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FU DONG, XIEFEI ZHI, LING ZHANG, and CHENGZHI YE

Abstract

The diurnal variations of coastal boundary layer jets (CBLJs) over the northern South China Sea (SCS) and their effects on the diurnal cycle of rainfall over southern China during the early-summer rainy season of 2010–2016 are examined based on the merged hourly gauge and satellite rainfall dataset, ERA5 reanalysis data and numerical simulations. CBLJs over the northern SCS exhibit two high-frequency regions with different diurnal cycles: one shows a nocturnal peak, located at the Beibu Gulf (WCBLJ); the other shows a double peak in the early morning and late afternoon, located over the coastal area of Guangdong (ECBLJ). Both of CBLJs are occurred more frequently near Hainan Island. The inertial oscillations triggered by the land–sea thermal contrast, dynamic effects of Hainan Island and effects of mountains over Vietnam are mainly attributed to the nocturnal WCBLJs, whereas the inertial oscillations induced by the large-scale sea breezes are responsible for nocturnal ECBLJs. The formation of afternoon ECBLJs mainly result from the thermal effects of Hainan Island. Nocturnal and morning rainfall over southern China are pronounced near the coast and the windward slope, while the afternoon rainfall peaks over the inland region in Guangdong Province. Due to dynamically forced lifting and moisture transport, WCBLJs and ECBLJs are essential for the formation of nocturnal and morning rainfall over Guangxi and Guangdong Province, respectively. In addition to the effects of solar heating, the afternoon rainfall over inland Guangdong is mainly affected by the ECBLJs and eastward-propagating rainfall belts from Guangxi Province, which are highly related to the occurrence of WCBLJs.

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Stacey M. Hitchcock, Todd P. Lane, Robert A. Warren, and Joshua S. Soderholm

Abstract

Linear precipitation systems are a prominent contributor to rainfall over Melbourne, Australia and the surrounding region. These systems are often convective in nature, frequently associated with cold fronts, and in some cases can lead to significant rainfall and flash flooding. Various types of linearly organized systems (e.g. squall lines, quasi-linear convective systems) have been the subject of much research in the US and elsewhere, but thus far relatively little analysis has been done on linear systems in Australia. In order to begin to understand rainfall extremes and how they may change in this region in the future, it is useful to explore the contribution of these types of systems and the characteristics that define them. To this end, we have examined the recently developed Australian Radar Archive (AURA), identifying objects that meet a specific set of relevant criteria, and used multiple methods to identify heavy and extreme daily rainfall. We found that on average, days with linear systems contribute over half of the total rainfall and 70-85% of heavy/extreme rainfall in the Melbourne region. The linear systems that occur on heavy rainfall days tend to be larger, slower-moving, and longer-lived, while those on extreme rainfall days also tend to be more intense and have a greater degree of southward propagation than linear systems on other days.

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Ruoyun Ma, Jianhua Sun, and Xinlin Yang

Abstract

The present work established a 7-yr climatology of the initiation, decay, and morphology of severe convective storms (SCSs) during the warm seasons (May–September) of 2011–18 (except 2014) over North China. This was achieved by using severe weather reports, precipitation observations, and composite Doppler radar reflectivity data. A total of 371 SCSs were identified. SCSs primarily initiated around noon with the highest frequency over the high terrain of Mount Taihang, and they mostly decayed over the plains at night. The storm morphologies were classified into three types of cellular storms (individual cells, clusters of cells, and broken lines), six types of linear systems (convective lines with no stratiform, with trailing stratiform, leading stratiform, parallel stratiform, embedded lines, and bow echoes), and nonlinear systems. Three types of severe convective weather, namely, short-duration heavy rainfall, hail, and thunderstorm high winds, associated with these morphologies were investigated. A total of 1429 morphology samples from the 371 SCSs were found to be responsible for 15 966 severe convective weather reports. Nonlinear systems were the most frequent morphology, followed by clusters of cells. Convective lines with trailing stratiform were the most frequent linear morphology. Linear (nonlinear) systems produced the most short-duration heavy rainfall (hail and thunderstorm high wind) reports. Bow echoes were most efficient in producing both short-duration heavy rainfall and thunderstorm high wind reports whereas broken lines had the highest efficiency for hail production. The results in the present study are helpful for local forecasters to better anticipate the storm types and associated hazardous weather.

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Yongming Wang and Xuguang Wang

Abstract

A convective-scale static background-error covariance (BEC) matrix is further developed to include the capability of direct reflectivity assimilation and evaluated within the GSI-based three-dimensional variational (3DVar) and hybrid ensemble–variational (EnVar) methods. Specific developments are summarized as follows: 1) Control variables (CVs) are extended to include reflectivity, vertical velocity, and all hydrometeor types. Various horizontal momentum and moisture CV options are included. 2) Cross correlations between all CVs are established. 3) A storm intensity-dependent binning method is adopted to separately calculate static error matrices for clear-air and storms with varying intensities. The resultant static BEC matrices are simultaneously applied at proper locations guided by the observed reflectivity. 4) The EnVar is extended to adaptively incorporate static BECs based on the quality of ensemble covariances. Evaluation and examination of the new static BECs are first performed on the 8 May 2003 Oklahoma City supercell. Detailed diagnostics and 3DVar examinations suggest zonal/meridional winds and pseudo–relative humidity are selected as horizontal momentum and moisture CVs for direct reflectivity assimilation, respectively; inclusion of cross correlations favors spin up and maintains the analyzed storms; application of binning improves characteristics and persistence of the simulated storm. Relative to an experiment using the full ensemble BECs (Exp-PureEnVar), incorporating static BECs in hybrid EnVar reduces spinup time and better analyzes reflectivity distributions while the background ensemble is deficient in sampling errors. Compared to both pure 3DVar and Exp-PureEnVar, hybrid EnVar better predicts reflectivity distributions and better maintains a strong mesocyclone. Further examination through the 20 May 2013 Oklahoma supercells confirms these results and additionally demonstrates the effectiveness of adaptive hybridization.

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Rachel E. Gutierrez and Matthew R. Kumjian

Abstract

Storms that produce gargantuan hail (defined here as ≥6 in. or 15 cm in maximum dimension), although seemingly rare, can cause extensive damage to property and infrastructure, and cause injury or even death to humans and animals. Currently, we are limited in our ability to accurately predict gargantuan hail and detect gargantuan hail on radar. In this study, we analyze the environmental and radar characteristics of gargantuan hail–producing storms to define the parameter space of environments in which gargantuan hail occurs, and compare environmental parameters and radar signatures in these storms to storms producing other sizes of hail. We find that traditionally used environmental parameters used for severe storm prediction, such as most unstable convective available potential energy (MUCAPE) and 0–6-km vertical wind shear, display considerable overlap between gargantuan hail–producing storm environments and those that produce smaller hail. There is a slight tendency for larger MUCAPE values for gargantuan hail cases, however. Additionally, gargantuan hail–producing storms seem to have larger low-level storm-relative winds and larger updraft widths than those storms producing smaller hail, implying updrafts less diluted by entrainment and perhaps maximizing the liquid water content available for hail growth. Moreover, radar reflectivity or products derived from it are not different from cases of smaller hail sizes. However, inferred mesocyclonic rotational velocities within the hail growth region of storms that produce gargantuan hail are significantly stronger than the rotational velocities found for smaller hail categories.

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Richard B. Bagley and Craig B. Clements

Abstract

The second largest fire shelter deployment in U.S. history occurred in August 2003 during the Devil Fire, which was burning in a remote and rugged region of the San Francisco Bay Area, when relative humidity abruptly dropped in the middle of the night, causing rapid fire growth. Nocturnal drying events in the higher elevations along California’s central coast are a unique phenomenon that poses a great risk to wildland firefighters. Single-digit relative humidity with dewpoints below −25°C is not uncommon during summer nights in this region. To provide the fire management community with knowledge of these hazardous conditions, an event criterion was established to develop a climatology of nocturnal drying and to investigate the synoptic patterns associated with these events. A lower-tropospheric source region of dry air was found over the northeastern Pacific Ocean corresponding to an area of maximum low-level divergence and associated subsidence. This dry air forms above a marine inversion and advects inland overnight with the marine layer and immerses higher-elevation terrain with warm and dry air. An average of 15–20 nocturnal drying events per year occur in elevations greater than 700 m in the San Francisco Bay Area, and their characteristics are highly variable, making them a challenge to forecast.

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M. Hagman, G. Svensson, and W. M. Angevine

Abstract

The Swedish Armed Forces configuration of the Weather Research and Forecasting (WRF) Model has problems in forecasting low clouds in stably stratified conditions when the ground is covered by snow. Reforecasts for January and February 2018, together with observations from Sodankylä in northern Finland, are analyzed to find the cause. The investigation is done iteratively between the single-column model (SCM), applied at Sodankylä, and the full 3D version. Our experiments show that the forecast error arises due to inadequate initialization of stratocumulus (Sc) clouds in WRF using the ECMWF global model, Integrated Forecasting System (IFS). By including bulk liquid water and bulk ice water content, from IFS in the initial profile, the downwelling longwave radiation increases and prevents the near-surface temperature from dropping abnormally. This, in turn, prevents artificial clouds from forming at the first model level. When no clouds are present in the IFS initial profile, the Sc clouds can be initialized using information from the observed vertical profiles. Generally, initialization of Sc clouds in WRF improves the forecast substantially.

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Yawen Shao, Quan J. Wang, Andrew Schepen, and Dongryeol Ryu

Abstract

For managing climate variability and adapting to climate change, seasonal forecasts are widely produced to inform decision-making. However, seasonal forecasts from global climate models are found to poorly reproduce temperature trends in observations. Furthermore, this problem is not addressed by existing forecast postprocessing methods that are needed to remedy biases and uncertainties in model forecasts. The inability of the forecasts to reproduce the trends severely undermines user confidence in the forecasts. In our previous work, we proposed a new statistical postprocessing model that counteracted departures in trends of model forecasts from observations. Here, we further extend this trend-aware forecast postprocessing methodology to carefully treat the trend uncertainty associated with the sampling variability due to limited data records. This new methodology is validated on forecasting seasonal averages of daily maximum and minimum temperatures for Australia based on the SEAS5 climate model of the European Centre for Medium-Range Weather Forecasts. The resulting postprocessed forecasts are shown to have proper trends embedded, leading to greater accuracy in regions with significant trends. The application of this new forecast postprocessing is expected to boost user confidence in seasonal climate forecasts.

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Charles N. Helms and Lance F. Bosart

Abstract

On 4–5 September 2013, a relatively shallow layer of northerly dry airflow was observed just west of the core deep convection associated with the low-level center of the pre-Gabrielle (2013) tropical disturbance. Shortly thereafter, the core deep convection of the disturbance collapsed after having persisted for well over 24 h. The present study provides an in-depth analysis of the interaction between this dry airflow layer and the pre-Gabrielle disturbance core deep convection using a combination of observations, reanalysis fields, and idealized simulations. Based on the analysis, we conclude that the dry airflow layer played an important role in the collapse of the core deep convection in the pre-Gabrielle disturbance. Furthermore, we found that the presence of storm-relative flow was critical to the inhibitive effects of the dry airflow layer on deep convection. The mechanism by which the dry airflow layer inhibited deep convection was found to be enhanced dry air entrainment.

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Yunhee Kang, Jong-Hoon Jeong, and Dong-In Lee

Abstract

An extreme-rainfall-producing linear mesoscale convective system (MCS) occurred over the Yellow Sea, Korea, on 13 August 2012, producing 430 mm of rainfall in less than 12 h, causing devastating flash floods and landslides. To understand the causative processes underlying this event, we examined the linear MCS’s formation and development mechanisms using observations and cloud-resolving models. The organized linear MCS produced extreme rainfall at Gunsan in a favorable large-scale environment. The synoptic environment showed the stationary surface front elongating from China to Korea; a southwesterly low-level jet transported the warm, moist air from low latitudes toward the front. In the upper-level synoptic environment, the trough and entrance regions of the upper-level jet were north of the heavy rainfall, promoting the development of convection. The extreme rainfall over the Gunsan area resulted from the back-building mode of the MCS, in which new convective cells continued to pass over the same area while the entire convective system was nearly stationary. The sea surface temperature (SST) during the extreme rainfall events was abnormally 1°C higher than the 30-yr climatological mean, and a local warm pool (>28.5°C) existed where the convective cells were continuously initiated. Cloud-resolving models simulated the low-level convergence, and the latent heat flux was large in the local warm SST field. These induced MCS formation and development, contributing to a significant rainfall increase over the Yellow Sea. The terrain’s influence on the large rainfall amount in the area was also noted.

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