Thunderstorm Research Articles

Effects of Within-Storm Variability on Allochthonous Flash Flooding: A Synthetic Study

Rainfall is a spatiotemporally variated process and one of the key elements to accurately capture both catchment runoff response and floodplain extents. Flash floods are the result of intense rainfall, typically associated to highly variable rain in both space and time, such as convective storms. In this work, the extent within-storm variability affects runoff and flooding is explored. The Kan catchment (Tehran, Iran) is used as base topography for the simulations. The allochthonous nature of floods in the catchment and how they interact with the effects of storm variability are further investigated. For this, 300 synthetic rainfall signals with different hyetograph variabilities are generated and imposed on a 1D/2D hydrodynamic model. Additionally, a set of simulations with different levels of spatial variability are performed. The results suggest that temporal and spatial variability affect the runoff response in different degrees. Peak discharge and hydrograph shapes, as well as flooded areas, are affected. The effect of storm temporal variability is shown to be significantly higher than storm spatial variability and storm properties such as return period, duration, and volume. Further on the influence of storm spatiotemporal variability on stream discharge and flood response is seen to be strongly dependent on the location within the drainage network at which it is assessed.

Types of Severe Convective Wind Events in Eastern Australia

Abstract Severe winds associated with thunderstorms and convection are a hazard affecting key aspects of society, including emergency management and infrastructure design. Several studies around the world have shown that severe convective winds (SCWs) can occur due to several different processes, in a range of atmospheric environments, with significant regional and temporal variations. However, in eastern Australia, the types of SCWs and their variability have not been assessed outside of individual case studies. Here, a combination of reanalysis, lightning, radar, and station data are used to characterize a set of 36 SCW events in four locations in eastern Australia. These events are objectively chosen based on the strongest measured wind gusts from station data (greater than 25 m s−1) over a 14-yr period, with 6-hourly lightning data and a 30-dBZ radar reflectivity threshold used to infer moist convective processes. Radar data analysis suggests that these SCW events are produced by several different types of parent thunderstorms, with station observations suggesting a range of temporal characteristics for these different event types. A clustering algorithm applied to environmental data is used to suggest three dominant types of events, based on low-level moisture, low-level temperature lapse rate, and deep-layer mean wind speed and vertical shear. Based on the distribution of synoptic conditions and thunderstorm properties for each environmental cluster, it is suggested that these three event types correspond to the following: 1) shallow vertical transport of strong synoptic-scale winds to the surface, 2) downbursts driven by subcloud evaporation, and 3) intense thunderstorms including supercells. Significance Statement The purpose of this study is to better understand the different types of severe wind events in eastern Australia that are produced by convective storms. We looked at 36 historical cases in four locations and find that severe winds can be produced by very different classes of convective storms. We also suggest that there are three key types of atmospheric environment that are associated with events in this region. These environments vary in terms of the vertical structure of temperature, moisture, and wind speed above the surface. Understanding the different types of environments that lead to severe convective winds can help to reduce uncertainties in future climate projections for this region based on environmental changes.

Electrical storm in hyperthyroidism: A case report

Electrical storm in hyperthyroidism: A case report

Retrieving Vertical Cloud Radar Reflectivity from MODIS Cloud Products with CGAN: An Evaluation for Different Cloud Types and Latitudes

Retrieving cloud vertical structures with satellite remote-sensing measurements is highly desirable and technically challenging. In this paper, the conditional adversarial neural network (CGAN) for retrieving the equivalent cloud radar reflectivity at 94 GHz of the Cloud Profile Radar (CPR) onboard CloudSat is extended and evaluated comprehensively for different cloud types and geographical regions. The CGAN-based retrieval model was extended with additional data samples and improved with a new normalization adjustment. The model was trained with the labeled datasets of the moderate-resolution imaging spectroradiometer (MODIS) cloud top pressure, cloud water path, cloud optical thickness, and effective particle radius data, and the CloudSat/CPR reflectivity from 2010 to 2017 over the global oceans. The test dataset, containing 24,427 cloud samples, was statistically analyzed to assess the performance of the model for eight cloud types and three latitude zones with multiple verification metrics. The results show that the CGAN model possesses good reliability for retrieving clouds with reflectivity > −25 dBZ. The model performed the best for deep convective systems, followed by nimbostratus, altostratus, and cumulus, but presented a very limited ability for stratus, cirrus, and altocumulus. The model performs better in the low and middle latitudes than in the high latitudes. This work demonstrated that the CGAN model can be used to retrieve vertical structures of deep convective clouds and nimbostratus with great confidence in the mid- and lower latitude region, laying the ground for retrieving reliable 3D cloud structures of the deep convective systems including convective storms and hurricanes from MODIS cloud products and used for predicting these storms.

The Impact of Vertical Wind Shear on the Outcome of Interactions Between Squall Lines and Cities

AbstractThis study examines how organized lines of deep convective storms can be impacted by a large city with a prominent urban heat island and how low‐level environmental vertical wind shear may influence the outcomes of that interaction. Idealized simulations of squall lines are conducted in which a simplified urban area—defined by perturbations to skin temperature and surface roughness length—is placed in the center of an otherwise horizontally homogeneous domain. Simulations are conducted with three different magnitudes of low‐level vertical wind shear representing “weak,” “medium,” and “strong” shear environments. Results show that storms experience noticeable modification—including enhanced downwind precipitation—after interacting with a prominent urban heat island in all three shear configurations. However, the details of the modification are a function of the shear magnitude. In the medium and strong shear simulations, updrafts are enhanced via increased buoyancy after passing over a prominent urban heat island. In contrast, little updraft strengthening is evident in the weak‐shear simulations. Instead, near‐surface winds are enhanced downwind of the urban heat island due to a more prominent descending rear‐inflow jet.

Deep Clouds on Jupiter

Jupiter’s atmospheric water abundance is a highly important cosmochemical parameter that is linked to processes of planetary formation, weather, and circulation. Remote sensing and in situ measurement attempts still leave room for substantial improvements to our knowledge of Jupiter’s atmospheric water abundance. With the motivation to advance our understanding of water in Jupiter’s atmosphere, we investigate observations and models of deep clouds. We discuss deep clouds in isolated convective storms (including a unique storm site in the North Equatorial Belt that episodically erupted in 2021–2022), cyclonic vortices, and northern high-latitude regions, as seen in Hubble Space Telescope visible/near-infrared imaging data. We evaluate the imaging data in continuum and weak methane band (727 nm) filters by comparison with radiative transfer simulations, 5 micron imaging (Gemini), and 5 micron spectroscopy (Keck), and conclude that the weak methane band imaging approach mostly detects variation in the upper cloud and haze opacity, although sensitivity to deeper cloud layers can be exploited if upper cloud/haze opacity can be separately constrained. The cloud-base water abundance is a function of cloud-base temperature, which must be estimated by extrapolating 0.5-bar observed temperatures downward to the condensation region near 5 bar. For a given cloud base pressure, the largest source of uncertainty on the local water abundance comes from the temperature gradient used for the extrapolation. We conclude that spatially resolved spectra to determine cloud heights—collected simultaneously with spatially-resolved mid-infrared spectra to determine 500-mbar temperatures and with improved lapse rate estimates—would be needed to answer the following very challenging question: Can observations of deep water clouds on Jupiter be used to constrain the atmospheric water abundance?

Successful percutaneous coronary intervention with extracorporeal membrane oxygenation in a patient with acute inferior wall myocardial infarction complicated by electrical storm, cardiogenic shock, and cardiac arrest: a case report

BackgroundHigh-risk patients with coronary heart disease who develop acute myocardial infarction (AMI) have severe coronary lesions. If severe complications occur, such as malignant ventricular arrhythmia, cardiogenic shock, and cardiac arrest, implementation of emergency percutaneous coronary intervention (PCI) may be hindered, leading to a higher perioperative mortality rate. Extracorporeal membrane oxygenation (ECMO) can pave the way for rapid myocardial reperfusion therapy. When cardiac arrest occurs, hemodynamic support with ECMO can facilitate revascularization with PCI, which can increase the time available for further salvage and treatment and reduce intraoperative risk during PCI.Case presentationHerein, we report a case of a 61-year-old man with AMI who suffered electrical storm of sustained malignant ventricular fibrillation, cardiogenic shock, and cardiac arrest and was successfully treated with PCI with ECMO support. During PCI, repeated aspiration and removal of the right coronary artery thrombus were performed, and blood flow was restored after right coronary artery balloon dilation. One episode of defibrillation was delivered to restore sinus rhythm. Then, stents were implanted in the distal and proximal right coronary artery lesions to achieve revascularization. After PCI with ECMO support, irreversible malignant arrhythmia returned to sinus rhythm through coronary perfusion, which prevented death following unsuccessful cardiopulmonary resuscitation. After applying active treatments, including anti-shock, mechanical ventilation, anti-inflammation, and organ support, the patient was discharged after his condition and vital signs stabilized. The patient was followed up once a week after hospital discharge, and his cardiopulmonary function recovered well.ConclusionsWith ECMO support, PCI should be performed immediately in patients with inferior wall AMI complicated by electrical storm of sustained ventricular fibrillation, cardiogenic shock, and cardiac arrest to facilitate stent placement, achieve complete revascularization, restore coronary perfusion, and avoid death

Proarrhythmic effect of bipolar epicardial left ventricular stimulation in CRT resolved maintaining biventricular pacing with unipolar-cathodical configuration: A peculiar case report.

The effect of cardiac resynchronization therapy (CRT) on the risk of ventricular arrhythmias is controversial. Several studies reported a decreased risk, but some studies reported a potential proarrhythmic effect of epicardial left ventricular pacing resolved upon discontinuation of biventricular pacing (BiVp). A 67-year-old woman with a history of heart failure due to nonischemic cardiomyopathy and left bundle branch block was hospitalized for CRT device implantation. Unpredictably, as soon as the leads have been connected to the generator, an electrical storm (ES) occurred with relapsing self-resolving polymorphic ventricular tachycardia (PVT) triggered by ventricular extra beats with short-long-short sequences. The ES was resolved without interrupting BiVp switching to unipolar left ventricular (LV) pacing. This allowed to keep CRT active with extreme clinical benefit for the patient and to demonstrate that the cause of the PVT was the anodic capture of bipolar LV stimulation. Reverse electrical remodeling was also demonstrated after 3 months of effective BiVp. Proarrhythmic effect of CRT is a rare but significant complication of CRT, and it may compel to discontinuation of the BiVp. The reversal of the physiological transmural activation sequence of epicardial LV pacing and subsequent prolonging of corrected QT interval have been speculated as the most probable explanation, but our case highlights the possibility that the anodic capture may play a relevant role in PVT genesis.

On the Impact of GPS Multipath Correction Maps and Post-Fit Residuals on Slant Wet Delays for Tracking Severe Weather Events

Climate change has increased the frequency and intensity of weather events with heavy precipitation, making communities worldwide more vulnerable to flash flooding. As a result, accurate fore- and nowcasting of impending excessive rainfall is crucial for warning and mitigating these hydro-meteorological hazards. The measurement of integrated water vapour along slant paths is made possible by ground-based global positioning system (GPS) receiver networks, delivering three-dimensional (3D) water vapour distributions at low cost and in real-time. As a result, these data are an invaluable supplementary source of knowledge for monitoring storm events and determining their paths. However, it is generally known that multipath effects at GPS stations have an influence on incoming signals, particularly at low elevations. Although estimates of zenith total delay and horizontal linear gradients make up the majority of the GPS products for meteorology to date, these products are not sufficient for understanding the full 3D distribution of water vapour above a station. Direct utilization of slant delays can address this lack of azimuthal information, although, at low elevations it is more prone to multipath (MP) errors. This study uses the convective storm event that happened on 27 July 2017 over Bulgaria, Greece, and Turkey, which caused flash floods and severe damage, to examine the effects of multipath-corrected slant wet delay (SWD) estimations on monitoring severe weather events. First, we reconstructed the one-way SWD by adding GPS post-fit phase residuals, describing the anisotropic component of the SWD. Because MP errors in the GPS phase observables can considerably impact SWD from individual satellites, we used an averaging technique to build station-specific MP correction maps by stacking the post-fit phase residuals acquired from a precise point positioning (PPP) processing strategy. The stacking was created by spatially organizing the residuals into congruent cells with an optimal resolution in terms of the elevation and azimuth at the local horizon.This enables approximately equal numbers of post-fit residuals to be distributed across each congruent cell. Finally, using these MP correction maps, the one-way SWD was improved for use in the weather event analysis. We found that the anisotropic component of the one-way SWD accounts for up to 20% of the overall SWD estimates. For a station that is strongly influenced by site-specific multipath error, the anisotropic component of SWD can reach up to 4.3 mm in equivalent precipitable water vapour. The result also showed that the spatio-temporal changes in the SWD as measured by GPS closely reflected the moisture field estimated from a numerical weather prediction model (ERA5 reanalysis) associated with this weather event.

Convective Storm VIL and Lightning Nowcasting Using Satellite and Weather Radar Measurements Based on Multi-Task Learning Models

Convective Storm VIL and Lightning Nowcasting Using Satellite and Weather Radar Measurements Based on Multi-Task Learning Models

An Empirical Relationship among Characteristics of Severe Convective Storms, Their Cloud-Top Properties and Environmental Parameters in Northern Eurasia

Severe convective storms that produce tornadoes and straight-line winds usually develop under particular environmental conditions and have specific signatures on the cloud tops associated with intense updrafts. In this study, we performed a comparative analysis of satellite-derived characteristics, with a focus on cloud-top properties, and ERA5-based environmental parameters of convective storms in forested regions of the western part of Northern Eurasia in 2006–2021. The analyzed sample includes 128 different convective storms that produced 138 tornadoes and 143 linear windstorms. We found most tornadoes and linear windstorms are generated by quasi-linear convective storms or supercells. Such supercells form under lower convective instability and precipitable water content compared to those for other types of storms. We found a significant negative correlation of minimum temperature on the storm cloud top with instability parameters. In turn, the longevity of convective storms significantly correlates with wind shear and storm-relative helicity. About half of the tornadoes and 2/3 of linear windstorms are associated with the presence of cloud-top signatures, such as overshooting tops, cold-ring or cold U/V features. The events associated with such signatures are formed under high values of instability parameters. Our results can be used for further analysis of peculiarities of tornado and linear windstorm formation and to enhance the predictability of such severe events, especially in regions with a lack of weather radar coverage.

Quantitative impacts of vertical transport on the long-term trend of nocturnal ozone increase over the Pearl River Delta region during 2006–2019

Abstract. The Pearl River Delta (PRD) region in southern China has been subject to severe ozone (O3) pollution during daytime and anomalous nocturnal O3 increase (NOI) during nighttime. In this study, the spatiotemporal variation of NOI events in the PRD region from 2006 to 2019 is comprehensively analysed, and the role of vertical transport in the occurrence of NOI events is quantified based on observed surface and vertical O3 and the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) dataset. The results show that the average annual frequency of NOI events in the whole PRD region during the 14 year period is estimated to be 53 ± 16 d yr−1, with an average of 58 ± 11 µg m−3 for the nocturnal O3 peak (NOP) concentration. Low-level jets (LLJs) are the main meteorological processes triggering NOI events, explaining on average 61 % of NOI events. Annual NOI events exhibit an upward trend before 2011 (4.70 d yr−1) and a downward trend thereafter (−0.72 d yr−1), which is consistent with the annual variation of LLJs (r=0.88, p<0.01). Although the contribution of convective storms (Conv) to NOI events is relatively small with an average value of 11 %, Conv-induced NOI events steadily increased at a rate of 0.26 d yr−1 during this 14 year period due to the impact of urbanisation. Seasonally, a relatively higher frequency of NOI events is observed in spring and autumn, which is consistent with the seasonal pattern of LLJs and maximum daily 8 h average (MDA8) O3. Spatially, NOI events are frequent in the eastern PRD, which agrees well with the spatial distribution of the frequency of LLJs and partially overlaps with the distribution of MDA8 O3 concentration, suggesting that vertical transport plays a more important role in NOI events than daytime O3 concentration. The Weather Research and Forecasting (WRF) model coupled with the Community Multiscale Air Quality (CMAQ) model and the observed vertical O3 profiles are further applied to illustrate the mechanisms of NOI formation caused by LLJs and Conv. The results confirm that both LLJs and Conv trigger NOI events by inducing downdrafts with the difference being that LLJs induce downdrafts by wind shear, while Conv by compensating downdrafts. Through observational and modelling analysis, this study presents the long-term (2006–2019) trends of NOI events in the PRD region and quantifies the contribution of meteorological processes for the first time, emphasising the importance of vertical transport, as well as daytime O3 concentration for the occurrence of NOI events.

Amazon windthrow disturbances are likely to increase with storm frequency under global warming

Forest mortality caused by convective storms (windthrow) is a major disturbance in the Amazon. However, the linkage between windthrows at the surface and convective storms in the atmosphere remains unclear. In addition, the current Earth system models (ESMs) lack mechanistic links between convective wind events and tree mortality. Here we find an empirical relationship that maps convective available potential energy, which is well simulated by ESMs, to the spatial pattern of large windthrow events. This relationship builds connections between strong convective storms and forest dynamics in the Amazon. Based on the relationship, our model projects a 51 ± 20% increase in the area favorable to extreme storms, and a 43 ± 17% increase in windthrow density within the Amazon by the end of this century under the high-emission scenario (SSP 585). These results indicate significant changes in tropical forest composition and carbon cycle dynamics under climate change.

Large-scale dynamics moderate impact-relevant changes to organised convective storms

Larger organised convective storms (mesoscale-convective systems) can lead to major flood events in Europe. Here we assess end-of-century changes to their characteristics in two convection-permitting climate simulations from the UK Met Office and ETH-Zürich that both use the high Representative Concentration Pathway 8.5 scenario but different approaches to represent atmospheric changes with global warming and different models. The UK Met Office projections indicate more frequent, smaller, and slower-moving storms, while ETH-Zürich projections show fewer, larger, and faster-moving storms. However, both simulations show increases to peak precipitation intensity, total precipitation volume, and temporal clustering, suggesting increasing risks from mesoscale-convective systems in the future. Importantly, the largest storms that pose increased flood risks are projected to increase in frequency and intensity. These results highlight that understanding large-scale dynamical drivers as well as the thermodynamical response of storms is essential for accurate projections of changes to storm hazards, needed for future climate adaptation.

Management of hemodynamically stable wide QRS complex tachycardia in patients with implantable cardioverter defibrillators.

The preparation phase includes reversal of potential arrhythmia "triggers", mild patient sedation, and patient monitoring for therapy delivery. Based on resource availability and competences, the most adequate therapeutic approach is chosen. This choice depends on whether a device specialist is readily available or not. In the case of ES in a "high-risk" patient an accelerated patient management protocol is advocated, which considers urgent ventricular tachycardia transcatheter ablation with or without mechanical cardiocirculatory support. Therapeutic phase is based on the use of intravenous anti-arrhythmic drugs mostly indicated in this clinical context are presented. Device interrogation is very important in this phase when sustained monomorphic VT diagnosis is confirmed, then ICD ATP algorithms, based on underlying VT cycle length, are proposed. In high-risk patients with intractable ES, intensive patient management considers MCS and transcatheter ablation. The patient is hospitalized for further diagnostics and management aimed at preventing arrhythmia recurrences.

Hail climatology and its possible attributions in Beijing, China: 1980-2021

Hail hazards have caused severe losses and threatened the safety of residents in Beijing, the Chinese capital city. A refined analysis of the spatial and temporal distribution of hailstorms in Beijing can help to evaluate the risk of hail and guide the operations of hail prevention. The distribution of weather stations is relatively sparse to figure out the fine distribution of hail events. Therefore, a quality-controlled dataset of disaster information data reported from information reporters is used to analyze the fine temporal and spatial distributions of hail days and events in Beijing from 1980 to 2021 in this study. Hail events and hail days show an obvious downward trend with years from 1981 to 2010, while hail events show a strong upward trend from 2011 to 2021. The seasonal pattern of hail events shows a unimodal distribution from March to October, and the peak appears in June. Most of the hail events occurred from 14:00 to 21:00, while the highest counts appeared from 15:00 to 17:00. More and larger hails occurred in the northwestern mountains rather than southeastern plains in Beijing, highly correlated with the topography. Both total and severe hails hit the mountain area statistically earlier than the plain area. The most frequent hours of hails in the northwestern area and southeastern area were concentrated in the range of 13:00—17:00 and 16:00—20:00 CST, respectively. This time delay is due to the initiation location and movement direction of the convective storms. The influence of ENSO on warm season hails is positive in Beijing, which has a lag of 3 months or longer. The arctic oscillation has a negative correlation with hail days in each month from May to September.

Pixel-CRN: A New Machine Learning Approach for Convective Storm Nowcasting

The short-term convective storm forecasting (i.e., nowcasting) mainly rely on weather radar which can resolve the 3D structure of convective storms. With the rapid development of numerical models, modern models can produce 3D reanalysis data which gives atmospheric background information of convective storms. Current deep learning nowcasting models use only 2D radar images for nowcasting and often require massive historical data for training. But it may not be operationally feasible to collect long-term radar data to train a new model. Hence, how to establish a nowcasting model using only a small dataset has become an important issue. In addition, existing models do not effectively use the state-of-the-art model reanalysis data, which is a shortcoming of these models. To tackle these problems, this article develops a pixel-wise convolutional recurrent neural network (Pixel-CRN) for precipitation nowcasting. It has three key designs: (1) Through a concise pixel-wise sampling and oversampling technique, Pixel-CRN can be trained using only a small dataset. (2) In spatial learning, Pixel-CRN embeds a spatial convolution subnet into the recurrent unit, which can input raw 3D radar and model reanalysis data, thus valuable atmospheric background information can be learned to assist nowcasting. (3) In spatiotemporal learning, according to the information bottleneck principle, Pixel-CRN builds a heterogeneous encoder-decoder structure to squeeze multi-channel 3D input data into latent space, and recurrently generates 30 and 60 min nowcasts. Compared with existing deep learning nowcasting methods, the experimental results show that Pixel-CRN can provide skillful results with a rather small training dataset.

Lightning risk estimation and preventive control method for power distribution networks referring to the indeterminacy of wind power and photovoltaic

• An estimation model based on the prediction of distributed power is put forward to calculate the operating risk of distribution network in lightning weather. • A two-step preventive protection strategy, namely the power flow transferring based on topological reconstruction, and the coordination of the controllable resource, is put forward. • Simulation shows topological reconstruction and the optimization to the distributed power source can improve the stability of distribution system operation, and cut down the load loss in extreme weather. The power distribution networks are deeply influenced by the lightning weather. Such impact includes not only the load loss caused by the outage of the overhead lines due to direct and/or indirect lightning strikes, but also the output fluctuation of the wind power and photovoltaic (PV) connected to the network. Since lightning storms can be forecasted to some extent, it would be useful to establish a model for lightning risk estimation and preventive control of the distribution network, in order to cut the economic loss in extreme weather. In this paper, the scene analysis method is used to simulate the indeterminacy of the wind and PV output based on the lightning storm pre-warning, and the lightning risk and operating state of the distribution networks can be estimated. Referring to the results, lightning preventive strategy of distribution network can be formulated by network topology reconstruction and resource synergy.

A patient with sepsis presenting to emergency with electrical storm

A patient with sepsis presenting to emergency with electrical storm

Ventricular Tachycardia Storm Management in Acute Cardiac Care: Prompt response to life-threatening conditions

Background: Ventricular Tachycardia (VT) storm or electrical storm (ES) is defined as cardiac electrical instability and refers to the occurrence of three or more ventricular tachyarrhythmias (VT and or ventricular fibrillation (VF)) in a 24-hour period, or VT recurring soon (within five minutes) after termination of another VT episode, or sustained or no sustained VT with total ectopic beats greater than sinus beats in a 24-hour period. The frequency of VT storms varies on population. When ICDs are implanted for primary prevention (4 percent), it is lower than when they are implanted for secondary prevention (20 percent). Case Summary: We presented patient with Ventricular Tachycardia (VT) storm. A 63-year old woman was admitted to emergency room with chief complaint frequent episodes of palpitation. She was found to have monomorphic VT with unstable hemodynamic. Then she got cardioversion 100 Joule, continued with lidocaine drip and VT reverted to sinus rhythm. Patient admitted to cardiovascular care unit, but she had VT refractory. She got complete revascularization for coronary artery before, but the episodic of VT still occurred with cardiogenic shock (CS) and pulmonary edema. She got cardioversion, amiodarone iv and inotropes, then observed this patient at CVCU. After the condition stable, this patient was discharged and planned for ICD insertion at the next admission. Discussion: We discuss the various available treatment options for VT storm and practical challenges faced in management of hemodynamically unstable VT storm. Initial management involves identifying and correcting the underlying ischemia, electrolyte imbalances, or other inciting factors.