Abstract

The scientific community has long acknowledged the importance of high-temporal resolution radar observations to advance science research and improve high-impact weather prediction. Development of innovative rapid-scan radar technologies over the past two decades has enabled radar volume scans of 10–60 s, compared to 3–5 min with traditional parabolic dish research radars and the WSR-88D radar network. This review examines the impact of rapid-scan radar technology, defined as radars collecting volume scans in 1 min or less, on atmospheric science research spanning different subdisciplines and evaluates the strengths and weaknesses of the use of rapid-scan radars. In particular, a significant body of literature has accumulated for tornado and severe thunderstorm research and forecasting applications, in addition to a growing number of studies of convection. Convection research has benefited substantially from more synchronous vertical views, but could benefit more substantially by leveraging multi-Doppler wind retrievals and complementary in-situ and remote sensors. In addition, several years of forecast evaluation studies are synthesized from radar testbed experiments, and the benefits of assimilating rapid-scan radar observations are analyzed. Although the current body of literature reflects the considerable utility of rapid-scan radars to science research, a weakness is that limited advancements in understanding of the physical mechanisms behind observed features have been enabled. There is considerable opportunity to bridge the gap in physical understanding with the current technology using coordinated efforts to include rapid-scan radars in field campaigns and expanding the breadth of meteorological phenomena studied.

Abstract

The Advanced Baseline Imager (ABI) aboard the GOES-16 and GOES-17 satellites provides high-resolution observations of cloud structures that could be highly beneficial for convective-scale DA. However, only clear-air radiance observations are typically assimilated at operational centers due to a variety of problems associated with cloudy radiance data. As such, many questions remain about how to best assimilate all-sky radiance data, especially when using hybrid DA systems such as EnVar wherein a nonlinear observation operator can lead to cost function gradient imbalance and slow minimization. Here, we develop new methods for assimilating all-sky radiance observations in EnVar using the novel Rapid Refresh Forecasting System (RRFS) that utilizes the Finite-Volume Cubed-Sphere (FV3) model. We first modify the EnVar solver by directly including brightness temperature (T_b ) as a state variable. This modification improves the balance of the cost function gradient and speeds up minimization. Including T_b as a state variable also improves the model fit to observations and increases forecast skill compared to utilizing a standard state vector configuration. We also evaluate the impact of assimilating ABI all-sky radiances in RRFS for a severe convective event in the central Great Plains. Assimilating the radiance observations results in better spinup of a tornadic supercell. These data also aid in suppressing spurious convection by reducing the snow hydrometeor content near the tropopause and weakening spurious anvil clouds. The all-sky radiance observations pair well with reflectivity observations that remove primarily liquid hydrometeors (i.e., rain) closer to the surface. Additionally, the benefits of assimilating the ABI observations continue into the forecast period, especially for localized convective events.

Abstract

The conditions associated with tropical cyclones undergoing downshear reformation are explored for the North Atlantic basin from 1998 to 2020. These storms were compared to analog tropical cyclones with similar intensity, vertical wind shear, and maximum potential intensity, but did not undergo downshear reformation. Storm-centered, shear-relative composites were generated using ERA5 and GridSat-B1 data. Downshear reformation predominately occurs for tropical cyclones of tropical storm intensity embedded in moderate vertical wind shear. A comparison between composites suggests that reformed storms are characterized by greater low-level and midtropospheric relative humidity downshear, larger surface latent heat fluxes downshear and left of shear, and larger low-level equivalent potential temperatures and CAPE right of shear. These factors increase thermodynamic favorability, building a reservoir of potential energy and decreasing dry air entrainment, promoting sustained convection downshear, and favoring the development of a new center.

Abstract

Old descriptive diaries are important sources of daily weather conditions before modern instrumental measurements were available. A previous study demonstrated the potential of reconstructing historical weather at a high temporal resolution by assimilating cloud cover converted from descriptive diaries. However, cloud cover often exhibits a non-Gaussian distribution, which violates the basic assumptions of most data assimilation schemes. In this study, we applied a Gaussian transformation (GT) approach to cloud cover data assimilation and conducted observing system simulation experiments (OSSEs) using 20 observation points over Japan. We performed experiments to assimilate cloud cover with large observational errors using the Global Spectral Model (GSM) and a local ensemble transform Kalman filter (LETKF). Without GT, meridional wind and temperature exhibited deteriorations in the lower troposphere compared with the experiment with no observations. In contrast, GT reduced the 2-month root-mean-square errors (RMSEs) by 5%–15% throughout the troposphere for wind, temperature, and specific humidity fields. Significant improvements include zonal wind at 500 hPa and temperature at 850 hPa with 6.4% and 7.3% improvements by GT, respectively, compared with the experiment without GT. We further demonstrate that the additional GT application to the precipitation background field improves precipitation estimation by 12.2%, with pronounced improvements over regions with monthly precipitation of less than 150 mm. We also explored the impact of cloud cover GT on a global scale and confirmed improvements extending from around the observation sites. Our results demonstrate the potential of GT in high-resolution historical weather reconstruction using old descriptive diaries.

Abstract

Severe storms produce hazardous weather phenomena, such as large hail, damaging winds, and tornadoes. However, relationships between convective parameters and confirmed severe weather occurrences are poorly quantified in south-central Brazil. This study explores severe weather reports and measurements from newly available datasets. Hail, damaging wind, and tornado reports are sourced from the PREVOTS project from June 2018 to December 2021, while measurements of convectively induced wind gusts from 1996 to 2019 are obtained from METAR reports and from Brazil’s operational network of automated weather stations. Proximal convective parameters were computed from ERA5 reanalysis for these reports and used to perform a discriminant analysis using mixed-layer CAPE and deep-layer shear (DLS). Compared to other regions, thermodynamic parameters associated with severe weather episodes exhibit lower magnitudes in south-central Brazil. DLS displays better performance in distinguishing different types of hazardous weather, but does not discriminate well between distinct severity levels. To address the sensitivity of the discriminant analysis to distinct environmental regimes and hazard types, five different discriminants are assessed. These include discriminants for any severe storm, severe hail only, severe wind gust only, and all environments but broken into “high” and “low” CAPE regimes. The best performance of the discriminant analysis is found for the “high” CAPE regime, followed by the severe wind regime. All discriminants demonstrate that DLS plays a more important role in conditioning Brazilian severe storm environments than other regions, confirming the need to ensure that parameters and discriminants are tuned to local severe weather conditions.

Abstract

Tropical cyclones that intensify abruptly experience “rapid intensification.” Rapid intensification remains a formidable forecast challenge, in part because the underlying science has not been settled. One way to reconcile the debates and inconsistencies in the literature is to presume that different forms (or modes) of rapid intensification exist. The present study provides evidence in support of this hypothesis by documenting two modes of rapid intensification in a global convection-permitting simulation and the HURDAT2 database. The “marathon mode” is characterized by a moderately paced and long-lived intensification period, whereas the “sprint mode” is characterized by explosive and short-lived intensification bursts. Differences between the modes were also found in initial vortex structure (well defined versus poorly defined), nature of intensification (symmetric versus asymmetric), and environmental conditions (weak shear versus strong shear). Collectively, these differences indicate that the two modes involve distinct intensification mechanisms. Recognizing the existence of multiple intensification modes may help to better understand and predict rapid intensification by, for example, explaining the lack of consensus in the literature, or by raising awareness that rapid intensification in strongly sheared cyclones is not just an exception to a rule, but a typical process.

Abstract

Recurving tropical cyclones (TCs) in the western North Pacific often cause heavy rainfall events (HREs) in East Asia. However, how their interactions with midlatitude flows alter the characteristics of HREs has remained unclear. The present study examines the synoptic-dynamic characteristics of HREs directly resulting from TCs in South Korea with a focus on the role of midlatitude baroclinic condition. The HREs are categorized into two clusters based on midlatitude tropopause patterns: i.e., strongly (C1) and weakly (C2) baroclinic conditions. The C1, which is common in late summer, is characterized by a well-defined trough-ridge couplet and jet streak at the tropopause. As TCs approach, the trough-ridge couplet amplifies but is anchored by divergent TC outflow. This leads to phase locking of the upstream trough with TCs and thereby prompts substantial structural changes of TCs reminiscent of extratropical transition. The synergistic TC–midlatitude flow interactions allow for enhanced quasigeostrophic forcing over a broad area. This allows HREs to occur even before TC landfall with more inland rainfall than C2 HREs. In contrast, C2, which is mainly observed in mid-summer, does not accompany the undulating tropopause. In the absence of strong interactions with midlatitude flows, TCs rapidly dissipate after HREs while maintaining their tropical features. The upward motion is confined to the inherent TC convection, and thus HREs occur only when TCs are located in the vicinity of the country. These findings suggest that midlatitude baroclinic condition determines the spatial extent of TC rainfall and the timing of TC-induced HREs in South Korea.

Abstract

This study aims to objectively identify storm-scale characteristics associated with tornado-like vortex (TLV) formation in an ensemble of high-resolution supercell simulations. An ensemble of 51 supercells is created using Cloud Model version 1 (CM1). The first member is initialized using a base state populated by the Rapid Update Cycle (RUC) proximity sounding near El Reno, Oklahoma, on 24 May 2011. The other 50 ensemble members are created by randomly perturbing the base state after a supercell has formed. There is considerable spread between ensemble members, with some supercells producing strong, long-lived TLVs, while others do not produce a TLV at all. The ensemble is analyzed using the ensemble sensitivity analysis (ESA) technique, uncovering storm-scale characteristics that are dynamically relevant to TLV formation. In the rear flank, divergence at the surface southeast of the TLV helps converge and contract existing vertical vorticity, but there is no meaningful sensitivity to rear-flank outflow temperature. In the forward flank, warm temperatures within the cold pool are important to TLV production and magnitude. The longitudinal positioning of strong streamwise vorticity is also a clear indicator of TLV formation and strength, especially within 5 min of when the TLV is measured.

Abstract

Streamwise vorticity currents (SVCs) have been hypothesized to enhance low-level mesocyclones within supercell thunderstorms and perhaps increase the likelihood of tornadogenesis. Recent observational studies have confirmed the existence of SVCs in supercells and numerical simulations have allowed for further investigation of SVCs. A suite of 19 idealized supercell simulations with varying midlevel shear orientations is analyzed to determine how SVC formation and characteristics may differ between storms. In our simulations, SVCs develop on the cold side of left-flank convergence boundaries and their updraft-relative positions are partially dependent on downdraft location. The magnitude, duration, and mean depth of SVCs do not differ significantly between simulations or between SVCs that precede tornado-like vortices (TLVs) and those that do not. Trajectories initialized within SVCs reveal two primary airstreams, one that flows through an SVC for the majority of its length, and another that originates in the modified inflow in the forward flank and then merges with the SVC. Vorticity budgets calculated along trajectories reveal that the first airstream exhibits significantly greater maximum streamwise vorticity magnitudes than the second airstream. The vorticity budgets also indicate that stretching of horizontal streamwise vorticity is the dominant contributor to the large values of streamwise vorticity within the SVCs. TLV formation does not require the development of an SVC beforehand; 44% of TLVs in the simulations are preceded by SVCs. When an SVC occurs, it is followed by a TLV 53% of the time, indicating not all SVCs lead to TLV formation.

Abstract

Airborne Doppler radar reflectivity data collected in hurricanes on the NOAA P-3 aircraft between 1997 and 2021 were parsed into different modes of precipitation: stratiform precipitation, shallow convection, moderate convection, and deep convection. Stratiform precipitation was the most frequent precipitation mode with 82.6% of all observed precipitation while deep convection was the most infrequent at 1.3%. When stratified by 12-hr intensity change, intensifying TCs had a greater areal coverage of total convection in the eyewall compared to weakening and steady-state TCs. The largest difference in the azimuthal distributions in the precipitation modes was in deep convection, which was mostly confined to the downshear-left quadrant in weakening and steady-state hurricanes and more symmetrically distributed in intensifying hurricanes. For all intensity change categories, the most symmetrically distributed precipitation mode was stratiform rain.

To build upon the results of a recent thermodynamic study, the precipitation data were recategorized for hurricanes experiencing deep-layer wind shear with either a northerly-component or southerly-component. Like intensifying storms, hurricanes that experienced northerly-component shear had a more symmetric distribution of deep convection than southerly-component shear storms, which had a distribution of deep convection that resembled weakening storms. The greatest difference in the precipitation distributions between the shear direction groups were in major hurricanes experiencing moderate (4.5–11 m s⁻¹) wind shear values. Consistent with previous airborne radar studies, the results suggest that considering the distribution of deep convection and the thermodynamic distributions associated with differing environmental wind shear direction could aid TC intensity forecasts.