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Lauren E. Pounds
,
Conrad L. Ziegler
,
Rebecca D. Adams-Selin
, and
Michael I. Biggerstaff

Abstract

This study uses a new, unique dataset created by combining multi-Doppler radar wind and reflectivity analysis, diabatic Lagrangian analysis (DLA) retrievals of temperature and water substance, and a complex hail trajectory model to create millions of numerically simulated hail trajectories in the Kingfisher, Oklahoma, supercell on 29 May 2012. The DLA output variables are used to obtain a realistic, 4D depiction of the storm’s thermal and hydrometeor structure as required input to the detailed hail growth trajectory model. Hail embryos are initialized in the hail growth module every 3 min of the radar analysis period (2251–0000 UTC) to produce over 2.7 million hail trajectories. A spatial integration technique considering all trajectories is used to identify locations within the supercell where melted particles and subsevere and severe hailstones reside in their lowest and highest concentrations. It is found that hailstones are more likely to reside for longer periods closer to the downshear updraft within the midlevel mesocyclone in a region of decelerated midlevel mesocyclonic horizontal flow, termed the downshear deceleration zone (DDZ). Additionally, clusters of trajectories are analyzed using a trajectory clustering method. Trajectory clusters show there are many trajectory pathways that result in hailstones ≥ 4.5 cm, including trajectories that begin upshear of the updraft away from ideal growth conditions and trajectories that grow within the DDZ. There are also trajectory clusters with similar shapes that experience widely different environmental and hailstone characteristics along the trajectory.

Significance Statement

The purpose of this study is to understand how hail grew in a thunderstorm that was observed by numerous instruments. The observations were input into a hail trajectory model to simulate hail growth. We found a part of the storm near the updraft where hailstones could remain aloft longer and therefore grow larger. Most modeled severe hailstones were found in the storm in this region. However, we also found that there are many different pathways hailstones can take to become large, although there are still some common characteristics among the pathways.

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Koji Terasaki
and
Takemasa Miyoshi

Abstract

Densely observed remote sensing data such as radars and satellites generally contain significant spatial error correlations. In data assimilation, the observation error covariance matrix is usually assumed to be diagonal, and the dense data are thinned or spatially averaged to compensate for neglecting the spatial observation error correlation. However, in theory, including the spatial observation error correlation in data assimilation can make better use of the dense data. This study performs perfect model observing system simulation experiments (OSSEs) using the nonhydrostatic icosahedral atmospheric model (NICAM) and the local ensemble transform Kalman filter (LETKF) to assess the impact of assimilating horizontally dense and error-correlated observations. The condition number of the observation error covariance matrix, defined as the ratio of the largest to smallest eigenvalues, is important for the numerical stability of the LETKF computation. A large condition number makes it difficult to compute the ensemble transform matrix correctly. Reducing the condition number by reconditioning is found effective for stable computation. The results show that including the horizontal observation error correlation with reconditioning makes the analysis more accurate but requires 6 times more computations than the case with the diagonal observation error covariance matrix.

Significance Statement

It is important to effectively utilize observations in data assimilation for more accurate weather prediction. Spatially dense observations are known to have an error correlation that is ignored in the data assimilation. This study explores assimilating dense observations by explicitly including observation error correlations with an idealized experiment. The results shows that the analysis is improved by including the observation error correlations. Also, the condition number of the observation error covariance matrix is essential for stable computations.

Open access
Michael S. Fischer
,
Robert F. Rogers
,
Paul D. Reasor
, and
Jason P. Dunion

Abstract

This study uses a recently developed airborne Doppler radar database to explore how vortex misalignment is related to tropical cyclone (TC) precipitation structure and intensity change. It is found that for relatively weak TCs, defined here as storms with a peak 10-m wind of 65 kt (1 kt = 0.51 m s−1) or less, the magnitude of vortex tilt is closely linked to the rate of subsequent TC intensity change, especially over the next 12–36 h. In strong TCs, defined as storms with a peak 10-m wind greater than 65 kt, vortex tilt magnitude is only weakly correlated with TC intensity change. Based on these findings, this study focuses on how vortex tilt is related to TC precipitation structure and intensity change in weak TCs. To illustrate how the TC precipitation structure is related to the magnitude of vortex misalignment, weak TCs are divided into two groups: small-tilt and large-tilt TCs. In large-tilt TCs, storms display a relatively large radius of maximum wind, the precipitation structure is asymmetric, and convection occurs more frequently near the midtropospheric TC center than the lower-tropospheric TC center. Alternatively, small-tilt TCs exhibit a greater areal coverage of precipitation inward of a relatively small radius of maximum wind. Greater rates of TC intensification, including rapid intensification, are shown to occur preferentially for TCs with greater vertical alignment and storms in relatively favorable environments.

Significance Statement

Accurately predicting tropical cyclone (TC) intensity change is challenging. This is particularly true for storms that undergo rapid intensity changes. Recent numerical modeling studies have suggested that vortex vertical alignment commonly precedes the onset of rapid intensification; however, this consensus is not unanimous. Until now, there has not been a systematic observational analysis of the relationship between vortex misalignment and TC intensity change. This study addresses this gap using a recently developed airborne radar database. We show that the degree of vortex misalignment is a useful predictor for TC intensity change, but primarily for weak storms. In these cases, more aligned TCs exhibit precipitation patterns that favor greater intensification rates. Future work should explore the causes of changes in vortex alignment.

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Yoshiki Fukutomi
and
Tetsuya Hiyama

Abstract

This study examined the dominant structure and characteristics of synoptic-scale (2–8-day periods) waves over northern Eurasia during 40 summer seasons (June–August, 1979–2018). The synoptic-scale wave patterns are isolated using an extended empirical orthogonal function (EEOF) analysis on the 300-hPa geopotential height anomalies, and a composite based on atmospheric circulation fields and gridded precipitation product. The wave patterns are classified into two types from two pairs of EEOF modes. These two different wave types are defined as the polar frontal (PF) mode and Arctic frontal (AF) mode, respectively. The PF-mode waves are initiated in the North Atlantic sector to the west of the British Isles. They propagate eastward across Siberia into the North Pacific, and produce precipitation mainly over the Eurasian polar frontal zone. The AF-mode wave train arcs along the climatological Arctic frontal zone (AFZ). The AF-mode waves originate near the Scandinavian Peninsula. Their eastward passage brings precipitation along the AFZ. The development of the synoptic-scale waves is reflected by unique background conditions over northern Eurasia. The lower-tropospheric baroclinicity in southern Siberia and central Asia favored the baroclinic growth of the PF-mode waves. The AF-mode waves are trapped in the well-organized baroclinic zone along the north coast of the Eurasian continent. The baroclinic zone is coupled with a band of large meridional gradient of potential vorticity in the upper troposphere, suggesting that this band acts as a waveguide for the AF-mode waves.

Significance Statement

This study examines the synoptic-scale waves in the 2–8-day range of time scales over northern Eurasia during summer. The synoptic-scale waves are categorized into two distinct types at different latitude bands by the EEOF analysis on the 300-hPa z anomalies. They are defined as polar frontal (PF) mode and Arctic frontal (AF) mode. Then the EEOF-based composite analysis is conducted to detect the large-scale circulation anomalies associated with the propagation of different types of synoptic-scale waves. The structure and characteristics are examined. The roles of the mean background conditions in the development and propagation of the respective types are discussed. The behavior of these wave disturbances as rain-producing weather systems is also examined.

Open access
I-Han Chen
,
Judith Berner
,
Christian Keil
,
Ying-Hwa Kuo
, and
George Craig

Abstract

This study uses the convective adjustment time scale to identify the climatological frequency of equilibrium and nonequilibrium convection in different parts of the contiguous United States (CONUS) as modeled by the operational convection-allowing High-Resolution Rapid Refresh (HRRR) forecast system. We find a qualitatively different climatology in the northern and southern domains separated by the 40°N parallel. The convective adjustment time scale picks up the fact that convection over the northern domains is governed by synoptic flow (leading to equilibrium), while locally forced, nonequilibrium convection dominates over the southern domains. Using a machine learning algorithm, we demonstrate that the convective adjustment time-scale diagnostic provides a sensible classification that agrees with the underlying dynamics of equilibrium and nonequilibrium convection. Furthermore, the convective adjustment time scale can indicate the model quantitative precipitation forecast (QPF) quality, as it correctly reflects the higher QPF skill for precipitation under strong synoptic forcing. This diagnostic based on the strength of forcing for convection will be employed in future studies across different parts of CONUS to objectively distinguish different weather situations and explore the potential connection to warm-season precipitation predictability.

Significance Statement

An objective classification metric that can delineate a wide range of forecasts into distinct scenarios can serve as a valuable tool. This study represents a pioneering effort in utilizing the convective adjustment time scale to identify the climatological frequency of warm-season precipitation under varying levels of synoptic forcing in different parts of the contiguous United States (CONUS). The results demonstrate that the convective adjustment time scale is a robust metric for categorizing precipitation events and establishing a direct link to their predictability. Overall, this study provides a valuable framework for future studies focused on the CONUS domain, offering guidance on how to employ the convective adjustment time scale to classify weather regimes and explore the influence of environmental conditions on predictability of convection.

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Robert Conrick
,
Clifford F. Mass
, and
Lynn McMurdie

Abstract

Current bulk microphysical parameterization schemes underpredict precipitation intensities and drop size distributions (DSDs) during warm rain periods, particularly upwind of coastal terrain. To help address this deficiency, this study introduces a set of modifications, called RCON, to the liquid-phase (warm rain) parameterization currently used in the Thompson–Eidhammer microphysical parameterization scheme. RCON introduces several model modifications, motivated by evaluating simulations from a bin scheme, which together result in more accurate precipitation simulations during periods of warm rain. Among the most significant changes are 1) the use of a wider cloud water DSD of lognormal shape instead of the gamma DSD used by the Thompson–Eidhammer parameterization and 2) enhancement of the cloud-to-rain autoconversion parameterization. Evaluation of RCON is performed for two warm rain events and an extended period during the Olympic Mountains Experiment (OLYMPEX) field campaign of winter 2015/16. We show that RCON modifications produce more realistic precipitation distributions and rain DSDs than the default Thompson–Eidhammer configuration. For the multimonth OLYMPEX period, we show that rain rates, rainwater mixing ratios, and raindrop number concentrations were increased relative to the Thompson–Eidhammer microphysical parameterization, while concurrently decreasing raindrop diameters in liquid-phase clouds. These changes are consistent with an increase in simulated warm rain. Finally, real-time evaluation of the scheme from August 2021 to August 2022 demonstrated improved precipitation prediction over coastal areas of the Pacific Northwest.

Significance Statement

Although the accurate simulation of warm rain is critical to forecasting the hydrology of coastal areas and windward slopes, many warm rain parameterizations underpredict precipitation in these locations. This study introduces and evaluates modifications to the Thompson–Eidhammer microphysics parameterization scheme that significantly improve the accuracy of rainfall prediction in those regions.

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Satoki Tsujino
,
Takeshi Horinouchi
, and
Udai Shimada

Abstract

Doppler weather radars are powerful tools for investigating the inner-core structure and intensity of tropical cyclones (TCs). The Doppler velocity can provide quantitative information on the vortex structure in the TCs. The generalized velocity track display (GVTD) technique has been used to retrieve the axisymmetric circulations and asymmetric tangential flows in the TCs from ground-based single-Doppler radar observations. GVTD can have limited applicability to asymmetric vortices due to the closure assumption of no asymmetric radial flows. The present study proposes a new closure formulation that includes asymmetric radial flows, based on the Helmholtz decomposition. Here it is assumed that the horizontal flow is predominantly rotational and expressed with a streamfunction, but limited inclusion of wavenumber-1 divergence is available. Unlike the original GVTD, the decomposition introduces consistency along the radius by solving all equations simultaneously. The new approach, named GVTD-X, is applied to analytical vortices and a real TC with asymmetric structures. This approach makes the retrieval of axisymmetric flow relatively insensitive to the contamination from asymmetric flows and to small errors in storm center location. For an analytical vortex with a wavenumber-2 asymmetry, the maximum relative error of the axisymmetric tangential wind retrieved by GVTD-X is less than 2% at the radius of the maximum wind speed. In practical applications, errors can be evaluated by comparing results for different maximum wavenumbers. When applied to a real TC, GVTD-X largely suppressed an artificial periodic fluctuation that occurs in GVTD from the aliasing of the neglected asymmetric radial flows.

Significance Statement

In tropical cyclone (TC) wind retrievals from single-Doppler weather radar observations, closure assumptions are required for the retrieval equations. The present study proposes a new closure allowing asymmetric radial winds and improving retrievals for TC winds in the previously developed technique. The relative error of the axisymmetric tangential wind in idealized vortices from the new approach is less than 2% at the radius of the maximum wind speed. In applying to a real TC with an elliptical eyewall, we found that the new approach can largely suppress an artificial evolution of the tangential winds in the previous retrieval technique.

Open access
Mary H. Korendyke
and
David M. Straus

Abstract

This paper analyzes the relationships between the circulation regimes of the 500-hPa height (z500) and 250-hPa zonal winds (u250) in the Pacific–North America region during boreal winter, and the 45-day Northern Hemisphere oscillation in z500. The regimes were calculated using a k-means clustering applied to the leading 12 principal components of the combined z500–u250 anomaly fields. We divided the oscillation into eight arbitrary phases. The oscillation phase z500 composite maps are spatially well correlated with regime z500 composites: phases 1–2 are best correlated with the Arctic Low, phases 3–5 are best correlated with the Pacific Trough, phase 6 is best correlated with the Arctic High, and phases 7–8 are best correlated with the Alaskan Ridge. We found that these correlations are generally consistent with the regimes that tend to occur during the individual oscillation phases: the Arctic Low occurs above significance in phases 1–2, the Pacific Trough occurs above significance in phase 3, and Alaskan Ridge occurs above significance in phases 7–8. Therefore, the oscillation has a preferred order with respect to the regimes. The regime transitions indicate a pattern that moves through the Pacific Wavetrain, a regime that appears for k = 5 as a mean state. Transitions out of this regime into different regimes are preferred in different phases of the oscillation. These results imply a possible enhancement to regime prediction using the low-frequency oscillations in combination with regimes.

Significance Statement

Subseasonal prediction, weather forecasting in the 2–4-week range, is important for many parts of society, e.g., water managers, emergency response units, and farmers. However, current prediction skill in this time range is low. This paper performs an initial analysis of a possible method to increase weather statistic prediction skill beyond 10 days in the winter for the Pacific–North America region. This is done by combining two ways of looking at large, long-lasting patterns of pressure systems in the atmosphere, which are associated with various weather statistics like precipitation extremes and storminess. The results indicate this method holds potential skill for enhancing subseasonal prediction. Further investigation might yield forecasting improvements in this important time range.

Open access
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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