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Cameron R. Homeyer
,
Elisa M. Murillo
, and
Matthew R. Kumjian

Abstract

Supercell storms are commonly responsible for severe hail, which is the costliest severe storm hazard in the United States and elsewhere. Radar observations of such storms are common and have been leveraged to estimate hail size and severe hail occurrence. However, many established relationships between radar-observed storm characteristics and severe hail occurrence have been found using data from few storms and in isolation from other radar metrics. This study leverages a 10-yr record of polarimetric Doppler radar observations in the United States to evaluate and compare radar observations of thousands of severe hail–producing supercells based on their maximum hail size. In agreement with prior studies, it is found that increasing hail size relates to increasing volume of high (≥50 dBZ) radar reflectivity, increasing midaltitude mesocyclone rotation (azimuthal shear), increasing storm-top divergence, and decreased differential reflectivity and copolar correlation coefficient at low levels (mostly below the environmental 0°C level). New insights include increasing vertical alignment of the storm mesocyclone with increasing hail size and a Doppler velocity spectrum width minimum aloft near storm center that increases in area with increasing hail size and is argued to indicate increasing updraft width. To complement the extensive radar analysis, near-storm environments from reanalyses are compared and indicate that the greatest environmental differences exist in the middle troposphere (within the hail growth region), especially the wind speed perpendicular to storm motion. Recommendations are given for future improvements to radar-based hail-size estimation.

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Takumi Honda
,
Yousuke Sato
, and
Takemasa Miyoshi

Abstract

Lightning flash observations are closely associated with the development of convective clouds and have a potential for convective-scale data assimilation with high-resolution numerical weather prediction models. A main challenge with the ensemble Kalman filter (EnKF) is that no ensemble members have nonzero lightning flashes in the places where a lightning flash is observed. In this situation, different model states provide all zero lightning, and the EnKF cannot assimilate the nonzero lightning data effectively. This problem is known as the zero-gradient issue. This study addresses the zero-gradient issue by adding regression-based ensemble perturbations derived from a statistical relationship between simulated lightning and atmospheric variables in the whole computational domain. Regression-based ensemble perturbations are applied if the number of ensemble members with nonzero lightning flashes is smaller than a prescribed threshold (N min). Observing system simulation experiments for a heavy precipitation event in Japan show that regression-based ensemble perturbations increase the ensemble spread and successfully induce the analysis increments associated with convection even if only a few members have nonzero lightning flashes. Furthermore, applying regression-based ensemble perturbations improves the forecast accuracy of precipitation although the improvement is sensitive to the choice of N min.

Significance Statement

This study develops an effective method to use lightning flash observations for weather prediction. Lightning flash observations include precious information of the inner structure of clouds, but their effective use for weather prediction is not straightforward since a weather prediction model often misses observed lightning flashes. Our new method uses ensemble-generated statistical relationships to compensate for the misses and successfully improves the forecast accuracy of heavy rains in a simulated case. Our future work will test the method with real observation data.

Open access
Kota Endo
,
Adam H. Monahan
,
Julie Bessac
,
Hannah M. Christensen
, and
Nils Weitzel

Abstract

High-resolution numerical models have been used to develop statistical models of the enhancement of sea surface fluxes resulting from spatial variability of sea surface wind. In particular, studies have shown that flux enhancement is not a deterministic function of the resolved state. Previous studies focused on single geographical areas or used a single high-resolution numerical model. This study extends the development of such statistical models by considering six different high-resolution models, four different geographical regions, and three different 10-day periods, allowing for a systematic investigation of the robustness of both the deterministic and stochastic parts of the data-driven parameterization. Results indicate that the deterministic part, based on regressing the unresolved normalized flux onto resolved-scale normalized flux and precipitation, is broadly robust across different models, regions, and time periods. The statistical features of the stochastic part of the model (spatial and temporal autocorrelation and parameters of a Gaussian process fit to the regression residual) are also found to be robust and not strongly sensitive to the underlying model, modeled geographical region, or time period studied. Best-fit Gaussian process parameters display robust spatial heterogeneity across models, indicating potential for improvements to the statistical model. These results illustrate the potential for the development of a generic, explicitly stochastic parameterization of sea surface flux enhancements dependent on wind variability.

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Wataru Yanase
,
Udai Shimada
,
Naoko Kitabatake
, and
Eigo Tochimoto

Abstract

Tropical transition (TT) is a cyclogenesis process in which a baroclinic disturbance is transformed into a tropical cyclone. Many studies have analyzed TT events over the North Atlantic. This study assesses TT processes from a possible subtropical cyclone to Tropical Storm Kirogi at a relatively high latitude over the western North Pacific in an environment of enhanced baroclinicity in August 2012. Analyses based on satellite observations, the JRA-55 reanalysis, and a simulation with 2.5-km horizontal grid spacing demonstrate three stages during the TT: the baroclinic, intermediate, and convective stages. Over the baroclinic stage, Kirogi had an asymmetric comma-shaped cloud pattern with convection in the northern and eastern parts of the cyclone. This convection is attributed to quasigeostrophic forcing and frontogenesis associated with advection of warm and moist air. Vorticity locally generated by this convection was advected to the cyclone center by cyclone-relative northerly flow. Kirogi also had a shallow warm-core structure due to the interaction with an upper-level cold trough extending from the midlatitudes. In the intermediate stage, the warm and moist air in the lower troposphere and the cold trough in the upper troposphere wrapped around Kirogi. In the convective stage, Kirogi attained characteristics of a typical tropical cyclone with convection concentrated near the cyclone center and a deep warm-core structure. These results demonstrate that baroclinic processes can directly trigger formation of a tropical storm at relatively high latitudes over the western North Pacific in a similar manner to that over the North Atlantic.

Significance Statement

Tropical cyclogenesis is an important process for early identification of tropical cyclone hazards. Tropical transition is a tropical cyclogenesis process that is triggered by a subtropical or extratropical disturbance. It is unique to relatively high latitudes and has social importance particularly for midlatitude countries. There have been fewer studies on tropical transition over the western North Pacific than over the North Atlantic. This study demonstrates the dynamics of a distinct tropical transition event that led to the formation of Tropical Storm Kirogi (2012) at a relatively high latitude over the western North Pacific.

Open access
Free access
Jannick Fischer
,
Matthew D. Flournoy
, and
Anthony W. Lyza

Abstract

Two recent articles investigated the evolution of supercell mesocyclone intensity during storm merger events using radar-indicated azimuthal shear. Both found that initially strong mesocyclones tended to weaken while initially weak mesocyclones statistically most frequently tended to intensify during the merger. However, these studies did not include null cases. In this article, random supercell periods are analyzed to test if a similar pattern of mesocyclone intensity variations happens in the absence of mergers. A similar pattern is found, suggesting that these intensity variations are stochastic rather than linked to merger events. Based on this finding, the datasets and conclusions of the previous two articles are reevaluated collaboratively.

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D. Rosenberg
,
B. Flynt
,
M. Govett
, and
I. Jankov

Abstract

A new software framework using a well-established high-order spectral element discretization is presented for solving the compressible Navier–Stokes equations for purposes of research in atmospheric dynamics in bounded and unbounded limited-area domains, with a view toward capturing spatiotemporal intermittency that may be particularly challenging to attain using low-order schemes. A review of the discretization is provided, emphasizing properties such as the matrix product formalism and other design considerations that will facilitate its effective use on emerging exascale platforms, and a new geometry-independent, element boundary exchange method is described to maintain continuity. A variety of test problems are presented that demonstrate accuracy of the implementation primarily in wave-dominated or transitional flow regimes; conservation properties are also demonstrated. A strong scaling CPU study in a three-dimensional domain without using threading shows an average parallel efficiency of ≳99% up to 2 × 104 MPI tasks that is not affected negatively by expansion polynomial order. On-node performance is also examined and reveals that, while the primary numerical operations achieve their theoretical arithmetic intensity, the application performance is largely limited by available memory bandwidth.

Significance Statement

This work considers the need for computationally efficient, high-order, low dissipation numerics to fully leverage emerging exascale computing resources in an effort to examine and improve the accuracy of numerical treatments of atmospheric and weather phenomena. A new spectral element implementation is introduced that attempts to address the issues involved. Well-understood tests are presented that illustrate the known efficacy of the method in wave-dominated, quasi-laminar, and relatively strong shear flow regimes, and good conservation properties for mass and total energy are achieved. Importantly, the implementation is shown to exhibit encouraging performance characteristics.

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Peiyu Wang
and
Zhiyong Meng

Abstract

Multiple parallel rainbands (MPRBs) involve the organization of mesoscale convective systems (MCSs) characterized by multiple parallel convective rainbands, which may produce high rainfall accumulation. A total of 178 MPRBs were identified from 2016 to 2020 in China, which were classified into the initiation type (∼40%), where rainbands initiate individually, and differentiation type (∼60%), where rainbands form through the splitting of large rainbands or merging of smaller cells. Results showed that the occurrence frequency of MPRBs peaks in July with a midnight major peak and a morning minor peak. The highest occurrence frequency is observed in the northern Beibu Gulf and its coastal areas, with minor high frequencies in Guangdong, northern Jiangxi, and southern Shandong provinces, typically in a southwesterly low-level jet to the west of the subtropical high. MPRBs mainly contain 3–4 rainbands with a spacing distance of 30–50 km and an orientation generally consistent with the direction of 850-hPa winds and 0–1-km vertical wind shear. MPRBs generally move slower than that of squall lines in East China ranging from 4 to 8 m s−1 with 16% being quasi-stationary, which is mainly due to the occurrence of band back building mainly associated with cold pool. Most MPRBs have training effects with band training as the dominant mode. Because of the band training effect and slower movement of MPRBs mainly due to band back building, 71% of MPRBs are associated with enhanced maximum hourly rainfall. Rainfall severity may be alleviated somewhat by the generally short duration of MPRBs with 78% being shorter than 2 h.

Significance Statement

The purpose of this study is to document the general features of mesoscale convective systems (MCSs) with a specific organization of multiple parallel rainbands (MPRBs). MCSs with this unique organization tend to produce extremely heavy rainfall partly due to the training of multiple rainbands as well as their slow movement because of back building. The organization pattern of MPRBs was previously found in a case study. The possible formation mechanism was also previously examined based on case studies. As a complement to these studies, this work aims to reveal the temporal and spatial distributions, movement and duration, morphology, precipitation patterns, and environmental features of MPRBs in China based on statistics using 5-yr radar reflectivity data.

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Brian A. Colle
,
Phillip Yeh
,
Joseph A. Finlon
,
Lynn McMurdie
,
Victoria McDonald
, and
Andrew DeLaFrance

Abstract

On 7 February 2020 a relatively deep cyclone (∼980 hPa) with midlevel frontogenesis produced heavy snow (20–30 mm liquid equivalent) over western and central New York State. Despite these characteristics, the precipitation was not organized into a narrow band of intensive snowfall. This event occurred during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. Using coordinated flight legs across New York State, a remote sensing aircraft (ER-2) sampled above the cloud, while a P-3 aircraft collected in-cloud data. These data are used to validate several Weather Research and Forecasting (WRF) Model simulations at 2- and 0.67-km grid spacing using different initial and boundary conditions (RAP, GFS, and ERA5 analyses) and microphysics schemes (Thompson and P3). The differences between the WRF runs are used to explore sensitivity to initial conditions and microphysics schemes. All 18–24-h runs realistically produced a broad sloping region of frontogenesis at midlevels typically; however, there were relatively large (20%–30%) uncertainties in the magnitude of this forcing using different analyses and initialization times. The differences in surface precipitation distribution are small (<10%) among the microphysics schemes, likely because there was little riming in the region of heaviest precipitation. Those runs with frontogenesis closest to the RAP analysis and a surface precipitation underprediction of 20%–30% have too little ice aloft and at low levels, suggesting deficiencies in ice generation and snow growth aloft in those runs. The 0.67-km grid produced more realistic convective cells aloft, but only 5%–10% more precipitation than the 2-km grid.

Significance Statement

Heavy snowfall from U.S. East Coast winter storms can cause major societal problems, yet few studies have investigated these storms using field observations and model data. This study focuses on the 7 February 2020 event, where 20–40 cm of snow fell over west-central New York. Our analysis shows a broad region of ascent, rather than a concentrated region favoring a well-defined snowband was the primary process contributing to snowfall. Last, model microphysics were validated within this storm using the in situ aircraft data. Errors in the snow generation aloft and snow growth at low levels likely contributed to the simulated surface precipitation underprediction, but most of the forecast uncertainty is from initial conditions for this short-term (∼24-h lead time) forecast.

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Matthew S. Van Den Broeke
,
Matthew B. Wilson
,
Cynthia A. Van Den Broeke
,
Devon J. Healey
,
Michaela J. Wood
, and
Raychel E. Nelson

Abstract

We present environmental and polarimetric radar observations of a long-lived December supercell that tracked approximately 750 km from Arkansas to northern Kentucky. The storm was associated with two long-track EF4 tornadoes, one of which was among the longest-tracked tornadoes recorded in the United States. The supercell’s life cycle is documented from 2000 UTC 10 to 0700 UTC 11 December 2021, using data from five operational polarimetric weather radars. After convection initiation in central Arkansas, it took nearly 4 h for a supercell to develop. Afterward, the storm’s Z DR column and arc became anomalously large leading up to genesis of the first EF4 tornado. During this time, the storm’s environment had moderate convective available potential energy (CAPE) and strong deep-layer shear. A cell interaction at about 0200 UTC disrupted the supercell updraft, weakening the Z DR arc and column, and initiating the largest radar-implied hailfall event observed with this storm. The remnant circulation associated with the first EF4 tornado did not fully dissipate, and it appeared to merge with the low-level mesocyclone on the nose of a rear-flank downdraft surge likely initiated by the hailfall. It is hypothesized that this merger was important to the intensification of the storm’s second EF4 tornado, which lasted nearly 3 h and traveled approximately 267 km. During the second EF4 tornado the storm experienced decreasing CAPE and increasing storm relative helicity. Increasing interactions with other cells eventually weakened the storm, and its original updraft was obscured before the storm’s remnants dissipated in northern Kentucky.

Significance Statement

In December 2021, a long-lived supercell thunderstorm produced two long-track, violent tornadoes, including one that produced historic damage across western Kentucky. Radar observations indicate that, once the storm became a supercell, its updraft became anomalously large relative to similar storms studied prior. Simultaneously its storm-relative inflow strengthened markedly, supporting the first long-lived tornado. Interactions with a developing thunderstorm disrupted the supercell’s updraft, leading to hail fallout and updraft weakening. The remnant circulation associated with the first strong tornado merged with the supercell’s updraft and became a rotation source for the second long-track tornado, which persisted for nearly 3 h. Eventually interactions with other thunderstorms weakened the supercell.

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