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Rainfall microphysical characteristics including raindrop fall speed, axis ratio, and canting angle were measured through field observations by using a high-speed optical disdrometer (HOD) during and after tornadic severe storm passage. High and low wind and turbulence characteristics were observed during and after passage, respectively, which provided an opportunity to compare the effects of the different wind and turbulence characteristics on raindrop characteristics. During passage, 9.4% of the raindrops larger than 1.0 mm in volume equivalent diameter (D) were identified as subterminal, whereas only 0.5% of the raindrops of the same size were detected as subterminal after passage. Contrary to findings in literature, we could not find any distinct superterminal fall speed behavior for raindrops with D < 1.0 mm during or after passage. For raindrops with D > 2.0 mm, deviations of the axis ratio distribution from the predicted distribution for the equilibrium raindrops were observed, and the deviations during passage were larger than those after passage. The deviations of the axis ratio distributions from the predicted distributions for the equilibrium raindrops were also observed for midsized (1.0 < D < 2.0 mm) raindrops; however, these deviations during and after passage were of similar magnitude. The canting angle distribution for raindrops with D > 2.0 mm was found to have the mean value of approximately 0° both during and after passage and the standard deviation values of 24.7° during passage and 13.6° after passage. This study shows the clear influence of wind on various rainfall microphysical characteristics and documents the observed value ranges of these characteristics under strong wind that are of importance for a number of rainfall applications, including radar rainfall retrievals and rainfall modeling.

To forecast tropical cyclone (TC) intensity and structure changes with fidelity, numerical weather prediction models must be “high definition,” i.e., horizontal grid spacing ≤ 3 km, so that they permit clouds and convection and resolve sharp gradients of momentum and moisture in the eyewall and rainbands. Storm-following nests are computationally efficient at fine resolutions, providing a practical approach to improve TC intensity forecasts. Under the Hurricane Forecast Improvement Project, the operational Hurricane Weather Research and Forecasting (HWRF) system was developed to include telescopic, storm-following nests for a single TC per model integration. Subsequently, HWRF evolved into a state-of-the-art tool for TC predictions around the globe, although its single-storm nesting approach does not adequately simulate TC–TC interactions as they are observed. Basin-scale HWRF (HWRF-B) was developed later with a multistorm nesting approach to improve the simulation of TC–TC interactions by producing high-resolution forecasts for multiple TCs simultaneously. In this study, the multistorm nesting approach in HWRF-B was compared with a single-storm nesting approach using an otherwise identical model configuration. The multistorm approach demonstrated TC intensity forecast improvements, including more realistic TC–TC interactions. Storm-following nests developed in HWRF and HWRF-B will be foundational to NOAA’s next-generation hurricane application in the Unified Forecast System.

Accurate estimation of the potential “upper limit” for extreme precipitation is critical for dam safety and water resources management, as dam failures pose significant risks to life and property. Methods used to estimate the theoretical upper limit of precipitation are often outdated and in need of updating. The rarity of extreme events means that old storms with limited observational data are often used to define the upper bound of precipitation. Observations of many important old storms are limited in spatial and temporal coverage, and sometimes of dubious quality. This reduces confidence in flood hazard assessments used in dam safety evaluations and leads to unknown or uncertain societal risk. This paper describes a method for generating and applying ensembles of high-resolution, state-of-the-art numerical model simulations of historical past extreme precipitation events to meet contemporary stakeholder needs. The method was designed as part of a research-to-application-focused partnership project to update state dam safety rules in Colorado and New Mexico. The results demonstrated multiple stakeholder and user benefits that were applied directly into storm analyses utilized for extreme rainfall estimation, and diagnostics were developed and ultimately used to update Colorado state dam safety rules, officially passed in January 2020. We discuss how what started as a prototype research foray to meet a specific user need may ultimately inform wider adoption of numerical simulations for water resources risk assessment, and how the historical event downscaling method performed offers near-term, implementable improvements to current dam safety flood risk estimates that can better serve society today.

The frontal structures of extratropical cyclones developing in the northwestern Pacific storm track are relatively poorly understood compared with those in Europe and the Atlantic Ocean, for which representative conceptual models have been developed. In this paper, the structures of cyclones and their associated fronts in the northwestern Pacific (NP), as well as in the Okhotsk Sea and Sea of Japan (OJ), are examined at their developing and mature stages using Japanese 55-year Reanalysis dataset. Furthermore, the frontal structures in the NP are compared with those in the northwestern Atlantic (NA). At the time of maximum deepening rate, cyclones in the NP are accompanied by strong warm and cold fronts, whereas cyclones in the OJ are more frequently accompanied by cold fronts than by warm fronts and tend to have stronger cold fronts than warm fronts. The weaker warm fronts than cold fronts to the east and northeast of cyclones in the OJ is likely due to the cyclones developing to the north and away from the region where the horizontal gradient of environmental potential temperature is strong. A comparison between mature cyclones in the NP and NA shows that the warm fronts in the NA tend to extend northeastward, whereas those in the NP extend more southeastward. These differences in warm fronts between NP and NA are suggested to be due to the difference in the horizontal structures of the warm currents between NP and NA.

Lasting updrafts are necessary to produce severe hail; conventional wisdom suggests that extremely large hailstones require updrafts of commensurate strength. Because updraft strength is largely controlled by convective available potential energy (CAPE), one would expect environments with larger CAPE to be conducive to storms producing larger hail. By systematically varying CAPE in a horizontally homogeneous initial environment, we simulate hail production in high-shear, high-instability supercell storms using Cloud Model 1 and a detailed 3D hail growth trajectory model. Our results suggest that CAPE modulates the updraft’s strength, width, and horizontal wind field, as well as the liquid water content along hailstones’ trajectories, all of which have a significant impact on final hail sizes. In particular, hail sizes are maximized for intermediate CAPE values in the range we examined. Results show a non-monotonic relationship between the hailstones’ residence time and CAPE due to changes to the updraft wind field. The ratio of updraft area to southerly wind speed within the updraft serves as a proxy for residence time. Storms in environments with large CAPE may produce smaller hail because the in-updraft horizontal wind speeds become too great, and hailstones are prematurely ejected out of the optimal growth region. Liquid water content (LWC) along favorable hailstone pathways also exhibits peak values for intermediate CAPE values, owing to the horizontal displacement across the midlevel updraft of moist inflow air from differing source levels. In other words, larger CAPE does not equal larger hail, and storm-structural nuances must be examined.

Recent numerical modeling studies demonstrate that dry tropical cyclones can be stably sustained via a supply of surface sensible heat flux. This raises questions of whether surface sensible heat flux (SHX) and latent heat flux (LHX) have the same effect on the intensity evolution of tropical cyclones. An estimation of equivalent potential temperature budget in the boundary layer shows that LHX leads to larger increase in equivalent potential temperature than SHX even when they possess the same magnitude. By formulating these two kinds of surface heat fluxes with the same mathematical framework, the simulated intensifications of moist and dry tropical cyclones are compared, with the former driven exclusively by LHX and the latter by SHX. Results show significantly larger intensification rates for the tropical cyclone driven by LHX than that by SHX, revealing low effectiveness of SHX in the intensification of tropical cyclones. The diabatic heating in the moist tropical cyclone occurs accompanying the convection, while it is merely pronounced near the surface in the dry tropical cyclone and is decoupled from the dry convection. A new surface pressure tendency equation is proposed, without incorporating the implicit pressure tendency term on the right-hand side. The budget analysis indicates that the SHX is less effective than LHX in lowering surface central pressure and therefore in tropical cyclone intensification. A series of sensitivity experiments suggest that the threshold of energy input required for spinning up a tropical cyclone is lower in the form of LHX than that of SHX.

In this first part of a two-part study, the three-dimensional structure of the inner-core boundary layer (BL) is investigated in a full-physics simulation of Hurricane Irma (2017). The BL structure is highlighted during periods of intensity change, with focus on features and mechanisms associated with storm decay. The azimuthal structure of the BL is shown to be linked to the vertical wind shear and storm motion. The BL inflow becomes more asymmetric under increased shear. As BL inflow asymmetry amplifies, asymmetries in the low-level primary circulation and thermodynamic structure develop. A mechanism is identified to explain the onset of pronounced structural asymmetries in coincidence with external forcing (e.g., through shear) that would amplify BL inflow along limited azimuth. The mechanism assumes enhanced advection of absolute angular momentum along the path of the amplified inflow (e.g., amplified downshear), which results in local spinup of the vortex and development of strong supergradient flow downwind and along the BL top. The associated agradient force results in the outward acceleration of air immediately above the BL inflow, affecting fields including divergence, vertical motion, entropy advection, and inertial stability. In this simulation, descending inflow in coincidence with amplified shear is identified as the conduit through which low-entropy air enters the inner-core BL, thereby hampering convection downwind and resulting in storm decay.

We have developed a technique to estimate the three-dimensional (3D) location of lightning optical pulses based on the stereo view of common lightning pulses from two different orbital instruments. The technique only requires the satellite position and the look vector to the lightning optical source. An example dataset of the Geostationary Lightning Mappers (GLMs) on GOES-16 and GOES-17 from 10 June 2019 is used to illustrate the technique. For this dataset, we find that the values for the stereo determination of cloud-top altitudes are on average lower by 740 m than the ones calculated from the lightning ellipsoid that is currently applied during geolocation. When we compare the locations to the Advanced Baseline Imager (ABI) Cloud Height Algorithm (ACHA), we find that our technique also produces slightly lower altitude values by 240 m. There is greater spread in our technique than either the lightning ellipsoid or the ABI cloud-top height that is likely due to the incorrect pairing of groups between the two GLMs and the 8–14-km resolution in the group locations. Based on GLM location errors derived from comparisons to ground truth sources, the uncertainty in the radial location determined by the stereo location technique is 5.2 km, while the altitude uncertainty is 4.0 km. The technique can be used to 3D map lightning or other optical sources such as bolides and other upper-atmospheric optical phenomena from any two orbital sensors with overlapping fields of view.

A 50-member convection-allowing ensemble was used to examine environmental factors influencing afternoon convection initiation (CI) and subsequent severe weather on 5 April 2017 during intensive observing period (IOP) 3b of the Verification of the Origins of Rotation in Tornadoes Experiment in the Southeast (VORTEX-SE). This case produced several weak tornadoes (rated EF1 or less), and numerous reports of significant hail (diameter ≥ 2 in.; ≥~5 cm), ahead of an eastward-moving surface cold front over eastern Alabama and southern Tennessee. Both observed and simulated CI was facilitated by mesoscale lower-tropospheric ascent maximized several tens of kilometers ahead of the cold-frontal position, and the simulated mesoscale ascent was linked to surface frontogenesis in the ensemble mean. Simulated maximum 2–5 km AGL updraft helicity (UHmax) was used as a proxy for severe-weather-producing mesocyclones, and considerable variability in UHmax occurred among the ensemble members. Ensemble members with UHmax > 100 m2 s−2 had stronger mesoscale ascent than in members with UHmax < 75 m2 s−2, which facilitated timelier CI by producing greater adiabatic cooling and moisture increases above the PBL. After CI, storms in the larger UHmax members moved northeastward toward a mesoscale region with larger convective available potential energy (CAPE) than in smaller UHmax members. The CAPE differences among members were influenced by differences in the location of an antecedent mesoscale convective system, which had a thermodynamically stabilizing influence on the environment toward which storms were moving. Despite providing good overall guidance, the model ensemble overpredicted severe weather likelihoods in northeastern Alabama, where comparisons with VORTEX-SE soundings revealed a positive CAPE bias.

This paper examines the impact of the meridional and vertical structures of a preexisting upstream storm track (PUST) organized by preexisting synoptic-scale eddies on eddy-driven blocking in a nonlinear multiscale interaction model. In this model, the blocking is assumed, based on observations, to be comprised of barotropic and first baroclinic modes, whereas the PUST consists of barotropic, first baroclinic, and second baroclinic modes. It is found that the nonlinearity (dispersion) of blocking is intensified (weakened) with increasing amplitude of the first baroclinic mode of the blocking itself. The blocking tends to be long lived in this case. The lifetime and strength of blocking are significantly influenced by the amplitude of the first baroclinic mode of blocking for given basic westerly winds (BWWs), whereas its spatial pattern and evolution are also affected by the meridional and vertical structures of the PUST. It is shown that the blocking mainly results from the transient eddy forcing induced by the barotropic and first baroclinic modes of PUST, whereas its second baroclinic mode contributes little to the transient eddy forcing. When the PUST shifts northward, eddy-driven blocking shows an asymmetric dipole structure with a strong anticyclone–weak cyclone in a uniform BWW, which induces northward-intensified westerly jet and storm-track anomalies mainly on the north side of blocking. However, when the PUST has no meridional shift and is mainly located in the upper troposphere, a north–south antisymmetric dipole blocking and an intensified split jet with maximum amplitude in the upper troposphere form easily for vertically varying BWWs without meridional shear.

Proximity soundings have long been used to explore how the vertical structure of temperature, humidity, and winds influence convective storms and their associated hazards. In severe thunderstorm research and forecasting, convective parameters are often used to summarize certain characteristics of the sounding. While extremely useful, these parameters are unable to describe the rich complexity that is readily apparent in hodographs and skew T–logp diagrams. Motivated by a desire to retain more of these details, the present study uses self-organizing maps (SOMs) to group soundings based on their full vertical structure. The analysis makes use of a sample of more than 10 000 model proximity soundings for right-moving supercells associated with tornadoes and significant severe hail and straight-line winds in the contiguous United States (CONUS). Separate SOMs are developed for the wind and thermodynamic profiles, each with 3 × 3 nodes, resulting in a set of nine hodographs and nine skew T–logp diagrams that broadly represent the spectrum of near-storm environments for significant severe right-moving supercells in the CONUS. Both SOMs are shown to provide a good representation of the variability in key convective parameters, although, for the thermodynamic SOM, variations in LCL heights and midlevel lapse rates are somewhat limited. Based on the soundings assigned to them, the SOM nodes are characterized in terms of their associated hazards, their relationship with storm mode and mesocyclone strength, and their spatial and temporal variability. Potential applications of the SOMs in severe weather forecasting and idealized numerical simulations are also highlighted.

Tropical cyclone (TC) translation speed (TCTS) can affect the duration of TC-related disasters, which is critical to coastal and inland areas. The long-term variation of TCTS and its relationship to the variability of the midlatitude jet stream and storm migration is discussed here for storms near the North Atlantic coast during 1948–2019. Our results reveal the prominent seasonality in the long-term variation of TCTS, which can be largely explained by the seasonality in the covariations of the midlatitude jet stream and storm locations. Specifically, significant increases of TCTS occur in June and October during the past decades, which may result from the equatorward displacement of the jet stream and poleward migration of storm locations. Prominent slowdown of TCTS is found in August, which is related to the weakened jet strength and equatorward storm migration. In September, the effects of poleward displacement and weakening of the jet stream on TCTS are largely compensated by the poleward storm migration, and therefore no significant change in TCTS is observed. Meanwhile, the multidecadal variability of the Atlantic may contribute to the multidecadal variability of TCTS. Our findings emphasize the significance in taking a seasonality view in discussing the variability and trends of near-coast Atlantic TCTS under climate change.

Author(s): Lin, II; Rogers, RF; Huang, HC; Liao, YC; Herndon, D; Yu, JY; Chang, YT; Zhang, JA; Patricola, CM; Pun, IF; Lien, CC | Abstract: Devastating Japan in October 2019, Supertyphoon (STY) Hagibis was an important typhoon in the history of the Pacific. A striking feature of Hagibis was its explosive rapid intensification (RI). In 24 h, Hagibis intensified by 100 knots (kt; 1 kt ≈ 0.51 m s-1), making it one of the fastest-intensifying typhoons ever observed. After RI, Hagibis's intensification stalled. Using the current typhoon intensity record holder, i.e., STY Haiyan (2013), as a benchmark, this work explores the intensity evolution differences of these two high-impact STYs. We found that the extremely high prestorm sea surface temperature reaching 30.5°C, deep/warm prestorm ocean heat content reaching 160 kJ cm-2, fast forward storm motion of ∼8 m s-1, small during-storm ocean cooling effect of ∼0.5°C, significant thunderstorm activity at its center, and rapid eyewall contraction were all important contributors to Hagibis's impressive intensification. There was 36% more air-sea flux for Hagibis's RI than for Haiyan's. After its spectacular RI, Hagibis's intensification stopped, despite favorable environments. Haiyan, by contrast, continued to intensify, reaching its record-breaking intensity of 170 kt. A key finding here is the multiple pathways that storm size affected the intensity evolution for both typhoons. After RI, Hagibis experienced a major size expansion, becoming the largest typhoon on record in the Pacific. This size enlargement, combined with a reduction in storm translational speed, induced stronger ocean cooling that reduced ocean flux and hindered intensification. The large storm size also contributed to slower eyewall replacement cycles (ERCs), which prolonged the negative impact of the ERC on intensification.

This article provides an overview of the experimental design, execution, education and public outreach, data collection, and initial scientific results from the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. RELAMPAGO was a major field campaign conducted in the Córdoba and Mendoza provinces in Argentina and western Rio Grande do Sul State in Brazil in 2018–19 that involved more than 200 scientists and students from the United States, Argentina, and Brazil. This campaign was motivated by the physical processes and societal impacts of deep convection that frequently initiates in this region, often along the complex terrain of the Sierras de Córdoba and Andes, and often grows rapidly upscale into dangerous storms that impact society. Observed storms during the experiment produced copious hail, intense flash flooding, extreme lightning flash rates, and other unusual lightning phenomena, but few tornadoes. The five distinct scientific foci of RELAMPAGO—convection initiation, severe weather, upscale growth, hydrometeorology, and lightning and electrification—are described, as are the deployment strategies to observe physical processes relevant to these foci. The campaign’s international cooperation, forecasting efforts, and mission planning strategies enabled a successful data collection effort. In addition, the legacy of RELAMPAGO in South America, including extensive multinational education, public outreach, and social media data gathering associated with the campaign, is summarized.

Both hurricanes and nor’easters can be destructive and deadly. The current study investigates whether, when all other features of a storm warning message are held constant, people perceive the risks posed by nor’easters and hurricanes differently and whether these differences affect their attitudes and decisions about taking protective action. We conducted an online experiment involving 1,700 Americans residing in northeastern coastal ZIP codes to test the effects of storm type (hurricane vs nor’easter). Participants were told that their area was under an evacuation order due to either a predicted hurricane or nor’easter. Reported message comprehension and perceived relevance were similar across storm type; however, storm type had small but significant effects on other dependent measures. Those in the hurricane condition were more likely to believe the storm would be severe (p = 0.007). They were also more likely to say that it is important to evacuate, that they would evacuate their homes, and that they would recommend to their neighbors that they evacuate (p < 0.001). Additional analysis demonstrated that the effect of storm type on evacuation likelihood is mediated, at least in part, by perceived severity. These findings provide evidence that people perceive hurricanes as more severe and more likely to require taking protective action than nor’easters, even when other attributes of the storms remain the same. Forecasters, broadcast meteorologists, and emergency management professionals should consider these small but important differences in perceptions when communicating about these types of storms.

During the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations-Cloud, Aerosol, and Complex Terrain Interactions (RELAMPAGO-CACTI) field experiments in 2018–19, an unprecedented number of balloon-borne soundings were collected in Argentina. Radiosondes were launched from both fixed and mobile platforms, yielding 2712 soundings during the period 15 October 2018–30 April 2019. Approximately 20% of these soundings were collected by highly mobile platforms, strategically positioned for each intensive observing period, and launching approximately once per hour. The combination of fixed and mobile soundings capture both the overall conditions characterizing the RELAMPAGO-CACTI campaign, as well as the detailed evolution of environments supporting the initiation and upscale growth of deep convective storms, including some that produced hazardous hail and heavy rainfall. Episodes of frequent convection were characterized by sufficient quantities of moisture and instability for deep convection, along with deep-layer vertical wind shear supportive of organized or rotating storms. A total of 11 soundings showed most unstable convective available potential energy (MUCAPE) exceeding 6000 J kg−1, comparable to the extreme instability observed in other parts of the world with intense deep convection. Parameters used to diagnose severe-storm potential showed that conditions were often favorable for supercells and severe hail, but not for tornadoes, primarily because of insufficient low-level wind shear. High-frequency soundings also revealed the structure and evolution of the boundary layer leading up to convection initiation, convectively generated cold pools, the South American low-level jet (SALLJ), and elevated nocturnal convection. This sounding dataset will enable improved understanding and prediction of convective storms and their surroundings in subtropical South America, as well as comparisons with other heavily studied regions such as the central United States that have not previously been possible.

Microphysical processes within mixed-phase convective clouds can have cascading impacts on cloud properties and resultant precipitation. This paper investigates the role of microphysics in the lake-effect storm (LES) observed during intensive observing period 4 of the Ontario Winter Lake-effect Systems field campaign. A microphysical ensemble is composed of 24 simulations that differ in the microphysics scheme used (e.g., Weather Research and Forecasting Model microphysics options or a choice of two bulk adaptive habit models) along with changes in the representation of aerosol and potential ice nuclei concentrations, ice nucleation parameterizations, rain and ice fall speeds, spectral indices, ice habit assumptions, and the number of moments used for modeling ice-phase hydrometeors in each adaptive habit model. Each of these changes to microphysics resulted in varied precipitation types at the surface; 15 members forecast a mixture of snow, ice, and graupel, 7 members forecast only snow and ice, and the remaining 2 members forecast a combination of snow, ice, graupel, and rain. Observations from an optical disdrometer positioned to the south of the LES core indicate that 92% of the observed particles were snow and ice, 5% were graupel, and 3% were rain and drizzle. Analysis of observations spanning more than a point location, such as polarimetric radar observations and aircraft measurements of liquid water content, provides insight into cloud composition and processes leading to the differences at the surface. Ensemble spread is controlled by hydrometeor type differences spurred by processes or parameters (e.g., ice fall speed) that affect graupel mass.

Southern Ocean (SO) surface winds are essential for ventilating the upper ocean by bringing heat and CO2 to the ocean interior. The relationships between mixed-layer ventilation, the Southern Annular Mode (SAM), and the storm tracks remain unclear because processes can be governed by short-term wind events as well as long-term means.In this study, observed time-varying 5-day probability density functions (PDFs) of ERA5 surface winds and stresses over the SO are used in a singular value decomposition to derive a linearly independent set of empirical basis functions. The first modes of wind (72% of the total wind variance) and stress (74% of the total stress variance) are highly correlated with a standard SAM index (r = 0.82) and reflect SAM’s role in driving cyclone intensity and, in turn, extreme westerly winds. This Joint PDFs of zonal and meridional wind show that southerly and less westerly winds associated with strong mixed-layer ventilation are more frequent during short and distinct negative SAM phases. The probability of these short-term events might be related to mid-latitude atmospheric circulation. The second mode describes seasonal changes in the wind variance (16% of the total variance) that are uncorrelated with the first mode.The analysis produces similar results when repeated using 5-day PDFs from a suite of scatterometer products. Differences between wind product PDFs resemble the first mode of the PDFs. Together, these results show a strong correlation between surface stress PDFs and the leading modes of atmospheric variability, suggesting that empirical modes can serve as a novel pathway for understanding differences and variability of surface stress PDFs.

The Mississippi River basin (MRB) is a flash flood hotspot receiving the most frequent flash floods and highest average rainfall accumulation of any region in the United States. Given the destruction flash floods cause in the current climate in the MRB, it is critical to understand how they will change in a future, warmer climate in order to prepare for these impacts. Recent work utilizing convection-permitting climate simulations to analyze future precipitation changes in flash flood–producing storms in the United States shows that the MRB experiences the greatest future increase in flash flood rainfall. This result motivates the goal of the present study to better understand the changes to precipitation characteristics and vertical velocity in flash flood–producing storms in the MRB. Specifically, the variations in flash flood–producing storm characteristics related to changes in vertical velocity in the MRB are examined by identifying 484 historical flash flood–producing storms from 2002 and 2013 and studying how they change in a future climate using 4-km convection-permitting simulations under a pseudo–global warming framework. In a future climate, precipitation and runoff increase by 17% and 32%, respectively, in flash flood–producing storms in the MRB. While rainfall increases in all flash flood–producing storms due to similar increases in moisture, it increases the most in storms with the strongest vertical velocity, suggesting that storm dynamics might modulate future changes in rainfall. These results are necessary to predict and prepare for the multifaceted impacts of climate change on flash flood–producing storms in order to create more resilient communities.

Changes in land surface and aerosol characteristics from urbanization can affect dynamic and microphysical properties of severe storms, thus affecting hazardous weather events resulting from these storms such as hail and tornadoes. We examine the joint and individual effects of urban land and anthropogenic aerosols of Kansas City on a severe convective storm observed during the 2015 Plains Elevated Convection At Night (PECAN) field campaign, focusing on storm evolution, convective intensity, and hail characteristics. The simulations are carried out at the cloud-resolving scale (1 km) using a version of WRF-Chem in which the spectral-bin microphysics (SBM) is coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). It is found that the urban land effect of Kansas City initiated a much stronger convective cell and the storm got further intensified when interacting with stronger turbulence induced by the urban land. The urban land effect also changed the storm path by diverting the storm toward the city, mainly resulting from enhanced urban land-induced convergence in the urban area and around the urban–rural boundaries. The joint effect of urban land and anthropogenic aerosols enhances occurrences of both severe hail and significant severe hail by ~20% by enhancing hail formation and growth from riming. Overall the urban land effect on convective intensity and hail is relatively larger than the anthropogenic aerosol effect, but the joint effect is more notable than either of the individual effects, emphasizing the importance of considering both effects in evaluating urbanization effects.

Verification methods for convection-allowing models (CAMs) should consider the finescale spatial and temporal detail provided by CAMs, and including both neighborhood and object-based methods can account for displaced features that may still provide useful information. This work explores both contingency table–based verification techniques and object-based verification techniques as they relate to forecasts of severe convection. Two key fields in severe weather forecasting are investigated: updraft helicity (UH) and simulated composite reflectivity. UH is used to generate severe weather probabilities called surrogate severe fields, which have two tunable parameters: the UH threshold and the smoothing level. Probabilities computed using the UH threshold and smoothing level that give the best area under the receiver operating curve result in very high probabilities, while optimizing the parameters based on the Brier score reliability component results in much lower probabilities. Subjective ratings from participants in the 2018 NOAA Hazardous Weather Testbed Spring Forecasting Experiment (SFE) provide a complementary evaluation source. This work compares the verification methodologies in the context of three CAMs using the Finite-Volume Cubed-Sphere Dynamical Core (FV3), which will be the foundation of the U.S. Unified Forecast System (UFS). Three agencies ran FV3-based CAMs during the five-week 2018 SFE. These FV3-based CAMs are verified alongside a current operational CAM, the High-Resolution Rapid Refresh version 3 (HRRRv3). The HRRR is planned to eventually use the FV3 dynamical core as part of the UFS; as such evaluations relative to current HRRR configurations are imperative to maintaining high forecast quality and informing future implementation decisions.

The spatial and temporal variation in multiscale structures during the rapid intensification of Hurricane Michael (2018) are explored using a coupled atmospheric–oceanic dataset obtained from NOAA WP-3D and G-IV aircraft missions. During Michael’s early life cycle, the importance of ocean structure is studied to explore how the storm intensified despite experiencing moderate vertical shear. Michael maintained a fairly symmetric precipitation distribution and resisted lateral mixing of dry environmental air into the circulation upshear. The storm also interacted with an oceanic eddy field leading to cross-storm sea surface temperature (SST) gradients of ~2.5°C. This led to the highest enthalpy fluxes occurring left of shear, favoring the sustainment of updrafts into the upshear quadrants and a quick recovery from low-entropy downdraft air. Later in the life cycle, Michael interacted with more uniform and higher SSTs that were greater than 28°C, while vertical shear imposed asymmetries in Michael’s secondary circulation and distribution of entropy. Midlevel (~4–8 km) outflow downshear, a feature characteristic of hurricanes in shear, transported high-entropy air from the eyewall region outward. This outflow created a cap that reduced entrainment across the boundary layer top, protecting it from dry midtropospheric air out to large radii (i.e., >100 km), and allowing for rapid energy increases from air–sea enthalpy fluxes. Upshear, low-level (~0.5–2 km) outflow transported high-entropy air outward, which aided boundary layer recovery from low-entropy downdraft air. This study underscores the importance of simultaneously measuring atmospheric and oceanographic parameters to understand tropical cyclone structure during rapid intensification.

The Global Precipitation Measurement (GPM) constellation of spaceborne sensors provides a variety of direct and indirect measurements of precipitation processes. Such observations can be employed to derive spatially and temporally consistent gridded precipitation estimates either via data-driven retrieval algorithms or by assimilation into physically based numerical weather models. We compare the data-driven Integrated Multisatellite Retrievals for GPM (IMERG) and the assimilation-enabled NASA-Unified Weather Research and Forecasting (NU-WRF) model against Stage IV reference precipitation for four major extreme rainfall events in the southeastern United States using an object-based analysis framework that decomposes gridded precipitation fields into storm objects. As an alternative to conventional “grid-by-grid analysis,” the object-based approach provides a promising way to diagnose spatial properties of storms, trace them through space and time, and connect their accuracy to storm types and input data sources. The evolution of two tropical cyclones are generally captured by IMERG and NU-WRF, while the less organized spatial patterns of two mesoscale convective systems pose challenges for both. NU-WRF rain rates are generally more accurate, while IMERG better captures storm location and shape. Both show higher skill in detecting large, intense storms compared to smaller, weaker storms. IMERG’s accuracy depends on the input microwave and infrared data sources; NU-WRF does not appear to exhibit this dependence. Findings highlight that an object-oriented view can provide deeper insights into satellite precipitation performance and that the satellite precipitation community should further explore the potential for “hybrid” data-driven and physics-driven estimates in order to make optimal usage of satellite observations.

An improved understanding of common differences between tornadic and nontornadic supercells is sought using a large set of observations from the operational NEXRAD WSR-88D polarimetric radar network in the contiguous United States. In particular, data from 478 nontornadic and 294 tornadic supercells during a 7-yr period (2011–17) are used to produce probability-matched composite means of microphysical and kinematic variables. Means, which are centered on echo-top maxima and in a horizontal coordinate system rotated such that storm motion points in the positive x dimension, are created in altitude relative to ground level at times of peak echo-top altitude and peak midlevel rotation for nontornadic supercells and times at and prior to the first tornado in tornadic supercells. Robust differences between supercell types are found, with consistent characteristics at and preceding tornadogenesis in tornadic storms. In particular, the mesocyclone is found to be vertically aligned in tornadic supercells and misaligned in nontornadic supercells. Microphysical differences found include a low-level radar reflectivity hook echo aligned with and ~10 km right of storm center in tornadic supercells and displaced 5–10 km down-motion in nontornadic supercells, a low-to-midlevel differential radar reflectivity dipole that is oriented more parallel to storm motion in tornadic supercells and more perpendicular in nontornadic supercells, and a separation between enhanced differential radar reflectivity and specific differential phase (with unique displacement-relative correlation coefficient reductions) at low levels that is more perpendicular to storm motion in tornadic supercells and more parallel in nontornadic supercells.

A very large database containing 24 years of scatterometer passes is analyzed to investigate the surface wind fields within tropical cyclones. The analysis confirms the left–right asymmetry of the wind field with the strongest winds directly to the right of the tropical cyclone center (Northern Hemisphere). At values greater than 2 times the radius to maximum winds, the asymmetry is approximately equal to the storm velocity of forward movement. Observed wind inflow angle (i.e., storm motion not subtracted) is shown to vary both radially and azimuthally within the tropical cyclone. The smallest observed wind inflow angles are found in the left-front quadrant with the largest values in the right-rear quadrant. As the velocity of forward movement increases and the central pressure decreases, observed inflow angles ahead of the storm decrease and those behind the storm increase. In the right-rear quadrant, the observed inflow angle increases with radius from the storm center. In all other quadrants, the observed inflow angle is approximately constant as a function of radial distance.

California receives much of its precipitation from cool-season atmospheric rivers, which contribute to water resources and flooding. In winter 2017, a large number of atmospheric rivers caused anomalous winter precipitation, near-saturated soils, and a partial melting of snowpack, which led to excessive runoff that damaged the emergency spillway of the Oroville Dam. Given the positive and negative impacts ARs have in California, it is necessary to understand how they will change in a future climate. While prior studies have examined future changes in the frequency of atmospheric rivers impacting the West Coast of the United States, these studies primarily use coarse global climate models that are unable to resolve the complex terrain of this region. Such a limitation is overcome by using a high-resolution convection-permitting regional climate model, which resolves complex topography and orographic rainfall processes that are the main drivers of heavy precipitation in landfalling atmospheric rivers. This high-resolution model is used to examine changes to precipitation and runoff in California’s cool season from 2002 to 2013, particularly in flood-producing storms associated with atmospheric rivers, in a future, warmer climate using a pseudo–global warming approach. In 45 flood-producing storms, precipitation and runoff increase by 21%–26% and 15%–34%, respectively, while SWE decreases by 32%–90%, with the greatest changes at mid-elevations. These trends are consistent with future precipitation changes during the entire cool season. Results suggest more intense floods and less snowpack available for water resources in the future, which should be carefully considered in California’s future water management plans.

Flash floods are high-impact events that can result in massive destruction, such as the May 2010 flash floods in the south-central United States that resulted in over $2 billion of damage. While floods in the current climate are already destructive, future flood risk is projected to increase based on work using global climate models. However, global climate models struggle to resolve precipitation structure, intensity, and duration, which motivated the use of convection-permitting climate models that more accurately depict these precipitation processes on a regional scale due to explicit representation of convection. These high-resolution convection-permitting simulations have been used to examine future changes to rainfall, but not explicitly floods. This study aims to fill this gap by examining future changes to rainfall characteristics and runoff in flash flood–producing storms over the United States using convection-permitting models under a pseudo–global warming framework. Flash flood accumulated rainfall increases on average by 21% over the United States in a future climate. Storm-generated runoff increases by 50% on average, suggesting increased runoff efficiency in future flash flood–producing storms. In addition to changes in nonmeteorological factors, which were not explored in this study, increased future runoff is possible due to the 7.5% K−1 increase in future hourly maximum rain rates. Though this median change in rain rates is consistent with Clausius–Clapeyron theory, some storms exhibit increased future rain rates well above this, likely associated with storm dynamics. Overall, results suggest that U.S. cities might need to prepare for more intense flash flood–producing storms in a future climate.

Despite their structural differences, supercells and quasi-linear convective systems (QLCS) are both capable of producing severe weather, including tornadoes. Previous research has highlighted multiple potential mechanisms by which horizontal vorticity may be reoriented into the vertical at low levels, but it is not clear in which situation what mechanism dominates. In this study, we use the CM1 model to simulate three different storm modes, each of which developed relatively large near-surface vertical vorticity. Using forward-integrated parcel trajectories, we analyze vorticity budgets and demonstrate that there seems to be a common mechanism for maintaining the near-surface vortices across storm structures. The parcels do not acquire vertical vorticity until they reach the base of the vortices. The vertical vorticity results from vigorous upward tilting of horizontal vorticity and simultaneous vertical stretching. While the parcels analyzed in our simulations do have a history of descent, they do not acquire appreciable vertical vorticity during their descent. Rather, during the analysis period relatively large horizontal vorticity develops as a result of horizontal stretching, and therefore this vorticity can be effectively tilted into the vertical.

Severe local storm (SLS) activity is known to occur within specific thermodynamic and kinematic environments. These environments are commonly associated with key synoptic-scale features--including southerly Great Plains low-level jets, drylines, elevated mixed layers, and extratropical cyclones--that link the large-scale climate to SLS environments. This work analyzes spatiotemporal distributions of both the environmental parameters and synoptic-scale features in ERA5 reanalysis and in Community Atmosphere Model version 6 (CAM6) during 1980--2014 over North America. Compared to radiosondes, ERA5 successfully reproduces SLS environments, with strong spatiotemporal correlations and low biases, especially over the Great Plains. Both ERA5 and CAM6 reproduce the climatology of SLS environments over the central United States as well as its strong seasonal and diurnal cycles. ERA5 and CAM6 also reproduce the climatological occurrence of the synoptic-scale features, with the distribution pattern similar to that of SLS environments. Compared to ERA5, CAM6 exhibits a high bias in Convective Available Potential Energy over the eastern United States primarily due to a high bias in surface moisture, and to a lesser extent, storm-relative helicity due to enhanced low-level winds. Composite analysis indicates consistent synoptic anomaly patterns favorable for significant SLS environments over much of the eastern half of the United States in both ERA5 and CAM6, though the pattern differs for the southeastern United States. Overall, results indicate that both ERA5 and CAM6 are capable of reproducing SLS environments as well as the synoptic-scale features and transient events that generate them., 25 pages, 15 figures

This study provides a statistical review on the forecast errors of tropical storm tracks and suggests a Bayesian procedure for updating the uncertainty about the error. The forecast track errors are assumed to form an axisymmetric bivariate normal distribution on a two-dimensional surface. The parameters are a mean vector and a covariance matrix, which imply the accuracy and precision of the operational forecast. A Bayesian method improves quantifying the varying parameters in the bivariate normal distribution. A normal-inverse-Wishart distribution is employed to determine the posterior distribution (i.e., the weights on the parameters). Based on the posterior distribution, the predictive probability density of track forecast errors is obtained as the marginal distribution. Here, “storm approach” is defined for any location within a specified radius of a tropical storm. Consequently, the storm approach probability for each location is derived through partial integration of the marginal distribution within the forecast storm radius. The storm approach probability is considered a realistic and effective representation of storm warning for communicating the threat to local residents since the location-specific interpretation is available on a par with the official track forecast.

Tropical cyclones (TCs) are among the most destructive natural phenomena with huge societal and economic impact. They form and evolve as the result of complex multiscale processes and nonlinear interactions. Even today the understanding and modeling of these processes is still lacking. A major goal of NASA is to bring the wealth of satellite and airborne observations to bear on addressing the unresolved scientific questions and improving our forecast models. Despite their significant amount, these observations are still underutilized in hurricane research and operations due to the complexity associated with finding and bringing together semicoincident and semicontemporaneous multiparameter data that are needed to describe the multiscale TC processes. Such data are traditionally archived in different formats, with different spatiotemporal resolution, across multiple databases, and hosted by various agencies. To address this shortcoming, NASA supported the development of the Jet Propulsion Laboratory (JPL) Tropical Cyclone Information System (TCIS)—a data analytic framework that integrates model forecasts with multiparameter satellite and airborne observations, providing interactive visualization and online analysis tools. TCIS supports interrogation of a large number of atmospheric and ocean variables, allowing for quick investigation of the structure of the tropical storms and their environments. This paper provides an overview of the TCIS’s components and features. It also summarizes recent pilot studies, providing examples of how the TCIS has inspired new research, helping to increase our understanding of TCs. The goal is to encourage more users to take full advantage of the novel capabilities. TCIS allows atmospheric scientists to focus on new ideas and concepts rather than painstakingly gathering data scattered over several agencies.

To provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature Twet and the other based on snow-depth measurements of accumulation and ablation. With data from 17 spatially distributed clusters (178 nodes) from two networks, in the American and Feather River basins of California’s Sierra Nevada, we analyzed transition elevation during 76 storm events in 2014–18. A Twet threshold of 0.5°C best matched the transition elevation defined by snow depth. Transition elevations using Twet in upper elevations of the basins generally agreed with atmospheric snow level from radars located at lower elevations, while radar snow level was ~100 m higher due to snow-level lowering on windward mountainsides during orographic lifting. Diurnal patterns of the difference between transition elevation and radar snow level were observed in the American basin, related to diurnal ground-temperature variations. However, these patterns were not found in the Feather basin due to complex terrain and higher uncertainties in transition-elevation estimates. The American basin tends to exhibit 100-m-higher transition elevations than does the Feather basin, consistent with the Feather basin being about 1° latitude farther north. Transition elevation averaged 155 m higher in intense atmospheric river events than in other events; meanwhile, snow-level lowering was enhanced with a 90-m-larger difference between radar snow level and transition elevation. On-the-ground continuous observations from distributed sensor networks can complement radar data and provide important ground truth and spatially resolved information on transition elevations in mountain basins.

Ice storms are important winter weather events that can have substantial environmental, economic, and social impacts. Mapping and assessment of damage after these events could be improved by making ice accretion measurements at a greater number of sites than is currently available. There is a need for low-cost collectors that can be distributed broadly in volunteer observation networks; however, use of low-cost collectors necessitates understanding of how collector characteristics and configurations influence measurements of ice accretion. A study was conducted at the Hubbard Brook Experimental Forest in New Hampshire that involved spraying water over passive ice collectors during freezing conditions to simulate ice storms of different intensity. The collectors consisted of plates composed of four different materials and installed horizontally; two different types of wires strung horizontally; and rods of three different materials, with three different diameters, and installed at three different inclinations. Results showed that planar ice thickness on plates was 2.5–3 times as great as the radial ice thickness on rods or wires, which is consistent with expectations based on theory and empirical evidence from previous studies. Rods mounted on an angle rather than horizontally reduced the formation of icicles and enabled more consistent measurements. Results such as these provide much needed information for comparing ice accretion data. Understanding of relationships among collector configurations could be refined further by collecting data from natural ice storms under a broader range of weather conditions.

The research outputs provided foundational knowledge on hailstone properties, microphysics, and severe storm dynamics [ ]a recent resurgence, little attention was paid to hail within the research communities, relative to more threatening perils (e g , tornadoes, hurricanes), despite the mounting costs of hail damage across the globe Figure 1 provides a time history of AMS journal publications that have “hail” or “hailstorm/s” in the title or as a keyword relative to other topics (i e , hurricanes/tropical cyclones, tornadoes, and climate change) The T-28 continued flying hail missions for 33 years, with its last flight in 2003 Since the 1980s, field programs have focused on severe storm dynamics and thermodynamics (VORTEX, STEPS, VORTEX-2, PECAN, TORUS, etc ) Since 2000, the population of Colorado has grown by 1 3 million people (2015 U S Census)

Several previous studies have demonstrated the significant sensitivity of simulated tropical cyclone structure and intensity to variations in surface-exchange coefficients for enthalpy (Ck) and momentum (Cd), respectively. In this study we investigate the consistency of the estimated peak intensity, intensification rate, and steady-state structure between an analytical model and idealized axisymmetric numerical simulations for both constant Ck and Cd values and various wind speed–dependent representations of Ck and Cd. The present analysis with constant Ck and Cd values demonstrates that the maximum wind speed is similar for identical Ck/Cd values less than 1, regardless of whether changes were made to Ck or Cd. However, for a given Ck/Cd greater than 1, the simulated and theoretical maximum wind speed are both greater if Cd is decreased compared to Ck increased. This behavior results because of a smaller enthalpy disequilibrium at the radius of maximum winds for larger Ck. Additionally, the intensification rate is shown to increase with Ck and Cd and the steady-state normalized wind speed beyond the radius of maximum winds is shown to increase with increasing Cd. Experiments with wind speed–dependent Ck and Cd were found to be generally consistent, in terms of the intensification rate and the simulated and analytical-model-estimated maximum wind speed, with the experiments with constant Ck and Cd.

The relationship between storm-relative helicity (SRH) and streamwise vorticity ωs is frequently invoked to explain the often robust connections between effective inflow layer (EIL) SRH and various supercell updraft properties. However, the definition of SRH also contains storm-relative (SR) flow, and the separate influences of SR flow and ωs on updraft dynamics are therefore convolved when SRH is used as a diagnostic tool. To clarify this issue, proximity soundings and numerical experiments are used to disentangle the separate influences of EIL SR flow and ωs on supercell updraft characteristics. Our results suggest that the magnitude of EIL ωs has little influence on whether supercellular storm mode occurs. Rather, the transition from nonsupercellular to supercellular storm mode is largely modulated by the magnitude of EIL SR flow. Furthermore, many updraft attributes such as updraft width, maximum vertical velocity, vertical mass flux at all levels, and maximum vertical vorticity at all levels are largely determined by EIL SR flow. For a constant EIL SR flow, storms with large EIL ωs have stronger low-level net rotation and vertical velocities, which affirms previously established connections between ωs and tornadogenesis. EIL ωs also influences storms’ precipitation and cold-pool patterns. Vertical nonlinear dynamic pressure acceleration (NLDPA) is larger at low levels when EIL ωs is large, but differences in NLDPA aloft become uncorrelated with EIL ωs because storms’ midlevel dynamic pressure perturbations are substantially influenced by the tilting of midlevel vorticity. Our results emphasize the importance of considering EIL SR flow in addition to EIL SRH in the research and forecasting of supercell properties.

The representation of the winter and summer extratropical storm tracks in both hemispheres is evaluated in detail for the available models in phase 6 of the Coupled Model intercomparison Project (CMIP6). The state of the storm tracks from 1979 to 2014 is compared to that in ERA5 using a Lagrangian objective cyclone tracking algorithm. It is found that the main biases present in the previous generation of models (CMIP5) still persist, albeit to a lesser extent. The equatorward bias around the SH is much reduced and there appears to be some improvement in mean biases with the higher-resolution models, such as the zonal tilt of the North Atlantic storm track. Low-resolution models have a tendency to underestimate the frequency of high-intensity cyclones with all models simulating a peak intensity that is too low for cyclones in the SH. Explosively developing cyclones are underestimated across all ocean basins and in both hemispheres. In particular the models struggle to capture the rapid deepening required for these cyclones. For all measures, the CMIP6 models exhibit an overall improvement compared to the previous generation of CMIP5 models. In the NH most improvements can be attributed to increased horizontal resolution, whereas in the SH the impact of resolution is less apparent and any improvements are likely a result of improved model physics.

On 8 February 2018, a supercell storm produced gargantuan (>15 cm or >6 in. in maximum dimension) hail as it moved over the heavily populated city of Villa Carlos Paz in Córdoba Province, Argentina. Observations of gargantuan hail are quite rare, but the large population density here yielded numerous witnesses and social media pictures and videos from this event that document multiple large hailstones. The storm was also sampled by the newly installed operational polarimetric C-band radar in Córdoba. During the RELAMPAGO campaign, the authors interviewed local residents about their accounts of the storm and uncovered additional social media video and photographs revealing extremely large hail at multiple locations in town. This article documents the case, including the meteorological conditions supporting the storm (with the aid of a high-resolution WRF simulation), the storm's observed radar signatures, and three noteworthy hailstones observed by residents. These hailstones include a freezer-preserved 4.48-in. (11.38 cm) maximum dimension stone that was scanned with a 3D infrared laser scanner, a 7.1-in. (18 cm) maximum dimension stone, and a hailstone photogrammetrically estimated to be between 7.4 and 9.3 in. (18.8-23.7 cm) in maximum dimension, which is close to or exceeds the world record for maximum dimension. Such a well-observed case is an important step forward in understanding environments and storms that produce gargantuan hail, and ultimately how to anticipate and detect such extreme events. Fil: Kumjian, Matthew R.. State University of Pennsylvania; Estados Unidos Fil: Gutierrez, Rachel. State University of Pennsylvania; Estados Unidos Fil: Soderholm, Joshua S.. Universitat Bonn; Alemania Fil: Nesbitt, Stephen William. University of Illinois at Urbana; Estados Unidos Fil: Maldonado, Paula Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Luna, Lorena Medina. National Center for Atmospheric Research; Estados Unidos Fil: Marquis, James. Pacific Northwest National Laboratory; Estados Unidos Fil: Bowley, Kevin A.. State University of Pennsylvania; Estados Unidos Fil: Alvarez Imaz, María de Los Milagros. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Salio, Paola Veronica. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina

This study examines the interaction between a northeast Pacific upper-ocean thermal anomaly and individual fall storm events between 2013 and 2016. In 2013, a large upper-ocean thermal anomaly formed in the Gulf of Alaska (GOA) with sea surface temperatures (SST) warmer than 4°C above the climatological norm. Formation of the anomaly was associated with a persistent atmospheric ridge in the GOA that produced a lull in storm activity in the boreal winter of 2013/14. While reduced storm activity was the apparent cause of this SST anomaly, we present cases where extratropical cyclones significantly eroded its mixed layer heat content on synoptic time scales. Case studies during the 4-yr period 2013–16 using satellite and Argo hydrographic observations show that early fall storms produced the largest surface heat fluxes and the greatest cooling of SST. The magnitude of thermal energy transfer from the ocean to the atmosphere during individual storm events was then determined using vertically integrated heat budgets based on Argo temperature profiles and reanalysis surface heat fluxes. Storm-induced surface heat flux anomalies accounted for approximately 50% of the warm anomaly cooling observed by Argo profiles. This rapid heat loss occurred over time scales of approximately 3–5 days. The decay of the warm SST anomaly (SSTa) occurred much more quickly than expected from classic thermal damping by SST-induced turbulent heat fluxes, which may be attributed here at least partly to much shallower mixed layers during early fall. Analysis of the individual surface flux terms indicated that the latent heat flux was the dominant contributor to storm-induced heat exchange across the air–sea interface.

A prototype of an efficient and accurate rapid forecasting and mapping system (RFMS) of storm surge is presented. Given a storm advisory from the National Hurricane Center, the RFMS can generate a coastal inundation map on a high-resolution grid in 1 min (reference system Intel Core i7–3770K). The foundation of the RFMS is a storm surge database consisting of high-resolution simulations of 490 optimal storms generated by a robust storm surge modeling system, Curvilinear-Grid Hydrodynamics in 3D (CH3D-SSMS). The RFMS uses an efficient quick kriging interpolation scheme to interpolate the surge response from the storm surge database, which considers tens of thousands of combinations of five landfall parameters of storms: central pressure deficit, radius to maximum wind, forward speed, heading direction, and landfall location. The RFMS is applied to southwest Florida using data from Hurricane Charley in 2004 and Hurricane Irma in 2017, and to the Florida Panhandle using data from Hurricane Michael in 2018 and validated with observed high water mark data. The RFMS results agree well with observation and direct simulation of the high-resolution CH3D-SSMS. The RFMS can be used for real-time forecasting during a hurricane or “what-if” scenarios for mitigation planning and preparedness training, or to produce a probabilistic flood map. The RFMS can provide more accurate surge prediction with uncertainties if NHC can provide more accurate storm forecasts in the future. By incorporating storms for future climate and sea level rise, the RFMS could be used to generate future flood maps for coastal resilience and adaptation planning.

The spatial structure of both the wind and wave fields within tropical cyclones is investigated using two large databases. The first of these was compiled from global overpasses of tropical cyclones by satellite altimeters. The second dataset consists of an extensive collection of North American buoy measurements during the passage of tropical cyclones (hurricanes). The combined datasets confirm the vortex structure of the tropical cyclone wind field with the strongest winds to the right (Northern Hemisphere) of the storm. The wave field largely mirrors the wind field but with greater right–left asymmetry that results from the extended fetch to the right of the translating tropical cyclone. The extensive in situ buoy database confirms previous studies indicating that the one-dimensional spectra are generally unimodal. The directional spectra are, however, directionally skewed, consisting of remotely generated waves radiating out from the center of the storm and locally generated wind sea. The one-dimensional wave spectra have many similarities to fetch-limited cases, although for a given peak frequency the spectra contain less energy than for a fetch-limited case. This result is consistent with the fact that much of the wave field is dominated by remotely generated waves.

The Southern Hemisphere summertime eddy-driven jet and storm tracks have shifted poleward over the recent few decades. In previous studies, explanations have mainly stressed the influence of external forcing in driving this trend. Here we examine the role of internal tropical SST variability in controlling the austral summer jet’s poleward migration, with a focus on interdecadal time scales. The role of external forcing and internal variability are isolated by using a hierarchy of Community Earth System Model version 1 (CESM1) simulations, including the pre-industrial control, large ensemble, and pacemaker runs. Model simulations suggest that in the early twenty-first century, both external forcing and internal tropical Pacific SST variability are important in driving a positive southern annular mode (SAM) phase and a poleward migration of the eddy-driven jet. Tropical Pacific SST variability, associated with the negative phase of the interdecadal Pacific oscillation (IPO), acts to shift the jet poleward over the southern Indian and southwestern Pacific Oceans and intensify the jet in the southeastern Pacific basin, while external forcing drives a significant poleward jet shift in the South Atlantic basin. In response to both external forcing and decadal Pacific SST variability, the transient eddy momentum flux convergence belt in the middle latitudes experiences a poleward migration due to the enhanced meridional temperature gradient, leading to a zonally symmetric southward migration of the eddy-driven jet. This mechanism distinguishes the influence of the IPO on the midlatitude circulation from the dynamical impact of ENSO, with the latter mainly promoting the subtropical wave-breaking critical latitude poleward and pushing the midlatitude jet to higher latitudes.

Using 5 years of operational Doppler radar, cloud-to-ground (CG) lightning observations, and National Centers for Environmental Prediction reanalysis data, this study examined the spatial and temporal characteristics of and correlations between summer storm and lightning activity over the Yangtze River Delta (YRD), with a focus on subseasonal variability and diurnal cycles. The spatiotemporal features of storm top, duration, maximum reflectivity, size, and cell-based vertical integrated liquid water were investigated using the Storm Cell Identification and Tracking algorithm. Our results revealed that there was high storm activity over the YRD, with weak diurnal variations during the mei-yu period. Specifically, storms were strongly associated with mei-yu fronts and exhibited a moderate size, duration, and intensity. On average, afternoon storms exhibited stronger reflectivity and higher storm tops than morning storms, as evidenced by the afternoon peak in CG lightning. The storm intensity strengthened in the post-mei-yu period, due to an increase in atmospheric instability; this was accompanied by a higher frequency of CG lighting. The diurnal cycles of storm frequency and CG lightning in the post-mei-yu period followed a unimodal pattern with an afternoon peak. This is attributable to increased thermodynamic instability in the afternoon, as little diurnal variation was observed for wind shear and moisture. An inverse correlation between lightning occurrence and mean peak current (MPC) for negative CG lightning was evident during the pre-mei-yu and mei-yu periods. The diurnal variation in MPC for negative CG lightning agreed well with that for storm intensity.

Tropical Cyclone Oswald (2013) is considered to be one of the highest-impact storms to make landfall in northern Australia even though it only reached a maximum category 1 intensity on the Australian category scale. After making landfall on the west coast of Cape York Peninsula, Oswald turned southward, and persisted for more than 7 days moving parallel to the coastline as far south as 30°S. As one of the wettest tropical cyclones (TCs) in Australian history, the favorable configurations of a lower-latitude active monsoon trough and two consecutive midlatitude trough–jet systems generally contributed to the maintenance of the Oswald circulation over land and prolonged rainfall. As a result, Oswald produced widespread heavy rainfall along the east coast with three maximum centers near Weipa, Townsville, and Rockhampton, respectively. Using high-resolution WRF simulations, the mechanisms associated with TC Oswald’s rainfall are analyzed. The results show that the rainfall involved different rainfall mechanisms at each stage. The land–sea surface friction contrast, the vertical wind shear, and monsoon trough were mostly responsible for the intensity and location for the first heavy rainfall center on the Cape York Peninsula. The second torrential rainfall near Townsville was primarily a result of the local topography and land–sea frictional convergence in a conditionally unstable monsoonal environment with frictional convergence due to TC motion modulating some offshore rainfall. The third rainfall area was largely dominated by persistent high vertical wind shear forcing, favorable large-scale quasigeostrophic dynamic lifting from two midlatitude trough–jet systems, and mesoscale frontogenesis lifting.

The NOAA Warn-on-Forecast System (WoFS) is an experimental rapidly updating convection-allowing ensemble designed to provide probabilistic operational guidance on high-impact thunderstorm hazards. The current WoFS uses physics diversity to help maintain ensemble spread. We assess the systematic impacts of the three WoFS PBL schemes—YSU, MYJ, and MYNN—using novel, object-based methods tailored to thunderstorms. Very short forecast lead times of 0–3 h are examined, which limits phase errors and thereby facilitates comparisons of observed and model storms that occurred in the same area at the same time. This evaluation framework facilitates assessment of systematic PBL scheme impacts on storms and storm environments. Forecasts using all three PBL schemes exhibit overly narrow ranges of surface temperature, dewpoint, and wind speed. The surface biases do not generally decrease at later forecast initialization times, indicating that systematic PBL scheme errors are not well mitigated by data assimilation. The YSU scheme exhibits the least bias of the three in surface temperature and moisture and in many sounding-derived convective variables. Interscheme environmental differences are similar both near and far from storms and qualitatively resemble the differences analyzed in previous studies. The YSU environments exhibit stronger mixing, as expected of nonlocal PBL schemes; are slightly less favorable for storm intensification; and produce correspondingly weaker storms than the MYJ and MYNN environments. On the other hand, systematic interscheme differences in storm morphology and storm location forecast skill are negligible. Overall, the results suggest that calibrating forecasts to correct for systematic differences between PBL schemes may modestly improve WoFS and other convection-allowing ensemble guidance at short lead times.

Ensemble Kalman filter (EnKF) analyses of the storms associated with the 8 May 2017 Colorado severe hail event using either the Milbrandt and Yau (MY) or the NSSL double-moment bulk microphysics scheme in the forecast model are evaluated. With each scheme, two experiments are conducted in which the reflectivity (Z) observations update in addition to dynamic and thermodynamic variables: 1) only the hydrometeor mixing ratios or 2) all microphysical variables. With fewer microphysical variables directly constrained by the Z observations, only updating hydrometeor mixing ratios causes the forecast error covariance structure to become unreliable, and results in larger errors in the analysis. Experiments that update all microphysical variables produce analyses with the lowest Z root-mean-square innovations; however, comparing the estimated hail size against hydrometeor classification algorithm output suggests that further constraint from observations is needed to more accurately estimate surface hail size. Ensemble correlation analyses are performed to determine the impact of hail growth assumptions in the MY and NSSL schemes on the forecast error covariance between microphysical and thermodynamic variables. In the MY scheme, Z is negatively correlated with updraft intensity because the strong updrafts produce abundant small hail aloft. The NSSL scheme predicts the growth of large hail aloft; consequently, Z is positively correlated with storm updraft intensity and hail state variables. Hail production processes are also shown to alter the background error covariance for liquid and frozen hydrometeor species. Results in this study suggest that EnKF analyses are sensitive to the choice of MP scheme (e.g., the treatment of hail growth processes).

Storm surge and coastal flooding caused by tropical cyclones (hurricanes) and extratropical cyclones (nor’easters) pose a threat to communities along the Atlantic coast of the United States. Climate change and sea level rise are altering the statistics of these extreme events in a rather complex fashion. Here we use a fully coupled global weather/climate modeling system (GFDL CM4) to study characteristics of extreme daily sea level (ESL) along the U.S. Atlantic coast and their response to global warming. We find that under natural weather processes, the Gulf of Mexico coast is most vulnerable to storm surge and related ESL. New Orleans is a striking hotspot with the highest surge efficiency in response to storm winds. Under a 1% per year atmospheric CO2 increase on centennial time scales, the anthropogenic signal in ESL is robust along the U.S. East Coast. It can emerge from the background variability as soon as in 20 years, or even before global sea level rise is taken into account. The regional dynamic sea level rise induced by the weakening of the Atlantic meridional overturning circulation facilitates this early emergence, especially during wintertime coastal flooding associated with nor’easters. Along the Gulf Coast, ESL is sensitive to the modification of hurricane characteristics under the CO2 forcing.

The organization and structure of thunderstorms determines the extent and severity of their hazards to the general public and their consequences for the Earth system. Distinguishing vigorous convective regions that produce heavy rain and hail from adjacent regions of stratiform clouds or overhanging anvil clouds that produce light to no rainfall is valuable in operations and physical research. Cloud-type algorithms that partition convection from stratiform regions have been developed for space-based radar, passive microwave, and now Geostationary Operational Environmental Satellites (GOES) Advanced Baseline Imager (ABI) multispectral products. However, there are limitations for each of these products including temporal availability, spatial coverage, and the degree to which they based on cloud microphysics. We have developed a cloud-type algorithm for GOES Geostationary Lightning Mapper (GLM) observations that identifies convective/nonconvective regions in thunderstorms based on signatures of interactions with nonconvective charge structures in the lightning flash data. The GLM sensor permits a rapid (20 s) update cycle over the combinedGOES-16–GOES-17domain across all hours of the day. Storm regions that do not produce lightning will not be classified by our algorithm, however. The GLM cloud-type product is intended to provide situational awareness of electrified nonconvective clouds and to complement other cloud-type retrievals by providing a contemporary assessment tied to lightning physics. We propose that a future combined ABI–GLM cloud-type algorithm would be a valuable product that could draw from the strengths of each instrument and approach.

Since the 1970s, the National Weather Service has trained citizens to collect, confirm, verify, or supplement radar and other data to contribute to a weather-ready nation. This study examines citizens who volunteer as weather spotters through a case study of an award-winning network. We uncover what motivates citizens to become involved in government science projects. Through the lens of relationship management theory and the related network approach, the study provides some of the first evidence on the benefits and drawbacks of citizens serving as amateur scientists and risk communicators and how these citizen scientists sustain their relationships with government scientists.

This study examines the spatiotemporal characteristics of the historic 10–14 August 2016 south-central Louisiana precipitation event. The storm was the result of a moisture-rich, tropical low pressure system, also known as a tropical easterly wave, that slowly tracked westward along the Gulf Coast from Florida to Texas. Once over south-central Louisiana, the storm was able to take advantage of anomalously high precipitable water, broad low-level instability, and continuous moisture inflow from the Gulf of Mexico to produce historic rainfall. Totals exceeded 254 mm (10 in.) for much of southern Louisiana, while locations adjacent to Baton Rouge and Lafayette received upward of 635 mm (25 in.). One station measured a 48-h rainfall total of 797.3 mm (31.39 in.)—the greatest 48-h total on record for Louisiana. Using calibrated radar data, the Storm Precipitation Analysis System (SPAS) revealed that one location likely received >864 mm (34 in.) of precipitation during the duration of the storm, well over the estimated 1000-yr return interval. A synoptic discussion of the event and analysis of the storm’s recurrence interval helps place this storm in a historical context.