Warning Area Research Articles

Early Warning of Regional Groundwater Pollution： A Case Study for Plain Area of Barkol-Yiwu Basin

Groundwater pollution early warning is an effective means for regional groundwater pollution prevention. The groundwater pollution early warning model coupled with the current situation of groundwater quality, groundwater quality variation trend, and groundwater pollution risk were applied to the plain area of Barkol-Yiwu Basin, and the regional scale groundwater pollution early warning was realized by combining the early warning of groundwater quality status and trend. The TOPSIS method based on comprehensive weight was used to evaluate the current situation of groundwater quality. The variation trend of groundwater quality was analyzed by calculating the trend interpolation results of 18 in-situ groundwater quality monitoring wells. The groundwater vulnerability map, groundwater pollution load map, and groundwater function value map were superimposed using the superposition index method to evaluate groundwater pollution risk. The results showed that the groundwater quality was good and relatively good, and the poor groundwater quality in some areas was mainly affected by the shallow groundwater depth and the large porosity of the vadose zone. Groundwater quality was stable from 2011 to 2022, mainly due to the leakage of wastewater generated by industries and agriculture into groundwater, resulting in the deterioration of groundwater quality in some areas. Groundwater pollution risk was generally low, and the dual effects of high vulnerability and high pollution load of groundwater led to local areas with high pollution risk. The early warning level of groundwater pollution was generally low, and the heavy and highly heavy warning areas accounted for 16.4% and 17.5% of the study area, respectively, mainly distributed in Xiamaya Township of Yiwu County and northern Santanghu Town, Dahongliuxia Township, and Dahe Town of Barkol County. The quaternary sediments exposed were mainly sandy pebbles, with developed pores and strong water permeability. The interception and adsorption capacity of pollutants were weak. Pollutants produced by industries, agriculture, and life easily leaked into groundwater aquifers, resulting in poor groundwater quality and high risk of groundwater pollution, which ultimately led to a high early warning level of groundwater pollution in some areas. The research on early warning of groundwater pollution provided an important theoretical basis for the development of groundwater pollution remediation.

Landslide Warning Area Delineation through Seismic Signals and Landslide Characteristics: Insights from the Silabaku Landslide in Southern Taiwan

Abstract Publishing timely warnings of areas potentially affected by landslides and subsequent events remains challenging in hazard assessment. Recently, seismic monitoring has emerged as a promising technique for landslide detection and location determination. However, the effectiveness of this approach is limited by location errors. To overcome this problem, we propose a hybrid method (a three-step process) through seismic analysis and consideration of prior geomorphological characteristics of areas and aspects in a landslide inventory to constrain the potential landslide locations. The first analysis entails a grid-based single-force inversion of 0.02–0.05 Hz seismic signals by spatial grid spacings of 0.2° and 0.05° to retrieve the single-force direction, the estimated landslide area, and a wide search range for a given source. The second analysis involves two location methods for high-frequency seismic signals (>1 Hz) with a finer spatial grid spacing of 0.01°, gradually reducing the landslide search region. By integrating seismology-determined information with a landslide inventory, potential landslide locations and warning areas could be identified effectively. Then we apply the proposed the three-step analysis method to the 2021 Silabaku landslide in southern Taiwan. The results showed that the seismic techniques we used progressively condensed the initial search range from 1831 to 770 km2, converging to a small area of 99 km2. The estimated landslide area was 0.80±0.04 km2, and the force direction was 154.09° ± 6.76°. Subsequently, according to the earlier information, we identified three possible landslide source locations from the 2020 landslide inventory. These findings have implications for warning for two road sections, one of which was subsequently damaged by debris flow after the Silabaku landslide. This study highlights the effectiveness of the hybrid three-step algorithm in constraining areas potentially affected by landslides, facilitating timely assessments for warnings in southern Taiwan.

A Spatial Analysis of Decisions Made in Response to Simulated Tornado Warnings in the United States

Abstract Although decision-making in response to tornado warnings is well researched, most studies do not examine whether individual responses to these warnings vary across different geographical locations and demographic groups. This gap is addressed by using data from a decision experiment that places participants virtually in a simulated tornado warning and asks them to minimize the costs of their decisions. The authors examine the following: 1) what demographic attributes may contribute to choices to minimize costs to protect assets at a specific location in a tornado warning, 2) whether there is a spatial component to how these attributes influence decision-making, and 3) if there are specific U.S. regions where individuals do not make protective decisions that minimize their overall cost. Multilevel regression analysis and poststratification are applied to data from the simulated decision experiment to estimate which demographic attributes and National Weather Service County Warning Areas are most associated with the costliest protective decisions. The results are then analyzed using spatial autocorrelation to identify spatial patterns. Results indicate that sex, race, and ethnicity are important factors that influence protection decisions. Findings also show that people across the southern portions of the United States tend to make more costly protective decisions, as defined in this work. Significance Statement Tornadoes, although rare, threaten both life and property. Studies have shown that certain demographic groups are more negatively impacted by disasters than others and are at higher risk of severe weather hazards. We ask if there are demographic characteristics or geographic locations in common among people who are more prone to making protection decisions during tornado warnings to minimize economic costs. Results can help warning providers, such as the National Weather Service, direct resources and education to specific types of decision-makers or locations to improve sheltering decisions.

Investigation of the aberrant record from bus GPS receiver onboard FORMOSAT-7/COSMIC-2 satellite constellation in low Earth orbit

The FORMOSAT-7/COSMIC-2 (F7/C2) satellite constellation, a joint Taiwan-US collaboration mission, was launched on 25 June 2019. Following the FORMOSAT-3/COSMIC, the F7/C2 mission aims to provide global users the next-generation global navigation satellite system (GNSS) radio occultation data. The mission consists of six identical small satellites with an inclination angle of 24°, launched to the parking orbit of 720 km, and then transferred to the mission orbit of 550 km. Each satellite bus is equipped with two commercial off-the-shelf global positioning system receivers manufactured by Surrey Satellite Technology Ltd. for positioning, navigation, and timing functions. This receiver generates “GPS Receiver (bus GPSR) Warm Start Requested (WSR)” messages after commissioning, which could be considered as a kind of single event effect (SEE). More than 7000 WSR events have been recorded in 3 years after launch, providing another opportunity to investigate the SEE with the commercial off-the-shelf bus GPSR. In addition, the F7/C2 mission is the first satellite constellation that allows scientists to investigate the SEE using the same constellation at different altitudes of Low-Earth orbit. This study investigates and discusses the cumulative rate, distribution of WSRs, and their relationships between altitude and geomagnetic field. The statistical method is applied to define a warning area of the high probability occurring the SEE of this kind of component based on the geomagnetic field, whose corresponding strength is around 21,200/20,550 nT and close to the South Atlantic Anomaly area. Moreover, the relationships with space weather, including the disturbance of the Earth's magnetic field (Kp index) and the solar activity (F10.7 index), are also analyzed and reported.

Evaluation of lightning warning technique with multi-source data for Vung Tau coastal area

In this paper, the authors used multi-source data, including the electric field data observed by EFM-100C at Rescue Station No. 1 on the “Bai Sau” beach in Vung Tau coastal area for 166 days from May to October 2019; Himawari satellite data and Nha Be weather radar data and the GLD-360 lightning position data to evaluate the lightning warning method. Radar and satellite data were used to determine deep convective clouds. The GLD-360 lightning position data were used to examine the consistency of lightning location with the deep convective clouds. The “two areas” method was applied. The Area of Concern (AOC) has a radius of 10 km from the electric field measurement station. The Warning Area (WA) is 20 km extending from the outermost AOC area. Due to the influence of sea-salt aerosol on the background electric field intensity, the electric field threshold selected for a warning is larger than the absolute value (1.5 kV/m). The results showed that the probability of detection (POD), failure to warn (FTW), and false alarm ratio (FAR) were 86.3%, 13.07%, and 23.17%, respectively. The average time of lightning warning for the Vung Tau coastal area is 23 minutes in advance. The warning time is equivalent to that in some studies around the world. The value is suitable for practical application in lightning prevention on the beach and in the Vung Tau coastal area.

CONCEPTUALIZATION OF A SATELLITE, UAS AND UGV DOWNSCALING APPROACH FOR ABANDONED WASTE DETECTION AND WASTE TO ENERGY PROSPECTS

Abstract. The aim of this research is to develop a multiparametric downscaling analysis for the detection of abandoned waste in the environment. This methodology, using a multi-technological approach, involves the adoption VHR satellite images, Unmanned Aircraft System (UAS) and Unmanned Ground Vehicles (UGV). The identified Warning Areas (WA) will be investigated through an in-situ analysis with air quality measurement devices based on advanced sensors mounted on drones. The creation of a Cadastre Accumulation of Abandoned Materials (CAMA) and the related APP will allow the administrations to monitor the phenomenon. Finally, the waste product analysis, retrieved by means of UAS dataset computation, allows to retrieve some interesting prospects regarding Waste to Energy framework. Here, preliminary results obtained by the on-going INTESA Project are presented.

Effect of driving distractions on driver mental workload in work zone’s warning area

Traffic accidents are common in advanced warning areas of a maintenance work zone. One of the reasons for the accident is that the complex driving environment of the warning area makes drivers need to change lanes and speed frequently. Another reason is that driving distractions shift the driver's mental workload and make the drivers unable to complete the driving task well. The paper aimed to examine the impact of visual and cognitive distractions on the driver’s mental workload, eye movements, and driving behaviour when driving in advanced warning areas of the maintenance work zones. Thirty-two participants (mean age = 23.97 years) participated in the experiment and completed 3 advanced warning area simulation scenes. The road initial speed limit of simulation scenes was different: 60 km/h, 80 km/h and 100 km/h. The drivers needed to pass three scenes under three types of distraction tasks (no task, visual task and cognitive task). Six indices were used to evaluate the effect of the advanced warning area and the distracting secondary tasks on the driver's mental workload: two related to eye movements, two related to driver behavior, and two related to the electroencephalogram. The TOPSIS analysis was used to solve the problem of multi-evaluation indices comparison, sorting and selection. The results show that the driver has higher vehicle control ability under the distraction-free task condition than in other scenes. Furthermore, the impact of visual distraction on drivers is more significant than that of cognitive distraction, suggesting more visual attention is required for drivers when passing the complex working zone.

The Evaluation in the Urban Projects Planning: A Logical-Deductive Model for the Definition of “Warning Areas” in the Esquilino District in the City of Rome (Italy)

With reference to the current focus on urban redevelopment issue, the evaluation of the projects plays a central role for the definition of effective urban development policies. In the present research, a logical-deductive model for the identification of “warning areas” is proposed. Given an urban area to be renovated, the developed methodological approach starts from the detection of the main existing architectural, historical and environmental emergencies in order to investigate the appreciation of the reference market for the higher or lower proximity to each considered urban pole. Thus, an econometric technique is implemented to examine the influence of each locational factor on selling prices, by assuming the property asset price increase as a proxy of the benefits generated by the urban redevelopment intervention for local communities. Furthermore, the proposed methodology is applied to the Esquilino district in the city of Rome (Italy), for which a relevant urge of urban regeneration is found, to orient the selection phases of the areas that need more attention from public entities.

Collaboration among Forecasters to Issue Severe Weather Hazard Information and Warnings Using the Hazard Services–Probabilistic Hazard Information (HS-PHI) Tool

Abstract This project tested software capabilities and operational implications related to interoffice collaboration during NWS severe weather warning operations within a proposed paradigm, Forecasting A Continuum of Environmental Threats (FACETs). Current NWS policy of each forecast office issuing warnings for an exclusive area of responsibility may result in inconsistent messaging. In contrast, the FACETs paradigm, with object-based, moving probabilistic and deterministic hazard information, could provide seamless information across NWS County Warning Areas (CWAs). An experiment was conducted that allowed NWS forecasters to test new software that incorporates FACETs-based hazard information and potential concepts of operation to improve messaging consistency between adjacent WFOs. Experiment scenarios consisted of a variety of storm and office border interactions, fictional events requiring nowcasts, and directives that mimicked differing inter-WFO warning philosophies. Surveys and semi-structured interviews were conducted to gauge forecasters’ confidence and workload levels, and to discuss potential solutions for interoffice collaboration and software issues. We found that forecasters were able to adapt quickly to the new software and concepts and were comfortable with collaborating with their neighboring WFO in warning operations. Although forecasters felt the software’s collaboration tools enabled them to communicate in a timely manner, adding this collaboration increased their workload when compared to their workload during current warning operations.

Creating a Communication Framework for FACETs: How Probabilistic Hazard Information Affected Warning Operations in NOAA’s Hazardous Weather Testbed

Abstract Scientists at NOAA are testing a new tool that allows forecasters to communicate estimated probabilities of severe hazards (tornadoes, severe wind, and hail) as part of the Forecasting a Continuum of Environmental Threats (FACETs) framework. In this study, we employ the embedded systems theory (EST)—a communication framework that analyzes small group workplace practices as products of group, organizational, and local dynamics—to understand how probabilistic hazard information (PHI) is produced and negotiated among multiple NWS weather forecast offices in an experimental setting. Gathering feedback from NWS meteorologists who participated in the 2020 Hazard Services (HS)-PHI Interoffice Collaboration experiment, we explored implications of local and interoffice collaboration while using this experimental tool. By using a qualitative thematic analysis, it was found that differing probability thresholds, forecasting styles, social dynamics, and workload will be social factors that developers should consider as they bring PHI toward operational readiness. Warning operations in this new paradigm were also implemented into the EST model to create a communication ecosystem for future weather hazard communication research. Significance Statement Meteorologists are currently exploring how to use probabilities to communicate life-saving information. From tornadoes to hail, a new type of probabilistic hazard information could fundamentally change the way that NWS meteorologists collaborate with one another when issuing weather products, especially near and along the boundaries of County Warning Areas. To explore potential collaboration challenges and solutions, we applied a communication framework and explored perceptions that NWS meteorologists had while using this new tool in an experimental setting. NWS meteorologists expressed that differing ways of communicating hazard information between each office, along with forecasting styles and workload, would change the way they go about producing critical hazard information to the public.

Study on debris flow risk monitoring and Early Warning in Nujiang Prefecture, Yunnan Province, China

Debris flow is the mainly the geological disasters in Nujiang Prefecture, while precipitation is the trigger of it, how to implement debris flow forecast based on precipitation monitoring data or forecast data is a hot issue in current debris flow disaster research field. Because of the special geomorphology in Nujiang Prefecture, due to the influence of human activities, geological disasters occur frequently, severely affect the local economic development. As a demonstration area of geological disaster monitoring and early warning in Yunnan Province, to build a well-developed geological disaster warning system, it is very important to spread it to other parts of Yunnan province. Based on the analysis of the current situation of geological disasters in Nujiang Prefecture, adopt appropriate monitoring method and calculation method to select the primary sites for debris flow monitoring and early warning in the Nu River basin for research.

Examination of the Forecast Process, Mesoscale Environment, and Evolution of the Northern Indiana/Northwest Ohio Derecho of 29 June 2012

A multicell cluster of thunderstorms moved into northern Indiana during the early afternoon hours of 29 June 2012, later evolving into a mature bowing mesoscale convective system (MCS) by the time it exited the County Warning Area of the Northern Indiana National Weather Service. This was the beginning of a derecho that would continue across the Appalachian Mountains and off the Atlantic coast, traveling 1000 km in 10 h and resulting in at least 18 fatalities. This derecho produced a measured wind gust of 41 m s-1 (79 kt) at Fort Wayne International Airport, the highest measured gust along the derecho’s path. The mesoscale environment was characterized by a strong cold pool, extreme instability (including near-record steep midlevel lapse rates), and weak to moderate vertical shear. This paper examines the source of this extreme environment as well as the catalyst for the sustainability of the MCS.

Assessment of NWS County Warning Area Tornado Risk, Exposure, and Vulnerability

AbstractThis study investigates the interrelationships between National Weather Service (NWS) county warning area (CWA) tornado risk, exposure, and societal vulnerability. CWA climatological tornado risk is determined using historical tornado event data, and exposure and vulnerability are assessed by employing present-day population, housing, socioeconomic, and demographic metrics. In addition, tornado watches, warnings, warning lead times, false alarm warnings, and unwarned tornado reports are examined in relation to CWA risk, exposure, and vulnerability. Results indicate that southeastern U.S. CWAs are more susceptible to tornado impacts because of their greater tornado frequencies and larger damage footprints intersecting more vulnerable populations (e.g., poverty and manufactured homes). Midwest CWAs experience fewer tornadoes relative to Southeast and southern plains CWAs but encompass faster tornado translational speeds and greater population densities where higher concentrations of vulnerable individuals often reside. Northern plains CWAs contain longer-tracked tornadoes on average and larger percentages of vulnerable elderly and rural persons. Southern plains CWAs experience the highest tornado frequencies in general and contain larger percentages of minority Latinx populations. Many of the most socially vulnerable CWAs have shorter warning lead times and greater percentages of false alarm warnings and unwarned tornadoes. Study findings provide NWS forecasters with an improved understanding of the relationships between tornado risk, exposure, vulnerability, and warning outcomes within their respective CWAs. Findings may also assist NWS Weather Forecast Offices and the Warning Decision Training Division with developing training materials aimed at increasing NWS forecaster knowledge of how tornado risk, exposure, and vulnerability factors influence local tornado disaster potential.

A Coupling Method for Eco-Geological Environmental Safety Assessment in Mining Areas Using PCA and Catastrophe Theory

Most mineral resources in China are located in the areas with fragile geologic environment, where long-term irrational exploitation of mineral resources has caused serious eco-geological environment problems in mining areas as well as their surrounding areas. Hence, it is of great significance to carry out eco-geological environment security assessment for ecological environment protection of mining area. Nevertheless, up to now, effective methods were still quite rare in the field of eco-geological environment security assessment on mining areas. With a focus on the serious ecological environment and geological environment of the Panxi mining area in China, based on GIS and RS, an indicator system and a method with catastrophe theory and the principal component analysis were constructed for evaluating eco-geological environment security of the mining areas; then, validation was carried out for proving their efficiency. The results indicated that, considering natural and human factors, the method eliminated the correlation between various variables and was capable of evaluating the eco-geological environment security in mining areas quantitatively and objectively. Comparing to the existed methods, the proposed method overcame the shortages of the commonly used “index × weight” method, which causing the same contribution of the indicator in different periods for eco-geological environment security. Our method eliminated the “weight” influence on the result and was especially suitable for studying the long time series of the eco-geological environment security assessment and the analysis of driving factors. Besides, the status of the eco-geological environment security in the study area was mainly in safe or relatively safe. The distribution of mild and severe warning areas was limited. The distribution of unsafety areas was small but concentrated in the mining concentrated area within the study area.

Groundwater pollution early warning based on QTR model for regional risk management: A case study in Luoyang city, China

Groundwater pollution early warning has been regarded as an effective tool for regional groundwater pollution prevention, especially in China. In this study, the systemic model was established to assess the groundwater pollution early warning by integrating the present situation of groundwater quality (Q), groundwater quality trend (T) and groundwater pollution risk (R). The model integrated spatial and temporal variation of groundwater quality, and combined the state and process of the groundwater pollution. Q, T and R were assessed by the methods of fuzzy comprehensive assessment, Spearman or nonparametric Mann-Kendall trend test, and overlay index, respectively. Taking the Luoyang City as an example, the groundwater pollution early warning mapping was generated, and verified by corresponding the groundwater quality classes and the early warning degrees. The results showed that the groundwater was dominated by the levels of no warning and light warning, which accounted for 77% of the study area. The serious and tremendous warning areas were affected by the worse trend and relatively bad/bad present situations of groundwater quality with the typical contaminants of total hardness, nitrate, Hg and COD. In summary, the present situation of groundwater quality was the most important factor of groundwater pollution early warning mapping in the study area. The worse trend of groundwater quality played equally a key role in the local regions, as well as the high pollution risk, which was mainly affected by the pollution source loading. Targeted measures for groundwater pollution prevention were proposed in the corresponding degrees of groundwater pollution early warning. The QTR model was proved to be effective for assessing the regional groundwater pollution early warning. The accuracy of the model could be improved if there is further data acquisition of groundwater quality in longer time series and in larger number, and further investigation of pollution sources.The QTR model is proposed and proved to be effective for assessing regional groundwater pollution early warning.

Spatiotemporal Analysis and Control of Landscape Eco-Security at the Urban Fringe in Shrinking Resource Cities: A Case Study in Daqing, China.

As the main bearing area of the ecological crisis in resource-rich cities, it is essential for the urban fringe to enhance regional ecological security during a city’s transformation. This paper takes Daqing City, the largest oilfield in China’s cold land, as an example. Based on remote sensing image data from 1980 to 2017, we use the DPSIR (Driving forces, Pressure, State, Impact, Response) framework and spatial auto-correlation analysis methods to assess and analyze the landscape eco-security change of the study area. From the perspective of time–space, the study area is partitioned, and control strategies are proposed. The results demonstrate that: (1) The landscape eco-security changes are mainly affected by oilfield exploitation and ecological protection policies; the index declined in 1980–2000 and increased in 2000–2017. (2) The landscape eco-security index has obvious spatial clustering characteristics, and the oil field is the main area of warning. (3) The study area determined the protection area of 1692.07 km2, the risk restoration area of 979.64 km2, and proposed partition control strategies. The results are expected to provide new decision-making ideas in order to develop land use management and ecological plans for the management of Daqing and other resource shrinking cities.

Dynamic identification of urban traffic congestion warning communities in heterogeneous networks

Network-wide traffic control strategies (e.g. perimeter control and route guidance) in urban networks have recently been mainly studied to relieve or postpone congestion based on the theory of macroscopic fundamental diagram (MFD). Nevertheless, these studies are mostly applied to the statically partitioned networks or the dynamic networks that fail to fully consider traffic state prediction, conflicting with strongly spatiotemporal variability of traffic congestion or objective of active traffic management (ATM). This paper proposes a methodology to dynamically identify critical congestion warning areas from heterogeneous urban road networks, which aids to design efficient perimeter control approaches. In the methodology, a dynamic directed weighted network is built on the base of the link connectivity and the real-time traffic loads, and a link travel time prediction method based on Kalman filter is developed to calibrate directed weight values and undirected input values for links. With the undirected link input information, a dynamic congestion warning community detection method which consists of three consecutive steps is developed. Firstly, it could capture emergence of new congestion areas based on the definition of congestion seed intersection. Secondly, expansion and regression of each congested area could be achieved with the objectives of spatial compactness and traffic condition homogeneity. Thirdly, a two-level merging algorithm of adjacent different congestion areas is designed utilizing modularity model in community detection of complex networks. The proposed methodology is validated using ground truth data from downtown network of Jinan City in China. The results show that the proposed algorithms can efficiently track congestion evolutionary processes and effectively detect congestion warning areas from the test real network.

Application of the Risk-Based Early Warning Method in a Fracture-Karst Water Source, North China.

The paper proposes a risk-based early warning considering characteristics of fracture-karst aquifer in North China and applied it in a super-large fracture-karst water source. Groundwater vulnerability, types of land use, water abundance, transmissivity and spatial temporal variation of groundwater quality were chosen as indexes of the method. Weights of factors were obtained by using AHP method based on relative importance of factors, maps of factors were zoned by GIS, early warning map was conducted based on extension theory with the help of GIS, ENVI+IDL. The early warning map fused five factors very well, serious and tremendous warning areas are mainly located in northwest and east with high or relatively high transmissivity and groundwater pollutant loading, and obviously deteriorated or deteriorated trend of petroleum. The early warning map warns people where more attention should be paid, and the paper guides decision making to take appropriate protection actions in different warning levels areas.

Assessment of In-Vehicle Messages in the Advance Warning Area of a Work Zone

Simulations and field tests have shown that the connected vehicle technologies would not only enhance the mobility and safety of traffic operation, but also possibly reduce fuel consumption and exhaust emissions. So far, there is no consistent evaluation procedure on the perfomances of these in vehicle messages to drivers in work zone area. The objective of this research is to test, compare and develop a warning system to prevent occurring of work zone crashes and reduce vehicle emission. The main purpose of this study is to test and evaluate the different set of warning messages in the advance warning area of a work zone and develop an evaluation system for the warning system from the perspective of speed, acceleration rate, brake positions, lane changing positions, emission and work load. The work load of the three types of warning system is evaluated based on the NASA-TASK Load Index. The application of the mixed audio and image messages was able to reduce the overall vehicle emissions (CO2, CO, HC, and NOx). With the help of the both audio and image messages, drivers tend to recognize the road situation earlier than in the conventional situation and this will have a positively influence on driving safety. Especially, the mixed messages scenario outweights the other two scenarios in speed, acceleration rate, braking positions, emission, and work load.

Nonmeteorological Influences on Severe Thunderstorm Warning Issuance: A Geographically Weighted Regression-Based Analysis of County Warning Area Boundaries, Land Cover, and Demographic Variables

Abstract Studies have shown that the spatial distribution of severe thunderstorm warnings demonstrates variation beyond what can be attributed to weather and climate alone. Investigating spatial patterns of these variations can provide insight into nonmeteorological factors that might lead forecasters to issue warnings. Geographically weighted regression was performed on a set of demographic and land cover descriptors to ascertain their relationships with National Weather Service (NWS) severe thunderstorm warning polygons issued by 36 NWS forecast offices in the central and southeastern United States from 2008 to 2015. County warning area (CWA) boundaries and cities were predominant sources of variability in warning counts. Global explained variance in verified and unverified severe thunderstorm warnings ranged from 67% to 81% for population, median income, and percent imperviousness across the study area, which supports the spatial influence of these variables on warning issuance. Local regression coefficients indicated that verified and unverified warning counts increased disproportionately in larger cities relative to the global trend, particularly for NWS weather forecast office locations. However, local explained variance tended to be lower in cities, possibly due to greater complexity of social and economic factors shaping warning issuance. Impacts of thunderstorm type and anthropogenic modification of existing storms should also be considered when interpreting the results of this study.