Ground-based Detection Research Articles

Reliability of visual detections of cirrus over Poland

Earth is a cloudy planet—at every moment, 62–72% of the planet is covered by cloud. Its presence and properties affect the flow of energy between the sun, Earth and the atmosphere. More comprehensive information about cloudiness is important to improve our understanding of the impact of cloud on Earth’s radiation budget. The aim of our work is to assess the accuracy of ground-based high-level cloud detections over Poland compared with satellite data. This project is the very first evaluation of error in visual high-cloud observation. Specifically, we answer a fundamental question: how effective are ground-based observers in detecting high-level cloud? Our unprecedented analysis is based on two datasets: traditional, visual observations from 43 selected synoptic stations and satellite (lidar) data, for the years 2006–2017. Ground-based observations were obtained from the archives of the Polish National Weather Service (IMWM-NRI), while satellite data came from the CALIPSO mission. Our final dataset comprised 7548 ground-based and satellite observations. Accuracy was assessed using the following indicators: probability of detection (Pd), probability of false alarm (Pfa), and overall accuracy (ACC). Overall (day and night observations), in the absence of lower-level cloud, observers correctly detected 80% of high-level cloud. However, when lower-level cloud was present, observers could not detect around 70% of high-level cloud. In sum, ground-based, high-level cloud detection is a function of the presence of lower-level cloud, the time of day, and the size of the area over which cirrus are observed/detected.

Assessment of vertical accuracy of open source 30m resolution space-borne digital elevation models

Highly accurate air-borne Digital Elevation Models (DEMs) are not commonly available in most regions of the world, particularly developing countries like Nepal. Better topographic data are required to assess catchment hydrology, flood/inundation propagation, and sediment transport/deposition. Ground-based surveys (i.e., topographic and bathymetry) and Light Detection and Ranging (LIDAR) are expensive in terms of cost and time. We rely mostly on space-borne DEMs when the area of interest is quite large. And, for river cross-sections at specific regions, ground-based surveys are conducted at some regular intervals. The ALOS World 3 D − 30 m (AW3D30), ASTER Global DEM Version 3 (ASTER GDEM v3), SRTM-30, and Carto DEM v3 are some of the popular and latest space-borne DEMs that have been made available to the general public free of charge at a spatial resolution of 30 m. The availability of multiple space-borne DEMs may likely puzzle the practitioners on the selection of appropriate products. Here in this study, we evaluate the vertical accuracy of different space-borne DEMs with respect to the ground-based survey points (2891 points) at river cross-sections and ground-based indicative spot heights (8102 points) across the West Rapti River basin, Nepal. Performance metrics, like mean error and root mean square error (RMSE), were used to quantify deviation with respect to observed elevation. The AW3D30 showed the lowest RMSE value (i.e., 3.41 m) in the lower region of the study area. We numerically simulated the inundation propagation based on four selected DEMs using a calibrated two-dimensional runoff inundation model, and we find the AW3D30 outperforms other DEMs. All four DEMs showed a similar tendency on a catchment scale with respect to the information of indicative spot heights, suggesting interchangeable applications of all four DEMs in hydrologic analyses. However, precise ground-based observations across the catchment are needed for assuring the applicability.

Properties of the RFI Environment at 1400–1427 MHz as Observed by the Soil Moisture Active/Passive Mission Microwave Radiometer

The soil moisture active/passive (SMAP) satellite microwave radiometer has been providing global measurements of L-band thermal emission from Earth since April 2015. Although the radiometer operates in the protected 1400-1427 MHz portion of the radio spectrum, its measurements are still corrupted by either radio frequency interference (RFI) from out-of-band emissions via legal sources or by sources operating in-band illegally. The SMAP radiometer includes a digital backend that enables implementation of multiple ground-based RFI detection and filtering algorithms. This data is used to collect statistics and trends of Earth's RFI environment. This article examines properties of the global RFI environment as observed by SMAP, including information on RFI source properties (obtained from analysis of SMAP multiple detector outputs) and the evolution of the RFI environment in time. Residual RFI contributions after the application of SMAP RFI processing are also examined as preliminary information for the development of future methods to address their effect.

An Integrated Technology of Ionospheric Backscatter Detection and Oblique Detection

Traditional single ground-based ionospheric detection methods often fail to obtain accurately ionospheric parameter information due to the measurement errors of detection systems and inverse algorithms. With the development of high frequency communication and radar sounding techniques, the ionospheric combined detection technology with multi-means is the most effective way to obtain the more accurate ionospheric characteristics. In this study, combined with ionospheric backscatter detection and oblique detection methods, an integrated ionospheric detection technology (quasi-backscatter detection technology) is proposed. The ionospheric parameters are obtained based on the minimum mean square error criterion and global searching method. The experimental results show that the inversion accuracy of ionospheric parameters is significantly improved by using quasi-backscatter detection system(42.3°N, GeoM). In addition, we simulate the propagation characteristics of the quasi-backscatter detection system by using ray tracing technique. And the variation characteristics between the propagation mode (and the propagation energy) and the angle of the transmitting-receiving beam are obtained.

Design of an Unmanned Ground Vehicle and LiDAR Pipeline for the High-Throughput Phenotyping of Biomass in Perennial Ryegrass

Perennial ryegrass biomass yield is an important driver of profitability for Australian dairy farmers, making it a primary goal for plant breeders. However, measuring and selecting cultivars for higher biomass yield is a major bottleneck in breeding, requiring conventional methods that may be imprecise, laborious, and/or destructive. For forage breeding programs to adopt phenomic technologies for biomass estimation, there exists the need to develop, integrate, and validate sensor-based data collection that is aligned with the growth characteristics of plants, plot design and size, and repeated measurements across the growing season to reduce the time and cost associated with the labor involved in data collection. A fully automated phenotyping platform (DairyBioBot) utilizing an unmanned ground vehicle (UGV) equipped with a ground-based Light Detection and Ranging (LiDAR) sensor and Real-Time Kinematic (RTK) positioning system was developed for the accurate and efficient measurement of plant volume as a proxy for biomass in large-scale perennial ryegrass field trials. The field data were collected from a perennial ryegrass row trial of 18 experimental varieties in 160 plots (three rows per plot). DairyBioBot utilized mission planning software to autonomously capture high-resolution LiDAR data and Global Positioning System (GPS) recordings. A custom developed data processing pipeline was used to generate a plant volume estimate from LiDAR data connected to GPS coordinates. A high correlation between LiDAR plant volume and biomass on a Fresh Mass (FM) basis was observed with the coefficient of determination of R2 = 0.71 at the row level and R2 = 0.73 at the plot level. This indicated that LiDAR plant volume is strongly correlated with biomass and therefore the DairyBioBot demonstrates the utility of an autonomous platform to estimate in-field biomass for perennial ryegrass. It is likely that no single platform will be optimal to measure plant biomass from landscape to plant scales; the development and application of autonomous ground-based platforms is of greatest benefit to forage breeding programs.

Evaluating the suitability of hyper- and multispectral imaging to detect foliar symptoms of the grapevine trunk disease Esca in vineyards

BackgroundGrapevine trunk diseases (GTDs) such as Esca are among the most devastating threats to viticulture. Due to the lack of efficient preventive and curative treatments, Esca causes severe economic losses worldwide. Since symptoms do not develop consecutively, the true incidence of the disease in a vineyard is difficult to assess. Therefore, an annual monitoring is required. In this context, automatic detection of symptoms could be a great relief for winegrowers. Spectral sensors have proven to be successful in disease detection, allowing a non-destructive, objective, and fast data acquisition. The aim of this study is to evaluate the feasibility of the in-field detection of foliar Esca symptoms over three consecutive years using ground-based hyperspectral and airborne multispectral imaging.ResultsHyperspectral disease detection models have been successfully developed using either original field data or manually annotated data. In a next step, these models were applied on plant scale. While the model using annotated data performed better during development, the model using original data showed higher classification accuracies when applied in practical work. Moreover, the transferability of disease detection models to unknown data was tested. Although the visible and near-infrared (VNIR) range showed promising results, the transfer of such models is challenging. Initial results indicate that external symptoms could be detected pre-symptomatically, but this needs further evaluation. Furthermore, an application specific multispectral approach was simulated by identifying the most important wavelengths for the differentiation tasks, which was then compared to real multispectral data. Even though the ground-based multispectral disease detection was successful, airborne detection remains difficult.ConclusionsIn this study, ground-based hyperspectral and airborne multispectral approaches for the detection of foliar Esca symptoms are presented. Both sensor systems seem to be suitable for the in-field detection of the disease, even though airborne data acquisition has to be further optimized. Our disease detection approaches could facilitate monitoring plant phenotypes in a vineyard.

Abundance measurements of H2O and carbon-bearing species in the atmosphere of WASP-127b confirm its supersolar metallicity

ABSTRACT The chemical abundances of exoplanet atmospheres may provide valuable information about the bulk compositions, formation pathways, and evolutionary histories of planets. Exoplanets with large, relatively cloud-free atmospheres, and which orbit bright stars provide the best opportunities for accurate abundance measurements. For this reason, we measured the transmission spectrum of the bright (V ∼ 10.2), large (1.37 RJ), sub-Saturn mass (0.19 MJ) exoplanet WASP-127b across the near-UV to near-infrared wavelength range (0.3–5 μm), using the Hubble and Spitzer Space Telescopes. Our results show a feature-rich transmission spectrum, with absorption from Na, H2O, and CO2, and wavelength-dependent scattering from small-particle condensates. We ran two types of atmospheric retrieval models: one enforcing chemical equilibrium, and the other which fit the abundances freely. Our retrieved abundances at chemical equilibrium for Na, O, and C are all supersolar, with abundances relative to solar values of 9$^{+15}_{-6}$, 16$^{+7}_{-5}$, and 26$^{+12}_{-9}$, respectively. Despite giving conflicting C/O ratios, both retrievals gave supersolar CO2 volume mixing ratios, which adds to the likelihood that WASP-127b’s bulk metallicity is supersolar, since CO2 abundance is highly sensitive to atmospheric metallicity. We detect water at a significance of 13.7σ. Our detection of Na is in agreement with previous ground-based detections, though we find a much lower abundance, and we also do not find evidence for Li or K despite increased sensitivity. In the future, spectroscopy with James Webb Space Telescope will be able to constrain WASP-127b’s C/O ratio, and may reveal the formation history of this metal-enriched, highly observable exoplanet.

3 m × 3 m heterolithic passive resonant gyroscope with cavity length stabilization

Large-scale high sensitivity laser gyroscopes have important applications for ground-based and space-based gravitational wave detection. We report on the development of a 3 m × 3 m heterolithic passive resonant gyroscope (HUST-1) which is installed on the ground of a cave laboratory. We operate the HUST-1 on different longitudinal cavity modes and the rotation sensitivity reaches 1.6 × 10−9 rad s−1 Hz−1/2 above 1 Hz. The drift of the cavity length is one of the major sensitivity limits for our gyroscope in the low frequency regime. By locking cavity length to an ultra-stable reference laser, we achieve a cavity length stability of 5.6 × 10−9 m Hz−1/2 at 0.1 mHz, a four orders of magnitude improvement over the unconstrained cavity in the low frequency regime. We stabilize the cavity length of a large-scale heterolithic passive resonant gyroscope through active feedback and realize long-term operation. The rotation sensitivity reaches 1.7 × 10−7 rad s−1 Hz−1/2 at 0.1 mHz, a three orders of magnitude improvement over the unconstrained cavity, which is no longer limited by the cavity length drift in this frequency range.

LRG-BEASTS: ground-based detection of sodium and a steep optical slope in the atmosphere of the highly inflated hot-saturn WASP-21b

ABSTRACT We present the optical transmission spectrum of the highly inflated Saturn-mass exoplanet WASP-21b, using three transits obtained with the ACAM instrument on the William Herschel Telescope through the LRG-BEASTS survey (Low Resolution Ground-Based Exoplanet Atmosphere Survey using Transmission Spectroscopy). Our transmission spectrum covers a wavelength range of 4635–9000 Å, achieving an average transit depth precision of 197 ppm compared to one atmospheric scale height at 246 ppm. We detect Na i absorption in a bin width of 30 Å at >4σ confidence, which extends over 100 Å. We see no evidence of absorption from K i. Atmospheric retrieval analysis of the scattering slope indicates it is too steep for Rayleigh scattering from H2, but is very similar to that of HD 189733b. The features observed in our transmission spectrum cannot be caused by stellar activity alone, with photometric monitoring of WASP-21 showing it to be an inactive star. We therefore conclude that aerosols in the atmosphere of WASP-21b are giving rise to the steep slope that we observe, and that WASP-21b is an excellent target for infrared observations to constrain its atmospheric metallicity.

Exploring rapid transient detection with the Athena Wide Field Imager

X-ray transients are among the most enigmatic objects in the cosmic sky. In recent years, the unpredictability and underlying nature of their transient behavior has prompted many studies. While significant progress has been made in this field, a more complete understanding of such events is often hampered by the delay in the rapid follow-up of any transient event. An efficient way to mitigate this constraint would be to devise a way for near real-time detection of such transient phenomena. The Advanced Telescope for High-Energy Astrophysics/Wide Field Imager (Athena/WFI), with its 40 ′ × 40 ′ field of view and large effective area, will detect a large number of x-ray variable or transient objects daily. We discuss an algorithm for the rapid onboard or ground-based detection of x-ray transients with WFI. We present a feasibility test of the algorithm using simulated Athena WFI data and show that a fairly simple algorithm can effectively detect transient and variable sources in typical Athena WFI observations.

Suitability of the MODIS-NDVI Time-Series for a Posteriori Evaluation of the Citrus Tristeza Virus Epidemic

The technological advances of remote sensing (RS) have allowed its use in a number of fields of application including plant disease depiction. In this study, an RS approach based on an 18-year (i.e., 2001–2018) time-series analysis of Normalized Difference Vegetation Index (NDVI) data, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and processed with TIMESAT free software, was applied in Sicily (insular Italy). The RS approach was carried out in four orchards infected by Citrus tristeza virus (CTV) at different temporal stages and characterized by heterogeneous conditions (e.g., elevation, location, plant age). The temporal analysis allowed the identification of specific metrics of the NDVI time-series at the selected sites during the study period. The most reliable parameter which was able to identify the temporal evolution of CTV syndrome and the impact of operational management practices was the “Base value” (i.e., average NDVI during the growing seasons, which reached R2 values up to 0.88), showing good relationships with “Peak value”, “Small integrated value” and “Amplitude”, with R2 values of 0.63, 0.70 and 0.75, respectively. The approach herein developed is valid to be transferred to regional agencies involved in and/or in charge of the management of plant diseases, especially if it is integrated with ground-based early detection methods or high-resolution RS approaches, in the case of quarantine plant pathogens requiring control measures at large-scale level.

Real-time laser Doppler spectra of complex targets in orbit from different ground-based observation stations

A new model for detecting the Doppler spectra of space targets is presented in this paper. The method takes into account the atmospheric attenuation and the changes in different ground-based observation stations. We calculate the real-time Doppler spectra and backscattered power of targets to demonstrate the effects of the proposed scheme. The micro and linear motions of orbiting targets are discussed with respect to the dimensions of the targets and the observation stations in the Lambertian and exponential cases. The results show that the height of the target causes the change of the backscattered power, the detection from different observation stations has a great influence on the backscattered power and the Doppler spectra are caused by linear motion. Our work will provide the theory and model for the development of micromotion detection, target recognition, ground-based LiDAR detection, and engineering applications.

Growth Height Determination of Tree Walls for Precise Monitoring in Apple Fruit Production Using UAV Photogrammetry

In apple cultivation, spatial information about phenotypic characteristics of tree walls would be beneficial for precise orchard management. Unmanned aerial vehicles (UAVs) can collect 3D structural information of ground surface objects at high resolution in a cost-effective and versatile way by using photogrammetry. The aim of this study is to delineate tree wall height information in an apple orchard applying a low-altitude flight pattern specifically designed for UAVs. This flight pattern implies small distances between the camera sensor and the tree walls when the camera is positioned in an oblique view toward the trees. In this way, it is assured that the depicted tree crown wall area will be largely covered with a larger ground sampling distance than that recorded from a nadir perspective, especially regarding the lower crown sections. Overlapping oblique view images were used to estimate 3D point cloud models by applying structure-from-motion (SfM) methods to calculate tree wall heights from them. The resulting height models were compared with ground-based light detection and ranging (LiDAR) data as reference. It was shown that the tree wall profiles from the UAV point clouds were strongly correlated with the LiDAR point clouds of two years (2018: R2 = 0.83; 2019: R2 = 0.88). However, underestimation of tree wall heights was detected with mean deviations of −0.11 m and −0.18 m for 2018 and 2019, respectively. This is attributed to the weaknesses of the UAV point clouds in resolving the very fine shoots of apple trees. Therefore, the shown approach is suitable for precise orchard management, but it underestimated vertical tree wall expanses, and widened tree gaps need to be accounted for.

Identification and Extraction of Geomorphological Features of Landslides Using Slope Units for Landslide Analysis

A slope unit is commonly used as calculation unit for regional landslide analysis. However, the capacity of the slope unit to reflect the geomorphological features of actual landslides still needs to be verified. This is because such accurate representation is critical to ensure the physical meaning of results from subsequent landslide stability analysis. This paper presents work conducted on landslides and slope extraction in two areas in China: The Jiangjia Gully area (Yunnan Province) and Fengjie County (Chongqing Municipality). Ground-based light detection and ranging (LiDAR) data are combined with field landslide terrace measurements to allow for the comparison of slope unit extraction methods (conventional vs. MIA-HSU) in terms of their ability to reflect the geomorphological features of shallow and deep-seated landslides. The results indicate that slope unit boundaries extracted by the conventional method do not match the geomorphological variations of actual landslides, and the method is therefore deficient in meaningfully extracting slope units for further landslide analysis. By contrast, slope units obtained using the MIA-HSU method accurately reflects the geomorphological features of both shallow and deep-seated landslides, and thus provides clearer geomorphological meaning and more reasonable calculation units for regional landslide assessment and prediction.

A Combined IR-GPS Satellite Analysis for Potential Applications in Detecting and Predicting Lightning Activity

Continuous estimates of the vertical integrated precipitable water vapor content from the tropospheric delay of the signal received by the antennas of the global positioning system (GPS) are used in this paper, in conjunction with the measurements of the Meteosat Second Generation (MSG) spinning enhanced visible and infrared imager (SEVIRI) radiometer and with the lightning activity, collected here by the ground-based lightning detection network (LINET), in order to identify links and recurrent patterns useful for improving nowcasting applications. The analysis of a couple of events is shown here as an example of more general behavior. Clear signs appear before the peak of lightning activity on a timescale from 2 to 3 h. In particular, the lightning activity is generally preceded by a period in which the difference between SEVIRI brightness temperature (TB) at channel 5 and channel 6 (i.e., ∆TB) presents quite constant values around 0 K. This trend is accompanied by an increase in precipitable water vapor (PWV) values, reaching a maximum in conjunction with the major flash activity. The results shown in this paper evidence good potentials of using radiometer and GPS measurements together for predicting the abrupt intensification of lightning activity in nowcasting systems.

First Detection of the [O i] 63 μm Emission from a Redshift 6 Dusty Galaxy

Abstract We report a ground-based detection of the [O i] 63 μm line in a z = 6.027 gravitationally lensed dusty star-forming galaxy (DSFG) G09.83808 using the Atacama Pathfinder EXperiment SEPIA 660 receiver, the first unambiguous detection of the [O i]63 line beyond redshift 3, and the first obtained from the ground. The [O i]63 line is robustly detected at 22 ± 5 Jy km s−1, corresponding to an intrinsic (de-lensed) luminosity of (5.4 ± 1.3) × 109 L ⊙. With the [O i]63/[C ii] luminosity ratio of 4, the [O i]63 line is the main coolant of the neutral gas in this galaxy, in agreement with model predictions. The high [O i]63 luminosity compensates for the pronounced [C ii] deficit ([C ii]/FIR ≃ 4 × 10−4). Using photon-dominated region models, we derive a source-averaged gas density n = 104.0 cm−3, and FUV field strength G = 104 G 0, comparable to the z = 2–4 DSFG population. If G09.83808 represents a typical high-redshift DSFG, the [O i]63 line from z = 6 non-lensed DSFGs should be routinely detectable in the Atacama Large Millimeter/submillimeter Array Band 9 observations with ∼15 minutes on-source, opening a new window to study the properties of the earliest DSFGs.

Characterization of Back-Scattering and Multipath in a Suburban Area after the Calibration of an X-Band Commercial Radar.

The increasing interest in the radar detection of low-elevation and small-size targets in complicated ground environments (such as urban, suburban, and mixed country areas) calls for a precise quantification of the radar detection capabilities in those areas. Hence, a set of procedures is devised and tested, both theoretically and experimentally, using a commercial X-band radar, to (i) calibrate the radar sensor (with an online evaluation of its losses) using standard scatterers, (ii) measure the multipath effect and compensate for it, and (iii) create “true radar cross section” maps of the area of interest for both point and distributed clutter. The above methods and the related field results are aimed at future qualification procedures and practical usage of small, cheap, and easily moveable radars for the detection of low-observable air targets, such as unmanned air vehicles/systems (UAV/UAS), in difficult ground areas. A significant set of experimental results as discussed in the paper confirms the great relevance of multipath in ground-based radar detection, with the need for correcting measures.

Terrestrial gamma-ray flashes as the high-energy effect of tropospheric thunderstorms in near-Earth space

<p indent="0mm">Thunderstorms in the troposphere produce lightning flashes and cause charge transfer of different strength at varying spatial and temporal scales, leading to various forms of transient electromagnetic effects in the vast space above thunderstorms. In particular, normal intra-cloud (IC) lightning can generate ionizing hard X-rays and gamma rays, forming Terrestrial Gamma-ray Flashes (TGFs). We briefly summarize the progress in TGF studies that has been achieved in the past decade based on multiple space-borne platforms: (1) TGFs are usually associated with the upward negative leader during the initial stage of IC flashes and are often accompanied by relatively strong IC discharge with high peak current and large charge transfer, which is called the energetic IC pulse (EIP); (2) based on the characteristics of TGF-related radio-frequency signals, we can develop a remote sensing approach with ground-based measurements of lightning signals, thereby greatly enriching the investigation dataset of TGFs and parent thunderstorms; (3) till date, no unified mechanism for TGF production has been developed due to a lack of effective observation with respect to the source region. Thermal runaway breakdown and relativistic runaway electron breakdown are the two mainstream theories to explain TGF production. Compared with transient luminous events (TLEs; e.g., red sprites, gigantic jets, and blue jets) as the lightning-induced dielectric breakdown in the mesosphere, studies on TGFs, in terms of both observations and theoretical interpretation, lag behind the research in Europe and the USA. However, along with China’s latest progress in space detection technology (particularly the implementation of the <italic>Insight</italic> Hard X-ray Modulation Telescope (<italic>Insight</italic>-HXMT) and the Gravitational-wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM)), researchers in China desire to make steady progress in the field of TGF studies through continuous efforts in developing ground-based lightning detection techniques.

TOI-222: a single-transit TESS candidate revealed to be a 34-d eclipsing binary with CORALIE, EulerCam, and NGTS

ABSTRACT We report the period, eccentricity, and mass determination for the Transiting Exoplanet Survey Satellite (TESS) single-transit event candidate TOI-222, which displayed a single 3000 ppm transit in the TESS 2-min cadence data from Sector 2. We determine the orbital period via radial velocity measurements (P = 33.9 d), which allowed for ground-based photometric detection of two subsequent transits. Our data show that the companion to TOI-222 is a low-mass star, with a radius of $0.18_{-0.10}^{+0.39}$ R⊙ and a mass of 0.23 ± 0.01 M⊙. This discovery showcases the ability to efficiently discover long-period systems from TESS single-transit events using a combination of radial velocity monitoring coupled with high-precision ground-based photometry.

Evaluating the Ability of Remote Sensing Observations to Identify Significantly Severe and Potentially Tornadic Storms.

Remote sensing observations, especially those from ground-based radars, have been used extensively to discriminate between severe and nonsevere storms. Recent upgrades to operational remote sensing networks in the United States have provided unprecedented spatial and temporal sampling to study such storms. These networks help forecasters subjectively identify storms capable of producing severe weather at the ground; however, uncertainties remain in how to objectively identify severe thunderstorms using the same data. Here, three large-area datasets (geostationary satellite, ground-based radar, and ground-based lightning detection) are used over 28 recent events in an attempt to objectively discriminate between severe and nonsevere storms, with an additional focus on severe storms that produce tornadoes. Among these datasets, radar observations, specifically those at mid- and upper levels (altitudes at and above 4 km), are shown to provide the greatest objective discrimination. Physical and kinematic storm characteristics from all analyzed datasets imply that significantly severe [≥2-in. (5.08 cm) hail and/or ≥65-kt (33.4 ms-1) straight-line winds] and tornadic storms have stronger upward motion and rotation than nonsevere and less severe storms. In addition, these metrics are greatest in tornadic storms during the time in which tornadoes occur.