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Kristen L. Axon
,
Adam L. Houston
,
Conrad L. Ziegler
,
Christopher C. Weiss
,
Erik N. Rasmussen
,
Michael C. Coniglio
,
Brian Argrow
,
Eric Frew
,
Sara Swenson
,
Anthony E. Reinhart
, and
Matthew B. Wilson

Abstract

On 28 May 2019, a tornadic supercell, observed as part of Targeted Observation by UAS and Radars of Supercells (TORUS) produced an EF-2 tornado near Tipton, Kansas. The supercell was observed to interact with multiple preexisting airmass boundaries. These boundaries and attendant air masses were examined using unoccupied aircraft system (UAS), mobile mesonets, radiosondes, and dual-Doppler analyses derived from TORUS mobile radars. The cool-side air mass of one of these boundaries was found to have higher equivalent potential temperature and backed winds relative to the warm-side air mass; features associated with mesoscale air masses with high theta-e (MAHTEs). It is hypothesized that these characteristics may have facilitated tornadogenesis. The two additional boundaries were produced by a nearby supercell and appeared to weaken the tornadic supercell. This work represents the first time that UAS have been used to examine the impact of preexisting airmass boundaries on a supercell, and it provides insights into the influence environmental heterogeneities can have on the evolution of a supercell.

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Steven J. Greybush
,
Todd D. Sikora
,
George S. Young
,
Quinlan Mulhern
,
Richard D. Clark
, and
Michael L. Jurewicz Sr.

Abstract

Data from rawinsondes launched during intensive observation periods (IOPs) of the Ontario Winter Lake-Effect Systems (OWLeS) field project reveal that elevated mixed layers (EMLs) in the lower troposphere were relatively common near Lake Ontario during OWLeS lake-effect events. Conservatively, EMLs exist in 193 of the 290 OWLeS IOP soundings. The distribution of EML base pressure derived from the OWLeS IOP soundings reveals two classes of EML, one that has a relatively low-elevation base (900–750 hPa) and one that has a relatively high-elevation base (750–500 hPa). It is hypothesized that the former class of EML, which is the focus of this research, is, at times, the result of mesoscale processes related to individual Great Lakes. WRF reanalysis fields from a case study during the OWLeS field project provide evidence of two means by which low-elevation base EMLs can originate from the lake-effect boundary layer convection and associated mesoscale circulations. First, such EMLs can form within the upper-level outflow branches of mesoscale solenoidal circulations. Evacuated Great Lakes–modified convective boundary layer air aloft then lies above ambient air of a greater static stability, forming EMLs. Second, such EMLs can form in the absence of a mesoscale solenoidal circulation when Great Lake–modified convective boundary layers overrun ambient air of a greater density. The reanalysis fields show that EMLs and layers of reduced static stability tied to Great Lakes–modified convective boundary layers can extend downwind for hundreds of kilometers from their areas of formation. Operational implications and avenues for future research are discussed.

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Yue Yang
and
Xuguang Wang

Abstract

The Gridpoint Statistical Interpolation (GSI)-based four- and three-dimensional ensemble–variational (4DEnVar and 3DEnVar) methods are compared as a smoother and a filter, respectively, for rapidly changing storms using the convective-scale direct radar reflectivity data assimilation (DA) framework. Two sets of experiments with varying DA window lengths (WLs; 20, 40, 100, and 160 min) and radar observation intervals (RIs; 20 and 5 min) are conducted for the 5–6 May 2019 case. The RI determines the temporal resolution of ensemble perturbations for the smoother and the DA interval for the filter spanning the WL. For experiments with a 20-min RI, evaluations suggest that the filter and the smoother have comparable performance with a 20-min WL; however, extending the WL results in the outperformance of the filter over the smoother. Diagnostics reveal that the degradation of the smoother is attributed to the increased degree of nonlinearity and the issue of time-independent localization as the WL extends. Evaluations for experiments with different RIs under the same WL indicate that the outperformance of the filter over the smoother diminishes for most forecast hours at thresholds of 30 dBZ and above when shortening the RI. Diagnostics show that more frequent interruptions of the model introduce model imbalance for the filter, and the increased temporal resolution of ensemble perturbations enhances the degree of nonlinearity for the smoother. The impact of model imbalance on the filter overwhelms the enhanced nonlinearity on the smoother as the RI reduces.

Significance Statement

The background uncertainties of rapidly changing storms suffer from fast error growth and high degrees of nonlinearities during the data assimilation (DA) period. Two variants of the ensemble-based DA method can account for such temporal evolution. The smoother uses background ensemble from multiple observation times over an assimilation period to estimate the propagation of statistics. The filter frequently calculates the statistics at multiple observation times over the same period. Current comparisons of the smoother and the filter were mostly performed using simple models; however, unknowns remain for convection-allowing forecasts with additional complexities. This study compares the filter and the smoother for the convective-scale analysis and prediction using a real-data study and finds that the comparison varies with the assimilation period and the observation interval.

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Han Li
,
Ziyu Yan
,
Melinda Peng
,
Xuyang Ge
, and
Zhuo Wang

Abstract

Tropical cyclones (TCs) accompanied by an upper-tropospheric cold low (CL) can experience unusual tracks. Idealized simulations resembling observed scenarios are designed in this study to investigate the impacts of a CL on TC tracks. The sensitivity of the TC motion to its location relative to the CL is examined. The results show that a TC follows a counterclockwise semicircle track if initially located east of a CL, while a TC experiences a small southward-looping track, followed by a sudden northward turn if initially located west of a CL. A TC on the west side experiences opposing CL and β steering, while they act in the same direction when a TC is on the east side of CL. The steering flow analyses show that the steering vector is dominated by upper-level flow induced by the CL at an early stage. The influence of CL extends downward and contributes to the lower-tropospheric asymmetric flow pattern of TC. As these two systems approach, the TC divergent outflow erodes the CL. The CL circulation is deformed and eventually merged with the TC when they are close. Since the erosion of CL, the TC motion is primarily related to β gyres at a later stage. The sensitivity of TC motion to the CL depth is also examined. TCs located west of a CL experience a westward track if the CL is shallow. In contrast, TCs initially located east of a CL all take a smooth track irrespective of the CL depth, and the CL depth mainly influences the track curvature and the TC translation speed.

Significance Statement

The purpose of this study is to better understand how an upper-tropospheric cold low affects the motion of a nearby tropical cyclone. Our findings highlight distinct track patterns based on the relative positions of the tropical cyclone and the cold low. When the tropical cyclone is located on the east side of a cold low, a mutual rotation occurs, leading to a counterclockwise semicircle track of tropical cyclone. Conversely, if the tropical cyclone is located to the west side of a cold low, the cold low approaches and captures it, resulting in an abrupt northward turn when the cold low is eroded by the tropical cyclone. These insights improve the predictability of tropical cyclones in the vicinity of cold lows.

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Zhilin Zeng
,
Lingdong Huang
,
David M. Schultz
,
Luis Garcia-Carreras
, and
Donghai Wang

Abstract

To understand why convection initiation and heavy rain sometimes occur ahead of fronts over South China in the presummer rainy season but sometimes do not, a climatology of 137 fronts is constructed, in which 34% of the fronts exhibit no prefrontal convection initiation (NoPCI), 31% of the fronts exhibit prefrontal convection initiation (PCI), and 35% of the fronts exhibit prefrontal convection initiation and heavy rain (PCI+HR). An anticyclonically curved upper-level jet streak and midtropospheric QG forcing produce synoptic-scale descent for the prefrontal region in NoPCI events, whereas the right-entrance region of a straight upper-level jet streak and forcing for ascent dominate the prefrontal region in PCI and PCI+HR events. Whether prefrontal convection and heavy rain occur is also related to the character of low-level flows. NoPCI features anticyclonic southerly winds, with an environment having low dewpoint throughout the troposphere, unfavorable for convection initiation. However, synoptic circulation of PCI and PCI+HR events favors a broad prefrontal surface low, which determines the greater cyclonic character of airflows in PCI+HR events, in contrast with that of the PCI events. Convective available potential energy is useful in distinguishing NoPCI and PCI events, and the three events have statistically significant differences in precipitable water. Moreover, larger magnitudes of precipitable water and bulk wind shear in PCI+HR events are conducive for prefrontal convection to produce heavy rain compared to those of PCI events. These results indicate the importance of the upper-level forcing on the prefrontal convection initiation, and heavy rain is sensitive to the changes in prefrontal airflow and moisture.

Significance Statement

Convection and heavy rain sometimes occur a few hundred kilometers ahead of fronts in the warm air over South China in early summer. To understand atmospheric conditions favoring or inhibiting convection and heavy rain ahead of fronts, we examine 46 fronts without prefrontal convection, 43 fronts with prefrontal convection, and 48 fronts with prefrontal convection and heavy rain. These scenarios have similarities in environmental behaviors but different large-scale conditions that favor or inhibit ascent in the prefrontal area. Specifically, prefrontal heavy rain tends to occur in a very moist environment with a prefrontal surface low. These findings help researchers and operational forecasters better discriminate the subtle conditions that favor or inhibit prefrontal convection and heavy rain over South China.

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Kelsey Malloy
,
Michael K. Tippett
, and
William J. Koshak

Abstract

Cloud-to-ground (CG) lightning substantially impacts human health and property. However, the relations between U.S. lightning activity and the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO), two predictable drivers of global climate variability, remain uncertain, in part because most lightning datasets have short records that cannot robustly reveal MJO- and ENSO-related patterns. To overcome this limitation, we developed an empirical model of 6-hourly lightning flash count over the contiguous United States (CONUS) using environmental variables (convective available potential energy and precipitation) and National Lightning Detection Network data for 2003–16. This model is shown to reproduce the observed daily and seasonal variability of lightning over most of CONUS. Then, the empirical model was applied to construct a proxy lightning dataset for the period 1979–2021, which was used to investigate the summer MJO–lightning relationship at daily resolution and the winter–spring ENSO–lightning relationship at seasonal resolution. Overall, no robust relationship between MJO phase and lightning patterns was found when seasonality was taken into consideration. El Niño is associated with increased lightning activity over the coastal Southeast United States during early winter, the Southwest during winter through spring, and the Northwest during late spring, whereas La Niña is associated with increased lightning activity over the Tennessee River valley during winter.

Significance Statement

Cloud-to-ground lightning is dangerous for humans via direct strikes or through triggering wildfires, generating air pollution, etc. How lightning activity can be affected by climate remains unclear, and it is challenging to study their links because the data record for lightning is short. With the available lightning record, we developed a model that relates lightning flash counts over the United States to environmental factors. This model well represents observed fluctuations in daily and seasonal lightning over most of the United States. Because the model only needs environmental information to predict lightning flash counts, we were able to construct a longer record of predicted lightning based on the longer data record of environmental variables. With this dataset, we investigated the links between lightning and climate and found that the state of sea surface temperatures in the tropical Pacific (El Niño–Southern Oscillation) is linked to changes in U.S. lightning patterns in winter and spring.

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Joshua B. Wadler
,
Joseph J. Cione
,
Robert F. Rogers
, and
Michael S. Fischer

Abstract

Airborne Doppler radar reflectivity data collected in hurricanes on the NOAA P-3 aircraft between 1997 and 2021 were parsed into different modes of precipitation: stratiform precipitation, shallow convection, moderate convection, and deep convection. Stratiform precipitation was the most frequent precipitation mode with 82.6% of all observed precipitation while deep convection was the most infrequent at 1.3%. When stratified by 12-h intensity change, intensifying TCs had a greater areal coverage of total convection in the eyewall compared to weakening and steady-state TCs. The largest difference in the azimuthal distributions in the precipitation modes was in deep convection, which was mostly confined to the downshear-left quadrant in weakening and steady-state hurricanes and more symmetrically distributed in intensifying hurricanes. For all intensity change categories, the most symmetrically distributed precipitation mode was stratiform rain. To build upon the results of a recent thermodynamic study, the precipitation data were recategorized for hurricanes experiencing deep-layer wind shear with either a northerly component or southerly component. Like intensifying storms, hurricanes that experienced northerly component shear had a more symmetric distribution of deep convection than southerly component shear storms, which had a distribution of deep convection that resembled weakening storms. The greatest difference in the precipitation distributions between the shear direction groups were in major hurricanes experiencing moderate (4.5–11 m s−1) wind shear values. Consistent with previous airborne radar studies, the results suggest that considering the distribution of deep convection and the thermodynamic distributions associated with differing environmental wind shear direction could aid TC intensity forecasts.

Significance Statement

This research investigates how the distribution of different types of precipitation are related to tropical cyclone (TC) intensity change. Even though deep convection—the tallest clouds—is the least frequent type of precipitation, it has the strongest relationship to intensity change with uniform distributions around the eyewall associated with intensification. Less significant relationships were noticed for shallower clouds and stratiform (lighter) rain. The study also analyzed how change in direction of the large-scale winds with height (wind shear) influences intensity change. When wind shear is northerly, there is a more symmetric distribution of deep convection compared to when wind shear is southerly. These relationships illustrate how wind shear direction influences TC convective structure and, in turn, TC intensity change.

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Jeremy R. Lilly
,
Darren Engwirda
,
Giacomo Capodaglio
,
Robert L. Higdon
, and
Mark R. Petersen

Abstract

We present the formulation and optimization of a Runge–Kutta-type time-stepping scheme for solving the shallow-water equations, aimed at substantially increasing the effective allowable time step over that of comparable methods. This scheme, called FB-RK(3,2), uses weighted forward–backward averaging of thickness data to advance the momentum equation. The weights for this averaging are chosen with an optimization process that employs a von Neumann–type analysis, ensuring that the weights maximize the admittable Courant number. Through a simplified local truncation error analysis and numerical experiments, we show that the method is at least second-order in time for any choice of weights and exhibits low dispersion and dissipation errors for well-resolved waves. Further, we show that an optimized FB-RK(3,2) can take time steps up to 2.8 times as large as a popular three-stage, third-order strong stability-preserving Runge–Kutta method in a quasi-linear test case. In fully nonlinear shallow-water test cases relevant to oceanic and atmospheric flows, FB-RK(3,2) outperforms SSPRK3 in admittable time step by factors roughly between 1.6 and 2.2, making the scheme approximately twice as computationally efficient with little to no effect on solution quality.

Significance Statement

The purpose of this work is to develop and optimize time-stepping schemes for models relevant to oceanic and atmospheric flows. Specifically, for the shallow-water equations we optimize for schemes that can take time steps as large as possible while retaining solution quality. We find that our optimized schemes can take time steps between 1.6 and 2.2 times larger than schemes that cost the same number of floating point operations, translating directly to a corresponding speedup. Our ultimate goal is to use these schemes in climate-scale simulations.

Open access
Arthur Avenas
,
Alexis Mouche
,
Pierre Tandeo
,
Jean-Francois Piolle
,
Dan Chavas
,
Ronan Fablet
,
John Knaff
, and
Bertrand Chapron

Abstract

The radius of maximum wind R max, an important parameter in tropical cyclone (TC) ocean surface wind structure, is currently resolved by only a few sensors so that, in most cases, it is estimated subjectively or via crude statistical models. Recently, a semiempirical model relying on an outer wind radius, intensity, and latitude was fit to best-track data. In this study we revise this semiempirical model and discuss its physical basis. While intensity and latitude are taken from best-track data, R max observations from high-resolution (3 km) spaceborne synthetic aperture radar (SAR) and wind radii from an intercalibrated dataset of medium-resolution radiometers and scatterometers are considered to revise the model coefficients. The new version of the model is then applied to the period 2010–20 and yields R max reanalyses and trends that are more accurate than best-track data. SAR measurements corroborate that fundamental conservation principles constrain the radial wind structure on average, endorsing the physical basis of the model. Observations highlight that departures from the average conservation situation are mainly explained by wind profile shape variations, confirming the model’s physical basis, which further shows that radial inflow, boundary layer depth, and drag coefficient also play roles. Physical understanding will benefit from improved observations of the near-core region from accumulated SAR observations and future missions. In the meantime, the revised model offers an efficient tool to provide guidance on R max when a radiometer or scatterometer observation is available, for either operations or reanalysis purposes.

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Akira Yamazaki
and
Shunsuke Noguchi

Abstract

This study conducts a thorough investigation into the behaviors of analysis ensemble spreads linked to stratospheric sudden warming (SSW) events. A stratosphere-resolving ensemble data assimilation system is used here to document the evolution of analysis spread leading up to a pair of warming events. Precursory signals of the increased ensemble spreads were found a few days prior to two SSW events that occurred during December 2018 and August–September 2019 in the Northern and Southern Hemispheres, respectively. The signals appeared in the upper and middle stratosphere and did not appear at lower heights. When the signals appeared, it was found that both tendency by forecast and analysis increment in a forecast-analysis (data assimilation) cycle simultaneously became large. An empirical orthogonal function analysis showed that the dominant structures of the precursory signals were equivalent barotropic and were 90° out-of-phase with the analysis ensemble-mean field. Over the same period, the upper and middle stratosphere became more susceptible to barotropic instability than in their previous states. We conclude that the differing growth of barotropically unstable modes across ensemble members can amplify spread during the lead-up to SSW events.

Significance Statement

Winds in the winter stratospheric polar vortex are typically westerly. Occasionally, however, warming over the pole leads to a reversal of the flow through a process known as stratospheric sudden warming. These events are difficult to predict even in state-of-the-art analysis and forecasting systems. In this study, we identify a precursor signal in the form of increased ensemble spread that appears to originate from differing realizations of growing barotropic modes across the ensemble. This signal could serve as a useful forecasting tool by enhancing situational awareness in the lead-up to potential stratospheric sudden warming events.

Open access