Severe Weather Activity Research Articles

The Experimental Warning Program of NOAA’s Hazardous Weather Testbed

Abstract NOAA’s Hazardous Weather Testbed (HWT) is a physical space and research framework to foster collaboration and evaluate emerging tools, technology, and products for NWS operations. The HWT’s Experimental Warning Program (EWP) focuses on research, technology, and communication that may improve severe and hazardous weather warnings and societal response. The EWP was established with three fundamental hypotheses: 1) collaboration with operational meteorologists increases the speed of the transition process and rate of adoption of beneficial applications and technology, 2) the transition of knowledge between research and operations benefits both the research and operational communities, and 3) including end users in experiments generates outcomes that are more reliable and useful for society. The EWP is designed to mimic the operations of any NWS Forecast Office, providing the opportunity for experiments to leverage live and archived severe weather activity anywhere in the United States. During the first decade of activity in the EWP, 15 experiments covered topics including new radar and satellite applications, storm-scale numerical models and data assimilation, total lightning use in severe weather forecasting, and multiple social science and end-user topics. The experiments range from exploratory and conceptual research to more controlled experimental design to establish statistical patterns and causal relationships. The EWP brought more than 400 NWS forecasters, 60 emergency managers, and 30 broadcast meteorologists to the HWT to participate in live demonstrations, archive events, and data-denial experiments influencing today’s operational warning environment and shaping the future of warning research, technology, and communication for years to come.

Doppler weather radar data assimilation at convective-allowing grid spacing for predicting an extreme weather event in Southern India

ABSTRACT Thunderstorms and heavy rainfall are the most devastating and dangerous weather phenomena over the tropical region. Southern Peninsula India in general and regions close to Western Ghats in particular are very prone to such severe weather activity. To improve the short-range forecasting of such extreme weather hazards, tremendous efforts are made to develop Doppler Weather Radar (DWR) network over Indian region for detection and continuous monitoring of weather activities. In this study, the Weather Research and Forecasting (WRF) model and its three-dimensional variational (3D-Var) data assimilation system are used to evaluate the importance of the frequently available DWR observations at convective-allowing grid spacing for predicting an extreme weather event. Various assimilation experiments are performed using background error covariance statistics generated from the National Meteorological Center (NMC) method and Ensemble method, quality control in radial winds, and with/without Digital Filter Initialization (DFI) schemes for DWR data assimilation. Results suggest that with the assimilation of DWR observations, the WRF model is able to predict selected rainfall events with less temporal, spatial and intensity error. Moreover, synoptic conditions are more favourable after DWR assimilation. Due to lack of precise initial conditions, control experiments are not able to capture this extreme weather activity. Results suggest that better skill is seen when the DFI method is used in combination with ensemble background error covariance as compared to other experiments. The maximum rainfall prediction skill is enhanced with DWR data assimilation experiment with DFI method and ensemble background error covariance statistics.

Synoptic Analysis of a Period with Above-normal Precipitation during the Dry Season in Southeastern Brazil

This study presents an analysis of a period with positive precipitation anomalies and anomalous severe weather activity in parts of the Southeastern Brazil during the dry season (austral winter). The objective of this work is to identify the synoptic pattern associated with the severe episodes on August 2018. The analysis was based on observational data and the CFSR (Climate Forecast System Reanalysis). Standardized anomalies of the main meteorological variables were used in the analysis. An anomalous trough in the mid and upper troposphere and the associated low-level flow from the Amazon Basin to Southeastern Brazil provided high amount of precipitable water, and were the main responsible for the rainfall markedly above the climatology along with severe hail and strong winds. The atmospheric environment was conditionally unstable due to a stationary front. These type of analyzes should be taken into consideration at this time of year to improve weather forecasts and minimize impacts in such circumstances.

Downscaled estimates of late 21st century severe weather from CCSM3

High-resolution dynamical downscaling is used to explore 2080–2090 peak-season hazardous convective weather as simulated from the Community Climate System Model version 3. Downscaling to 4 km grid spacing is performed using the Weather Research and Forecasting model. Tornadoes, damaging wind gusts, and large hail are simulated using a model proxy at hourly intervals for locations east of the U.S. Continental Divide. Future period results are placed into context using 1980–1990 output. While a limited sample size exists, a statistically significant increase in synthetic severe weather activity is noted in March, whereas event frequency is shown to slightly increase in April, and stay the same in May. These increases are primarily found in the Mississippi, Tennessee, and Ohio River valleys. Diurnally, most of the increase in hazardous convective weather activity is shown to be in the hours surrounding local sunset. Peak-season severe weather is also shown to be more variable in the future with a skewed potential toward larger counts. Finally, modeled proxy events are compared to environmental parameters known to generate hazardous convective weather activity. These environmental conditions explain over 80 % of the variance associated with modeled reports during March–May and show an increasing future tendency. Finally, challenges associated with dynamical downscaling for purposes of resolving severe local storms are discussed.

Génesis de tormentas severas y su incidencia en la Región de Murcia

En el Sureste peninsular son constantes las situaciones de inestabilidad convectiva alimentadas en niveles altos atmosféricos por irrupciones de masas de aire ártica/polar. Bajo estas condiciones, debido al desplazamiento de los núcleos convectivos, las cuencas y valles fluviales intrabéticos son bastante proclives a los meteoros severos, tales como lluvias torrenciales, granizo o descargas eléctricas. Uno de los sistemas más perjudiciales, las supercélulas, suelen gestarse en los meses estivales o tardo-estivales, especialmente con la superficie terrestre muy calentada, acompañado además de altos índices de cizalla y helicidad. En este trabajo se analizan estos factores y las situaciones de inestabilidad convectiva más importantes registradas en la Región de Murcia (Sureste de España) en época reciente. La zona más afectada por las tormentas severas corresponde al norte de la Región, principalmente debido a vaguadas y vórtices fríos de origen ártico/polar marítimo de onda corta. Para ello se han utilizado: (i) los datos de estaciones meteorológicas en superficie y (ii) los sondeos aerológicos disponibles en el área, en particular los relativos a régimen de temperaturas, estratificación térmica vertical e indicadores de inestabilidad atmosférica. Se han obtenido correlaciones entre diferentes variables tormentosas, mostrando, por ejemplo, una buena relación la altitud con el número de días de tormenta, pero no así con las tormentas severas.

A 10‐year spatial climatology of squall line storms across Oklahoma

AbstractSevere thunderstorms are an important and relatively common component of the annual weather across the State of Oklahoma. Such weather brings hazardous features such as, large hail, damaging winds, and tornadoes, while also providing beneficial precipitation vital to the state's agricultural and hydrological needs. In any given year, severe weather activity is dictated by seasonal and monthly changes in atmospheric conditions, which frequently determine the type and severity of subsequent storms.This study focuses on a 10‐year period between 1994 and 2003 to quantify the spatial and temporal characteristics of severe squall line storms across Oklahoma. A squall line is a linearly organized set of storms that has a sharp radar reflectivity gradient at its leading edge typically followed by a less intense stratiform region. Squall line storms are one of the most significant storm modes observed in Oklahoma due to their large aerial extent, long durations, high winds, heavy rains, and hail. For this study, geographic information systems (GIS) were used to store geo‐referenced storm data and spatially analyse storm events across varying timescales. The analysis revealed that squall lines were most predominant across eastern Oklahoma with a decreasing westward gradient. The annual averaged storm track was from the west to east, while the monthly mean squall line tracks were oriented from southwest to northeast from January through April, from west to east during May, from northwest to southeast from June through September, and from southwest to northeast through the end of the year. In addition, high‐resolution analyses of squall line initiation and termination locations revealed important geographical variability in typical storm lifecycle. Copyright © 2007 Royal Meteorological Society

An Interactive Severe Weather Activity to Motivate Student Learning

An interactive Web-based severe weather activity has been developed at Iowa State University with broad applications to motivate student learning. The exercise uses an extensive archive of weather data emphasizing warm-season severe convective events and cold-season winter storms. Several variations of the activity have been developed based upon the meteorological background of students. The flexible design of the activity may allow for its use in K–12 settings, or as a significant training tool for weather forecasters outside the classroom.

Global warming and severe weather activity

The concentration of atmospheric CO2 has been significantly increasing mainly due to human consumption of fossil fuels since the middle of the 18th century. Although the recent increases of CO2 could possibly give rise to some warming, serious problems remain unresolved in relation to the concept of global warming. The focus of this paper is directed at two areas: the first is the credibility of the global warming prediction, and the second is the long-term trend in severe weather activity associated with global warming. The global warming during the last century has been confirmed by observational data. The magnitude of the warming averaged globally is about 0.6°C during the last century, and is consistent with the computed increase in CO2 concentration. The observational data indicate a large degree of hemispheric asymmetry; the warming of the Northern Hemisphere is slower and sometimes temporarily interrupted comparing with that of Southern Hemisphere. It is an open question why this hemispherical asymmetry is of opposite sense to the results of numerical simulations for the increases in CO2 concentration. This question may possibly be resolved by consideration of the climatic effects of increases in anthropogenic aerosol levels in the troposphere in addition to greenhouse gas effects. One question raised by global warming is whether the frequency and intensity of extreme weather events have shown a long-term increased in association with global warming. Since extreme weather such as torrential rainfall and tropical cyclones are relatively small-scale, short-lived phenomena, they cannot be successfully simulated using general circulation models (GCM) at the present time. Furthermore, the limited period of the available observational data makes it difficult to produce any meaningful results with conventional statistical methods. A new statistical method, which was proposed by the present author and a colleague, is applied to the maximum daily precipitation data, and significant evidence is found for an interdecadal increasing trend in the intensity of extremely heavy rainfall. It is argued that the most likely cause of this trend is global warming. With regard to the relation between global warming and tropical cyclone activity, no significant results have yet been obtained either by numerical simulation or statistical analysis of historical data. Recent research analyzing historical data on the relation between tropical cyclone intensity and sea surface temperature has emphasized that the warmer sea surface accompanied by global warming could increase the maximum possible intensity of cyclones, although no appreciable change would be seen in the average intensity of regular storms.

Radar-Climatology of Delhi and neighbourhood: Occurrence of severe weather

Occurrence of severe weather, observed within a range of 200 miles around Delhi, has been investigated with reference to the maximum heights of echo tops reported in the area. While the number of severe weather reports increases with the increase in maximum heights of echo tops in the area, no significant increase in severe weather activity is observed when the echo tops reach or penetrate the tropopause. The monthly distribution of the number of hail occurrences as well as their preferred hours of occurrence have also been studied for the region.

Detection of Developing Tornadic Activity *

Identification of developing severe weather activity as tornadic in nature may be possible, in many cases, by detection of rapidly recurrent sferics directional pips which occur as “long bursts.” Correlation of sferics storm locations from which these bursts were received with the subsequent development of tornadoes and funnel clouds is made.