainfall in Zhengzhou. For the hourly rainfall, a few members are able to capture the evolution and propagation of extreme rainfall. However, all ensemble members underestimate the extreme hourly rainfall and have position errors of a few tens to a few hundreds of kilometers. Such results suggest that the predictability of the extreme hourly rainfall at the accuracy of city scale in Zhengzhou is low, especially by deterministic forecasting models, and the occurrence of the extreme requires that many favorable conditions to happen simultaneously. In terms of the Brier score, CEFS_GEFS performs better than CEFS_ERA. The latter lacks spread, especially in regions with scarce rain, resulting in less dispersion in precipitation distributions and larger probability forecast error. When a neighborhood is applied, the probability of precipitation (POP) is significantly increased over Zhengzhou. While the traditional POP shows almost no skill for hourly rainfall ≥ 25 mm h−1, the neighborhood POP significantly improves the forecast skill score, for both daily and hourly rainfall, suggesting higher predictability when spatial error among the ensemble members is allowed.

This 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. The resolution of the operational China Meteorological Administration Mesoscale model (CMA‐MESO) was upgraded to 3 km in 2020. However, the overall performance of the precipitation forecast has not been evaluated comprehensively, and the main factors causing precipitation forecast biases are not well understood. This study analyzed the CMA‐MESO precipitation forecasts during the 2020 super Meiyu season. Generally, CMA‐MESO well reproduced the distribution and propagation of precipitation, but the intensity was overestimated, especially in eastern coastal areas of China. CMA‐MESO tended to produce an overly strong southwesterly low‐level wind that transported too much warm moist air to eastern coastal areas, resulting in excessive rainfall. Further comparative evaluation suggested that the overestimation of low‐level winds might be related to the larger NW–SE temperature gradient of CMA‐MESO. The findings of the current study could provide guidance for improving physical parameterization in the future. Performance of the operational CMA‐MESO in China at convection‐permitting resolution was evaluatedCMA‐MESO can well reproduce the distribution and propagation of precipitation, but overestimates precipitation in eastern coastal areasOverestimation of low‐level wind speed is the main reason for the overestimation of precipitation in eastern coastal areas Performance of the operational CMA‐MESO in China at convection‐permitting resolution was evaluated CMA‐MESO can well reproduce the distribution and propagation of precipitation, but overestimates precipitation in eastern coastal areas Overestimation of low‐level wind speed is the main reason for the overestimation of precipitation in eastern coastal areas

An extremely heavy rainfall event occurred in Zhengzhou, China, on 20 July 2021 and produced an hourly rainfall rate of 201.9 mm, which broke the station record for mainland China. Based on radar observations and a convection-permitting simulation using the WRF-ARW model, this paper investigates the multiscale processes, especially those at the mesoscale, that support the extreme observed hourly rainfall. Results show that the extreme rainfall occurred in an environment characteristic of warm-sector heavy rainfall, with abundant warm moist air transported from the ocean by an abnormally northward-displaced western Pacific subtropical high and Typhoon In-Fa (2021). However, rather than through back building and echo training of convective cells often found in warm-sector heavy rainfall events, this extreme hourly rainfall event was caused by a single, quasi-stationary storm in Zhengzhou. Scale separation analysis reveals that the extreme-rain-producing storm was supported and maintained by the dynamic lifting of low-level converging flows from the north, south, and east of the storm. The low-level northerly flow originated from a mesoscale barrier jet on the eastern slope of the Taihang Mountain due to terrain blocking of large-scale easterly flows, which reached an overall balance with the southerly winds in association with a low-level meso-β-scale vortex located to the west of Zhengzhou. The large-scale easterly inflows that fed the deep convection via transport of thermodynamically unstable air into the storm prevented the eastward propagation of the weak, shallow cold pool. As a result, the convective storm was nearly stationary over Zhengzhou, resulting in record-breaking hourly precipitation.

Parallel back-building convective lines are often observed extending to the southwest of some mesoscale convective systems (MCSs) embedded in the mei-yu front in China. The convective lines with echo training behavior can quickly develop into a stronger convective group of echoes, resulting in locally heavy rainfall within the mei-yu front rainband. The initiation mechanism of the back-building convective lines is still unclear and is studied based on high-resolution numerical simulation of a case that occurred during 27–28 June 2013. In the present case, the new convection along the convective lines was found to be forced by nonuniform interaction between the cold outflow associated with the mei-yu front MCSs and the warm southerly airflow on the south side of the mei-yu front, which both are modified by local terrain. The mei-yu front MCSs evolved from the western to the eastern side of a basin surrounded by several mesoscale mountains and induced cold outflow centered over the eastern part of the basin. The strong southwest airflow ahead of the mei-yu front passed the Nanling Mountains and impacted the cold outflow within the basin. The nonuniform interaction led to the first stage of parallel convective line formation, in which the low mountains along the boundary of the two airflows enhanced the heterogeneity of their interaction. Subsequently, the convective group quickly developed from the first stage convective lines resulted in apparent precipitation cooling that enhanced the cold outflow and made the cold outflow a sharp southward windshift. The enhanced cold outflow pushed the warm southerly airflow southward and impacted the mountains on the southeast side of the basin, where the roughly parallel mountain valleys or gaps play a controlling role in a second stage formation of parallel convective lines.

A regional ensemble Kalman filter (EnKF) data assimilation (DA) and forecast system was recently established based on the Gridpoint Statistical Interpolation (GSI) analysis system. The EnKF DA system was tested with continuous three-hourly updated cycles followed by 18-h deterministic forecasts from every three-hourly ensemble mean analysis. Initial tests showed negative to neutral impacts of assimilating satellite radiance data due to the improper bias correction procedure. In this study, two bias correction schemes within the established EnKF DA system are investigated and the impact of assimilating additional polar-orbiting satellite radiance is also investigated. Two group experiments are conducted. The purpose of the first group is to evaluate the bias correction procedure. Two online bias correction methods based on GSI 3DVar and EnKF algorithms are used to assimilate AMSU-A radiance data. Results show that both variational and EnKF-based bias correction procedures effectively reduce the observation and background radiance differences, achieving positive impacts on forecasts. With proper bias correction, we assimilate full radiance observations including AMSU-A, AMSU-B, AIRS, HIRS3/4, and MHS in the second group. The relative percentage improvements (RPIs) for all forecast variables compared to those without radiance data assimilation are mostly positive, with the RPI of upper-air relative humidity being the largest. Additionally, precipitation forecasts on a downscaled 13-km grid from 40-km EnKF analyses are also improved by radiance assimilation for almost all forecast hours.

The concave mountainous area of Pearl River Delta (PRD) is a summer rainfall hotspot of South China due to the presence of warm‐moist monsoon flow and complex orography. This study evaluated the performance of a convection‐permitting Weather Research and Forecasting (WRF) model in forecasting nocturnal rainfall in this area, focusing on days with low level southwesterly winds during the summers of 2013–2015. Results showed that the nocturnal rainfall exhibited two centers, one located along the large‐scale northern mountains and the other along the small‐scale Huadu Hill. WRF demonstrated superior performance in predicting rainfall over the northern mountainous region. In contrast, WRF significantly underestimated nocturnal rainfall both near local Huadu Hill and in the foothill area of northern mountains, which were strongly influenced by local forcings. Using high‐resolution analyses from Variational Doppler Radar Analysis System (VDRAS) and Automatic Weather Stations observations, we firstly identified the sources of forecast errors in triggering a typical localized nocturnal convection. Results revealed that WRF severely underestimated thermal contrast between the Guangdong‐Hong Kong‐Macao Greater Bay Area urban agglomeration and the concave mountains, leading to the absence of the northeastern/northern inflows toward the cities. Consequently, low level convergence and updrafts near the convection initiation position were too weak to lift air parcels above the severely overestimated level of free convection, thereby failing to trigger the convection. VDRAS‐based sensitivity experiments, with a specific focus on assimilating surface temperature, validated the crucial role of urban‐mountain thermal contrast on local winds that triggered the nocturnal convection. The concave mountainous region of Pearl River Delta serves as a summer rainfall hotspot in South China, and heavy rainfall at night, especially those influenced by local forcings, pose significant challenges for forecasters. This study evaluated the performance of convection‐permitting Weather Research and Forecasting (WRF) model in forecasting nocturnal rainfall on days with low level southwesterly winds during the 2013–2015 summers. Results showed that WRF exhibited limitations in forecasting nighttime precipitation that developed locally within the concave mountainous area. Based on a localized heavy rainfall event, we identified sources of errors in predicting nocturnal convection initiation (CI). There was a significant cold bias over the Guangdong‐Hong Kong‐Macao Greater Bay Area urban agglomeration, which led to a seriously underestimated temperature difference between urban area and concave mountains. Consequently, WRF failed to predict urban inflows, and the predicted low level convergence and updrafts near the CI location were too weak to lift air parcels above the seriously overestimated level of free convection, resulting in a failure to trigger the convection. This study emphasizes that, over a complex geographical environment characterized by concave mountains and urban agglomeration, accurately predicting the urban‐mountain thermal contrast and local circulations is crucial for nighttime precipitation forecast. Nocturnal rainfall that developed locally within the concave mountainous area of South China was severely underestimatedForecast bias in localized convection initiation was related to underestimated thermal contrast between urban area and concave mountains Nocturnal rainfall that developed locally within the concave mountainous area of South China was severely underestimated Forecast bias in localized convection initiation was related to underestimated thermal contrast between urban area and concave mountains

The precipitation in Sichuan Basin (SB), China, exhibits pronounced diurnal variation, including minimum rainfall in daytime and a prominent peak near midnight. This study investigates the primary mechanism of precipitation diurnal variation in SB using forecasts from three summer months of 2013 produced at a 4‐km grid spacing. The model forecasts reproduce the observed spatial distributions and diurnal cycles well, including the peak precipitation in SB at around 02 local solar time (LST). Contrary to the common belief that emphasizes the solenoidal effects associated with the Tibetan and Yunnan‐Guizhou Plateaus, prominent diurnal inertial oscillations of boundary layer south‐southwesterly low‐level jet into SB are shown to play more important roles in modulating the diurnal cycles of precipitation in SB. A basinwide moisture budget analysis is performed to reveal that the moisture flux from the southeast side of the basin dominates within the diurnal oscillations of the net moisture flux into the basin, and the much enhanced nocturnal low‐level jet plays a crucial role in the formation of nocturnal precipitation within the basin. The net moisture flux into SB reaches maximum at around 22 LST, the time boundary layer perturbation winds from the daily mean in the direction normal to the southeastern boundary of SB reach maximum, which is about 4 hr before precipitation peak at around 02 LST. Shallow thermally forced nighttime downslope flows and daytime upslope flows on the Tibetan Plateau and Yunnan‐Guizhou Plateau slopes contribute only a small portion of moisture fluxes through the basin boundaries. The diurnal cycles of summer precipitation, including the prominent peak shortly after midnight, are reproduced well by 4‐km forecastsThe diurnal variations of the southerly low‐level jet are found to play dominant roles in controlling the precipitation diurnal cyclesThe diurnal variations of low‐level jet can be explained well by the boundary layer inertial oscillations theory of Blackadar

The diurnal variation of precipitation over the Dabie Mountains (DBM) in eastern China during the 2013 mei-yu season is investigated with forecasts of a regional convection-permitting model. Simulated precipitation is verified against surface rain-gauge observations. The observed morning precipitation peak on the windward (relative to the prevailing synoptic-scale wind) side of the DBM is reproduced with good spatial and temporal accuracy. The interaction between the DBM and a nocturnal boundary layer low-level jet (BLJ) due to the inertial oscillation mechanism is shown to be responsible for this precipitation peak. The BLJ is aligned with the lower-level southwesterly synoptic-scale flow that carries abundant moisture. The BLJ core is established at around 0200 LST upwind of the mountains. It moves towards the DBM and reaches maximum intensity at about 70 km ahead of the mountains. When the BLJ impinges upon the windward side of the DBM in the early morning, mechanical lifting of moist air leads to condensation and subsequent precipitation. 大别山地区是江淮流域一个暴雨中心, 降水日变化呈现典型的双峰结构, 其中清晨降水峰值的形成机制原因较为复杂, 过去存在较大的争议. 本文利用南京大学夏季实时运行的4km WRF, 研究了梅雨期间大别山地区清晨峰值降水的形成机制, 模式预报很好地再现了大别山地区的降水时空分布和日变化特征. 研究表明, 大别山迎风坡区域夜间边界层急流存在明显的惯性振荡, 凌晨5点左右惯性振荡方向与盛行风方向重合, 夜间边界层急流强度达到最强; 当低层暖湿气流输送到大别山地区时, 地形抬升作用进一步增强了降水. 夜间边界层急流增强和大别山地形的抬升作用是该地区清晨降水峰值形成的主要机制.

Based on potential vorticity (PV) thinking, northeast China cold vortex (NCCV) corresponds to an upper‐level high PV anomaly from stratospheric PV downward intrusion. Within a vortex, latent heating from precipitation would produce a vertical dipole of PV anomalies that would affect structures and evolution of the vortex. In this paper, three‐dimensional structures and evolution of NCCV and, effects of latent heating from precipitation along bent‐back, cold and warm fronts on them are investigated based on convection‐allowing simulations for an intense NCCV case during 8–17 June 2012. Trajectory analysis shows that the negative upper‐level diabatic PV anomaly from bent‐back frontal precipitation, near the vortex center, is the dominant contributor to erosion of high PV in the vortex core region as it is advected in, leading to the weakening of the vortex. The negative PV anomalies along the cold and warm fronts, at the east‐to‐southeast side of the vortex, are mostly advected downstream away from the NCCV. In the middle troposphere, positive PV anomalies are primarily generated along fronts and the accumulated positive PV anomalies filling the vortex region help to reinforce the low‐level cyclonic circulation. The lower‐level PV is affected by surface heating and cooling through their effects on static stability, but such effects are periodic and create mainly diurnal variations. The NCCV eventually decays as the upper‐level vortex weakens due to significant PV erosion. Northeast China cold vortex (NCCV) is responsible for much of the warm season precipitation in northeast China. Based on convection‐allowing simulations of a characteristic case, the distribution and effects of latent heating release from precipitation in bent‐back, cold and warm frontal regions on the structures and evolution of potential vorticity (PV) within the NCCV are studied. Negative upper‐level PV anomalies generated at the bent‐back front are primarily responsible for the filamentation and erosion of high PV in the core of NCCV, leading to the weakening of the vortex. At middle‐to‐low levels, positive PV anomalies generated reinforce the low‐level circulations. However, the lower‐level PV exhibits a significant diurnal cycle, which is mainly affected by the surface heating and cooling through reducing static stability at daytime and increasing static stability during night. The overall system eventually decays as the upper‐level vortex weakens. Precipitation in northeast China cold vortex produces negative upper‐level potential vorticity (PV) anomaly that weakens the upper level cold vortexNegative PV anomaly produced at the bent‐back front is the dominant contributor to the erosion of upper‐level high PV in the vortex centerLower‐level vortex is enhanced by positive PV anomaly from precipitation, and the PV has diurnal variations due to surface heating/cooling Precipitation in northeast China cold vortex produces negative upper‐level potential vorticity (PV) anomaly that weakens the upper level cold vortex Negative PV anomaly produced at the bent‐back front is the dominant contributor to the erosion of upper‐level high PV in the vortex center Lower‐level vortex is enhanced by positive PV anomaly from precipitation, and the PV has diurnal variations due to surface heating/cooling

Convection‐permitting simulations are used to investigate the key mechanism of Meiyu precipitation diurnal cycle over China. Six days from the 2014 Meiyu season are used to produce a “north” composite rainband over the Yangtze‐Huaihe River Basin and another 6 days used to produce a “south” composite band. Both rainbands have peak rainfall in the early morning, while the south band has a secondary peak in the afternoon. Low‐level ageostrophic winds (AGWs) are found to exhibit diurnal cycles with clockwise rotations and their directions, and magnitudes depend on the background geostrophic monsoon flows. Net moisture flux into a control volume enclosing each rainband is almost purely due to AGWs. For both rainbands, net flux reaches maximum at ~04 LST, about 3–4 hr before morning precipitation peak. For the north band, a prominent minimum occurs at ~19 LST, 4 hr before the precipitation minimum. The moisture fluxes through the southern control volume boundary make the largest contributions to the net flux and its diurnal variations. The diurnal variations of the AGWs and their relationship with the background monsoon flows agree very well with the prediction of Blackadar boundary layer inertial oscillation theory, and the convergence forcing by the AGWs resulting from the inertial oscillations plays a paramount role in modulating the diurnal cycles of Meiyu front precipitation, including the creation of early morning peak and evening minimum. Feedback of latent heat release plays only a secondary role. The commonly recognized diurnal monsoon variability can be explained by the Blackadar inertial oscillation theory. Meiyu precipitation over China show pronounced diurnal cycles including early morning maximum and evening minimumThe morning maximum and evening minimum are directly linked to maximum low‐level moisture convergence and divergence that occur 2‐3 hr earlierDiurnal variations in the boundary layer winds due to inertial oscillations are primarily responsible for the variations in low‐level convergence forcing and precipitation diurnal cycles

A dual-resolution (DR) version of a regional ensemble Kalman filter (EnKF)-3D ensemble variational (3DEnVar) coupled hybrid data assimilation system is implemented as a prototype for the operational Rapid Refresh forecasting system. The DR 3DEnVar system combines a high-resolution (HR) deterministic background forecast with lower-resolution (LR) EnKF ensemble perturbations used for flow-dependent background error covariance to produce a HR analysis. The computational cost is substantially reduced by running the ensemble forecasts and EnKF analyses at LR. The DR 3DEnVar system is tested with 3-h cycles over a 9-day period using a 40/∼13-km grid spacing combination. The HR forecasts from the DR hybrid analyses are compared with forecasts launched from HR Gridpoint Statistical Interpolation (GSI) 3D variational (3DVar) analyses, and single LR hybrid analyses interpolated to the HR grid. With the DR 3DEnVar system, a 90% weight for the ensemble covariance yields the lowest forecast errors and the DR hybrid system clearly outperforms the HR GSI 3DVar. Humidity and wind forecasts are also better than those launched from interpolated LR hybrid analyses, but the temperature forecasts are slightly worse. The humidity forecasts are improved most. For precipitation forecasts, the DR 3DEnVar always outperforms HR GSI 3DVar. It also outperforms the LR 3DEnVar, except for the initial forecast period and lower thresholds. 本文介绍了一套为业务快速更新预报系统建立的区域集合卡尔曼滤波和3D集合变分耦合的双分辨率混合同化系统. 双分辨率混合同化系统使用了确定性高分辨率背景场和低分辨率的集合卡尔曼滤波的集合扰动, 其中后者为高分辨率分析场的获得提供了流依赖背景误差协方差. 低分辨率的集合卡尔曼滤波分析和集合预报减小了计算成本. 基于9天每3小时循环, 和40/~13km分辨率的配置对双分辨率的混合同化系统进行了测试. 通过与GSI三维变分同化系统、和基于粗分辨率混合同化系统分析场插值场的高分辨率预报结果进行的对比和分析显示: 使用90%的集合流依赖背景误差协方差, 双分辨率混合同化系统能够获得最小预报误差, 并显著优于高分辨率GSI三维变分系统. 此外, 湿度和风场的预报明显优于粗分辨率混合同化系统分析场插值预报的结果, 但温度场不然. 对各变量的评分显示湿度预报提高最为显著. 并与之一致, 双分辨率混合同化系统相对于GSI三维变分系统, 得到了更为精确的降水预报; 并且, 除低阈值降水和初始预报阶段以外, 双分辨率混合同化系统优于粗分辨率混合同化系统分析场的插值场预报.

Forecasts at a 4 km convection‐permitting resolution over China during the summer season have been produced with the Weather Research and Forecasting model at Nanjing University since 2013. Precipitation forecasts from 2013 to 2014 are evaluated with dense rain gauge observations and compared with operational global model forecasts. Overall, the 4 km forecasts show very good agreement with observations over most parts of China, outperforming global forecasts in terms of spatial distribution, intensity, and diurnal variation. Quantitative evaluations with the Gilbert skill score further confirm the better performance of the 4 km forecasts over global forecasts for heavy precipitation, especially for the thresholds of 100 and 150 mm d−1. Besides bulk characteristics, the representations of some unique features of summer precipitation in China under the influence of the East Asian summer monsoon are further evaluated. These include the northward progression and southward retreat of the main rainband through the summer season, the diurnal variations of precipitation, and the meridional and zonal propagation of precipitation episodes associated with background synoptic flow and the embedded mesoscale convective systems. The 4 km forecast is able to faithfully reproduce most of the features while overprediction of afternoon convection near the southern China coast is found to be a main deficiency that requires further investigations. Precipitation forecasts are produced at a 4 km convection‐permitting resolution over China in summer of 2013–2014The 4 km forecast outperforms global forecasts in terms of spatial distribution, intensity, timing, and duration of heavy precipitationThe unique intraseasonal movement, diurnal cycles, and propagation of summer precipitation in China are also well forecast

The impact of horizontal propagation of mountain waves on the orographic gravity wave drag (OGWD) in the stratosphere and lower mesosphere of the Northern Hemisphere is evaluated for the first time. Using a fine‐resolution (1 arc min) terrain and 2.5°×2.5° European Centre for Medium‐Range Weather Forecasts ERA‐Interim reanalysis data during 2011–2016, two sets of OGWD are calculated offline according to a traditional parameterization scheme (without horizontal propagation) and a newly proposed scheme (with horizontal propagation). In both cases, the zonal mean OGWDs show similar spatial patterns and undergo a notable seasonal variation. In winter, the OGWD is mainly distributed in the upper stratosphere and lower mesosphere of middle to high latitudes, whereas the summertime OGWD is confined in the lower stratosphere. Comparison between the two sets of OGWD reveal that the horizontal propagation of mountain waves tends to decrease (increase) the OGWD in the lower stratosphere (middle to upper stratosphere and lower mesosphere). Consequently, including the horizontal propagation of mountain waves in the parameterization of OGWD can reduce the excessive OGWD in the lower stratosphere and strengthen the insufficient gravity wave forcing in the mesosphere, which are the known problems of traditional OGWD schemes. The impact of horizontal propagation is more prominent in winter than in summer, with the OGWD in western Tibetan Plateau, Rocky Mountains, and Greenland notably affected. Impact of horizontal propagation of mountain wave on wave drag in the stratosphere and lower mesosphere is evaluated using reanalysis dataHorizontal propagation reduces (enhances) the orographic wave drag in the lower stratosphere (middle to upper stratosphere and lower mesosphere)The impact of horizontal propagation is most prominent in winter, over the western Tibetan Plateau, Rocky Mountains, and Greenland

We have successfully incorporated a 3‐dimensional sub‐grid terrain solar radiative effect (3D STSRE) parameterization scheme into a convection‐permitting Weather Research and Forecasting model (WRF_CPM) in this study. Impacts of 3D STSRE scheme on the ability of WRF_CPM in forecasting the precipitation in summer over the Tibetan Plateau (TP) and nearby regions with complex terrain have been systematically addressed by conducting experiments without and with the 3D STSRE scheme. Results show that the application of 3D STSRE scheme can obviously mitigate the overestimation of surface solar radiation (SSR) and rainfall over TP and nearby regions, especially over the areas with much more rugged terrain (i.e., southern TP) in the WRF_CPM without 3D STSRE scheme. Further mechanism analyses indicate that the decreased surface heating induced by the reduction of SSR reduces the intensity of the thermal‐low pressure over the TP, which leads to the diminished strength of southwesterly winds and thereafter the weaker convergence of moisture flux over the southern TP. Moreover, the weakened surface thermal forcing makes the local atmosphere more stable, suppressing the vertical water vapor transport and local convection. These effects greatly alleviate the overestimation of precipitation over the southern TP produced by the WRF_CPM without the 3D STSRE scheme. The sub‐grid terrain solar radiative effect (STSRE) is crucial to land‐air interaction, especially over the regions with complicated terrain, such as the Tibetan Plateau (TP). While the plane‐parallel radiative scheme which neglects the STSRE on the surface solar radiation (SSR) is used in most current weather models. Inaccurate depiction of SSR would cause large biases in the surface temperature and precipitation forecast. In this study, a newly developed 3‐dimensional (3D) STSRE scheme with solid physical processes and accurate sub‐grid terrain features is introduced into a convection‐permitting Weather Research and Forecasting (WRF_CPM) model. Results indicate that the adoption of 3D STSRE scheme can reduce the overestimation of the SSR and precipitation over the TP. Findings of this work emphasize the importance of considering the STSRE in high‐resolution weather models and provide an effective way to improve the short‐range precipitation forecast over regions with complex terrain. A 3D sub‐grid terrain solar radiative effect scheme has been applied in the Weather Research and Forecasting model and its impact on weather forecast has been studiedThe 3‐dimensional sub‐grid terrain solar radiative effect reduces the overestimation of surface solar radiation, leading to the thermal low over the Tibetan Plateau weakenedThe weakened thermal low together with the more stable atmosphere reduces the overestimation of precipitation forecast over Tibetan Plateau A 3D sub‐grid terrain solar radiative effect scheme has been applied in the Weather Research and Forecasting model and its impact on weather forecast has been studied The 3‐dimensional sub‐grid terrain solar radiative effect reduces the overestimation of surface solar radiation, leading to the thermal low over the Tibetan Plateau weakened The weakened thermal low together with the more stable atmosphere reduces the overestimation of precipitation forecast over Tibetan Plateau

In the late afternoon of 19 March 2014, a severe hailstorm swept through eastern central Zhejiang province, China. The storm produced golf ball‐sized hail, strong winds, and lighting, lasting approximately 1 h over the coastal city of Taizhou. The Advanced Regional Prediction System is used to simulate the hailstorm using different configurations of the Milbrandt‐Yau microphysics scheme that predict one, two, or three moments of the hydrometeor particle size distribution. Simulated fields, including accumulated precipitation and maximum estimated hail size (MESH), are verified against rain gauge observations and radar‐derived MESH, respectively. For the case of the 19 March 2014 storms, the general evolution is better predicted with multimoment microphysics schemes than with the one‐moment scheme; the three‐moment scheme produces the best forecast. Predictions from the three‐moment scheme qualitatively agree with observations in terms of size and amount of hail reaching the surface. The life cycle of the hailstorm is analyzed, using the most skillful, three‐moment forecast. Based upon the tendency of surface hail mass flux, the hailstorm life cycle can be divided into three stages: developing, mature, and dissipating. Microphysical budget analyses are used to examine microphysical processes and characteristics during these three stages. The vertical structures within the storm and their link to environmental shear conditions are discussed; together with the rapid fall of hailstones, these structures and conditions appear to dictate this pulse storm's short life span. Finally, a conceptual model for the life cycle of pulse hailstorms is proposed. A three‐moment microphysics scheme was found to produce the best prediction of a pulse hailstorm and hailfall at surface for an east China caseHail prediction verified well against radar‐derived maximum estimated hail size (MESH) and available surface observationsHail collection of supercooled rain and cloud water dominates the hail production; a three‐stage conceptual model for pulse hailstorm life cycle is proposed

The performance of 4‐km Weather Research and Forecasting model in predicting reflectivity structure in China over three summer months is investigated using three‐dimensional (3D) reflectivity observations. Three verification domains, namely Southern China (SC), Central and Eastern China , and North China, that correspond to the three major rainfall centers of mainland China are selected. Results show that the forecasts reproduce the distribution and diurnal variation of precipitation well, but significant differences exist in the vertical distributions of the predicted and observed reflectivities. In observations, the highest frequency (of reflectivity ≥35 dBZ) occurs between 3 and 6 km, whereas it is at the surface in the forecast. The forecasts tend to over‐predict reflectivity intensity at the lower levels, especially in SC. Further evaluation using object‐based verification methods show that the forecasts greatly underestimate the afternoon peak frequency of precipitation clouds with reflectivity >30 dBZ. The forecasts fail to reproduce the diurnal variation of 35 dBZ mean and maximum height of the objects, producing less variation than observations. Analyses show that the failure in properly reproducing small‐scale reflectivity objects (with diameter <100 km) is primarily responsible for the underestimation of the mean and maximum object heights. Evaluation using additional 3D information show that the forecasts tend to produce a greater proportion of faster‐moving small‐scale objects. This study reveals that the simulation of the 3D structure of precipitation clouds in terms of reflectivity remains a great challenge, especially for smaller convective cells. The simulation of precipitation clouds is associated carries the largest uncertainty in numerical weather prediction and climate models. With continued advancement in observations and numerical models, forecasts of horizontal distribution, intensity, diurnal variation and propagation of precipitation have been greatly improved. However, faithful representation of three‐dimensional (3D) cloud structure remains a great challenge, with the lack of systematic evaluations being one of the key causes. In this study, 3D gridded radar reflectivity observations are used to evaluate the precipitation clouds structure (with reflectivity ≥30 dBZ) predicted at a convection‐permitting‐resolution (CPR) over three summer months of 2016 in China. The evaluation reveals differences between the simulated and observed reflectivity structures, including the reflectivity intensity profile, the 35 dBZ mean and maximum height, the fraction of fast‐moving objects. CPR models still have difficulties in simulating 3D reflectivity structures especially for relatively small‐scale objects (with diameter <100 km). Reflectivity structure predicted by the 4‐km Weather Research and Forecasting model are evaluated using 3D radar observationsThe model overpredicts the intensity of reflectivity at lower levels and fails to reproduce the diurnal variation of object heightThe failure to correctly reproduce the structure of smaller reflectivity objects is primarily responsible for the deviations Reflectivity structure predicted by the 4‐km Weather Research and Forecasting model are evaluated using 3D radar observations The model overpredicts the intensity of reflectivity at lower levels and fails to reproduce the diurnal variation of object height The failure to correctly reproduce the structure of smaller reflectivity objects is primarily responsible for the deviations

On 21 July 2012, an extreme rainfall event that recorded a maximum rainfall amount over 24 hours of 460 mm, occurred in Beijing, China. Most operational models failed to predict such an extreme amount. In this study, a convective-permitting ensemble forecast system (CEFS), at 4-km grid spacing, covering the entire mainland of China, is applied to this extreme rainfall case. CEFS consists of 22 members and uses multiple physics parameterizations. For the event, the predicted maximum is 415 mm d-1in the probability-matched ensemble mean. The predicted high-probability heavy rain region is located in southwest Beijing, as was observed. Ensemble-based verification scores are then investigated. For a small verification domain covering Beijing and its surrounding areas, the precipitation rank histogram of CEFS is much flatter than that of a reference global ensemble. CEFS has a lower (higher) Brier score and a higher resolution than the global ensemble for precipitation, indicating more reliable probabilistic forecasting by CEFS. Additionally, forecasts of different ensemble members are compared and discussed. Most of the extreme rainfall comes from convection in the warm sector east of an approaching cold front. A few members of CEFS successfully reproduce such precipitation, and orographic lift of highly moist low-level flows with a significantly southeasterly component is suggested to have played important roles in producing the initial convection. Comparisons between good and bad forecast members indicate a strong sensitivity of the extreme rainfall to the mesoscale environmental conditions, and, to less of an extent, the model physics.

In June after the onset of the East Asian summer monsoon season, rainfall on the south side of Hainan Island (HNI) of China exhibits a trimodal pattern with an unusual peak near noon. A typical case of 20 June 2017 is chosen to analyze the mechanisms through a convection‐permitting simulation together with rainfall observations. Clockwise rotation in low‐level winds is found at and off the coast of south HNI, leading to maximum onshore southwesterly winds in the late morning that is closely linked to the diurnal variation of rainfall. The offshore diurnal variations of low‐level winds are tracked upstream and attributed to boundary layer inertial oscillations over the inland plain of Indochina Peninsula. In addition, a short wide gap comprised mostly of hills lower than 700 m is located across the higher Annamite Range along the east coast of the Peninsula, right upstream of HNI. Nocturnal boundary layer low‐level jet (LLJ) forming over the plain passes through the gap with significant acceleration due to gap channeling and downslope flow effects, reaching peak intensity off the Peninsula coast at around 09 local standard time (LST). The enhanced LLJ propagates downstream towards HNI and impinges on the mountains at around 12 LST when rainfall reaches peak there. As the inertial‐oscillation‐indued perturbation winds approaching the Island weaken and eventually reverse direction, lifting weakens and low‐level stability increases as descending motion develops offshore. Rainfall on the southern Island therefore dissipates in late afternoon. In June after the onset of East Asian summer monsoon, rainfall on southern Hainan Island (HNI) of China has an unusual peak near noon. A representative case is numerically simulated at 2 km horizontal grid spacing and analyzed. It is found that the diurnal variation of rainfall is closely linked to diurnal variation of low‐level onshore winds which reach peak intensity around noon, and the source of such variations can be tracked upstream to the inland plain of Indochina Peninsula (ICP). Over the plain, afternoon boundary layer mixing causes low‐level wind speed minimum while boundary layer low‐level jet reaches peak speed in early morning due to inertial oscillation after the boundary layer flow becomes freed of the surface friction when mixing is shut off. The peak perturbation wind is advected toward HNI, and reaches the Island around noon. The lifting by mountains on southern HNI of the intensified low‐level winds causes peak rainfall there around noon. In the afternoon, the perturbation winds weaken and eventually reverse direction, causing dissipation of rainfall. In addition, the low‐level flow is accelerated when it passes through a gap in the coastal Annamite Range of ICP, amplifying the effect of inertial oscillations. Diurnal clockwise rotation in the low‐level winds is found to be linked to an around‐noon rainfall peak on southern Hainan Island (HNI) in JuneDownwind advection of the upstream boundary layer inertial oscillations is responsible for the around‐noon rainfall peak over HNIA gap across Annamite Range of Indochina Peninsula amplifies and transports boundary layer inertial oscillation signals downstream Diurnal clockwise rotation in the low‐level winds is found to be linked to an around‐noon rainfall peak on southern Hainan Island (HNI) in June Downwind advection of the upstream boundary layer inertial oscillations is responsible for the around‐noon rainfall peak over HNI A gap across Annamite Range of Indochina Peninsula amplifies and transports boundary layer inertial oscillation signals downstream

The traditional threat score based on fixed thresholds for precipitation verification is sensitive to intensity forecast bias. In this study, the neighborhood precipitation threat score is modified by defining the thresholds in terms of the percentiles of overall precipitation instead of fixed threshold values. The impact of intensity forecast bias on the calculated threat score is reduced. The method is tested with the forecasts of a tropical storm that re-intensified after making landfall and caused heavy flooding. The forecasts are produced with and without radar data assimilation. The forecast with assimilation of both radial velocity and reflectivity produce precipitation patterns that better match observations but have large positive intensity bias. When using fixed thresholds, the neighborhood threat scores fail to yield high scores for forecasts that have good pattern match with observations, due to large intensity bias. In contrast, the percentile-based neighborhood method yields the highest score for the forecast with the best pattern match and the smallest position error. The percentile-based method also yields scores that are more consistent with object-based verifications, which are less sensitive to intensity bias, demonstrating the potential value of percentile-based verification.

An extreme rainfall case occurred on 20 July 2016 in northern China, producing over 600 mm of maximum 24 hr accumulated rainfall. The case is characterized by low‐echo centroid (LEC) based on radar observations. It is simulated by Weather Research and Forecasting model at 4 km grid spacing using the Morrison two‐moment microphysics scheme. Infrared brightness temperature (BT) simulated using a radiative transfer model together with simulated reflectivity are used to evaluate the simulated cloud structures. In general, the model predicts the rainfall amount, location, and propagation well. However, it fails to accurately predict the three‐dimensional cloud structures. The predicted convective cores (>35 dBZ) are higher than the freezing level, suggesting the presence of active cold‐cloud processes while the observed LEC suggests that warm‐cloud processes dominate. The simulation also produces too many upper level clouds and over‐predicts the fractions of overshooting clouds, resulting great over‐prediction of cloud top height (CTH). Additionally, the sensitivity of simulated BT to predicted cloud properties including CTH, cloud species and hydrometeor effective radii are examined to better understand the sources of error in simulated BT. Among those factors, CTH is found to be most critical to BT simulation. For every kilometer of CTH over‐prediction, there is about 6.431 K of negative BT bias owing to the lapse rate and the absorption and scattering effects of cloud particles. For most cloudy regions, cloud ice dominates the effect on simulated BT. Using diagnosed effective radii of simulated hydrometeors within the radiative transfer model results in small improvement to the BT simulation. The 3D cloud structure of a severe low‐echo centroid (LEC) convection case is poorly simulated with three popular two‐moment microphysics schemesOver‐prediction of convective core heights and upper‐level cloud fraction suggest deficiencies in the microphysics schemes in simulating LECSimulated brightness temperature is most sensitive to cloud top height and vertical distribution of ice particles The 3D cloud structure of a severe low‐echo centroid (LEC) convection case is poorly simulated with three popular two‐moment microphysics schemes Over‐prediction of convective core heights and upper‐level cloud fraction suggest deficiencies in the microphysics schemes in simulating LEC Simulated brightness temperature is most sensitive to cloud top height and vertical distribution of ice particles

Dual‐polarization radars can provide rich three‐dimensional (3D) information on cloud precipitation structure. To utilize the existing polarimetric radar network in operational data assimilation systems, a new polarimetric radar‐based cloud analysis method is introduced. New features include the employment of fuzzy‐logic hydrometeor classification, improved estimation of liquid and ice regions, and newly‐added number concentration estimation. The new scheme is evaluated with a typical squall line case. Results show that the 3D cloud precipitation structure and short‐term precipitation forecast is consistently improved. With extra information from the polarimetric observations, the new scheme is able to produce reasonable polarimetric signatures for analysis. More supercooled water results in more latent heat release which enhances the updraft, leading to stronger convection in the subsequent forecast. This study emphasizes the importance of correct initial liquid and ice particle condition for the prediction of deep convection. Severe convective storms have always been one of the most the disastrous types of weather. However, due to their relatively small scale and rapid evolution, such storms are difficult to predict. Polarimetric radar networks have been established for nearly a decade and have been widely used in the monitoring and short‐term forecast of severe weather. Yet, this extra polarimetric information has not been used in the operational data assimilation system, which is key to a successful forecast. A new dual‐polarization (dual‐pol) radar‐based cloud analysis aiming to improve short‐term forecasts is therefore proposed. Results show that the new scheme is able to capture the 3D in‐cloud signature of deep convection. Consistent improvements are found for the prediction of 3D structure of deep convection and as well as for the quantitative precipitation forecast. A modified cloud analysis model is proposed for polarimetric radar data assimilationA fuzzy‐logic method combined with ZDPis used to classify hydrometeor particles, followed by a partially double‐moment retrieval schemeExperiments with polarimetric‐data‐based cloud analysis show consistent improvement on analysis and forecast A modified cloud analysis model is proposed for polarimetric radar data assimilation A fuzzy‐logic method combined with ZDPis used to classify hydrometeor particles, followed by a partially double‐moment retrieval scheme Experiments with polarimetric‐data‐based cloud analysis show consistent improvement on analysis and forecast

In a recent study, we evaluated the performance of real‐time convection‐permitting WRF model forecasting over China. Although the overall rainfall distribution and diurnal cycle are well simulated, the model greatly overestimates the rainfall intensity in southern China and the predicted rainfall shows a southeast location bias. In this study, possible factors contributing to the precipitation forecast bias are discussed. The precipitation over southern China is found to be greatly influenced by land‐sea circulations. While the model captures diurnal variations of winds well, the predicted amplitude and onset timing of the land/sea breezes differ from observations. Cold bias of land‐surface temperature is shown to partially cause wind bias. In the afternoon, the cold bias results in a weakened inland penetration of sea breeze, which in turn leads to more rain on the eastern south‐China coastline. During nighttime, excessive cooling over land results in a stronger land breeze, leading to location bias of early morning precipitation. While the observed coastal rain belt is mostly located over land during early morning, the predicted coastal rain belt is mostly located over ocean. In addition, the model overestimates moisture at low levels, especially over the southern slope of the coastal mountains and over ocean, which explains the excessive rainfall over southern China. This study emphasizes the importance of accurately simulating land‐surface‐related variables for precipitation forecast in coastal regions where land‐sea contrast plays an important role. The initiation and propagation of convection over southern China are greatly influenced by land‐sea circulationsCold bias over land results in a weaker sea breeze during the afternoon and a stronger land breeze at night, causing rainfall location biasOverprediction of moisture along the coastal mountains and over the ocean is the primary cause of excessive rainfall The initiation and propagation of convection over southern China are greatly influenced by land‐sea circulations Cold bias over land results in a weaker sea breeze during the afternoon and a stronger land breeze at night, causing rainfall location bias Overprediction of moisture along the coastal mountains and over the ocean is the primary cause of excessive rainfall

The initiation and organization of a long‐duration hail‐producing mesoscale convective system (MCS) in eastern China are investigated using convection‐allowing simulations at 3‐km grid spacing with the Advanced Regional Prediction System. The lifecycle of this MCS is characterized by two stages. In the first stage, a series of convective storms are initiated along the northwest border of Jiangsu Provinces. These storms organize into a northwest southeast line as they moved southeastward, eventually organizing into an eastward moving bow‐echo structure during the second stage. Our analyses show that the storms initiate along a northwest‐southeast oriented convergence boundary set up between two low‐level mesoscale vortices, one to the northwest of Jiangsu Province and one over the East China Sea. Comparisons between the fake‐dry and control simulations show that the rearward (westward) spreading of a cold pool from another MCS proceeding the hail‐producing MCS plays a key role in generating and enhancing the vortex over Eastern China Sea. The tilting of baroclinically generated horizontal vorticity along the edge of the cold outflow creates a cyclonic and anticyclonic vortex couplet. The cyclonic vortex becomes the dominant East China Sea vortex as it is superposed onto the background cyclonic circulation. This cold outflow‐induced vortex also has strong impacts on the later organization of the hail‐producing MCS, leading to the eventual establishment of a bow‐echo structure. Finally, a three‐stage conceptual model for the initiation and organization of the long‐lasting multicellular MCS is proposed, and the understanding on the complex interactions between two MCSs will be helpful to operational forecasters. Storm initiation occurred along a northwest‐southeast oriented convergence zone and finally organized into an MCS with a bow‐echoTwo low‐level mesoscale vortices, one overland and one over the East China Sea, set up the strong convergence zoneAn earlier MCS plays key roles in generating and enhancing the vortex over sea via baroclinic vorticity generation at the edge of its rearward spreading cold pool