The Statistical Severe Convective Risk Assessment Model

Abstract This study introduces a system that objectively assesses severe thunderstorm nowcast probabilities based on hourly mesoscale data across the contiguous United States during the period from 2006 to 2014. Previous studies have evaluated the diagnostic utility of parameters in characterizing severe thunderstorm environments. In contrast, the present study merges cloud-to-ground lightning flash data with both severe thunderstorm report and Storm Prediction Center Mesoscale Analysis system data to create lightning-conditioned prognostic probabilities for numerous parameters, thus incorporating null-severe cases. The resulting dataset and corresponding probabilities are called the Statistical Severe Convective Risk Assessment Model (SSCRAM), which incorporates a sample size of over 3.8 million 40-km grid boxes. A subset of five parameters of SSCRAM is investigated in the present study. This system shows that severe storm probabilities do not vary strongly across the range of values for buoyancy parameters compared to vertical shear parameters. The significant tornado parameter [where “significant” refers to tornadoes producing (Fujita scale) F2/(enhanced Fujita scale) EF2 damage] exhibits considerable skill at identifying downstream tornado events, with higher conditional probabilities of occurrence at larger values, similar to effective storm-relative helicity, both findings being consistent with previous studies. Meanwhile, lifting condensation level heights are associated with conditional probabilities that vary little within an optimal range of values for tornado occurrence, yielding less skill in quantifying tornado potential using this parameter compared to effective storm-relative helicity. The systematic assessment of probabilities using convective environmental information could have applications in present-day operational forecasting duties and the upcoming warn-on-forecast initiatives.

Download Full-text

The Challenge of Forecasting Significant Tornadoes from June to October Using Convective Parameters

Weather and Forecasting ◽

10.1175/waf-d-16-0005.1 ◽

2016 ◽

Vol 31 (6) ◽

pp. 2075-2084 ◽

Cited By ~ 9

Author(s):

John A. Hart ◽

Ariel E. Cohen

Keyword(s):

Convective Available Potential Energy ◽

The United States ◽

Environmental Data ◽

Assessment Model ◽

Vertical Shear ◽

Risk Assessment Model ◽

Conditional Probabilities ◽

Severe Thunderstorm ◽

Parameter Values ◽

Effective Layer

Abstract This study is an application of the Statistical Severe Convective Risk Assessment Model (SSCRAM), which objectively assesses conditional severe thunderstorm probabilities based on archived hourly mesoscale data across the United States collected from 2006 to 2014. In the present study, SSCRAM is used to assess the utility of severe thunderstorm parameters commonly employed by forecasters in anticipating thunderstorms that produce significant tornadoes (i.e., causing F2/EF2 or greater damage) from June through October. The utility during June–October is compared to that during other months. Previous studies have identified some aspects of the summertime challenge in severe storm forecasting, and this study provides an in-depth quantification of the within-year variability of severe storms predictability. Conditional probabilities of significant tornadoes downstream of lightning occurrence using common parameter values, such as the effective-layer significant tornado parameter, convective available potential energy, and vertical shear, are found to substantially decrease during the months of June–October compared to other months. Furthermore, conditional probabilities of significant tornadoes during June–October associated with these parameters are nearly invariable regardless of value, highlighting the challenge of using objective environmental data to attempt to forecast significant tornadoes from June through October.

Download Full-text

The characteristics of lightning risk and zoning in Beijing simulated by a risk assessment model

Natural Hazards and Earth System Science ◽

10.5194/nhess-14-1985-2014 ◽

2014 ◽

Vol 14 (8) ◽

pp. 1985-1997 ◽

Cited By ~ 4

Author(s):

H. Hu ◽

J. Wang ◽

J. Pan

Keyword(s):

Risk Assessment ◽

Rural Areas ◽

Urban Areas ◽

High Elevation ◽

Assessment Model ◽

Lightning Flash ◽

Risk Assessment Model ◽

Human Beings ◽

Location Factor ◽

Property Loss

Abstract. In this study, the cloud-to-ground (CG) lightning flash/stroke density was derived from the lightning location finder (LLF) data recorded between 2007 and 2011. The vulnerability of land surfaces was then assessed from the classification of the study areas into buildings, outdoor areas under the building canopy and open-field areas, which makes it convenient to deduce the location factor and confirm the protective capability. Subsequently, the potential number of dangerous lightning events at a location could be estimated from the product of the CG stroke density and the location's vulnerability. Although the human beings and all their material properties are identically exposed to lightning, the lightning casualty risk and property loss risk was assessed respectively due to their vulnerability discrepancy. Our analysis of the CG flash density in Beijing revealed that the valley of JuMaHe to the southwest, the ChangPing–ShunYi zone downwind of the Beijing metropolis, and the mountainous PingGu–MiYun zone near the coast are the most active lightning areas, with densities greater than 1.5 flashes km−2 year−1. Moreover, the mountainous northeastern, northern, and northwestern rural areas are relatively more vulnerable to lightning because the high-elevation terrain attracts lightning and there is little protection. In contrast, lightning incidents by induced lightning are most likely to occur in densely populated urban areas, and the property damage caused by lightning here is more extensive than that in suburban and rural areas. However, casualty incidents caused by direct lightning strokes seldom occur in urban areas. On the other hand, the simulation based on the lightning risk assessment model (LRAM) demonstrates that the casualty risk is higher in rural areas, whereas the property loss risk is higher in urban areas, and this conclusion is also supported by the historical casualty and damage reports.

Download Full-text

The Influence of Human-Organizational Factors on Falling Accidents From Historical Text Data

Frontiers in Public Health ◽

10.3389/fpubh.2021.783537 ◽

2022 ◽

Vol 9 ◽

Author(s):

Xixi Luo ◽

Quanlong Liu ◽

Zunxiang Qiu

Keyword(s):

Risk Assessment ◽

Safety Culture ◽

Government Regulation ◽

Process Management ◽

Organizational Factors ◽

Assessment Model ◽

Risk Assessment Model ◽

Site Management ◽

Organizational Influence ◽

Analysis System

This paper firstly proposes a modified human factor classification analysis system (HFACS) framework based on literature analysis and the characteristics of falling accidents in construction. Second, a Bayesian network (BN) topology is constructed based on the dependence between human factors and organizational factors, and the probability distribution of the human-organizational factors in a BN risk assessment model is calculated based on falling accident reports and fuzzy set theory. Finally, the sensitivity of the causal factors is determined. The results show that 1) the most important reason for falling accidents is unsafe on-site supervision. 2) There are significant factors that influence falling accidents at different levels in the proposed model, including operation violations in the unsafe acts layer, factors related to an adverse technological environment for the unsafe acts layer, loopholes in site management in the unsafe on-site supervision layer, lack of safety culture in the adverse organizational influence layer, and lax government regulation in the adverse external environment layer. 3) According to the results of the BN risk assessment model, the most likely causes are loopholes in site management work, lack of safety culture, insufficient safety inspections and acceptance, vulnerable process management and operation violations.

Download Full-text

The characteristics of lightning risk and zoning in Beijing simulated by a risk assessment model

Natural Hazards and Earth System Sciences Discussions ◽

10.5194/nhessd-1-4115-2013 ◽

2013 ◽

Vol 1 (4) ◽

pp. 4115-4154 ◽

Cited By ~ 1

Author(s):

H. Hu ◽

J. Wang ◽

J. Pan

Keyword(s):

Risk Assessment ◽

Rural Areas ◽

Urban Areas ◽

High Elevation ◽

Assessment Model ◽

Lightning Flash ◽

Risk Assessment Model ◽

Human Beings ◽

Location Factor ◽

Property Loss

Abstract. In this study, the Cloud-to-Ground (CG) lightning flash/stroke density has been derived from the Lightning Location Finder (LLF) data recorded in recent years. Meanwhile, the vulnerability on land surfaces has been assessed by the classification of the building, outdoor area under the building canopy and open-field area, which makes it convenient to deduce the location factor and confirm the protective capability. Then, the number of dangerous lightning event can be estimated by product of the CG stroke density and vulnerability. Although the human beings and all their material properties are identically exposed to lightning, the lightning casualty risk and property loss risk have been assessed respectively due to their vulnerability discrepancy. The analysis of the CG flash density in Beijing revealed that the JuMaHe river-valley in the southwestern region, the ChangPing–ShunYi zone downwind of the Beijing metropolis, and the mountainous PingGu–MiYun zone near the seashore are the most active lightning areas, with densities greater than 1.5 fl km-2 yr-1. Moreover, the mountainous northeastern, northern, and northwestern rural areas are relatively vulnerable to lightning due to the ability of high elevation terrain to attract lightning and the lack of protection measures. In contrast, lightning incidents by indirect lightning are most likely to occur in urban areas with high population density and aggregated properties, and the property damages caused by lightning are more extensive than those in suburban and rural areas. However, casualty incidents caused by direct lightning strokes seldom occur in urban areas. On the other hand, the simulation based on the Lightning Risk Assessment Model (LRAM) demonstrates that the casualty risk is higher in rural, whereas the property loss risk is higher in urban, and this conclusion is also supported by the historical casualty and damage reports.

Download Full-text

Risk assessment model for venous thromboembolism in hospitalized surgical and non-surgical patients in the 4th Hungarian Antithrombotic Guidelines entitled “Diminution and Treatment of Venous Thromboembolism”

Orvosi Hetilap ◽

10.1556/oh.2010.28944 ◽

2010 ◽

Vol 151 (34) ◽

pp. 1365-1374 ◽

Cited By ~ 1

Author(s):

Marianna Dávid ◽

Hajna Losonczy ◽

Miklós Udvardy ◽

Zoltán Boda ◽

György Blaskó ◽

...

Keyword(s):

Risk Assessment ◽

Venous Thromboembolism ◽

Assessment Model ◽

Surgical Patients ◽

Risk Assessment Model

A kórházban kezelt sebészeti és belgyógyászati betegekben jelentős a vénásthromboembolia-rizikó. Profilaxis nélkül, a műtét típusától függően, a sebészeti beavatkozások kapcsán a betegek 15–60%-ában alakul ki mélyvénás trombózis vagy tüdőembólia, és az utóbbi ma is vezető kórházi halálok. Bár a vénás thromboemboliát leggyakrabban a közelmúltban végzett műtéttel vagy traumával hozzák kapcsolatba, a szimptómás thromboemboliás események 50–70%-a és a fatális tüdőembóliák 70–80%-a nem a sebészeti betegekben alakul ki. Nemzetközi és hazai felmérések alapján a nagy kockázattal rendelkező sebészeti betegek többsége megkapja a szükséges trombózisprofilaxist. Azonban profilaxis nélkül marad a rizikóval rendelkező belgyógyászati betegek jelentős része, a konszenzuson alapuló nemzetközi és hazai irányelvi ajánlások ellenére. A belgyógyászati betegek körében növelni kell a profilaxisban részesülők arányát és el kell érni, hogy trombózisrizikó esetén a betegek megkapják a hatásos megelőzést. A beteg trombóziskockázatának felmérése fontos eszköze a vénás thromboembolia által veszélyeztetett betegek felderítésének, megkönnyíti a döntést a profilaxis elrendeléséről és javítja az irányelvi ajánlások betartását. A trombózisveszély megállapításakor, ha nem ellenjavallt, profilaxist kell alkalmazni. „A thromboemboliák kockázatának csökkentése és kezelése” című, 4. magyar antithromboticus irányelv felhívja a figyelmet a vénástrombózis-rizikó felmérésének szükségességére, és elsőként tartalmazza a kórházban fekvő belgyógyászati és sebészeti betegek kockázati kérdőívét. Ismertetjük a kockázatbecslő kérdőíveket és áttekintjük a kérdőívekben szereplő rizikófaktorokra vonatkozó bizonyítékokon alapuló adatokat.

Download Full-text

Signature Analysis: Statistical Models and Their Application to FA

ISTFA 1996: Conference Proceedings from the 22nd International Symposium for Testing and Failure Analysis ◽

10.31399/asm.cp.istfa1996p0183 ◽

1996 ◽

Author(s):

C.K. Lakshminarayan ◽

S. Pabbisetty ◽

O. Adams ◽

F. Pires ◽

M. Thomas ◽

...

Keyword(s):

Risk Assessment ◽

Failure Analysis ◽

Statistical Models ◽

Essential Elements ◽

Assessment Model ◽

Signature Analysis ◽

Risk Assessment Model ◽

Sample Sizes ◽

Reliability Engineering ◽

Semiconductor Chips

Abstract This paper deals with the basic concepts of Signature Analysis and the application of statistical models for its implementation. It develops a scheme for computing sample sizes when the failures are random. It also introduces statistical models that comprehend correlations among failures that fail due to the same failure mechanism. The idea of correlation is important because semiconductor chips are processed in batches. Also any risk assessment model should comprehend correlations over time. The statistical models developed will provide the required sample sizes for the Failure Analysis lab to state "We are A% confident that B% of future parts will fail due to the same signature." The paper provides tables and graphs for the evaluation of such a risk assessment. The implementation of Signature Analysis will achieve the dual objective of improved customer satisfaction and reduced cycle time. This paper will also highlight it's applicability as well as the essential elements that need to be in place for it to be effective. Different examples have been illustrated of how the concept is being used by Failure Analysis Operations (FA) and Customer Quality and Reliability Engineering groups.

Download Full-text