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Travis Griggs
,
James Flynn
,
Yuxuan Wang
,
Sergio Alvarez
,
Michael Comas
, and
Paul Walter

Abstract

Photochemical modeling outputs showing high ozone concentrations over the Gulf of Mexico and Galveston Bay during ozone episodes in the Houston-Galveston-Brazoria (HGB) region have not been previously verified using in-situ observations. Such data was collected systematically, for the first time, from July-October 2021 from three boats deployed for the Galveston Offshore Ozone Observations (GO3) and Tracking Aerosol Convection Interactions ExpeRiment - Air Quality (TRACER-AQ) field campaigns. A pontoon boat and a commercial vessel operated in Galveston Bay, while another commercial vessel operated in the Gulf of Mexico offshore of Galveston. All three boats had continuously operating sampling systems that included ozone analyzers and weather stations, and the two boats operating in Galveston Bay had a ceilometer. The sampling systems operated autonomously on the two commercial boats as they traveled their daily routes. Thirty-seven ozonesondes were launched over water on forecast high ozone days in Galveston Bay and the Gulf of Mexico. During the campaigns, multiple periods of ozone exceeding 100 ppbv were observed over water in Galveston Bay and the Gulf of Mexico. These events included previously identified conditions for high ozone events in the HGB region, such as the bay/sea breeze recirculation and post-frontal environments, as well as a localized coastal high ozone event after the passing of a tropical system (Hurricane Nicholas) that was not well forecast.

Open access
YaoKun Li

Abstract

The ENSO phase locking to the annual cycle is investigated by applying a spatiotemporal oscillator (STO) model, in which the annual cycle of the climatological thermocline depth and its associated parameter are introduced. It is easy to derive its analytic solution which demonstrates a harmonic oscillation of a combined variable. The ENSO phase locking can be theoretically proven by discussing the distribution of the calendar months of the peak time of the sea surface temperature anomaly (SSTA) time series. The calendar months of the peak time can be divided into two parts. The first part can evenly distribute in any a month of a year and hence no phase locking feature while the second part, directly associated with the annual cycle, adds an increment onto the first part to make it move toward the phase of the annual cycle to realize the phase locking feature. This is the physical mechanism of the ENSO phase locking. With observed seasonal variation of the climatological thermocline depth, calculated Niño 3.4 index time series approach to extreme values in November with higher probability, reproducing the observed phase locking phenomenon quite well. The maximum probability of the calendar month that the ENSO peak time occurs is directly determined by the phase of the annual cycle and the stronger the annual cycle is, the larger the maximum probability is.

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Gregory J. Stumpf
and
Sarah M. Stough

Abstract

Legacy National Weather Service verification techniques, when applied to current static severe convective warnings, exhibit limitations, particularly in accounting for the precise spatial and temporal aspects of warnings and severe convective events. Consequently, they are not particularly well-suited for application to some proposed future National Weather Service warning delivery methods considered under the Forecasting a Continuum of Environmental Threats (FACETs) initiative. These methods include Threats-In-Motion (TIM), wherein warning polygons move nearly continuously with convective hazards, and Probabilistic Hazard Information (PHI), a concept that involves augmenting warnings with rapidly updating probabilistic plumes.

A new geospatial verification method was developed and evaluated, by which warnings and observations are placed on equivalent grids within a common reference frame, with each grid cell being represented as a hit, miss, false alarm, or correct null for each minute. New measures are computed, including false alarm area, and location-specific lead time, departure time, and false alarm time.

Using the 27 April 2011 tornado event, we applied the TIM and PHI warning techniques to demonstrate the benefits of rapidly updating warning areas, showcase the application of the geospatial verification method within this novel warning framework, and highlight the impact of varying probabilistic warning thresholds on warning performance. Additionally, the geospatial verification method was tested on a storm-based warning dataset (2008-2022) to derive annual, monthly, and hourly statistics.

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Chris Vagasky
,
Ronald L. Holle
,
Martin J. Murphy
,
John A. Cramer
,
Ryan K. Said
,
Mitchell Guthrie
, and
Jesse Hietanen

Abstract

The number of cloud-to-ground (CG) flashes over the contiguous U.S. (CONUS) has been estimated to be from as small as 25 million per year to as many as 40 million. In addition, many CG flashes contact the ground in more than one place. To clarify these values, recent data from the National Lightning Detection Network (NLDN) have been examined since the network is performing well enough to make precise updates to the number of CG flashes and their associated ground contact points. The average number of CG flashes is calculated to be about 23.4 million per year over CONUS, and the average number of ground contact points is calculated as 36.8 million per year. Knowledge of these two parameters is critical to lightning protection standards, as well as better understanding of the effects of lightning on forest fire initiation, geophysical interactions, human safety, and applications that benefit from knowing that a single flash may transfer charge to ground in multiple, widely-spaced locations. Sensitivity tests to assess the effects of misclassification of CG and in-cloud (IC) lightning are also made to place bounds on these estimates; and the likely uncertainty is a few percent.

Open access
Fang-Ching Chien
and
Yen-Chao Chiu

Abstract

This paper investigates the impact of the environmental conditions during the first half of the 2020 mei-yu season (Y20) and the southwest vortex (SWV), as well as their interaction, on heavy precipitation in southern Taiwan during late May 2020, based on a quantitative approach through ensemble simulations. The control experiment successfully replicates observed heavy precipitation in southern and central Taiwan and reveals a positive spatial correlation between precipitation occurrence probabilities and mean accumulated precipitation, emphasizing continuous rainfall accumulation over intermittent extreme events. Comparative analyses with sensitivity experiments elucidate that the Y20, featuring an extended western North Pacific subtropical high, intensify pressure gradients and southwesterly flow near Taiwan, favoring precipitation in windward regions but hindering it in the east. The SWV creates a moist and vortical environment near Taiwan, amplifying moisture supply and westerly winds, promoting precipitation in southern Taiwan, and enhancing frontal activity. The interaction between the SWV and the Y20, though limited in its impact on providing favorable wind and moisture conditions for precipitation southwest of Taiwan, significantly contributes to precipitation in southern Taiwan. The reason is that although the SWV primarily enhances moisture and the Y20 predominantly boost southwesterly flow, creating favorable conditions for rainfall, substantial precipitation occurs only when both factors converge in a nonlinear interaction. The interaction increases frontal activity over the Taiwan Strait and influences the movement and strength of the SWV, enhancing southwesterly flow and moisture flux in southwestern Taiwan.

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Sheng Chen
,
Wen Zheng Jiang
,
Yuhuan Xue
,
Hongyu Ma
,
Yong Qing Yu
,
Zhanli Wang
, and
Fangli Qiao

Abstract

The large scatter of the drag coefficient CD at a given wind speed and its discrepancy in coastal regions and open oceans have received increasing attention. However, the parameterization of CD is still an open question, especially in coastal regions. Therefore, this study systematically investigated the influence of surface waves on wind stress based on in situ observations of surface waves and air–sea fluxes on three coastal tower-based platforms in different regions. A formulation that is a function of only wind speed was established in the wind speed range of 1–20 m s−1, and when extended to 30 m s−1, it could predict the saturation of coastal CD at a 20 m s−1 wind speed and then the attenuation. However, this wind-based formulation does not simulate the scatter of CD in practice. By further analyzing the effect of wave states on wind stress, the parameters of wave age and directionality of wind and waves were incorporated into the wind-based formulation, and a new wave-state-based parameterization on CD was proposed, which can estimate the widely spread CD values to a large extent and the saturation of CD. The RMSE between this new parameterization and observations reduce approximately 20% and 9% relative to the COARE and wind-based formula. The applicability of this new parameterization was further demonstrated through a comparison between the newly parameterized CD and observed asymmetric CD in different quadrants of a tropical cyclone. The wave-state-based parameterization scheme requires three parameters, wind speed U10, wave age β, and wave off-wind angle θ, and it is expected to be applied to coastal regions.

Significance Statement

Wind stress over the ocean plays an important role in numerical simulations for both the atmosphere and ocean, which requires accurate parameterization. However, parameterization of wind stress or drag coefficient CD is still an open question due to the complexity of the potential factors behind wind stress, especially for coastal regions. This manuscript provided a new wave-state-based parameterization scheme at low to high wind speeds for coastal regions, based on field observations on three coastal towers. This new parameterization can predict the saturation of CD at a wind speed of 20 m s−1 and then the attenuation, agreeing well with the previous coastal observations, and simulate the large scatter of CD to a large extent. Furthermore, it can predict the asymmetric CD in different quadrants of a tropical cyclone, consistent with the observations. This parameterization scheme requires only three parameters, wind speed, wave age, and misalignment angle between wind and wave, which can be conveniently applied to the numerical models.

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Katherine E. McKeown
,
Casey E. Davenport
,
Matthew D. Eastin
,
Sarah M. Purpura
, and
Roger R. Riggin IV

Abstract

The evolution of supercell thunderstorms traversing complex terrain is not well understood and remains a short-term forecast challenge across the Appalachian Mountains of the eastern United States. Although case studies have been conducted, there has been no large multi-case observational analysis focusing on the central and southern Appalachians. To address this gap, we analyzed 62 isolated warm-season supercells that occurred in this region. Each supercell was categorized as either crossing (∼40%) or noncrossing (∼60%) based on their maintenance of supercellular structure while traversing prominent terrain. The structural evolution of each storm was analyzed via operationally relevant parameters extracted from WSR-88D radar data. The most significant differences in radar-observed structure among storm categories were associated with the mesocyclone; crossing storms exhibited stronger, wider, and deeper mesocyclones, along with more prominent and persistent hook echoes. Crossing storms also moved faster. Among the supercells that crossed the most prominent peaks and ridges, significant increases in base reflectivity, vertically integrated liquid, echo tops, and mesocyclone intensity/depth were observed, in conjunction with more frequent large hail and tornado reports, as the storms ascended windward slopes. Then, as the supercells descended leeward slopes, significant increases in mesocyclone depth and tornado frequency were observed. Such results reinforce the notion that supercell evolution can be modulated substantially by passage through and over complex terrain.

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Aiswarya Lakshmi K.K.
,
Swaroop Sahoo
,
Sounak Kumar Biswas
, and
V. Chandrasekar

Abstract

Weather radars with dual-polarization capabilities enable the study of various characteristics of hydrometeors, including their size, shape, and orientation. Radar polarimetric measurements, coupled with Doppler information, allow for analysis in the spectral domain. This analysis can be leveraged to reveal valuable insight into the microphysics and kinematics of hydrometeors in precipitation systems. This paper uses spectral polarimetry to investigate precipitation microphysics and kinematics in storm environments observed during the RELAMPAGO field experiment in Argentina. This study uses range height indicator (RHI) scan measurements from a C-Band polarimetric Doppler weather radar deployed during the field campaign. In this work, the impact of storm dynamics on hydrometeors is studied, including the size sorting of hydrometeors due to vertical wind shear. In addition, particle microphysical processes because of aggregation and growth of ice crystals in anvil clouds, as well as graupel formation resulting from the riming of ice crystals and dendrites are also analyzed here. The presence of different particle size distributions because of the mixing of hydrometeors in a sheared environment and resulting size sorting has been reported using spectral differential reflectivity (sZdr ) slope. Spectral reflectivity (sZh ) and sZdr have also been used to understand the signature of ice crystal aggregation in an anvil cloud. The regions of pristine ice crystals are identified from vertical profiles of spectral polarimetric variables in anvil cloud because of sZh < 0 dB and sZdr values around 2 dB. It is also found that the growth process of these ice crystals causes a skewed bimodal sZh spectrum due to the presence of both pristine ice crystals and dry snow. Next, graupel formation due to riming has been studied and it is found that the riming process produces sZh values of about 10 dB and corresponding sZdr values of 1 dB. This positive sZdr indicates the presence of needle/columnar secondary ice particles formed by ice multiplication processes in the riming zones. Lastly, the temporal evolution of a storm is investigated by analyzing changes in hydrometeor types with time and their influence on the spectral polarimetric variables.

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Yoonjin Lee
and
Kyle Hilburn

Abstract

Geostationary Operational Environmental Satellites (GOES) Radar Estimation via Machine Learning to Inform NWP (GREMLIN) is a machine learning model that outputs composite reflectivity using GOES-R Series Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) input data. GREMLIN is useful for observing severe weather and initializing convection for short-term forecasts, especially over regions without ground-based radars. This study expands the evaluation of GREMLIN’s accuracy against the Multi-Radar/Multi-Sensor (MRMS) System to the entire contiguous United States (CONUS) for the entire annual cycle. Regional and temporal variation of validation metrics are examined over CONUS by season, day-of-year, and time-of-day. Since GREMLIN was trained with data in spring and summer, root-mean square difference (RMSD) and bias are lowest in the order of summer, spring, fall, and winter. In summer, diurnal patterns of RMSD follow those of precipitation occurrence. Winter has the highest RMSD due to cold surfaces mistaken as precipitating clouds, but some of these errors can be removed by applying the ABI clear sky mask product and correcting biases using a lookup table. In GREMLIN, strong echoes are closely related to the existence of lightning and corresponding low brightness temperatures, which result in different error distributions over different regions of CONUS. This leads to negative biases in cold seasons over Washington state, lower 30 dBZ critical success index due to high misses over the Northeast, and higher false alarms over Florida due to higher frequency of lightning.

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Jie Peng
,
Miaohua Mao
, and
Meng Xia

Abstract

The dynamics of typhoon-induced waves in semienclosed seas become an interesting topic with the increase of typhoon intensity. Based on the calibrated Simulating Waves Nearshore (SWAN) model, wave dynamics were investigated under distinct typhoon tracks [e.g., Matmo (2014), Rumbia (2018), and Lekima (2019)] in the Bohai Sea. Distributions of significant wave heights (SWHs) are affected by the typhoon wind fields and are directly related to the typhoon tracks. The classical JONSWAP wave spectra were adopted for the analysis of sea states (e.g., wind seas or swells) to further explain variations in wave heights. Results indicate that the dominant sea state with higher energy experiences significant spatiotemporal variability under distinct tracks. For typhoons passing through the central part of the Bohai Sea (e.g., Rumbia), high-energy waves are observed under swell-dominated and mixed sea states, which are subjected to the fetch limitation in the semienclosed sea and rapid changes in typhoon winds. The high energy waves induced by other typhoons passing along the edges of the Bohai Sea correspond to the wind-sea-dominated sea state. Spatiotemporal variability of the sea state exhibits a high correlation with its position relative to the typhoon center. Therefore, a reference frame based on the radius of the maximum wind speed was established to discuss the sea states in this semienclosed sea. Further investigations reveal that swells (wind seas) dominate the regions within the radius of the maximum wind speed (elsewhere), and the double-peaked wave spectra tend to appear in the left quadrants.

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