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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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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.

Open access
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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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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James N. Marquis, Adam C. Varble, Paul Robinson, T. Connor Nelson, and Katja Friedrich

Abstract

Data from scanning radars, radiosondes, and vertical profilers deployed during three field campaigns are analyzed to study interactions between cloud-scale updrafts associated with initiating deep moist convection and the surrounding environment. Three cases are analyzed in which the radar networks permitted dual-Doppler wind retrievals in clear air preceding and during the onset of surface precipitation. These observations capture the evolution of (i) the mesoscale and boundary layer flow, and (ii) low-level updrafts associated with deep moist convection initiation (CI) events yielding sustained or short-lived precipitating storms. The elimination of convective inhibition did not distinguish between sustained and unsustained CI events, though the vertical distribution of convective available potential energy may have played a role. The clearest signal differentiating the initiation of sustained versus unsustained precipitating deep convection was the depth of the low-level horizontal wind convergence associated with the mesoscale flow feature triggering CI, a sharp surface wind shift boundary, or orographic upslope flow. The depth of the boundary layer relative to the height of the LFC failed to be a consistent indicator of CI potential. Widths of the earliest detectable low-level updrafts associated with sustained precipitating deep convection were ~3–5 km, larger than updrafts associated with surrounding boundary layer turbulence (~1–3 km wide). It is hypothesized that updrafts of this larger size are important for initiating cells to survive the destructive effects of buoyancy dilution via entrainment.

Open access
Kristofer S. Tuftedal, Michael M. French, Darrel M. Kingfield, and Jeffrey C. Snyder

Abstract

The time preceding supercell tornadogenesis and tornadogenesis “failure” has been studied extensively to identify differing attributes related to tornado production or lack thereof. Studies from the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX) found that air in the rear-flank downdraft (RFD) regions of non- and weakly tornadic supercells had different near-surface thermodynamic characteristics than that in strongly tornadic supercells. Subsequently, it was proposed that microphysical processes are likely to have an impact on the resulting thermodynamics of the near-surface RFD region. One way to view proxies to microphysical features, namely, drop size distributions (DSDs), is through use of polarimetric radar data. Studies from the second VORTEX used data from dual-polarization radars to provide evidence of different DSDs in the hook echoes of tornadic and nontornadic supercells. However, radar-based studies during these projects were limited to a small number of cases preventing result generalizations. This study compiles 68 tornadic and 62 nontornadic supercells using Weather Surveillance Radar–1988 Doppler (WSR-88D) data to analyze changes in polarimetric radar variables leading up to, and at, tornadogenesis and tornadogenesis failure. Case types generally did not show notable hook echo differences in variables between sets, but did show spatial hook echo quadrant DSD differences. Consistent with past studies, differential radar reflectivity factor (Z DR) generally decreased leading up to tornadogenesis and tornadogenesis failure; in both sets, estimated total number concentration increased during the same times. Relationships between DSDs and the near-storm environment, and implications of results for nowcasting tornadogenesis, also are discussed.

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Alex D. Crawford, Erika A. P. Schreiber, Nathan Sommer, Mark C. Serreze, Julienne C. Stroeve, and David G. Barber

Abstract

Lagrangian detection and tracking algorithms are frequently used to study the development, distribution, and trends of extratropical cyclones. Past research shows that results from these algorithms are sensitive to both spatial and temporal resolutions of the gridded input fields, with coarser resolutions typically underestimating cyclone frequency by failing to capture weak, small, and short-lived systems. The fifth-generation atmospheric reanalysis from the European Centre for Medium-Range Weather Forecasts (ERA5) offers finer resolution, and, therefore, more precise information regarding storm locations and development than previous global reanalyses. However, our sensitivity tests show that using ERA5 sea level pressure fields at their finest-possible resolution does not necessarily lead to better cyclone detection and tracking. If a common number of nearest neighbors is used when detecting minima in sea level pressure (like past studies), finer spatial resolution leads to noisier fields that unrealistically break up multicenter cyclones. Using a common search distance instead (with more neighbors at finer resolution) resolves the issue without smoothing inputs. Doing this also makes cyclone frequency, life span, and average depth insensitive to refining spatial resolution beyond 100 km. Results using 6- and 3-h temporal resolutions have only minor differences, but using 1-h temporal resolution with a maximum allowed propagation speed of 150 km h−1 leads to unrealistic track splitting. This can be counteracted by increasing the maximum propagation speed, but modest sensitivity to temporal resolution persists for several cyclone characteristics. Therefore, we recommend caution if applying existing algorithms to temporal resolutions finer than 3 h and careful evaluation of algorithm settings.

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Peter N. Blossey, Christopher S. Bretherton, and Johannes Mohrmann

Abstract

The goal of this study is to challenge a large-eddy simulation model with a range of observations from a modern field campaign and to develop case studies useful to other modelers. The 2015 Cloud System Evolution in the Trades (CSET) field campaign provided a wealth of in situ and remote sensing observations of subtropical cloud transitions in the summertime northeast Pacific. Two Lagrangian case studies based on these observations are used to validate the thermodynamic, radiative, and microphysical properties of large-eddy simulations (LES) of the stratocumulus to cumulus transition. The two cases contrast a relatively fast cloud transition in a clean, initially well-mixed boundary layer versus a slower transition in an initially decoupled boundary layer with higher aerosol concentrations and stronger mean subsidence. For each case, simulations of two neighboring trajectories sample mesoscale variability and the coherence of the transition in adjacent air masses. In both cases, LES broadly reproduce satellite and aircraft observations of the transition. Simulations of the first case match observations more closely than for the second case, where simulations underestimate cloud cover early in the simulations and overestimate cloud top height later. For the first case, simulated cloud fraction and liquid water path increase if a larger cloud droplet number concentration is prescribed. In the second case, precipitation onset and inversion cloud breakup occur earlier when the LES domain is chosen to be large enough to support strong mesoscale organization.

Open access