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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. Plain Language Summary: 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. Key Points: 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 [ABSTRACT FROM AUTHOR]

With the development of refined numerical forecasts, problems such as score distortion due to the division of precipitation thresholds in both traditional and improved scoring methods for precipitation forecasts and the increasing subjective risk arising from the scale setting of the neighborhood spatial verification method have become increasingly prominent. To address these issues, a general comprehensive evaluation method (GCEM) is developed for cross-scale precipitation forecasts by directly analyzing the proximity of precipitation forecasts and observations in this study. In addition to the core indicator of the precipitation accuracy score (PAS), the GCEM system also includes score indices for insufficient precipitation forecasts, excessive precipitation forecasts, precipitation forecast biases, and clear/rainy forecasts. The PAS does not distinguish the magnitude of precipitation and does not delimit the area of influence; it constitutes a fair scoring formula with objective performance and can be suitable for evaluating rainfall events such as general and extreme precipitation. The PAS can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts, enabling the quantitative evaluation of the comprehensive capability of various refined precipitation forecasting products. Based on the GCEM, comparative experiments between the PAS and threat score (TS) are conducted for two typical precipitation weather processes. The results show that relative to the TS, the PAS better aligns with subjective expectations, indicating that the PAS is more reasonable than the TS. In the case of an extreme-precipitation event in Henan, China, two high-resolution models were evaluated using the PAS, TS, and fraction skill score (FSS), verifying the evaluation ability of PAS scoring for predicting extreme-precipitation events. In addition, other indices of the GCEM are utilized to analyze the range and extent of both insufficient and excessive forecasts of precipitation, as well as the precipitation forecasting ability for different weather processes. These indices not only provide overall scores similar to those of the TS for individual cases but also support two-dimensional score distribution plots which can comprehensively reflect the performance and characteristics of precipitation forecasts. Both theoretical and practical applications demonstrate that the GCEM exhibits distinct advantages and potential promotion and application value compared to the various mainstream precipitation forecast verification methods. [ABSTRACT FROM AUTHOR]

With the development of refined numerical forecasts, the problems such as the score distortion due to the division of precipitation thresholds in both traditional and improved scoring methods for precipitation forecast and the increasing subjective risk arisen from the scale setting of the neighbourhood spatial verification method have become increasingly prominent. To solve this issue, a general comprehensive evaluation method (GCEM) has been developed for cross-scale precipitation forecasts by directly analysing the proximity of precipitation forecasts and observations in this study. In addition to the core element of the precipitation forecast accuracy score (PAS) index, the GCEM system also includes score indices for insufficient precipitation forecasts, excessive precipitation forecasts, precipitation forecast biases and clear/rainy forecasts. The PAS does not distinguish the magnitude of precipitation and delimit the area of influence, it constitutes a fair scoring formula with objective performance and can be suitable for evaluating the rainfall events such as general and extreme precipitation. The PAS can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts, enabling the quantitative evaluation of the comprehensive capability of various refined precipitation forecasting products. Based on the GCEM, comparative experiments between the PAS and TS are conducted for two typical precipitation weather processes. The results show that relative to TS, the PAS aligns with subjective expectations much more, indicating that the PAS is more reasonable than the TS. In addition, other indices of the GCEM are utilized to analyse the range and extent of both insufficient and excessive forecasts of precipitation, as well as the precipitation forecast ability in two weather processes. These indices not only provide overall scores for individual cases similar to the TS but also offer two-dimensional score distribution plots, which can comprehensively reflect the performance and characteristics of precipitation forecasts. Both theoretical and practical applications demonstrate that the GCEM exhibits distinct advantages and potential promotion and application value compared to the various mainstream precipitation forecast verification methods. [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: 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. Key Points: 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 [ABSTRACT FROM AUTHOR]

The diurnal variation characteristics of precipitation in summer (June–August) during the period of 2015–2019 over the Northern Slope of the Tianshan Mountains (NSTM) was analyzed using hourly simulated data from Nanjing University's real-time forecasting system (WRF_NJU) with 4 km resolution, Automatic Weather Station (AWS) data, and the ERA5-Land data through using methods such as the Rotated Empirical Orthogonal Function (REOF) and Coefficient of Variation (CV). The results show that the diurnal variation pattern of the precipitation over the NSTM simulated by WRF_NJU aligns closely with that of the observational AWS data, and it captured spatial distribution, peak values, and the times of precipitation reasonably well. The hourly precipitation amount (PA), precipitation frequency (PF), and precipitation intensity (PI) all show characteristics of being greater in the afternoon to nighttime than from early morning to noon, and the diurnal variations of precipitation in this region are significantly influenced by altitude. The PA, PF, and PI peak over the southern edge of the Junggar Basin (JB) below 1000 m occurred at around 2200 Local Solar Time (LST). In contrast, peak PA over the mountainous regions above 3000 m occurred at around 1500 LST. Further analysis with REOF and CV indicated that the difference in diurnal variations of precipitation between the mountainous regions and the JB is most pronounced likely due to the topographical influences. The peak PA over the mountainous regions mainly occurred at around 1500 LST, while that of the JB occurred at around 0100 LST. High CV regions for PI are predominantly found over the area near the central JB and the middle Tianshan mountains, whereas high CV regions for the PF are located in the central and northern parts of Urumqi and Changji. In addition, different land surface categories exhibit distinct patterns of diurnal precipitation variation, i.e., the forests, grasslands, and water bodies exhibit their peak PA in the period from early morning to noon, while the impervious surfaces, croplands, and barren lands exhibit their peak PA in the period from afternoon to nighttime. [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: 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. Key Points: 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 [ABSTRACT FROM AUTHOR]

The diurnal variation characteristics and basic statistical features of summer precipitation (from June to August) in the Ili region from 2015 to 2019 were investigated based on 4 km resolution Weather Research and Forecasting model simulation data from Nanjing University (WRF_NJU). The results show that the overall diurnal variation characteristics of precipitation (DVCP) reflected by the WRF_NJU data were consistent with respect to the observations and reanalysis data. The total precipitation pattern exhibited high (low) values on the east (west), with higher (lower) values over the mountainous (valley) area. Hourly precipitation amount (PA), precipitation frequency (PF), and precipitation intensity (PI) show similar diurnal variation characteristics, with peaks occurring at around 1700 LST in the mountainous area and around 2000 LST in valleys. Furthermore, moderate to intense precipitation contributes up to 87.88% of the total precipitation. The peaks in the mountainous area occur earlier than the valleys, while the peaks in western part of the valleys occur earlier than the eastern part. The PA peaks over the valleys and slopes occurred from the evening to early morning and from the afternoon to evening, respectively. In addition, the rotated empirical orthogonal function (REOF) analysis implied that the DVCP exhibits distinct differences between mountainous and valleys, and peak precipitation occurs during the evening in basin– and wedge–shaped areas, while the mountain peaks and foothill regions exhibit semi–diurnal variation characteristics. Among several basic meteorological factors, the vertical velocity (VV) and water vapor mixing ratio (WVMR) provided major contributions to the DVCP in both areas with high and low coefficients of variation, and the WVMR (VV) probably played a more significant role in mountainous (valleys) areas. [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: 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. Key Points: 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 [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: 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). Key Points: 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 [ABSTRACT FROM AUTHOR]

A climatology of significant tornadoes [SIGTOR, tornadoes rated (E)F2+ on the (enhanced) Fujita scale] within China and in three subregions, including northern, central, and southern China, is first presented for the period 1980–2016. In total, 129 SIGTOR are recorded in China, with an average of 3.5 per year. The tornado inflow environments of the south-central and southeast regions of the United States (USC and USSE) are compared with those of China and its subregions based on sounding-derived parameters including shear, storm-relative helicity, convective available potential energy (CAPE), lifting condensation level (LCL), etc. Soundings are extracted from the ERA5 reanalysis dataset. The results confirm that the SIGTOR in USSE are characterized by high shear, low CAPE, and low LCL whereas those in USC are characterized by moderate-to-high shear, high CAPE, and high LCL. The thermodynamic conditions of tornadic cases are favorable for China, with moderate-to-high CAPE and low-to-moderate LCL, but their kinematic conditions are much less favorable than in the United States, a fact that is believed to be primarily responsible for the lower tornado frequency and intensity in China. The high CAPE in China is due mostly to high humidity. For three subregions in China, the central China cases account for 60% of total samples, and its environmental features are similar to those of China. The average shear with northern China cases is stronger than that with the other two subregions, and the midlayer is relatively dry. The southern China SIGTOR have the most conducive humidity conditions, but the CAPE and shear there are the lowest. The northern, central, and southern China environments can be considered as representative of midlatitude, subtropical, and tropical regions. Significance Statement: We document the climatological characteristics of significant tornadoes (SIGTOR) within China and compare the inflow environments of SIGTOR in China and its subregions with those in the U.S. central and southeastern regions. The availability of hourly high-resolution ERA5 data makes the environments based on extracted proximity soundings much more accurate than possible with earlier reanalyses. The environmental characteristics show systematic differences in the tornado environments of different regions of China and the United States and suggest different roles played by thermodynamic and kinematic conditions for tornado formation. Overall, the environmental differences are consistent with the resulting frequency and intensities of SIGTOR. The findings are helpful toward improving tornado forecasting and warning or even understanding of potential impacts of climate change on SIGTOR, especially in China, where such studies are rarer. [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: 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. Key Points: 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 [ABSTRACT FROM AUTHOR]

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. Key Points: 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 [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: 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. Key Points: A modified cloud analysis model is proposed for polarimetric radar data assimilationA fuzzy‐logic method combined with ZDP is 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 [ABSTRACT FROM AUTHOR]

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. Key Points: 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 [ABSTRACT FROM AUTHOR]

The impact of assimilating China's operational X‐band Phased‐Array radar's (X‐PAR) data on the analysis and warning forecast of the vortex structure and intensity of the June 8, 2018 Foshan, Guangdong province, tornadic storm was investigated for the first time using an Ensemble Kalman Filter (EnKF) data assimilation system. Both radar radial velocity (Vr) and reflectivity (Z) from two S‐band operational radars and one X‐PAR were assimilated. Deterministic forecasts were launched every 6 min from 05:42 UTC (20 min before the tornado touched down) to 06:00 UTC from the EnKF mean analysis field. Five experiments were conducted to examine the added capability of Z assimilation of the EnKF system, and to investigate the impact of assimilating X‐PAR data on the analysis and prediction of the tornadic storm. Compared to the experiment without Z assimilation, the assimilation of Z reduced the analysis error and greatly reduced the forecast error of Z. The assimilation of X‐PAR data greatly improved the vortex structure of the tornadic storm at low levels, and improved the intensity of the rear inflow of the tornadic storm, especially with a higher assimilation frequency. Compared to the experiments without X‐PAR data assimilation, assimilating X‐PAR data improved the predictability of tornadic storm. Plain Language Summary: Tornadoes are difficult to predict worldwide. However, the scan speed of current operational S‐band (10 cm wavelength) radar is too slow to capture the evolution of tornadoes. The newly built X‐band (3 cm wavelength) Phase‐Array radar (X‐PAR) network in Guangdong Province, China, are hopeful to fill in the gap with their higher scan frequency and higher spatial resolution, which can capture the fine‐scale structure and rapid evolution of small scale systems such as tornadic storms. This study focuses on a case where a tornado embedded within the typhoon Ewiniar was well captured by the X‐PAR network. It demonstrated for the first time the use of X‐PAR data on the prediction of a tornadic storm in China. We used ensemble‐based data assimilation techniques named Ensemble Kalman Filter to utilize the information provided by the X‐PAR data. With the improved information, the analyzed tornadic storm vortex structure at low levels was greatly improved, especially with a higher assimilation frequency. Compared to the experiments without X‐PAR data, the experiment using X‐PAR data successfully predicted the tornadic vortex a few minutes in advance. Key Points: The impact of assimilating China's X‐band Phased‐Array radar (X‐PAR) radar data on the analysis and forecast of a tornadic storm was first investigated using an Ensemble Kalman Filter systemThe assimilation of X‐PAR data helps to produce a more realistic‐looking tornadic storm structure, especially at low levelsIncreasing assimilation frequency of X‐PAR data reduces the analysis error and subsequently improves the 8‐min tornadic storm forecast [ABSTRACT FROM AUTHOR]

In numerical simulations of deep convection at kilometer-scale horizontal resolutions, in-cloud subgrid-scale (SGS) turbulence plays an important role in the transport of heat, moisture, and other scalars. By coarse graining a 50 m high-resolution large-eddy simulation (LES) of an idealized supercell storm to kilometer-scale grid spacings ranging from 250 m to 4 km, the SGS fluxes of heat, moisture, cloud, and precipitating water contents are diagnosed a priori. The kilometer-scale simulations are shown to be within the "gray zone" as in-cloud SGS turbulent fluxes are comparable in magnitude to the resolved fluxes at 4 km spacing, and do not become negligible until ~500 m spacing. Vertical and horizontal SGS fluxes are of comparable magnitudes; both exhibit nonlocal characteristics associated with deep convection as opposed to local gradient-diffusion type of turbulent mixing. As such, they are poorly parameterized by eddy-diffusivity-based closures. To improve the SGS representation of turbulent fluxes in deep convective storms, a scale-similarity LES closure is adapted to kilometer-scale simulations. The model exhibits good correlations with LES-diagnosed SGS fluxes, and is capable of representing countergradient fluxes. In a posteriori tests, supercell storms simulated with the refined similarity closure model at kilometer-scale resolutions show better agreement with the LES benchmark in terms of SGS fluxes than those with a turbulent-kinetic-energy-based gradient-diffusion scheme. However, it underestimates the strength of updrafts, which is suggested to be a consequence of the model effective resolution being lower than the native grid resolution. [ABSTRACT FROM AUTHOR]

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. Key Points: 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 [ABSTRACT FROM AUTHOR]

The impact of assimilating differential reflectivity ZDR in addition to reflectivity (ZH) and radial velocity (Vr) from a polarimetric radar on the analysis of a tornadic supercell storm using an ensemble Kalman filter (EnKF) is studied in an observing system simulation experiment (OSSE) framework assuming a perfect forecast model. A double‐moment microphysics scheme is used to allow for proper simulation of polarimetric signatures. Root‐mean‐square errors of analysed state variables are calculated and the structure and intensity of analysed fields and derived quantities are examined. Compared to the baseline experiment assimilating radial velocity and reflectivity only, the assimilation of additional ZDR further reduces the errors of all state variables. The analysed hydrometeor fields are improved in both pattern and intensity distributions. Polarimetric signatures including ZDR and KDP columns, and ZDR arc in the supercell, are much better reproduced. Sensitivity experiments are performed that exclude the updating of hydrometeor number concentrations by ZDR or of state variables not directly linked to ZDR via observation operators. The results show that if number concentrations are not updated together with the mixing ratios, most of the benefit of assimilating ZDR is lost. Among other state variables, the updating of water vapour mixing ratio qv has the largest positive impact while the impact of updating vertical wind w comes in second. The updating of horizontal wind components or temperature has a much smaller but still noticeable impact. Reliable flow‐dependent cross‐covariances among the state variables and observation prior as derived from the forecast ensemble and used in EnKF are clearly very beneficial. [ABSTRACT FROM AUTHOR]

The vertical turbulent velocity variance normalized by the convective velocity squared as a function of the boundary layer depth–normalized height [i.e., ] in the convective boundary layer (CBL) over a homogeneous surface exhibits a near-universal profile, as demonstrated by field observations, laboratory experiments, and numerical simulations. The profile holds over a wide CBL stability range set by the friction velocity, CBL depth, and surface heating. In contrast, the normalized horizontal turbulent velocity variance increases monotonically with decreasing stability. This study investigates the independence of the profile to changes in CBL stability, or more precisely, wind shear. Large-eddy simulations of several convective and neutral cases are performed by varying surface heating and geostrophic winds. Analysis of the turbulent kinetic energy budgets reveals that the conversion term between and depends almost entirely on buoyancy. This explains why does not vary with shear, which is a source to only. Further analysis through rotational and divergent decomposition suggests that the near-universal profile of is fundamentally related to the dynamics and interactions of local and nonlocal CBL turbulence. Specifically, the preferential interactions between local wavenumbers and the downscale energy cascade of CBL turbulence offer plausible explanations to the universal profile of . [ABSTRACT FROM AUTHOR]

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. Key Points: 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 [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

A grid-refinement-based method is implemented in a community atmospheric model to improve the representation of convective boundary layer (CBL) turbulence on gray-zone [i.e., ;O(1) km] grids. At this resolution, CBL convection is partially resolved and partially subgrid scale (SGS), such that neither traditional mesoscale planetary boundary layer (PBL) schemes nor SGS closures for large-eddy simulations (LESs) are appropriate. The proposed method utilizes two-way interactive nesting to refine the horizontal resolution of the unstable surface layer of the daytime CBL. SGS turbulent mixing in the fine nest and coarse parent grids are parameterized by an LES turbulence closure and a PBL scheme, respectively. The method does not rely on predetermined empirical functions to introduce grid (scale) dependency and in theory works with any PBL scheme. Compared to the stand-alone gray-zone simulation, the proposed approach shows improvements in terms of higher-order statistics, the timing of the onset of resolved convection, and the convective structures. A deficiency of the method exists when the nest domain is limited to the surface layer; the convective structures become gradually contaminated by spurious convection on the parent gray-zone grid. A deeper nest domain alleviates the issue at increased computational costs. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Compared to the representation of vertical turbulent mixing through various planetary boundary layer (PBL) schemes, the treatment of horizontal turbulent mixing in the boundary layer has received much less attention. In mesoscale and convective-scale models, subgrid-scale horizontal turbulent mixing has traditionally been associated with mesoscale circulations or eddies. Its parameterization most often adopts the gradient-diffusion model, where the horizontal mixing coefficients are usually set constant, or through the 2D Smagorinsky formulation, or in some cases based on the 1.5-order turbulence kinetic energy (TKE) closure. For horizontal turbulent mixing associated with boundary layer eddies, the traditional schemes are shown to perform poorly. This work investigates the characteristic turbulence velocity and length scales based on analysis of a well-resolved, wide-domain large-eddy simulation of a convective boundary layer (CBL). To improve the representation of horizontal turbulent mixing by CBL eddies, a class of schemes is proposed with different levels of sophistication. The first two schemes can be used together with first-order PBL schemes, while the third uses TKE to define its characteristic velocity scale and can be used together with TKE-based higher-order PBL schemes. The proposed parameterizations are tested a posteriori in idealized simulations of turbulent dispersion of a passive scalar. Comparisons show improved horizontal dispersion by the proposed schemes and further demonstrate the weakness of the existing schemes. [ABSTRACT FROM AUTHOR]

The Thematic Mapper onboard Landsat 4, 5, and Enhanced Thematic Mapper Plus (\textTM/ETM+) onboard Landsat 7 have frequency bands (green and SWIR) to effectively measure water body extents and their changes via the Modified Normalized Difference Water Index (MNDWI). Here, we developed a technique, called the thematic imagery-altimetry system (TIAS), to infer the vertical water changes from MNDWI horizontal water extent changes by integrating long-term \textTM/ETM+ imageries with available digital elevation models (DEMs). The result is a technique to quantify water level changes of natural or artificial water bodies over two decades. Several DEMs were used to compute intersects with \textTM/ETM+ water extent time series to evaluate the robustness of the technique. These DEMs include: the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Map version 2 (ASTER-GDEM2, at 1 arcsec resolution), the Shuttle Radar Topography Mission version 2 (SRTM C-band at 1 arcsec), and the Global Multiresolution Terrain Elevation Data (GMTED2010 at 7.5 arcsec). We demonstrated our technique near Hoover Dam (HD) in Lake Mead to quantify its respective decadal water level changes. The dammed water had experienced extraordinary level variation in the past 20 years due to natural decline from intake or artificial impoundments. The discrepancy of the HD water level changes from an analysis of 32-year (1984–2015) time series, including 584 Landsat scenes, using the GMTED2010 DEM, has a RMSE reached 0.85 \pm 0.63\; \textm (91% of data) as compared with in situ stage record. [ABSTRACT FROM PUBLISHER]

In recent years, traceability systems have been developed as effective tools for improving the transparency of supply chains, thereby guaranteeing the quality and safety of food products. In this study, we proposed a cattle/beef supply chain traceability model and a traceability system based on radio frequency identification (RFID) technology and the EPCglobal network. First of all, the transformations of traceability units were defined and analyzed throughout the cattle/beef chain. Secondly, we described the internal and external traceability information acquisition, transformation, and transmission processes throughout the beef supply chain in detail, and explained a methodology for modeling traceability information using the electronic product code information service (EPCIS) framework. Then, the traceability system was implemented based on Fosstrak and FreePastry software packages, and animal ear tag code and electronic product code (EPC) were employed to identify traceability units. Finally, a cattle/beef supply chain included breeding business, slaughter and processing business, distribution business and sales outlet was used as a case study to evaluate the beef supply chain traceability system. The results demonstrated that the major advantages of the traceability system are the effective sharing of information among business and the gapless traceability of the cattle/beef supply chain. [ABSTRACT FROM AUTHOR]

The radar-enhanced GSI (version 3.1) system and the WRF-ARW (version 3.4.1) model were modified to assimilate radar/lightning-proxy reflectivity. First, cloud-to-ground lightning data were converted to reflectivity using a simple assumed relationship between flash density and reflectivity. Next, the reflectivity was used in the cloud analysis of GSI to adjust the cloud/hydrometeors and moisture. Additionally, the radar/lightning-proxy reflectivity was simultaneously converted to a 3D temperature tendency. Finally, the model-calculated temperature tendencies from the explicit microphysics scheme, as well as cumulus parameterization at 3D grid points at which the radar temperature tendency is available, were updated in a forward full-physics step of diabatic digital filter initialization in the WRF-ARW. The WRF-GSI system was tested using a mesoscale convective system that occurred on June 5, 2009, and by assimilating Doppler radar and lightning data, respectively. The forecasted reflectivity with assimilation corresponded more closely to the observed reflectivity than that of the parallel experiment without assimilation, particularly during the first 6 h. After assimilation, the short-range precipitation prediction improved, although the precipitation intensity was stronger than the observed one. In addition, the improvements obtained by assimilating lightning data were worse than those from assimilating radar reflectivity over the first 3 h but improved thereafter. [ABSTRACT FROM AUTHOR]

A coupled ensemble square root filter-three-dimensional ensemble-variational hybrid (EnSRF-En3DVar) data assimilation (DA) system is developed for the operational Rapid Refresh (RAP) forecasting system. The En3DVar hybrid system employs the extended control variable method, and is built on the NCEP operational gridpoint statistical interpolation (GSI) three-dimensional variational data assimilation (3DVar) framework. It is coupled with an EnSRF system for RAP, which provides ensemble perturbations. Recursive filters (RF) are used to localize ensemble covariance in both horizontal and vertical within the En3DVar. The coupled En3DVar hybrid system is evaluated with 3-h cycles over a 9-day period with active convection. All conventional observations used by operational RAP are included. The En3DVar hybrid system is run at ⅓ of the operational RAP horizontal resolution or about 40-km grid spacing, and its performance is compared to parallel GSI 3DVar and EnSRF runs using the same datasets and resolution. Short-term forecasts initialized from the 3-hourly analyses are verified against sounding and surface observations. When using equally weighted static and ensemble background error covariances and 40 ensemble members, the En3DVar hybrid system outperforms the corresponding GSI 3DVar and EnSRF. When the recursive filter coefficients are tuned to achieve a similar height-dependent localization as in the EnSRF, the En3DVar results using pure ensemble covariance are close to EnSRF. Two-way coupling between EnSRF and En3DVar did not produce noticeable improvement over one-way coupling. Downscaled precipitation forecast skill on the 13-km RAP grid from the En3DVar hybrid is better than those from GSI 3DVar analyses. [ABSTRACT FROM AUTHOR]

Twice-daily 48-h tropical cyclone (TC) forecasts were produced for the fall 2010 Atlantic hurricane season using the Advanced Research core of the Weather Research and Forecasting (WRF-ARW) model on a large 4-km grid covering much of the northern Atlantic. WRF forecasts initialized from operational Global Forecast System (GFS) analyses based on the gridpoint statistical interpolation (GSI) three-dimensional variational data assimilation (3DVAR) system and from experimental global ensemble Kalman filter (EnKF) analyses, and corresponding global GFS forecasts were intercompared. For the track, WRF forecasts show improvement over GFS forecasts using either set of initial conditions (ICs). The EnKF-initialized GFS and WRF are also better than the corresponding GSI-initialized forecasts, but the difference is not always statistically significant. At all lead times, the WRF track errors are comparable to or smaller than the National Hurricane Center (NHC) official track forecast error, with those of the EnKF WRF being smallest. For weaker TCs, more improvement comes from the model (resolution) than from the ICs. For hurricane intensity TCs, EnKF ICs produce better track forecasts than GSI ICs, with the best forecast coming from WRF at most lead times. For intensity, EnKF ICs consistently outperform GSI ICs in both models for weaker TCs. For hurricane-strength TCs, EnKF ICs produce forecasts statistically indistinguishable from GSI ICs in either model. For all TCs combined, WRF produces about half the error of the corresponding GFS simulation beyond 24 h, and at 36 and 48 h, the errors are smaller than those from NHC official forecasts. The improvement is even greater for hurricane-strength TCs. Overall, the WRF forecasts initialized with EnKF ICs have the smallest intensity error, and the difference is statistically significant compared to the GFS forecasts. [ABSTRACT FROM AUTHOR]

A regional ensemble Kalman filter (EnKF) system is established for potential Rapid Refresh (RAP) operational application. The system borrows data processing and observation operators from the gridpoint statistical interpolation (GSI), and precalculates observation priors using the GSI. The ensemble square root Kalman filter (EnSRF) algorithm is used, which updates both the state vector and observation priors. All conventional observations that are used in the operational RAP GSI are assimilated. To minimize computational costs, the EnKF is run at ⅓ of the operational RAP resolution or about 40-km grid spacing, and its performance is compared to the GSI using the same datasets and resolution. Short-range (up to 18 h, the RAP forecast length) forecasts are verified against soundings, surface observations, and precipitation data. Experiments are run with 3-hourly assimilation cycles over a 9-day convectively active retrospective period from spring 2010. The EnKF performance was improved by extensive tuning, including the use of height-dependent covariance localization scales and adaptive covariance inflation. When multiple physics parameterization schemes are employed by the EnKF, forecast errors are further reduced, especially for relative humidity and temperature at the upper levels and for surface variables. The best EnKF configuration produces lower forecast errors than the parallel GSI run. Gilbert skill scores of precipitation forecasts on the 13-km RAP grid initialized from the 3-hourly EnKF analyses are consistently better than those from GSI analyses. [ABSTRACT FROM AUTHOR]

Wavelet-decomposition-based intensity-scale skill (ISS) score is a verification metric which decomposes the forecast fields into different scales and then calculates verification scores. However, due to the "double-penalty" issues, ISS at small scales are often very low even when the forecasts appear subjectively skillful. The displacement error is an important reason for the low ISS. To address this problem, verification methods based on a combination of neighborhood and scale-separation verification approaches are explored. Instead of calculating ISS, a neighborhood-based fractions skill score at different spatial scales, which we call IS_FSS is proposed. Additionally, to reduce the impact of intensity bias, percentile-based instead of fixed thresholds are used in IS_FSS, leading to ISP_FSS. Those two newly developed verification scores are then used to assess WRF forecasts at 4 km and 12 km grid spacings (WRF-4 and WRF-12, respectively) for a case and the entire Meiyu season of 2016. Compared to ISS scores, both IS_FSS and ISP_FSS show more positive verification scores of both WRF-4 and WRF-12 at small scales. Moreover, IS_FSS and ISP_FSS are able to differentiate WRF-12 and WRF-4 forecasts at smaller scales when ISS cannot. Both scores indicate that WRF-4 outperforms WRF-12 for spatial scales from 12 km through 96 km. The scores of WRF-12 improve more when using ISP_FSS than WRF-4, because the former has higher intensity bias. • New scale-dependent intensity-scale fractions skill scale (IS_FSS) verification metrics for precipitation are proposed. • The "double-penalty" issue with the original intensity-scale scores is alleviated by applying the neighborhood idea employed by FSS. • Both IS_FSS and percentile-based IS_FSS indicate that 4 km WRF performs better than 12 km WRF for all spatial scales examined. [ABSTRACT FROM AUTHOR]

An EF4 supercell tornado that occurred on 23 June 2016 in Funing, China is simulated using the WRF model. Five nested forecast experiments are run, with the horizontal grid spacing of the inner-most nest being 4000, 1333, 444, 148, and 49 m, respectively. All experiments reproduce the general characteristics of the observed supercell storm, but tornado-like vortex does not develop until the grid spacing is 444 m or less. The tornadoes on the 444, 148 and 49 m grids reach EF1, EF2 and EF3 intensities, respectively. The tornado vortex simulated on the 444 m grid tends to maintain a one-cell structure, while a ring of high-vorticity develops during the mature stage of the tornado vortex on the 148 m grid leading to a two-cell structure. On the 49 m grid, microscale vortices along the outflow boundary merge into and help organize the main tornado vortex while multiple 'suction vortices' develop later along the high-vorticity ring leading to a multi-vortex tornado. These sub-vortices create localized regions of intense winds due to the super-positioning of the sub-vortex and main vortex circulations and the system translation speed. Sub-vortices also create irregular strong surface wind patterns with localized 'damage cores', broadening the tornadic wind swath; these are consistent with the Funing tornado damage survey. Based on the results, we recommend a horizontal grid spacing of at least 500 m for real-time warn-on-forecast applications in order to capture tornado-like vortices while for tornado dynamics, prediction and predictability studies 50 m or less is recommended. • An EF4 tornado in eastern China is successfully simulated from 3D initial conditions. • A tornado-like vortex is simulated only at grid spaces 444 m or smaller. • The tornado reaches EF2 and EF3 intensities on the 148 and 49 m grids, respectively. • The 49 m grid spacing is needed to resolve sub-vortices in the main tornado vortex. • The sub-vortices in the 49 m simulation strongly affect surface wind speeds. [ABSTRACT FROM AUTHOR]

Introduction: Soil salinization is a serious abiotic stress for grapevines. The rhizosphere microbiota of plants can help counter the negative effects caused by salt stress, but the distinction between rhizosphere microbes of salt-tolerant and salt-sensitive varieties remains unclear., Methods: This study employed metagenomic sequencing to explore the rhizosphere microbial community of grapevine rootstocks 101-14 (salt tolerant) and 5BB (salt sensitive) with or without salt stress., Results and Discussion: Compared to the control (treated with ddH 2 O), salt stress induced greater changes in the rhizosphere microbiota of 101-14 than in that of 5BB. The relative abundances of more plant growth-promoting bacteria, including Planctomycetes, Bacteroidetes, Verrucomicrobia, Cyanobacteria, Gemmatimonadetes, Chloroflexi, and Firmicutes, were increased in 101-14 under salt stress, whereas only the relative abundances of four phyla (Actinobacteria, Gemmatimonadetes, Chloroflexi, and Cyanobacteria) were increased in 5BB under salt stress while those of three phyla (Acidobacteria, Verrucomicrobia, and Firmicutes) were depleted. The differentially enriched functions (KEGG level 2) in 101-14 were mainly associated with pathways related to cell motility; folding, sorting, and degradation functions; glycan biosynthesis and metabolism; xenobiotics biodegradation and metabolism; and metabolism of cofactors and vitamins, whereas only the translation function was differentially enriched in 5BB. Under salt stress, the rhizosphere microbiota functions of 101-14 and 5BB differed greatly, especially pathways related to metabolism. Further analysis revealed that pathways associated with sulfur and glutathione metabolism as well as bacterial chemotaxis were uniquely enriched in 101-14 under salt stress and therefore might play vital roles in the mitigation of salt stress on grapevines. In addition, the abundance of various sulfur cycle-related genes, including genes involved in assimilatory sulfate reduction ( cysNC , cysQ , sat , and sir ), sulfur reduction ( fsr ), SOX systems ( soxB ), sulfur oxidation ( sqr ), organic sulfur transformation ( tpa , mdh , gdh , and betC ), increased significantly in 101-14 after treatment with NaCl; these genes might mitigate the harmful effects of salt on grapevine. In short, the study findings indicate that both the composition and functions of the rhizosphere microbial community contribute to the enhanced tolerance of some grapevines to salt stress., Competing Interests: KZ was affiliated with Huaian Herong Ecological Agriculture Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wang, Wang, Wang, Zhu and Wu.)