scholarly journals A Simple and Flexible Method for Ranking Severe Weather Events

2006 ◽  
Vol 21 (6) ◽  
pp. 939-951 ◽  
Author(s):  
C. A. Doswell ◽  
R. Edwards ◽  
R. L. Thompson ◽  
J. A. Hart ◽  
K. C. Crosbie
Keyword(s):  
Secular Trends ◽  
Severe Weather ◽  
Weather Events ◽  
Multiple Variables ◽  
Convective Weather ◽  
The Impact ◽  
Severe Weather Event ◽  
Intended Use ◽  
Made In ◽  
Tornado Outbreak

Abstract The notion of an “outbreak” of severe weather has been used for decades, but has never been formally defined. There are many different criteria by which outbreaks can be defined based on severe weather occurrence data, and there is not likely to be any compelling logic to choose any single criterion as ideal for all purposes. Therefore, a method has been developed that uses multiple variables and allows for considerable flexibility. The technique can be adapted easily to any project that needs to establish a ranking of weather events. The intended use involves isolating the most important tornado outbreak days, as well as important outbreak days of primarily nontornadic severe convective weather, during a period when the number of reports has been growing rapidly from nonmeteorological factors. The method is illustrated for both tornadic and primarily nontornadic severe weather event day cases. The impact of the secular trends in the data has been reduced by a simple detrending scheme. The effect of detrending is less important for the tornado outbreak cases and is illustrated by comparing rankings with and without detrending. It is shown that the resulting rankings are relatively resistant to secular trends in the data, as intended, and not strongly sensitive to the choices made in applying the method. The rankings are also consistent with subjective judgments of the relative importance of historical tornado outbreak cases.

scholarly journals The Impact of the Storm Prediction Center's Convective Outlooks and Watches on Emergency Management Operational Planning

2021 ◽  
pp. 36-46
Author(s):  
Heather A. Cross ◽  
Dennis Cavanaugh ◽  
Christopher C. Buonanno ◽  
Amy Hyman
Keyword(s):  
Emergency Management ◽  
Severe Weather ◽  
Emergency Operations ◽  
Risk Levels ◽  
Severe Thunderstorms ◽  
Emergency Managers ◽  
Weather Events ◽  
Storm Prediction ◽  
Near Term ◽  
The Impact

For many emergency managers (EMs) and National Weather Service (NWS) forecasters, Convective Outlooks issued by the Storm Prediction Center (SPC) influence the preparation for near-term severe weather events. However, research into how and when EMs utilize that information, and how it influences their emergency operations plan, is limited. Therefore, to better understand how SPC Convective Outlooks are used for severe weather planning, a survey was conducted of NWS core partners in the emergency management sector. The results show EMs prefer to wait until an Enhanced Risk for severe thunderstorms is issued to prepare for severe weather. In addition, the Day 2 Convective Outlook serves as the threshold for higher, value-based decision making. The survey was also used to analyze how the issuance of different risk levels in SPC Convective Outlooks impact emergency management preparedness compared to preparations conducted when a Convective Watch is issued.

Examination of Convection-Allowing Configurations of the WRF Model for the Prediction of Severe Convective Weather: The SPC/NSSL Spring Program 2004

2006 ◽  
Vol 21 (2) ◽  
pp. 167-181 ◽  
Author(s):  
John S. Kain ◽  
S. J. Weiss ◽  
J. J. Levit ◽  
M. E. Baldwin ◽  
D. R. Bright
Keyword(s):  
Weather Forecasting ◽  
Wrf Model ◽  
Value Added ◽  
Severe Weather ◽  
Convective Initiation ◽  
A Value ◽  
Human Decision ◽  
Forecast Models ◽  
Convective Weather ◽  
The Impact

Abstract Convection-allowing configurations of the Weather Research and Forecast (WRF) model were evaluated during the 2004 Storm Prediction Center–National Severe Storms Laboratory Spring Program in a simulated severe weather forecasting environment. The utility of the WRF forecasts was assessed in two different ways. First, WRF output was used in the preparation of daily experimental human forecasts for severe weather. These forecasts were compared with corresponding predictions made without access to WRF data to provide a measure of the impact of the experimental data on the human decision-making process. Second, WRF output was compared directly with output from current operational forecast models. Results indicate that human forecasts showed a small, but measurable, improvement when forecasters had access to the high-resolution WRF output and, in the mean, the WRF output received higher ratings than the operational Eta Model on subjective performance measures related to convective initiation, evolution, and mode. The results suggest that convection-allowing models have the potential to provide a value-added benefit to the traditional guidance package used by severe weather forecasters.

The role of gap analyses in energy assurance planning

2017 ◽  
Vol 11 (3) ◽  
pp. 181
Author(s):  
Katherine Shea, JD
Keyword(s):  
Local Governments ◽  
Power Loss ◽  
Gap Analysis ◽  
Hurricane Sandy ◽  
Severe Weather ◽  
Power Outages ◽  
Weather Events ◽  
State And Local ◽  
The Impact

Energy-related emergencies, such as power outages or interruptions to other energy supplies, can arise from a number of factors. Common causes include severe weather events—such as snowstorms, hurricanes, or summer storms with strong winds—as well as energy infrastructure that is overburdened, aging, or in need of repair. As past experience indicates, jurisdictions will continue to experience severe weather events, as well as confront infrastructure issues that make future power outages likely. As a result, state and local governments have turned to energy assurance planning, an energy-specific form of planning that helps jurisdictions prepare for and recover from energy emergencies. Energy assurance recognizes that power loss/disruption cannot be eradicated completely, but jurisdictions can mitigate the impact of power loss through effective planning. This article discusses the role of energy assurance planning and provides a description of what energy assurance means and why developing such plans at the state and local levels is important. In addition, this article discusses the role of statutory gap analyses in energy assurance planning and discusses how a gap analysis can be used by planners to identify trends and gaps in energy assurance. To provide context, a recently conducted statutory gap analysis analyzing national emergency backup power trends is provided as a case study. A summary of this project and key findings is included. Finally, this article briefly touches on legislation as an alternative to energy assurance planning, and provides summaries of recent legislative proposals introduced in the aftermath of Hurricane Sandy.

A comparison between 4D-VAR and cycling 3D-VAR methods for the simulation of a severe weather event in Central Italy. Preliminary results.

2020 ◽  
Author(s):  
Vincenzo Mazzarella ◽  
Rossella Ferretti
Keyword(s):  
Positive Impact ◽  
Central Italy ◽  
Wrf Model ◽  
Severe Weather ◽  
Precipitation Forecast ◽  
Mountain Range ◽  
Weather Event ◽  
Maximum Rainfall ◽  
The Impact ◽  
Severe Weather Event

<p>Nowadays, the use of 4D-VAR assimilation technique has been investigated in several scientific papers with the aim of improving the localization and timing of precipitation in complex orography regions. The results show the positive impact in rainfall forecast but, the need to resolve the tangent linear and adjoint model makes the 4D-VAR computationally too expensive. Hence, it is used in operationally only in large forecast centres. To the aim of exploring a more reasonable method, a comparison between a cycling 3D-VAR, that needs less computational resources, and 4D-VAR techniques is performed for a severe weather event occurred in Central Italy. A cut-off low (992 hPa), located in western side of Sicily region, was associated with a strong south-easterly flow over Central Adriatic region, which supplied a large amount of warm and moist air. This mesoscale configuration, coupled with the Apennines mountain range that further increased the air column instability, produced heavy rainfall in Abruzzo region (Central Italy).</p><p>The numerical simulations are carried out using the Weather Research and Forecasting (WRF) model. In-situ surface and upper-air observations are assimilated in combination with radar reflectivity and radial velocity data over a high-resolution domain. Several experiments have been performed in order to evaluate the impact of 4D-VAR and cycling 3D-VAR in the precipitation forecast. In addition, a statistical analysis has been carried out to objectively compare the simulations. Two different verification approaches are used: Receiver Operating Characteristic (ROC) curve and Fraction Skill Score (FSS). Both statistical scores are calculated for different threshold values in the study area and in the sub-regions where the maximum rainfall occurred.</p>

Advanced MUlti-GNSS Array for Monitoring Severe Weather Events (AMUSE): Project overview

2020 ◽  
Author(s):  
Karina Wilgan ◽  
Jens Wickert ◽  
Galina Dick ◽  
Florian Zus ◽  
Torsten Schmidt ◽  
...  
Keyword(s):  
Water Vapor ◽  
Severe Weather ◽  
Precipitation Forecast ◽  
Spatiotemporal Resolution ◽  
Weather Forecasts ◽  
Precise Knowledge ◽  
Weather Events ◽  
Data Products ◽  
New Generation ◽  
The Impact

<p>Global Navigation Satellite Systems (GNSS) have revolutionized positioning, navigation, and timing, becoming a common part of our everyday life. Aside from these well-known civilian and commercial applications, GNSS is currently established as a powerful and versatile observation tool for geosciences. An outstanding application in this context is the operational monitoring of atmospheric water vapor with high spatiotemporal resolution. The water vapor is the most abundant greenhouse gas, which accounts for about 70% of atmospheric warming and plays a key role in the atmospheric energy exchange. The precise knowledge of its highly variable spatial and temporal distribution is a precondition for precise modeling of the atmospheric state as a base for numerical weather forecasts especially with focus to the strong precipitation and severe weather events.</p><p>The data from European GNSS networks are widely operationally used to improve regional weather forecasts in several countries. However, the impact of the currently provided data products to the forecast systems is still limited due to the exclusively focusing on GPS-only based data products; to the limited atmospheric information content, which is provided mostly in the zenith direction and to the time delay between measurement and providing the data products, which is currently about one hour.</p><p>AMUSE is a recent research project, funded by the DFG (German Research Council) and performed in close cooperation of TUB, GFZ and DWD during 2020-2022. The project foci are the major limitations of currently operationally used generation of GNSS-based water vapor data. AMUSE will pioneer the development of next generation data products. Main addressed innovations are:  1) Developments to provide multi-GNSS instead of GPS-only data, including GLONASS, Galileo and BeiDou; 2) Developments to provide high quality slant observations, containing water vapor information along the line-of-sight from the respective ground stations; 3) Developments to shorten the delay between measurements and the provision of the products to the meteorological services.</p><p>This GNSS-focused work of AMUSE will be complemented by the contribution of German Weather Service DWD to investigate in detail and to quantify the forecast improvement, which can be reached by the new generation GNSS-based meteorology data. Several dedicated forecast experiments will be conducted with focus on one of the most challenging issues, the precipitation forecast in case of severe weather events. These studies will support the future assimilation of the new generation data to the regional forecast system of DWD and potentially also to other European weather services.</p>

Emerging Disabilities That Result From or Are Exacerbated by Severe Weather Events: Implications for Rehabilitation Counselors

2019 ◽  
Vol 33 (1) ◽  
pp. 8-23
Author(s):  
Lynn C. Koch ◽  
Julie Hill ◽  
Phillip D. Rumrill
Keyword(s):  
Rehabilitation Counseling ◽  
Severe Weather ◽  
Chronic Illnesses ◽  
Rehabilitation Counselors ◽  
Negative Consequences ◽  
Foreseeable Future ◽  
Policy And Practice ◽  
Weather Events ◽  
The Impact ◽  
Rehabilitation Assessment

BackgroundRehabilitation counselors can anticipate providing services to growing numbers of individuals who have disabilities that were acquired in (or exacerbated by) severe weather events. The impact of these events on individuals’ psychosocial and vocational functioning is an important factor to address in holistic rehabilitation assessment and planning.ObjectivesThe objectives of this article are to (a) provide an overview of how severe weather events contribute to the onset and exacerbation of chronic illnesses and disabilities, (b) identify populations most at risk of experiencing the negative consequences of severe weather events, and (c) consider implications for rehabilitation counseling policy and practice.MethodsWe reviewed literature on severe weather events and their impact on human health and functioning to better understand the impact of these events on affected individuals.ResultsThe review revealed that severe weather events have increased in frequency, intensity, and length, and this trend is expected to continue into the foreseeable future. Severe weather events are an emerging cause of disability that requires unique assessment and planning considerations for rehabilitation counselors.ConclusionsThe increase in recent decades of severe weather events as a cause or contributor to disability has numerous implications for rehabilitation counseling practice that are discussed in this article.

scholarly journals Splitting of the middle layer of LPW SAFNWC/MSG satellite product in order to improve the monitoring of pre-convective environments

2008 ◽  
Vol 2 (1) ◽  
pp. 71-75
Author(s):  
G. Cuevas ◽  
M. A. Martinez ◽  
M. Velazquez ◽  
J. Ruiz ◽  
M. Manso
Keyword(s):  
Neural Networks ◽  
Precipitable Water ◽  
Middle Layer ◽  
Horizontal Resolution ◽  
Severe Weather ◽  
Convective System ◽  
Weather Event ◽  
Radar Images ◽  
The Impact ◽  
Severe Weather Event

Abstract. Seven of the infrared channels from the Spinning Enhanced Visible and Infrared Imagery (SEVIRI) instrument, on board the Meteosat Second Generation (MSG), are used to retrieve Layer Precipitable Water (LPW) and Stability Analysis Imagery (SAI) in the SAFNWC framework. Both products are retrieved using a statistical retrieval based on neural networks; they are routinely generated every fifteen minutes at a satellite horizontal resolution of 3 km in NADIR only in cloud-free areas. Many factors are involved in the development of severe weather and these parameters are only some of the indicators. However, due to the high resolution of these products, the use of them in conjunction with satellite and radar images can help to identify mesoscale features related to convection. The MSG moisture and parcel instability time trend fields are especially useful during the period previous to convection. Once the outbreak of convection occurs, the products calculated in the clear air pixels surrounding the convective system can give us hints to anticipate its evolution. SAFNWC LPW and SAI were analyzed for a severe weather event during August 2004. A thunderstorm over Teruel (Spain) produced intense precipitation and hail; a tornado developed while this thunderstorm was moving towards SE. The pre-convective parcel potential buoyancy and moisture SAFNWC products changed in a way that was consistent with the observed intense convective activity. In previous studies, the atmospheric moisture in medium levels, which has been proven to be relevant in some cases, was represented by only one level parameter (ML: middle layer LPW). However, it was observed that this layer is too thick to do an adequate analysis of moisture available for convection. Hence, an improvement on the LPW algorithm has been carried out by splitting the middle layer into two new sub-layers (approximately separated at 700 hPa) and training two new neural networks. The impact of monitoring moisture in the new sub-layers separately in this severe weather event has been tested, and the improvements achieved have been evaluated.

scholarly journals Objective Climatological Analysis of Extreme Weather Events in Arizona during the North American Monsoon

2016 ◽  
Vol 55 (11) ◽  
pp. 2431-2450 ◽  
Author(s):  
Jeremy J. Mazon ◽  
Christopher L. Castro ◽  
David K. Adams ◽  
Hsin-I Chang ◽  
Carlos M. Carrillo ◽  
...  
Keyword(s):  
Extreme Events ◽  
Extreme Weather ◽  
Severe Weather ◽  
North American Monsoon ◽  
Type I ◽  
Type Ii ◽  
Weather Event ◽  
The North ◽  
Weather Events ◽  
Severe Weather Event

AbstractAlmost one-half of the annual precipitation in the southwestern United States occurs during the North American monsoon (NAM). Given favorable synoptic-scale conditions, organized monsoon thunderstorms may affect relatively large geographic areas. Through an objective analysis of atmospheric reanalysis and observational data, the dominant synoptic patterns associated with NAM extreme events are determined for the period from 1993 to 2010. Thermodynamically favorable extreme-weather-event days are selected on the basis of atmospheric instability and precipitable water vapor from Tucson, Arizona, rawinsonde data. The atmospheric circulation patterns at 500 hPa associated with the extreme events are objectively characterized using principal component analysis. The first two dominant modes of 500-hPa geopotential-height anomalies of the severe-weather-event days correspond to type-I and type-II severe-weather-event patterns previously subjectively identified by Maddox et al. These patterns reflect a positioning of the monsoon ridge to the north and east or north and west, respectively, from its position in the “Four Corners” region during the period of the climatological maximum of monsoon precipitation from mid-July to mid-August. An hourly radar–gauge precipitation product shows evidence of organized, westward-propagating convection in Arizona during the type-I and type-II severe weather events. This new methodological approach for objectively identifying severe weather events may be easily adapted to inform operational forecasting or analysis of gridded climate data.

scholarly journals The Impact of Assimilating Surface Pressure Observations on Severe Weather Events in a WRF Mesoscale Ensemble System

2010 ◽  
Vol 138 (5) ◽  
pp. 1673-1694 ◽  
Author(s):  
Dustan M. Wheatley ◽  
David J. Stensrud
Keyword(s):  
Surface Pressure ◽  
Primary Objective ◽  
Severe Weather ◽  
Ensemble Forecasts ◽  
Convective Systems ◽  
Cold Pools ◽  
Weather Events ◽  
Mesoscale Convective ◽  
Mean Pressure ◽  
The Impact

Abstract Surface pressure observations are assimilated into a Weather Research and Forecast ensemble using an ensemble Kalman filter (EnKF) approach and the results are compared with observations for two severe weather events. Several EnKF experiments are performed to evaluate the relative impacts of two very different pressure observations: altimeter setting (a total pressure field) and 1-h surface pressure tendency. The primary objective of this study is to determine the surface pressure observation that is most successful in producing realistic mesoscale features, such as convectively driven cold pools, which often play an important role in future convective development. Results show that ensemble-mean pressure analyses produced from the assimilation of surface temperature, moisture, and winds possess significant errors in regard to mesohigh strength and location. The addition of surface pressure tendency observations within the assimilation yields limited ability to constrain such errors, while the assimilation of altimeter setting yields accurate depictions of the mesoscale pressure patterns associated with mesoscale convective systems. The mesoscale temperature patterns produced by all the ensembles are quite similar and tend to reproduce the observed features. Results suggest that even though surface pressure observations can have large cross covariances with temperature and the wind components, the resulting analyses fail to improve upon the EnKF temperature and wind analyses that exclude the surface pressure observations. Ensemble forecasts following the assimilation period show the potential to improve short-range forecasting of surface pressure.

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