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Hongpei Yang
and
Yu Du

Abstract

During the development of squall lines, low-frequency gravity waves exhibit contrasting behaviors behind and ahead of the system, corresponding to its low-level upshear and downshear sides, respectively. This study employed idealized numerical simulations to investigate how low-level shear and tilted convective heating influence waves during two distinct stages of squall-line evolution. In the initial stage, low-level shear speeds up upshear waves, while it has contrasting effects on the amplitudes of different wave modes, distinguishing it from the Doppler effect. Downshear deep tropospheric downdraft (n = 1 wave) exhibits larger amplitudes, resulting in strengthened low-level inflow and upper-level outflow. However, n = 2 wave with low-level ascent and high-level descent has higher amplitude upshear and exhibits a higher altitude of peak w values downshear, leading to the development of a more extensive upshear low-level cloud deck and a higher altitude of downshear cloud deck. In the mature stage, as the convective updraft greatly tilts rearward (upshear), stronger n = 1 waves occur behind the system, while downshear-propagating n = 2 waves exhibit larger amplitudes. These varying wave behaviors subsequently contribute to the storm-relative circulation pattern. Ahead of the squall line, stronger n = 2 waves and weaker n = 1 waves produce intense outflow concentrated at higher altitudes, along with moderate midlevel inflow and weak low-level inflow. Conversely, behind the system, the remarkable high pressure in the upper troposphere and wake low are attributed to more intense n = 1 waves. Additionally, the cloud anvil features greater width and depth rearward and is situated at higher altitudes ahead of the system due to the joint effects of n = 1 and n = 2 waves.

Significance Statement

Squall lines are a significant source of high-impact weather events, and their development has been partially explained through linear wave dynamics. While the recurrent generation of waves during squall-line evolution has been found, the differentiation of wave behavior behind and ahead of the system, as well as its implications for storm circulation, has remained unclear. This study employs idealized simulations to reveal that during different stages of convection, low-level shear and the tilting of convective heating exert contrasting effects on wave behaviors. Moreover, various wave modes exhibit distinct responses to specific factors, and their combined effect elucidates the structural discrepancies observed both rearward and forward of the convective updraft. These findings could allow a step toward a better understanding of the intricate interaction between waves and convections.

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Francesco De Martin
,
Silvio Davolio
,
Mario Marcello Miglietta
, and
Vincenzo Levizzani

Abstract

The Po Valley in northern Italy is a hotspot for tornadoes in Europe in spite of being surrounded by two mountain ridges: the Alps in the north and the Apennines in the southwest. The research focuses on the case study of 19 September 2021, when seven tornadoes (four of them rated as F2) developed in the Po Valley in a few hours. The event was analyzed using observations and numerical simulations with the convection-permitting Modello Locale in Hybrid Coordinates (MOLOCH) model. Observations show that during the event in the Po Valley, there were two surface boundaries that created a triple point: an outflow boundary generated by convection triggered in the Alpine foothills and a dryline generated by downslope winds from the Apennines, while warm and moist air advected westward from the Adriatic Sea east (ahead) of the boundaries. Tornadoes developed about 20 km northeast of the triple point. Numerical simulations with 500-m grid spacing suggest that the development of supercells and drylines in the Po Valley was sensitive to the elevation of the Apennines. Simulated vertical profiles show that the best combination of instability and wind shear for the development of tornadoes was attained within a narrow area located ahead of the dryline. A conceptual model for the development of tornadoes in the Po Valley is proposed, and the differences between tornado environments over a flat terrain and over a region with complex terrain are discussed.

Significance Statement

The Po Valley is a highly populated area where some of the most violent tornadoes in Europe have developed. We investigated a tornado outbreak that occurred on 19 September 2021 in this region, in order to identify its main environmental characteristics. High-resolution numerical simulations revealed that values of instability and wind shear were compatible with the development of several tornadoes only in a narrow area close to the intersection of two surface boundaries (a triple point). Moreover, the atmospheric environment during the tornado outbreak was strongly influenced by the presence of mountain ridges surrounding the plain. We have summarized our results in a conceptual model that can potentially be used for forecasting applications.

Open access
Yu-Chieng Liou
,
Tzu-Jui Chou
,
Yu-Ting Cheng
, and
Yung-Lin Teng

Abstract

This study presents a sequential procedure formulated by combining a multiple-Doppler radar wind synthesis technique with a thermodynamic retrieval method, which can be applied to retrieve the three-dimensional wind, pressure, temperature, rainwater mixing ratio, and moisture over complex terrain. The retrieved meteorological state variables are utilized to reinitialize a high-resolution numerical model, which then carries out time integration using four different microphysical (MP) schemes, including the Goddard Cumulus Ensemble (GCE), Morrison (MOR), WRF single-moment 6-class (WSM6), and WRF double-moment 6-class (WDM6) schemes. It is found that through this procedure, the short-term quantitative precipitation forecast (QPF) skill of a numerical model over mountainous areas can be significantly improved up to 6 h. The moisture field plays a crucial role in producing the correct rainfall forecast. Since no specific microphysical scheme outperforms the others, a combination of various rainfall scenarios forecasted by different MP schemes is suggested in order to provide a stable and reliable rainfall forecast. This work also demonstrates that, with the proposed approach, radar data from only two volume scans are sufficient to improve the rainfall forecasts. This is because the unobserved meteorological state variables are instantaneously retrieved and directly used to reinitialize the model, thereby the model spinup time can be effectively shortened.

Open access
Yaodeng Chen
,
Hong Zheng
,
Tao Sun
,
Deming Meng
,
Luyao Qin
, and
Jinfang Yin

Abstract

On 20–21 July 2021, a record-breaking rainfall event occurred in Henan Province, China, and a maximum hourly accumulated precipitation of 201.9 mm was recorded at Zhengzhou Meteorological Station. To improve the prediction of such extreme rainfall and to better understand the impacts of the radar reflectivity assimilation on forecasting, we assimilated radar reflectivity data using the hydrometeor background error covariance (HBEC) that includes vertical and multivariate correlations and then diagnosed the dynamic, thermal, and microphysical forecasts of this event. The results show that the radar reflectivity assimilation based on the HBEC properly transferred the observed radar reflectivity to the analysis of hydrometeors and other model states, and clearly improved the heavy rainfall forecast. The diagnosis of the dynamic and thermal forecasts indicated that the reflectivity assimilation based on the HBEC improved the convective environments of the precipitation systems, with stronger cold pools near the surface and deeper and wetter updrafts near Zhengzhou station, when compared with the experiment that did not assimilate radar reflectivity and the experiment that assimilated radar reflectivity without using the HBEC. The diagnosis of the microphysical forecasts further shows that assimilating reflectivity data using HBEC contributed to higher conversion rates of water vapor and cloud water to graupel and higher conversion rates of graupel and cloud water to rainwater, when compared with the other experiments. These improvements of both convective environments and microphysical processes within the convections ultimately enhanced the forecasts of this extreme rainfall event.

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Matthew C. Brown
,
Geoffrey R. Marion
, and
Michael C. Coniglio

Abstract

Observational and modeling efforts have explored the formation and maintenance of mesovortices, which contribute to severe hazards in quasi-linear convective systems (QLCS). There exists an important interplay between environmental shear and cold pool-induced circulations which, when balanced, allow for upright QLCS updrafts with maximized lift along storm outflow boundaries. Numerical simulations have primarily tested the sensitivity of squall lines to zonally-varying low-level (LL) shear profiles (i.e., purely line-normal, assuming a north-south oriented system), but observed near-storm environments of mesovortex-producing QLCSs exhibit substantial LL hodograph curvature (i.e., line-parallel shear). Therefore, previous QLCS simulations may fail to capture the full impacts of LL shear variability on mesovortex characteristics. To this end, this study employs an ensemble of idealized QLCS simulations with systematic variations in the orientation and magnitude of the ambient LL shear vector, all while holding 0–3-km line-normal shear constant. This allows for a nuanced examination of how line-parallel shear modulates system structure, as well as mesovortex strength, size, and longevity. Results indicate that hodographs with LL curvature support squall lines with prominent bowing segments and wider, more intense rotating updrafts. Shear orientation also impacts mesovortex characteristics, with curved hodographs favoring cyclonic vortices that are stronger, wider, deeper and longer-lived than those produced with straight-line wind profiles. These results provide a more complete physical understanding of how LL shear variability influences the generation of rotation in squall lines.

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R. M. Samelson
,
S. M. Durski
,
D. B. Chelton
,
E. D. Skyllingstad
, and
P. L. Barbour

Abstract

The dependence of surface-current damping on the definition of surface current for the relative wind is examined in coupled ocean-atmosphere numerical simulations of the northern California Current System (nCCS) during March through October 2009. The model response is analyzed for wind stress computed from relative wind for six different choices of effective model surface velocity. Simulations without surface-current coupling are also considered. As a function of the geographically varying uppermost grid-level depth, the model uppermost grid-level velocity is found to have a wind-drift component with a log-layer structure. Mean geostrophic wind work is concentrated in the shelf and slope regions during March through May (MAM) and in the deep offshore region in June through September (JJAS). The surface-current damping effect on ocean kinetic energy depends more strongly on the parameterization of atmospheric planetary boundary layer (PBL) turbulence than on the surface-current coupling formulation: weaker PBL mixing gives stronger surface-current damping. The damping effect is stronger in the less energetic, offshore region than in the more energetic region closer to the coast. During MAM, the changes in kinetic energy and geostrophic wind-work in the shelf and slope regions are spatially correlated, while during JJAS, the changes in geostrophic wind-work are strongly modulated by SST-stress coupling. The wind-drift-corrected surface-current formulations result in large changes in the effective wind-work based on the product of stress and relative-wind surface current but in only small changes in the kinetic energy of the circulation.

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Christopher M. Hartman
,
Falko Judt
, and
Xingchao Chen

Abstract

Tropical cyclone formation is known to require abundant water vapor in the lower to middle troposphere within the incipient disturbance. In this study, we assess the impacts of local water vapor analysis uncertainty on the predictability of the formation of Hurricane Irma (2017). To this end, we reduce the magnitude of the incipient disturbance’s water vapor perturbations obtained from an ensemble-based data assimilation system that constrained moisture by assimilating all-sky infrared and microwave radiances. Five-day ensemble forecasts are initialized two days before genesis using each set of modified analysis perturbations. Growth of convective differences and intensity uncertainty are evaluated for each ensemble forecast. We observe that when initializing an ensemble forecast with only moisture uncertainty within the incipient disturbance, the resulting intensity uncertainty at every lead time exceeds half that of an ensemble containing initial perturbations to all variables throughout the domain. Although ensembles with different initial moisture uncertainty amplitudes reveal a similar pathway to genesis, uncertainty in genesis timing varies substantially across ensembles since moister members exhibit earlier spinup of the low-level vortex. These differences in genesis timing are traced back to the first 6–12 h of integration, when differences in the position and intensity of mesoscale convective systems across ensemble members develop more quickly with greater initial moisture uncertainty. In addition, the rapid growth of intensity uncertainty may be greatly modulated by the diurnal cycle. Ultimately, this study underscores the importance of targeting the incipient disturbance with high spatiotemporal water vapor observations for ingestion into data assimilation systems.

Significance Statement

Hurricanes form from clusters of thunderstorms that organize into a coherent system. One of the key ingredients for the formation process is an abundance of moisture. In this study, we test the sensitivity of hurricane formation to the initial moisture content in the vicinity of the cluster of thunderstorms that would become Hurricane Irma (2017). To do so, we initialize sets of forecasts each having a different variability of initial moisture content within the embryonic disturbance. Our results show that the predictability of hurricane formation is highly dependent on the uncertainty of the moisture content within the initial disturbance. Consequently, more high-quality observations of the moisture within the precursor disturbances to hurricanes are expected to improve forecasts of their formation.

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Carly R. Tozer
,
James S. Risbey
,
Michael J. Pook
,
Didier P. Monselesan
,
Damien Irving
,
Nandini Ramesh
, and
Doug Richardson

Abstract

Despite common background La Niña conditions, Australia was very dry in November 2020 and wet in November 2021. This paper aims to provide an explanation for this difference. Large-scale drivers of Australian rainfall, including the El Niño Southern Oscillation, Indian Ocean Dipole, Southern Annular Mode and Madden Julian Oscillation, were examined but did not provide obvious clues for the differences. We found that the absence (in 2020) or presence (in 2021) of an enhanced thermal wind and subtropical jet over the Australian continent contributed to the rainfall anomalies. In general, La Niña sets up warm sea surface temperatures around northern Australia, which enhances the meridional temperature gradient over the continent, and hence thermal wind and subtropical jet. In November 2021 these warm sea surface temperatures, coupled with a persistent mid-latitude trough, which advected cold air over the Australian continent, led to an enhanced meridional temperature gradient and subtropical jet over Australia. The enhanced jet provided favourable conditions for the development of rain-bearing weather systems across Australia. In 2020 the continent was warm, displacing the latitude of maximum meridional temperature gradient south of the continent, resulting in fewer instances of the subtropical jet over Australia, and little development of weather systems over the continent. We highlight that although La Niña tilts the odds to wetter conditions for Australia, in any given month, variability in temperatures over the continent can contribute to subtropical jet variability and resulting rainfall in ways which confound the normal expectation from La Niña.

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David Landry
,
Anastase Charantonis
, and
Claire Monteleoni

Abstract

We propose a neural network approach to produce probabilistic weather forecasts from a deterministic numerical weather prediction. Our approach is applied to operational surface temperature outputs from the Global Deterministic Prediction System up to ten-day lead times, targeting METAR observations in Canada and the United States. We show how postprocessing performance is improved by training a single model for multiple lead times. Multiple strategies to condition the network for the lead time are studied, including a supplementary predictor and an embedding. The proposed model is evaluated for accuracy, spread, distribution calibration, and its behavior under extremes. The neural network approach decreases CRPS by 15% and has improved distribution calibration compared to a naive probabilistic model based on past forecast errors. Our approach increases the value of a deterministic forecast by adding information about the uncertainty, without incurring the cost of simulating multiple trajectories. It applies to any gridded forecast including the recent machine learning-based weather prediction models. It requires no information regarding forecast spread and can be trained to generate probabilistic predictions from any deterministic forecast.

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Matthew D. Flournoy
,
Anthony W. Lyza
,
Andrew R. Wade
, and
Jannick Fischer

Abstract

Cell mergers with supercells are relatively common, but much remains unknown about how they may influence subsequent supercell hazards. Furthermore, many outstanding questions regarding mesocyclone evolution exist despite numerous studies linking supercell hazards with the background environments in which they occur. In this study, we analyze the Multi-Year Reanalysis of Remotely Sensed Storms dataset along with hundreds of observed supercell tracks to begin addressing these ideas. In line with recent studies, the outcome of a supercell-cell merger (specifically the final strength of the low-level supercell mesocyclone) is not strongly related to the background environment. Of the parameters that we tested, mixed-layer (ML) LCL exhibited the largest correlation, but the very small coefficient of determination suggests limited operational use. More significantly, the incorporation of Storm Prediction Center objective analyses yields novel quantification of observed mesocyclone strengths in different environments. Of the environmental characteristics tested, kinematic parameters like 0–3-km storm-relative helicity (SRH) and 0–3-km bulk wind difference are more correlated with peak mesocyclone intensity than thermodynamic variables like CAPE and CIN. 0–3-km SRH exhibits the largest correlation, and its variability explains roughly one-third of the variance of peak azimuthal shear. We show trends in peak mesocyclone intensity across notable environmental parameter spaces, as well as how low-level mesocyclone strength fluctuates as background environmental characteristics evolve. Environmental trends during and preceding the times of peak mesocyclone strength are quantified. These analyses may be useful for predicting short-term mesocyclone intensity changes in real time.

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