Journal articles on the topic 'Storms'
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1
Wallace, Robinson, Katja Friedrich, Wiebke Deierling, Evan A. Kalina, and Paul Schlatter. "The Lightning and Dual-Polarization Radar Characteristics of Three Hail-Accumulating Thunderstorms." Weather and Forecasting 35, no. 4 (August 1, 2020): 1583–603. http://dx.doi.org/10.1175/waf-d-19-0224.1.
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AbstractThunderstorms that produce hail accumulations at the surface can impact residents by obstructing roadways, closing airports, and causing localized flooding from hail-clogged drainages. These storms have recently gained an increased interest within the scientific community. However, differences that are observable in real time between these storms and storms that produce nonimpactful hail accumulations have yet to be documented. Similarly, the characteristics within a single storm that are useful to quantify or predict hail accumulations are not fully understood. This study uses lightning and dual-polarization radar data to characterize hail accumulations from three storms that occurred on the same day along the Colorado–Wyoming Front Range. Each storm’s characteristics are verified against radar-derived hail accumulation maps and in situ observations. The storms differed in maximum accumulation, either producing 22 cm, 7 cm, or no accumulation. The magnitude of surface hail accumulations is found to be dependent on a combination of in-cloud hail production, storm translation speed, and hailstone melting. The optimal combination for substantial hail accumulations is enhanced in-cloud hail production, slow storm speed, and limited hailstone melting. However, during periods of similar in-cloud hail production, lesser accumulations are derived when storm speed and/or hailstone melting, identified by radar presentation, is sufficiently large. These results will aid forecasters in identifying when hail accumulations are occurring in real time.
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Chernogor, L. F. "Physics of geospace storms." Kosmìčna nauka ì tehnologìâ 27, no. 1 (2021): 3–77. http://dx.doi.org/10.15407/knit2021.01.003.
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A review of our knowledge about the coupling of solar-terrestrial processes, manifestations of geospace storms, and variations in space weather is presented. Space weather effects are analyzed within the system paradigm concept. The system where geospace storms occur is a Sun–interplanetary medium–magnetosphere–ionosphere–atmosphere–Earth (interior spheres) aggregate (SIMMIAE). An early twenty-first- century geospace superstorm that occurred on November 7 – 10, 2004, is examined in detail. Clustered instrument observations of this storm effects are presented. The investigation of the physical effects of geospace storms is noted to be the most important field of study in space geophysics. The problem of subsystem coupling in the SIMMIAE system during a geospace storm is interdisciplinary in nature. Its solution requires an application of the system approach. The problem has a multifactor character. The subsystem response is determined by the simultaneous (synergetic) impact of a few disturbing factors. It is important to note that the SIMMIAE is an open, nonlinear, and nonstationary system. Within it, direct coupling and feedback processes, positive and negative linkages operate. Due to the myriads of manifestations of geospace storms, because of the unique nature of each storm, the investigation of occurring physical effects is far from complete. In addition to a thorough investigation of the storm’s physical effects, there is an urgent need to model and forecast the storms adequately and in detail. The solution to these problems will facilitate the survival and steady progress of our civilization, relying more and more on new state-of-the-art technology. The more technologically reliant our society is, the more vulnerable the civilization's infrastructure to solar and geospace storm impacts becomes. A classification of geostorms based on Akasofu's epsilon parameter has been advanced. Six types of geostorm have been introduced, and a geostorm index has been suggested. A classification of ionospheric storms and disturbances based on the magnitude of variations in the peak density of the F2 layer has been suggested. Five types of the ionospheric storm have been introduced. An ionospheric index characterizing the intensity of negative and positive ionospheric storms has been suggested. A classification of ionospheric storms and disturbances based on the magnitude of variations in the lower-ionosphere electron density has been proposed. Six types of the positive ionospheric storm have been introduced. The appropriate ionospheric index has been suggested. The physics-based model of the evolution of each group of ionospheric storms and disturbances has been determined. The linkages among magnetic, ionospheric, and atmospheric storms, as well as electric field disturbances, have been shown.
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Kimball, Sytske K. "A Modeling Study of Hurricane Landfall in a Dry Environment." Monthly Weather Review 134, no. 7 (July 1, 2006): 1901–18. http://dx.doi.org/10.1175/mwr3155.1.
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Abstract The effects of dry air intrusion on landfalling hurricanes are investigated using eight numerical simulations. The simulations differ in the initial amount of moisture in the storm core and its horizontal extent from the storm center. The storms evolve very differently during the 36-h simulation. Storms with a small radial extent of moisture develop minimal rainbands, intensify rapidly in the first 3 h, and weaken as dry air from the 800–850-hPa layer wraps cyclonically and inward around the storm core. As the air approaches the core, it sinks (possibly by eyewall downdrafts or as a result of evaporative cooling), reaches the storm’s inflow layer, and entrains into the eyewall updrafts. Storms with large radial extent of moisture develop into larger storms with large rainbands, having smaller intensification rates initially, but continue to intensify for a longer period of time. Rainband downdrafts release low equivalent potential temperature air into the moat region. Low-level convergence into the rainbands reduces the magnitude of eyewall inflow. Both factors reduce storm intensification initially. Simultaneously, the rainbands act as a barrier between the moist core and the dry environment, preventing dry air from penetrating the storm core. As land is approached, inflowing air is no longer replenished with heat and moisture. Eventually, rainband convection erodes and dry air approaches the storm core from the landward side causing the storms to weaken. Without the presence of land, a hurricane can sustain itself in a dry environment, provided its moist envelope is large enough.
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Wang, Yu, Hong-Qing Wang, Lei Han, Yin-Jing Lin, and Yan Zhang. "Statistical Characteristics of Unsteady Storms in Radar Observations for the Beijing–Tianjin Region." Journal of Applied Meteorology and Climatology 54, no. 1 (January 2015): 106–16. http://dx.doi.org/10.1175/jamc-d-14-0043.1.
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AbstractThis study was designed to provide basic information for the improvement of storm nowcasting. According to the mean direction deviation of storm movement, storms were classified into three types: 1) steady storms (S storms, extrapolated efficiently), 2) unsteady storms (U storms, extrapolated poorly), and 3) transitional storms (T storms). The U storms do not fit the linear extrapolation processes because of their unsteady movements. A 6-yr warm-season radar observation dataset was used to highlight and analyze the differences between U storms and S storms. The analysis included geometric features, dynamic factors, and environmental parameters. The results showed that storms with the following characteristics changed movement direction most easily in the Beijing–Tianjin region: 1) smaller storm area, 2) lower thickness (echo-top height minus base height), 3) lower movement speed, 4) weaker updrafts and the maximum value located in the mid- and upper troposphere, 5) storm-relative vertical wind profiles dominated by directional shear instead of speed shear, 6) lower relative humidity in the mid- and upper troposphere, and 7) higher surface evaporation and ground roughness.
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Zhang, Weiqing, William Perrie, and Weibiao Li. "Impacts of Waves and Sea Spray on Midlatitude Storm Structure and Intensity." Monthly Weather Review 134, no. 9 (September 1, 2006): 2418–42. http://dx.doi.org/10.1175/mwr3191.1.
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Abstract A coupled atmosphere–wave–sea spray model system is used to evaluate the combined impacts of spray evaporation and wave drag on midlatitude storms. The focus of this paper is on the role of air–sea fluxes on storm intensity and development, and related impacts on the structure of the atmospheric boundary layer. The composite model system consists of the Canadian Mesoscale Compressible Community atmospheric model coupled to the operational wave model WAVEWATCH III, and a recent bulk parameterization for heat fluxes due to sea spray. The case studies are extratropical Hurricane Earl (in 1998) and two intense winter storms from 2000 and 2002, hereafter denoted “superbomb” and “bomb,” respectively. The results show that sea spray tends to intensify storms, whereas wave-related drag tends to weaken storms. The mechanisms by which spray and wave-related drag can influence storm intensity are quite different. When wind speeds are high and sea surface temperatures warm, spray can significantly increase the surface heat fluxes. By comparison, momentum fluxes related to wave drag are important over regions of the storm where young, newly generated waves are prevalent, for example during the rapid development phase of the storm. These momentum fluxes decrease in areas where the storm waves reach maturity. The collective influence of spray and waves on storm intensity depends on their occurrence in the early stages of a storm’s rapid intensification phase, and their spatial distribution with respect to the storm center. Moreover, for the case of the superbomb, a potential vorticity framework is used to show the relative importance of these surface flux impacts compared with baroclinic processes.
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Kumar, Edwin A., and Sushil Kumar. "Geomagnetic Storm Effect on F2-Region Ionosphere during 2012 at Low- and Mid-Latitude-Latitude Stations in the Southern Hemisphere." Atmosphere 13, no. 3 (March 15, 2022): 480. http://dx.doi.org/10.3390/atmos13030480.
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The ionospheric effects of six intense geomagnetic storms with Dst index ≤ −100 nT that occurred in 2012 were studied at a low-latitude station, Darwin (Geomagnetic coordinates, 21.96° S, 202.84° E), a low-mid-latitude station, Townsville (28.95° S, 220.72° E), and a mid-latitude station, Canberra (45.65° S, 226.30° E), in the Australian Region, by analyzing the storm–time variations in the critical frequency of the F2-region (foF2). Out of six storms, a storm of 23–24 April did not produce any ionospheric effect. The storms of 30 September–3 October (minimum Dst = −122 nT) and 7–10 October (minimum Dst = −109 nT) are presented as case studies and the same analysis was done for the other four storms. The storm of 30 September–3 October, during its main phase, produced a positive ionospheric storm at all three stations with a maximum percentage increase in foF2 (∆foF2%) of 45.3% at Canberra whereas during the recovery phase it produced a negative ionospheric storm at all three stations with a maximum ∆foF2% of −63.5% at Canberra associated with a decrease in virtual height of the F-layer (h’F). The storm of 7–10 October produced a strong long-duration negative ionospheric storm associated with an increase in h’F during its recovery phase at all three stations with a maximum ∆foF2% of −65.1% at Townsville. The negative ionospheric storms with comparatively longer duration were more pronounced in comparison to positive storms and occurred only during the recovery phase of storms. The storm main phase showed positive ionospheric storms for two storms (14–15 July and 30 September–3 October) and other three storms did not produce any ionospheric storm at the low-latitude station indicating prompt penetrating electric fields (PPEFs) associated with these storms did not propagate to the low latitude. The positive ionospheric storms during the main phase are accounted to PPEFs affecting ionospheric equatorial E × B drifts and traveling ionospheric disturbances due to joule heating at the high latitudes. The ionospheric effects during the recovery phase are accounted to the disturbance dynamo electric fields and overshielding electric field affecting E × B drifts and the storm-induced circulation from high latitudes toward low latitudes leading to changes in the natural gas composition [O/N2] ratio.
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Smith, Brianne K., James Smith, and Mary Lynn Baeck. "Flash Flood–Producing Storm Properties in a Small Urban Watershed." Journal of Hydrometeorology 17, no. 10 (October 1, 2016): 2631–47. http://dx.doi.org/10.1175/jhm-d-16-0070.1.
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Abstract The structure and evolution of flash flood–producing storms over a small urban watershed in the mid-Atlantic United States with a prototypical flash flood response is examined. Lagrangian storm properties are investigated through analyses of the 32 storms that produced the largest peak discharges in Moores Run between January 2000 and May 2014. The Thunderstorm Identification, Tracking, Analysis, and Nowcasting (TITAN) algorithm is used to track storm characteristics over their life cycle with a focus on storm size, movement, intensity, and location. First, the 13 June 2003 and 1 June 2006 storms, which produced the two largest peak discharges for the study period, are analyzed. Heavy rainfall for the 13 June 2003 and 1 June 2006 storms were caused by a collapsing thunderstorm cell and a slow-moving, low-echo centroid storm. Analyses of the 32 storms show that collapsing storm cells play an important role in peak rainfall rate production and flash flooding. Storm motion is predominantly southwest-to-northeast, and approximately half of the storms exhibited some linear organization. Mean storm total rainfall for the 32 storms displayed an asymmetric distribution around Moores Run, with sharply decreasing gradients southwest of the watershed (upwind and into the city) and increased rainfall to the northeast (downwind and away from the city). Results indicate urban modification of rainfall in flash flood–producing storms. There was no evidence that the storms split around Baltimore. Flood-producing rainfall was highly concentrated in time; on average, approximately 21% of the storm total rainfall fell within 15 min.
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Eichler, Timothy, and Wayne Higgins. "Climatology and ENSO-Related Variability of North American Extratropical Cyclone Activity." Journal of Climate 19, no. 10 (May 15, 2006): 2076–93. http://dx.doi.org/10.1175/jcli3725.1.
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Abstract The climatology and interannual variability of North American extratropical cyclones are examined using 6-hourly sea level pressure data from the NCEP–NCAR reanalysis for the period 1950–2002 and ECMWF 40-yr Re-Analysis (ERA-40) data from 1971 to 2000. The climatology includes an evaluation of the seasonal frequency and intensity of storms as well as an analysis of extreme event intensity. ENSO variability is evaluated by ENSO phase with emphasis on boreal winter. Results show an enhanced East Coast storm track during El Niño as well as an equatorward shift in storm tracks in the North Pacific for storms generated from both the NCEP–NCAR reanalysis and ERA-40 datasets. Observed precipitation close to a storm’s center is used to determine which phase of the ENSO cycle is associated with the most productive storms and where they occur. During El Niño winters, a precipitation maximum is located east of the Appalachians and is associated with an enhanced East Coast storm track. During La Niña winters, the precipitation maximum shifts to the Ohio Valley and is associated with an enhanced Great Lakes storm track. Along the U.S. west coast, there is a precipitation maximum in the Pacific Northwest during La Niña winters, which is due to a storm track west of Washington State.
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Zhai, Changzhi, Yutian Chen, Xiaoyun Cheng, and Xunzhe Yin. "Spatiotemporal Evolution and Drivers of the Four Ionospheric Storms over the American Sector during the August 2018 Geomagnetic Storm." Atmosphere 14, no. 2 (February 7, 2023): 335. http://dx.doi.org/10.3390/atmos14020335.
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The spatiotemporal variations and mechanisms of the ionospheric storms over the American sector during the August 2018 geomagnetic storm are investigated. One positive and one negative ionospheric storm occurred in North America and two positive storms were observed in South America. The ionosphere showed prominent hemispheric asymmetries during the four storms. The maximum VTEC (vertical total electron content) variation was more than 15 TECU during the positive storms and about −10 during the negative storm. The GUVI (Global Ultraviolet Imager) oxygen (O) to nitrogen (N2) column density ratio (∑O/N2) and SuperDARN (Super Dual Auroral Radar Network) polar cap potential results showed that the electric field variations played a decisive role in generating the North American negative storm while the thermspheric composition changes were responsible for the North American positive storm and the two South America positive storms.
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Molina, Rosa, Giorgio Manno, Carlo Lo Re, Giorgio Anfuso, and Giuseppe Ciraolo. "Storm Energy Flux Characterization along the Mediterranean Coast of Andalusia (Spain)." Water 11, no. 3 (March 11, 2019): 509. http://dx.doi.org/10.3390/w11030509.
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This paper investigates wave climate and storm characteristics along the Mediterranean coast of Andalusia, for the period 1979–2014, by means of the analysis of wave data on four prediction points obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF). Normally, to characterize storms, researchers use the so-called “power index”. In this paper, a different approach was adopted based on the assessment of the wave energy flux of each storm, using a robust definition of sea storm. During the investigated period, a total of 2961 storm events were recorded. They were classified by means of their associated energy flux into five classes, from low- (Class I) to high-energetic (Class V). Each point showed a different behavior in terms of energy, number, and duration of storms. Nine stormy years, i.e., years with a high cumulative energy, were recorded in 1980, 1983, 1990, 1992, 1995, 2001, 2008, 2010, and 2013.
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Rudlosky, Scott D., and Henry E. Fuelberg. "Documenting Storm Severity in the Mid-Atlantic Region Using Lightning and Radar Information." Monthly Weather Review 141, no. 9 (August 28, 2013): 3186–202. http://dx.doi.org/10.1175/mwr-d-12-00287.1.
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Abstract Storm severity in the mid-Atlantic region of the United States is examined using lightning, radar, and model-derived information. Automated Warning Decision Support System (WDSS) procedures are developed to create grids of lightning and radar parameters, cluster individual storm features, and data mine the lightning and radar attributes of 1252 severe and nonsevere storms. The study first examines the influence of serial correlation and uses autocorrelation functions to document the persistence of lightning and radar parameters. Decorrelation times are found to vary by parameter, storm severity, and mathematical operator, but the great majority are between three and six lags, suggesting that consecutive 2-min storm samples (following a storm) are effectively independent after only 6–12 min. The study next describes the distribution of lightning jumps in severe and nonsevere storms, differences between various types of severe storms (e.g., severe wind only), and relationships between lightning and radar parameters. The 2σ lightning jump algorithm (with a 10 flashes min−1 activation threshold) yields 0.92 jumps h−1 for nonsevere storms and 1.44 jumps h−1 in severe storms. Applying a 10-mm maximum expected size of hail (MESH) threshold to the 2σ lightning jump algorithm reduces the frequency of lightning jumps in nonsevere storms to 0.61 jumps h−1. Although radar-derived parameters are comparable between storms that produce severe wind plus hail and those that produce tornadoes, tornadic storms exhibit much greater intracloud (IC) and cloud-to-ground (CG) flash rates. Correlations further illustrate that lightning data provide complementary storm-scale information to radar-derived measures of storm intensity.
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Ge, Zongyuan. "Description, Origination and Prediction of Geomagnetic Storm." Highlights in Science, Engineering and Technology 72 (December 15, 2023): 217–30. http://dx.doi.org/10.54097/cpf07c70.
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The research of geomagnetic storm has developed rapidly, and many new geomagnetic storm prediction methods have appeared. In order to summarize the previous research on geomagnetic storms, and points out the improvement direction of several existing forecasting methods. This paper uses the method of literature research to introduce the basic knowledge of geomagnetic storms, the interplanetary origin, and three forecasting methods: analysis of the change of cosmic ray flux to predict geomagnetic storms, evaluation of neural networks to analyze solar wind data for geomagnetic storm prediction and using very low frequency signal to predict geomagnetic storms. The advantages and disadvantages of the above three forecasting methods are compared. According to the analysis, one can have a relatively comprehensive understanding of geomagnetic storms and grasp the basic ideas of the existing geomagnetic storm forecast methods, the forecast lead and accuracy of geomagnetic storm can be achieved by combining many existing forecasting methods. A deeper study of the relationship between Earth and the Sun could also lead to the discovery of new methods for predicting geomagnetic storms.
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Co, Nguyen Thanh, and Dinh Van Manh. "CÁC ĐẶC TRƯNG BÃO VÀ NƯỚC DÂNG DO BÃO Ở CÁC VÙNG BỜ NƯỚC TA." Tạp chí Khoa học và Công nghệ Biển 18, no. 1 (June 21, 2018): 1–9. http://dx.doi.org/10.15625/1859-3097/18/1/8682.
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Tropical storms and storm surges are dangerous. The damage caused by them is very huge. Therefore, studying characteristics of storms and storm surges is of great interest today. This paper presents some study results on characteristics of tropical storms and storm surges, which landed in Vietnam during 1951-2015. These characteristics are determined based on the storm data collected on website of Japan Meteorological Agency, JMA. In the paper, the storm surges are calculated by a numerical model as TSIM 08 software. This softwave is established by the Institute of Mechanics, Vietnam Academy of Science and Technology. The numerical model has been calibrated and verified by measured storm surge data at the hydrographic, oceanographic stations along the Vietnam coast and the survey’s storm surge data in some storms.
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Lukens, Katherine E., Ernesto Hugo Berbery, and Kevin I. Hodges. "The Imprint of Strong-Storm Tracks on Winter Weather in North America." Journal of Climate 31, no. 5 (March 2018): 2057–74. http://dx.doi.org/10.1175/jcli-d-17-0420.1.
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Northern Hemisphere winter storm tracks and their relation to winter weather are investigated using NCEP CFSR data. Storm tracks are described by isentropic PV maxima within a Lagrangian framework; these correspond well with those described in previous studies. The current diagnostics focus on strong-storm tracks, which comprise storms that achieve a maximum PV exceeding the mean value by one standard deviation. Large increases in diabatic heating related to deep convection occur where the storm tracks are most intense. The cyclogenesis pattern shows that strong storms generally develop on the upstream sectors of the tracks. Intensification happens toward the eastern North Pacific and all across the North Atlantic Ocean, where enhanced storm-track-related weather is found. In this study, the relation of storm tracks to near-surface winds and precipitation is evaluated. The largest increases in storm-track-related winds are found where strong storms tend to develop and intensify, while storm precipitation is enhanced in areas where the storm tracks have their highest intensity. Strong storms represent about 16% of all storms but contribute 30%–50% of the storm precipitation in the storm-track regions. Both strong-storm-related winds and precipitation are prone to cause storm-related losses in the eastern U.S. and North American coasts. Over the oceans, maritime operations are expected to be most vulnerable to damage offshore of the U.S. coasts. Despite making up a small fraction of all storms, the strong-storm tracks have a significant imprint on winter weather in North America potentially leading to structural and economic loss.
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Briggs, William M. "On the Changes in the Number and Intensity of North Atlantic Tropical Cyclones." Journal of Climate 21, no. 6 (March 15, 2008): 1387–402. http://dx.doi.org/10.1175/2007jcli1871.1.
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Abstract Bayesian statistical models were developed for the number of tropical cyclones, the rate at which these cyclones became hurricanes, and the rate at which hurricanes became category 4+ storms in the North Atlantic using data from 1966 to 2006 and from 1975 to 2006. It is found that, controlling for the cold tongue index (CTI), North Atlantic Oscillation index (NAOI), and the Atlantic Multidecadal Oscillation (AMO), it is improbable that the number of tropical cyclones has linearly increased since 1966, but that the number has increased since 1975. The differences between these two results have to do with the numbers of storms at the start of these two periods: it was easier to say a linear increase was present starting from circa 1975 since the storms in that period were at a low point. The rate at which storms become hurricanes appears to have decreased, and the rate at which category 4+ storms evolved from hurricanes appears to have increased. Both of these results are also dependent on the starting year. Storm intensity was also investigated by measuring the distribution of individual storm lifetimes in days, storm track length, and Emanuel’s power dissipation index. Little evidence was found that mean individual storm intensity has changed through time, but it is noted that the variability of intensity has certainly increased. Any increase in cumulative yearly storm intensity and potential destructiveness is therefore due to the increasing number of storms and not due to any increase in the intensity of individual storms. CTI was not always significant, but lower CTIs were associated with more storms, higher rates of conversion, and higher intensities. NAOI was only weakly associated: the effect was negative for the number of storms, the rate of hurricanes evolving from storms, and intensity, but it was positive for the rate of category 4+ storms evolving from hurricanes. AMO was rarely significant except in explaining the number of storms using the 1966–2006 data. Its direction was always positive as expected; however, higher values of the AMO were associated with more storms, higher rates of conversion, and higher intensities.
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Abraha, Gebregiorgis, Tesfay Yemane, and Tsegaye Kassa. "Geomagnetic storms and their impacts on Ethiopian power grid." Advances in Astronomy and Space Physics 10, no. 2 (2020): 55–64. http://dx.doi.org/10.17721/2227-1481.10.55-64.
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In present work we analysed eight geomagnetic storm events in 2015/2016 and studied the possible influence of these events on Ethiopian power grids. The results showed that the majority of the forced power outages occurred in the period of the main phase of events and the recovery period of the geomagnetic storms. The geomagnetic storms are characterised by different indices and parameters such as the disturbance storm time (Dst) values, coronal mass ejection (CME) speed, solar wind speed (V sw) and interplanetary magnetic field (IMF-Bz) on the selected dates. In most cases the observed geomagnetic storms were produced by the CME-driven storms as they show a storm sudden commencement (SSCs) before the main storms, and also have the short recovery periods. The sudden jumps of the solar wind velocities and IMF-Bz are also consistent with occurrence of the CMEs. Moreover, this effect can be traced in changes of Earth magnetic field during geomagnetic storm and quiet days. The observed CME-driven storms can produce highly variable magnetic fields on the transformers and provide forced outages, however the studied outages have not been recognised as those one driven by a geomagnetic storm.
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Workoff, Thomas E., David A. R. Kristovich, Neil F. Laird, Robert LaPlante, and Daniel Leins. "Influence of the Lake Erie Overlake Boundary Layer on Deep Convective Storm Evolution." Weather and Forecasting 27, no. 5 (April 28, 2012): 1279–89. http://dx.doi.org/10.1175/waf-d-11-00076.1.
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Abstract The influence that the overlake boundary layer has on storm intensity and structure is not well understood. To improve scientists’ understanding of the evolution of storms crossing Lake Erie, 111 events during 2001–09 were examined using observations from Weather Surveillance Radar-1988 Doppler (WSR-88D), surface, buoy, and rawinsonde sites. It was found that on average, all storm modes tended to weaken over the lake; however, considerable variability in changes of storm intensity existed, with some storms exhibiting steady-state or increasing intensity in specific environments. Noteworthy changes in the storm maximum reflectivity generally occurred within 60 min after storms crossed the upwind shoreline. Isolated and cluster storm modes exhibited much greater weakening than those storms organized into lines or convective complexes. The atmospheric parameters having the greatest influence on storm intensity over Lake Erie varied by mode. Isolated and cluster storms generally weakened more rapidly with increasingly cold overlake surface air temperatures. Linear and complex systems, on the other hand, tended to exhibit constant or increasing maximum reflectivity with cooler overlake surface air temperatures. It is suggested that strongly stable conditions near the lake surface limit the amount of boundary layer air ingested into storms in these cases.
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Bao, Tana, Guilin Xi, Yanling Hao, I.-Shin Chang, Jing Wu, Zhichao Xue, Erdemtu Jin, Wenxing Zhang, and Yuhai Bao. "The Transport Path and Vertical Structure of Dust Storms in East Asia and the Impacts on Cities in Northern China." Remote Sensing 15, no. 12 (June 19, 2023): 3183. http://dx.doi.org/10.3390/rs15123183.
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Dust storm disasters have emerged as a significant environmental challenge in East Asia. However, relying on a single monitoring method to track dust storms presents limitations and can be variable. Therefore, it is necessary to use a combination of ground and remote sensing monitoring methods to explore the source and impact range of dust storms in order to fully characterize them. To achieve this, we examined the sources and impact ranges of dust storms in East Asia from 1980 to 2020 using both ground station data and remote sensing data. In addition, we focused on three specific dust storm events in the region. Our results indicate that the central source areas of dust storms are located in southern Mongolia and the Taklamakan Desert in China. Dust storms are mainly transported and spread in the northwestern region, while they are relatively rare in the southeastern region. The HYSPLIT model simulations reveal that the primary source directions of dust storms in East Asia are northwest, west, and north, the region involved includes Kazakhstan, southern Mongolia, and the Taklimakan Desert in China. The vertical structure of the dust storm layer depends on the source of the dust storm and the intensity of the dust storm event. Dust grain stratification probably occurs due to differences in dust storm sources, grain size, and regularity. These findings demonstrate that a combination of ground-based and remote sensing monitoring methods is an effective approach to fully characterize dust storms and can provide more comprehensive information for dust storm studies.
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Murphy, Kelley M., Lawrence D. Carey, Christopher J. Schultz, Nathan Curtis, and Kristin M. Calhoun. "Automated and Objective Thunderstorm Identification and Tracking Using Geostationary Lightning Mapper (GLM) Data." Journal of Applied Meteorology and Climatology 63, no. 1 (January 2024): 47–64. http://dx.doi.org/10.1175/jamc-d-22-0143.1.
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Abstract A unique storm identification and tracking method is analyzed in varying storm environments within the United States spanning 273 hours in 2018. The methodology uses a quantity calculated through fusion of radar-based vertically integrated liquid (VIL) and satellite-based GLM flash rate density (FRD) called VILFRD to identify storms in space and time. This research analyzes GLM data use within VILFRD for the first time (method original: O), assesses four modifications to VILFRD implementation to find a more stable storm size with time (method new: N), larger storms (method original dilated: OD), or both (method new dilated: ND), and compares VILFRD methods with storm tracking using the 35-dBZ isosurface at −10°C (method non-VILFRD: NV). A case study analysis from 2019 is included to assess methods on a smaller scale and introduce a “lightning only” (LO) version of VILFRD. Large study results highlight that VILFRD-based storm identification produces smaller storms with more lightning than the NV method, and the NV method produces larger storms with a more stable size over time. Methods N and ND create smaller storm size fluctuations, but size changes more often. Dilation (OD, ND) creates larger storms and almost double the number of storms identified relative to nondilated methods (O, N, NV). The case study results closely resemble the large sample results and show that the LO method identifies storms with more lightning and shorter durations. Overall, these findings can aid in choice of storm tracking method based on desired user application and promote further testing of a lightning-only version of VILFRD.
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Yang, Kun, Vladimir Paramygin, and Y. Peter Sheng. "An objective and efficient method for estimating probabilistic coastal inundation hazards." Natural Hazards 99, no. 2 (October 4, 2019): 1105–30. http://dx.doi.org/10.1007/s11069-019-03807-w.
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Abstract The joint probability method (JPM) is the traditional way to determine the base flood elevation due to storm surge, and it usually requires simulation of storm surge response from tens of thousands of synthetic storms. The simulated storm surge is combined with probabilistic storm rates to create flood maps with various return periods. However, the map production requires enormous computational cost if state-of-the-art hydrodynamic models with high-resolution numerical grids are used; hence, optimal sampling (JPM-OS) with a small number of (~ 100–200) optimal (representative) storms is preferred. This paper presents a significantly improved JPM-OS, where a small number of optimal storms are objectively selected, and simulated storm surge responses of tens of thousands of storms are accurately interpolated from those for the optimal storms using a highly efficient kriging surrogate model. This study focuses on Southwest Florida and considers ~ 150 optimal storms that are selected based on simulations using either the low fidelity (with low resolution and simple physics) SLOSH model or the high fidelity (with high resolution and comprehensive physics) CH3D model. Surge responses to the optimal storms are simulated using both SLOSH and CH3D, and the flood elevations are calculated using JPM-OS with highly efficient kriging interpolations. For verification, the probabilistic inundation maps are compared to those obtained by the traditional JPM and variations of JPM-OS that employ different interpolation schemes, and computed probabilistic water levels are compared to those calculated by historical storm methods. The inundation maps obtained with the JPM-OS differ less than 10% from those obtained with JPM for 20,625 storms, with only 4% of the computational time.
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Taylor, John R., Mark Lester, and Timothy K. Yeoman. "Seasonal variations in the occurrence of geomagnetic storms." Annales Geophysicae 14, no. 3 (March 31, 1996): 286–89. http://dx.doi.org/10.1007/s00585-996-0286-1.
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Abstract. Seasonal variations in the onset of magnetic storms are investigated. For the purposes of this study storms have been defined as events in which Dst falls below –50 nT for at least four consecutive hours. The storms have been classified as either storm sudden commencements (SSCs; storms initiated by a sudden commencement) or as storm gradual commencements (SGCs; all other storms). It is found that the semi-annual variation of magnetic activity is reflected in the occurrence statistics of SGC events only, indicative that the solar wind origin is different for SSCs and SGCs. It is suggested that the heliospheric latitude model of seasonal magnetic activity is relatively ineffective in modulating the previously observed seasonal variations in the occurrence of magnetic storms.
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Roberts, J. F., A. J. Champion, L. C. Dawkins, K. I. Hodges, L. C. Shaffrey, D. B. Stephenson, M. A. Stringer, H. E. Thornton, and B. D. Youngman. "The XWS open access catalogue of extreme European windstorms from 1979 to 2012." Natural Hazards and Earth System Sciences 14, no. 9 (September 22, 2014): 2487–501. http://dx.doi.org/10.5194/nhess-14-2487-2014.
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Abstract. The XWS (eXtreme WindStorms) catalogue consists of storm tracks and model-generated maximum 3 s wind-gust footprints for 50 of the most extreme winter windstorms to hit Europe in the period 1979–2012. The catalogue is intended to be a valuable resource for both academia and industries such as (re)insurance, for example allowing users to characterise extreme European storms, and validate climate and catastrophe models. Several storm severity indices were investigated to find which could best represent a list of known high-loss (severe) storms. The best-performing index was Sft, which is a combination of storm area calculated from the storm footprint and maximum 925 hPa wind speed from the storm track. All the listed severe storms are included in the catalogue, and the remaining ones were selected using Sft. A comparison of the model footprint to station observations revealed that storms were generally well represented, although for some storms the highest gusts were underestimated. Possible reasons for this underestimation include the model failing to simulate strong enough pressure gradients and not representing convective gusts. A new recalibration method was developed to estimate the true distribution of gusts at each grid point and correct for this underestimation. The recalibration model allows for storm-to-storm variation which is essential given that different storms have different degrees of model bias. The catalogue is available at http://www.europeanwindstorms.org .
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Roberts, J. F., A. J. Champion, L. C. Dawkins, K. I. Hodges, L. C. Shaffrey, D. B. Stephenson, M. A. Stringer, H. E. Thornton, and B. D. Youngman. "The XWS open access catalogue of extreme European windstorms from 1979–2012." Natural Hazards and Earth System Sciences Discussions 2, no. 3 (March 7, 2014): 2011–48. http://dx.doi.org/10.5194/nhessd-2-2011-2014.
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Abstract. The XWS (eXtreme WindStorms) catalogue consists of storm tracks and model-generated maximum three-second wind-gust footprints for 50 of the most extreme winter windstorms to hit Europe over 1979–2012. The catalogue is intended to be a valuable resource for both academia and industries such as (re)insurance, for example allowing users to characterise extreme European storms, and validate climate and catastrophe models. Several storm severity indices were investigated to find which could best represent a list of known high loss (severe) storms. The best performing index was Sft, which is a combination of storm area calculated from the storm footprint and maximum 925 hPa wind speed from the storm track. All the listed severe storms are included in the catalogue, and the remaining ones were selected using Sft. A comparison of the model footprint to station observations revealed that storms were generally well represented, although for some storms the highest gusts were underestimated due to the model not simulating strong enough pressure gradients. A new recalibration method was developed to estimate the true distribution of gusts at each grid point and correct for this underestimation. The recalibration model allows for storm-to-storm variation which is essential given that different storms have different degrees of model bias. The catalogue is available at http:///www.europeanwindstorms.org/.
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Mendoza, E. T., J. A. Jimenez, and J. Mateo. "A coastal storms intensity scale for the Catalan sea (NW Mediterranean)." Natural Hazards and Earth System Sciences 11, no. 9 (September 15, 2011): 2453–62. http://dx.doi.org/10.5194/nhess-11-2453-2011.
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Abstract. A 5-class intensity scale for wave storms in the Catalan coast is presented. This has been done by analysing a storm data set which comprises 5 buoys during the period 1988/2008. The obtained classification improves the former proposal of Mendoza and Jiménez (2008) by better resolving spatial and temporal variability in wave storms in the area. The obtained classification reflects the increase in wave storm properties as the storm category increases. Because the selected classification parameter was the energy content which implicitly contains Hs and storm duration, this variable was used to define class limits; class I storms (24–250 m2 h), class II storms (251–500 m2 h), class III (501–700 m2 h), class IV storms (701–1200 m2 h) and class V storms (>1200 m2 h). The energy content variable was also used as proxy for induced hazards; the observed increase in energy content for higher classes reflected a significant increase in the intensity of the potential hazards. Lastly, the dominant synoptic situation for wave storms along the Catalan coast was the presence of a Mediterranean cyclone although a direct correspondence on cyclone's intensity over the western Mediterranean with wave energy content was not found.
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Sweeney, John. "A three-century storm climatology for Dublin 1715–2000." Irish Geography 33, no. 1 (December 23, 2014): 1–14. http://dx.doi.org/10.55650/igj.2000.300.
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A need to quantify belter the hazard posed by storms in Ireland exists, particularly during a lime of imminent climate change. To assist this, a rudimentary storm chronology lor the Dublin region was constructed for the period 1715- 2000 using documentary and instrumental records. The former, using early newspapers and other weather catalogues, indicates a period of marked storm activity in the early eighteenth century which corresponds to the later stages of the Little Ice Age in Ireland. Instrumental records, though also imperfect, suggest that the twentieth century had a number of stormy intervals, particularly in the 1920s, 1960s and early 1990s. These were probably comparable to the early eighteenth century in storm frequency and severity. A clear link between storm frequency and cyclonic synoptic circulation types was established, with stormy decades evident at times of high frequencies of Jenkinson-Lamb cyclonic types. Preliminary analysis of some of the most severe storms indicated that rapid deepening of sometimes quite small wave depressions close to Ireland are the most common occurrence, though this may not have been so in the past. An expectation of increases in storm activity in the vicinity of Ireland exists for the medium term as global warming proceeds, though in the longer term a decline in vigour of the westerly circulation can be anticipated.
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Cusack, S. "The observed clustering of damaging extra-tropical cyclones in Europe." Natural Hazards and Earth System Sciences Discussions 3, no. 12 (December 18, 2015): 7457–86. http://dx.doi.org/10.5194/nhessd-3-7457-2015.
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Abstract. The clustering of severe European windstorms on annual timescales has substantial impacts on the re/insurance industry. Management of the risk is impaired by large uncertainties in estimates of clustering from historical storm datasets typically covering the past few decades. The uncertainties are unusually large because clustering depends on the variance of storm counts. Eight storm datasets are gathered for analysis in this study in order to reduce these uncertainties. Six of the datasets contain more than 100~years of severe storm information to reduce sampling errors, and the diversity of information sources and analysis methods between datasets sample observational errors. All storm severity measures used in this study reflect damage, to suit re/insurance applications. It is found that the shortest storm dataset of 42 years in length provides estimates of clustering with very large sampling and observational errors. The dataset does provide some useful information: indications of stronger clustering for more severe storms, particularly for southern countries off the main storm track. However, substantially different results are produced by removal of one stormy season, 1989/1990, which illustrates the large uncertainties from a 42-year dataset. The extended storm records place 1989/1990 into a much longer historical context to produce more robust estimates of clustering. All the extended storm datasets show a greater degree of clustering with increasing storm severity and suggest clustering of severe storms is much more material than weaker storms. Further, they contain signs of stronger clustering in areas off the main storm track, and weaker clustering for smaller-sized areas, though these signals are smaller than uncertainties in actual values. Both the improvement of existing storm records and development of new historical storm datasets would help to improve management of this risk.
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Frazier, Garth, Roger M. Waxler, Carrick Talmadge, Claus Hetzer, and Hank Buchanan. "Comparison of infrasound emissions from tornadic and non-tornadic storms." Journal of the Acoustical Society of America 151, no. 4 (April 2022): A160. http://dx.doi.org/10.1121/10.0010972.
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At a previous ASA meeting (Spring 2019), some results corresponding to application of maximum likelihood estimation with the complex Wishart distribution to direction-of-arrival of infrasound from tornadic storms were presented. In this presentation, updated results are presented and compared with estimation of direction-of-arrival of infrasound from two non-tornadic storms that were measured with the same infrasound arrays. One of these storms was similar to the tornadic storm in that it consisted of numerous isolated storm cells with frequent lightning. The other storm was significantly different in that it was a well-organized squall line that produced only limited lightning. The tornadic storm yielded very well-defined direction-of-arrival tracks in contrast to the non-tornadic storms.
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Van Den Broeke, Matthew S. "Polarimetric Variability of Classic Supercell Storms as a Function of Environment." Journal of Applied Meteorology and Climatology 55, no. 9 (September 2016): 1907–25. http://dx.doi.org/10.1175/jamc-d-15-0346.1.
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AbstractClassic supercell storms occur in a generally well understood environment characterized by instability and vertical wind shear. Within this broadly favorable environment, large day-to-day variability in environmental parameters may lead to widely varying radar presentation of storms. Of interest here is whether specific storm structures exhibit repeatable characteristics in similar environments and whether radar presentation can be predicted with knowledge of environmental characteristics. Specifically, this paper focuses on (i) updraft characteristics inferred using differential reflectivity ZDR columns, (ii) characteristics of storm-relative inflow inferred using ZDR arcs, and (iii) areal extent and cyclicality of polarimetrically inferred hailfall at low levels. Variability of these radar features is compared among storms in similar environments and among a larger subset of storms across highly varying environments. The similarity of storms in similar and different environments is quantified, and tornadic and nontornadic storms are compared. Associations between inferred updraft, inflow, and hailfall characteristics and environmental variables are discussed. Storm features generally exhibit greater similarity among storms in similar environments than across environments, although exceptions occur. The results indicate that many radar features of classic supercells may be useful to learn about microphysical variability across environments.
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Loureiro, Carlos, and Andrew Cooper. "Temporal variability in winter wave conditions and storminess in the northwest of Ireland." Irish Geography 51, no. 2 (January 28, 2019): 155–70. http://dx.doi.org/10.55650/igj.2018.1369.
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Winter storms have significant morphological impacts in coastal areas, often leading to extensive infrastructure damage and socio-economic disruption. While storm-dominated coastal environments, such as the northwest coast of Ireland, are generally attuned to highly energetic wave conditions, morphological impacts can be intensified by changes in the frequency and sequencing of storm events, particularly during storm-groups or exceptional winter seasons. Aiming to assess the variability in frequency and sequencing of wintertime wave conditions and storms in the northwest of Ireland, we combine observational records (M4 buoy) with data from two independent wave reanalyses (ERA-Interim and WAVEWATCH III) and perform a statistical analysis of wave conditions over the past six decades. Both reanalyses represent observed wave heights with very good skill. Excellent agreement between modelled data and observations was identified up to the 99th percentile, despite a slight underestimation/overestimation by ERA-Interim/WAVEWATCH III for waves above the 90% exceedance level. The winter of 2014/15 was the most energetic on record (67 years), but not the stormiest. The results show that highly energetic and stormy winters occur in clusters during positive phases of the North Atlantic Oscillation. Significant positive temporal trends for winter wave height, number of storms per winter and average winter storm wave height, suggest that winters are becoming more energetic and stormier, with potential implications for the erosion and recovery of coastal systems in the northwest of Ireland.
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Vandenberghe, S., N. E. C. Verhoest, E. Buyse, and B. De Baets. "A stochastic design rainfall generator based on copulas and mass curves." Hydrology and Earth System Sciences Discussions 7, no. 3 (June 22, 2010): 3613–48. http://dx.doi.org/10.5194/hessd-7-3613-2010.
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Abstract. The use of design storms can be very useful in many hydrological and hydraulic practices. In this study, the concept of a copula-based secondary return period in combination with the concept of mass curves is used to generate design storms. The analysis is based on storms selected from the 105 year rainfall time series with a 10 min resolution, measured at Uccle, Belgium. In first instance, bivariate copulas and secondary return periods are explained, together with a focus on which couple of storm variables is of highest interest for the analysis and a discussion of how the results might be affected by the goodness-of-fit of the copula. Subsequently, the fitted copula is used to sample storms with a predefined secondary return period for which characteristic variables such as storm duration and total storm depth can be derived. In order to construct design storms with a realistic storm structure, mass curves of 1st, 2nd, 3rd and 4th quartile storms are developed. An analysis shows that the assumption of independence between the secondary return period and the internal storm structure could be made. Based on the mass curves, a technique is developed to randomly generate an intrastorm structure. The coupling of both techniques eventually results in a methodology for stochastic design storm generation. Finally, its practical usefulness for design studies is illustrated based on the generation of design storm ensembles and rainfall-runoff modelling.
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Vandenberghe, S., N. E. C. Verhoest, E. Buyse, and B. De Baets. "A stochastic design rainfall generator based on copulas and mass curves." Hydrology and Earth System Sciences 14, no. 12 (December 3, 2010): 2429–42. http://dx.doi.org/10.5194/hess-14-2429-2010.
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Abstract. The use of design storms can be very useful in many hydrological and hydraulic practices. In this study, the concept of a copula-based secondary return period in combination with the concept of mass curves is used to generate point-scale design storms. The analysis is based on storms selected from the 105 year rainfall time series with a 10 min resolution, measured at Uccle, Belgium. In first instance, bivariate copulas and secondary return periods are explained, together with a focus on which couple of storm variables is of highest interest for the analysis and a discussion of how the results might be affected by the goodness-of-fit of the copula. Subsequently, the fitted copula is used to sample storms with a predefined secondary return period for which characteristic variables such as storm duration and total storm depth can be derived. In order to construct design storms with a realistic storm structure, mass curves of 1st, 2nd, 3rd and 4th quartile storms are developed. An analysis shows that the assumption of independence between the secondary return period and the internal storm structure could be made. Based on the mass curves, a technique is developed to randomly generate an intrastorm structure. The coupling of both techniques eventually results in a methodology for stochastic design storm generation. Finally, its practical usefulness for design studies is illustrated based on the generation of a set of statistically identical design storm and rainfall-runoff modelling.
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Nixon, Wilfrid A., and Lin Qiu. "Developing a Storm Severity Index." Transportation Research Record: Journal of the Transportation Research Board 1911, no. 1 (January 2005): 143–48. http://dx.doi.org/10.1177/0361198105191100114.
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A primary goal in winter highway maintenance is to develop various maintenance processes so that quality control can be measured. If actions can be measured, they can be improved. A difficulty with this approach is that winter maintenance addresses the impacts of winter weather on the transportation system and that weather is inherently uncontrollable. Consequently, for a quality process to be applied to winter maintenance, the severity of individual storms must be assessed. This paper presents one way in which the severity of a storm can be measured, specifically by an index. The first step in developing an index for individual storms is to develop a method of describing storms. The method here describes storms by using six factors, including prestorm and poststorm conditions and temperatures, wind speed, and precipitation type. The matrix created is a refinement of that presented in FHWA's manual of practice for effective anti-icing. With the use of a simplified variation of this matrix-based description of storms (more than 250 descriptions), a score is generated for each storm type. This score is then adjusted so that scores for all storms fall into a normal distribution between 0 and 1. This ranking of storms was evaluated by winter maintenance garage supervisors at the Iowa Department of Transportation. Supervisors were asked to rank 10 storms (presented as brief written descriptions) from easiest to hardest to handle. Results were compared with those of the initial storm severity index. From that comparison, numerical values for certain factors were adjusted so that storm severity index scores for these 10 storms agreed with rankings given by the garage supervisors.
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Pan, Cuilin, Xianwei Wang, Lin Liu, Dashan Wang, and Huabing Huang. "Characteristics of Heavy Storms and the Scaling Relation with Air Temperature by Event Process-Based Analysis in South China." Water 11, no. 2 (January 22, 2019): 185. http://dx.doi.org/10.3390/w11020185.
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The negative scaling rate between precipitation extremes and the air temperature in tropic and subtropic regions is still a puzzling issue. This study investigates the scaling rate from two aspects, storm characteristics (types) and event process-based temperature variations. Heavy storms in South China are developed by different weather systems with unique meteorological characteristics each season, such as the warm-front storms (January), cold-front storms (April to mid-May), monsoon storms (late May to June), convective storms, and typhoon storms (July to September). This study analyzes the storm characteristics using the hourly rainfall data from 1990 to 2017; compares the storm hyetographs derived from the one-minute rainfall data during 2008–2017; and investigates the interactions between heavy storms and meteorological factors including air temperature, relative humidity, surface pressure, and wind speed at 42 weather stations in Guangzhou during 2015–2017. Most storms, except for typhoon and warm-front storms, had a short duration (3 h) and intense rates (~13 mm/h) in Guangzhou, South China. Convective storms were dominant (50%) in occurrence and had the strongest intensity (15.8 mm/h). Storms in urban areas had stronger interactions with meteorological factors and showed different hyetographs from suburban areas. Meteorological factors had larger variations with the storms that occurred in the day time than at night. The air temperature could rise 6 °C and drop 4 °C prior to and post-summer storms against the diurnal mean state. The 24-hour mean air temperature prior to the storms produced more reliable scaling rates than the naturally daily mean air temperature. The precipitation extremes showed a peak-like scaling relation with the 24-hour mean air temperature and had a break temperature of 28 °C. Below 28 °C, the relative humidity was 80%–100%, and it showed a positive scaling rate. Above 28 °C, the negative scaling relation was likely caused by a lack of moisture in the atmosphere, where the relative humidity decreased with the air temperature increase.
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Šopko, František. "Severe convective storms and heavy rain between 24th June and 1st July 2022." Meteorologické zprávy 76, no. 1 (March 29, 2023): 16–22. http://dx.doi.org/10.59984/mz.2023.01.02.
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The storm season of 2022 was rich in dangerous and notable storm situations. Although dangerous stormy weather occurred also in other months of summer, especially in August, the longest period of more than a week with storms occurred in the last week of June, when the high intensity of precipitation led to a repeated announcement of even an extreme warning level. This period is evaluated in detail in the article. In that season, storm situations were continuously communicated on social networks having elicited a positive response from the professional and lay public.
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Cerruti, Brian J., and Steven G. Decker. "The Local Winter Storm Scale: A Measure of the Intrinsic Ability of Winter Storms to Disrupt Society." Bulletin of the American Meteorological Society 92, no. 6 (June 1, 2011): 721–37. http://dx.doi.org/10.1175/2010bams3191.1.
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A local winter storm scale (LWSS) is developed to categorize the disruption caused by winter storms using archived surface weather observations from a single location along the U.S. East Coast. Development of LWSS is motivated by the recognition that the observed societal impact from a given winter storm (called realized disruption here) arises from the convolution of two factors, the meteorological conditions that lead to disruption (i.e., intrinsic disruption) and society's susceptibility to winter weather. LWSS is designed to measure the first factor, intrinsic disruption. The scale uses maximum sustained winds, wind gusts, storm-total snowfall and icing accumulations, and minimum visibility to arrive at a categorical value between 0 and 5 inclusive. An alternate method is used to quantify the realized disruption that each storm produced and helps calibrate aspects of LWSS. All winter storms observed at Newark Liberty International Airport over the 15 cold seasons between 1995/96 and 2009/10 were categorized using LWSS. Focusing on one location reduces the variability in societal susceptibility, which allows the relationship between intrinsic disruption and realized disruption to be quantified. Some important factors related to societal susceptibility were found to increase storms' realized disruption, including occurrence during a weekday, off-peak season, and less than two days subsequent to a previous storm. A closer examination of the 9–11 February 2010 winter storm demonstrates LWSS's ability to depict the spatial variability of the storm's intrinsic disruption. This information is used to infer variations in societal susceptibility between metropolitan areas and reveals the need for an instantaneous intrinsic disruption index to account for temporal variations in storm intensity.
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Shehu, Bora, and Uwe Haberlandt. "Improving radar-based rainfall nowcasting by a nearest-neighbour approach – Part 1: Storm characteristics." Hydrology and Earth System Sciences 26, no. 6 (March 25, 2022): 1631–58. http://dx.doi.org/10.5194/hess-26-1631-2022.
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Abstract. The nowcast of rainfall storms at fine temporal and spatial resolutions is quite challenging due to the unpredictable nature of rainfall at such scales. Typically, rainfall storms are recognized by weather radar and extrapolated in the future by the Lagrangian persistence. However, storm evolution is much more dynamic and complex than the Lagrangian persistence, leading to short forecast horizons, especially for convective events. Thus, the aim of this paper is to investigate the improvement that past similar storms can introduce to the object-oriented radar-based nowcast. Here we propose a nearest-neighbour approach that measures first the similarity between the “to-be-nowcasted” storm and past observed storms and later uses the behaviour of the past most similar storms to issue either a single nowcast (by averaging the 4 most similar storm responses) or an ensemble nowcast (by considering the 30 most similar storm responses). Three questions are tackled here. (i) What features should be used to describe storms in order to check for similarity? (ii) How should similarity between past storms be measured? (iii) Is this similarity useful for object-oriented nowcast? For this purpose, individual storms from 110 events in the period 2000–2018 recognized within the Hanover Radar Range (R∼115 km2), Germany, are used as a basis for investigation. A “leave-one-event-out” cross-validation is employed to test the nearest-neighbour approach for the prediction of the area, mean intensity, the x and y velocity components, and the total lifetime of the to-be-nowcasted storm for lead times from + 5 min up to + 3 h. Prior to the application, two importance analysis methods (Pearson correlation and partial information correlation) are employed to identify the most important predictors. The results indicate that most of the storms behave similarly, and the knowledge obtained from such similar past storms helps to capture better the storm dissipation and improves the nowcast compared to the Lagrangian persistence, especially for convective events (storms shorter than 3 h) and longer lead times (from 1 to 3 h). The main advantage of the nearest-neighbour approach is seen when applied in a probabilistic way (with the 30 closest neighbours as ensembles) rather than in a deterministic way (averaging the response from the four closest neighbours). The probabilistic approach seems promising, especially for convective storms, and it can be further improved by either increasing the sample size, employing more suitable methods for the predictor identification, or selecting physical predictors.
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Yin, Lirong, Lei Wang, Lijun Ge, Jiawei Tian, Zhengtong Yin, Mingzhe Liu, and Wenfeng Zheng. "Study on the Thermospheric Density Distribution Pattern during Geomagnetic Activity." Applied Sciences 13, no. 9 (April 30, 2023): 5564. http://dx.doi.org/10.3390/app13095564.
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The atmospheric density of the thermosphere is a fundamental parameter for spacecraft launch and orbit control. Under magnetic storm conditions, the thermospheric atmospheric density experiences significant fluctuations, which have a negative impact on spacecraft control. Exploring thermospheric density during geomagnetic storms can help to mitigate the effects of such events. Research on the inversion of accelerometer measurements for different satellites and the variations of atmospheric density under extreme conditions is still in its infancy. In this paper, the distribution of atmospheric density during three geomagnetic storms is investigated from the inversion results of the Swarm-C accelerometer. Three major geomagnetic storms and their recovery phases are selected as case studies. The thermospheric density obtained by Swarm-C is separated into day and night regions. The empirical orthogonal function analysis method is used to study the spatiotemporal distribution of thermospheric density during geomagnetic storms. The results indicate that storms have a more significant impact on nighttime thermospheric density. The impact of magnetic storms on the temporal distribution of thermospheric density is considerable. The first-order empirical orthogonal function (EOF) time coefficient value on the day after the storm is the largest, reaching 2–3 times that before the magnetic storm. The impact of magnetic storms on atmospheric density is mainly reflected in the time distribution. The spatial distribution of atmospheric density is less affected by magnetic storms and is relatively stable in the short term. The impact of magnetic storms on the spatial distribution of nighttime thermospheric density is more significant than that of daytime regions, and the response of daytime regions to magnetic storms is slower.
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A, Kashyapi, Shripad V K, and Natu J C. "Cyclonic storms and Depressions over the north Indian Ocean during 2019*." MAUSAM 71, no. 3 (August 3, 2021): 357–76. http://dx.doi.org/10.54302/mausam.v71i3.35.
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During 2019, in all 12 intense low pressure systems formed over the Indian Seas. These include; one Super cyclonic storm (KYARR), one extremely severe cyclonic storm (FANI), 4 very Severe Cyclonic Storms (VAYU, HIKAA, MAHA & BULBUL), 2 Cyclonic Storms (PABUK & PAWAN), 3 Deep Depressions and 1 Depression. Out of these 12 systems, 4 systems formed over the Bay of Bengal and 8 over the Arabian Sea. Arabian Sea remained exceptionally active in terms of cyclogenesis this year, especially in the post monsoon season. The season-wise distribution had been one cyclonic storm in winter, one in pre-monsoon season, 2 depressions and 2 very severe cyclonic storms during the monsoon season and 4 cyclonic storms and 3 depressions in Post monsoon season.
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Burcea, Sorin, Roxana Cică, and Roxana Bojariu. "Radar-derived convective storms' climatology for the Prut River basin: 2003–2017." Natural Hazards and Earth System Sciences 19, no. 7 (July 3, 2019): 1305–18. http://dx.doi.org/10.5194/nhess-19-1305-2019.
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Abstract. Weather radar measurements are used to study the climatology of convective storms and their characteristics in the transboundary Prut River basin. The Storm Cell Identification and Tracking (SCIT) algorithm was used to process the volumetric reflectivity measurements, in order to identify, characterize, and track the convective storm cells. The storm attribute table output of the algorithm was used to separate the convective from the stratiform storm cells, by applying a simple selection criterion based on the average vertically integrated liquid (VIL) values. The radar-derived characteristics of convective storms were used to document the spatial and temporal distributions and storm properties in terms of duration, distance travelled, movement direction, and intensity. The results show that 94.3 % of all convective storm cells were detected during May–August, with the peak in July. The peak time for convective storm cells' occurrence was in the afternoon and evening hours between 10:00 and 18:00 UTC. The median duration of a convective storm was 42 min, the median distance travelled was 23 km, and the median movement speed was 7.7 m s−1. The average movement of storms varied with months, but overall most convective storms move from the south-west and south–south-east. Also, the analysis shows that the longer-lasting convective storms were the most intense. The spatial distribution of the convective cells reveals yearly variation patterns and hotspots but also highlights the limitations of radar measurement at longer distances. Reanalysis data suggest that low values of sea level pressure over the Black Sea can act as a dynamical driver of convective storms in the analysed area.
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Salmun, H., A. Molod, F. S. Buonaiuto, K. Wisniewska, and K. C. Clarke. "East Coast Cool-Weather Storms in the New York Metropolitan Region." Journal of Applied Meteorology and Climatology 48, no. 11 (November 1, 2009): 2320–30. http://dx.doi.org/10.1175/2009jamc2183.1.
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Abstract New York coastal regions are frequently exposed to winter extratropical storm systems that exhibit a wide range of local impacts. Studies of these systems either have used localized water-level or beach erosion data to identify and characterize the storms or have used meteorological conditions from reanalysis data to provide a general regional “climatology” of storms. The use of meteorological conditions to identify these storms allows an independent assessment of impacts on the coastal environment and therefore can be used to predict the impacts. However, the intensity of these storms can exhibit substantial spatial variability that may not be captured by the relatively large scales of the studies using reanalysis data, and this fact may affect the localized assessment of storm impact on the coastal communities. A method that uses data from National Data Buoy Center stations in the New York metropolitan area to identify East Coast cool-weather storms (ECCSs) and to describe their climatological characteristics is presented. An assessment of the presence of storm conditions and a three-level intensity scale was developed using surface pressure data as measured at the buoys. This study identified ECCSs during the period from 1977 through 2007 and developed storm climatologies for each level of storm intensity. General agreement with established climatologies demonstrated the robustness of the method. The impact of the storms on the coastal environment was assessed by computing “storm average” values of storm-surge data and by examining beach erosion along the south shore of Long Island, New York. A regression analysis demonstrated that the best storm-surge predictor is based on measurements of significant wave height at a nearby buoy.
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Lemke, Laura, and Jon K. Miller. "DEVELOPMENT OF A STORM EROSION CLIMATOLOGY FOR THE NEW JERSEY COAST, US." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 93. http://dx.doi.org/10.9753/icce.v36.papers.93.
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In this study, the Storm Erosion Index (SEI), developed by Miller and Livermont (2008), is used to reevaluate storms that have impacted New Jersey over the past several decades based on their erosion potential. This index considers all three drivers of coastal erosion including wave height, water level, and storm duration and has been shown to more closely correlated to observed erosion than more traditional indices (Miller and Livermont 2008). Here, storms are assessed at thirteen shoreline segments defined along the Atlantic coast of New Jersey. When reevaluated with SEI, the top three storms across all shoreline segments are the December 1992 nor’easter, the Veteran’s Day Storm in November 2009, and Hurricane Sandy in October 2012. In general, the December 1992 nor’easter and Hurricane Sandy are more highly ranked in the northern half of the state with Hurricane Sandy having a maximum return period of 38 years. The Veteran’s Day Storm on the other hand is more highly ranked in the southern half of the state having a maximum return period of 42 years. A closer look at these three storms illustrates the importance of each of the three drivers of coastal erosion in determining erosion potential. A particular emphasis is placed on storm duration which explains why the Veteran’s Day Storm (td = ~90 hours) outranks Hurricane Sandy (td = ~60 hours) in the southern portion of the state. The assessment performed in this study produces a record of historical storms ranked by SEI that future storms can be compared to. This allows for an understanding of the erosion potential of future storms in the context of what has occurred previously.
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Xue, Junchen, Sreeja Vadakke Veettil, Marcio Aquino, Xiaogong Hu, Lin Quan, Dun Liu, Peng Guo, and Mengjie Wu. "Performance of BDS B1 Frequency Standard Point Positioning during the Main Phase of Different Classified Geomagnetic Storms in China and the Surrounding Area." Remote Sensing 14, no. 5 (March 3, 2022): 1240. http://dx.doi.org/10.3390/rs14051240.
Full textAbstract:
Geomagnetic storms are one of the space weather events. The radio signals transmitted by modern navigation systems suffer from the effects of magnetic storms, which can degrade the performance of the whole system. In this study, the performance of the BeiDou Navigation Satellite System (BDS) B1 frequency standard point positioning (SPP) in China and the surrounding area during different classes of storm was investigated for the first time. The statistical analysis of the results revealed that the accuracy of the BDS-2 B1 frequency SPP deteriorated during the storms. The probability of the extrema of the positioning error statistics was largest during strong storms, followed by moderate and weak storms. The positioning accuracy for storms of a similar class was found not to be at the same level. The root mean square error in positioning for the different classes of storm could be at least tens of centimeters in the east, north and up directions. The findings in this study could contribute toward the error constraint of BDS positioning accuracy during different classes of geomagnetic storm and be beneficial to other systems, such as BDS-3, as well.
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Anoruo, Chukwuma Moses, Francisca Nneka Okeke, and Kingsley Chukwudi Okpala. "Africa mid and low latitude ionosphere response observed during the geomagnetic storms of July 15 and 9 March 2012 using GPS." Journal of Physics: Conference Series 2214, no. 1 (February 1, 2022): 012022. http://dx.doi.org/10.1088/1742-6596/2214/1/012022.
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Abstract In this paper, the initial and recovery phases of July 15 and March 9, 2012 geomagnetic storms in African mid and low latitudes ionosphere has been studied using GPS. We employ relative total electron content (rTEC) variations using 2 stations from the Africa Geodetic Reference Frame (AFREF) to characterize African sector ionosphere responses during both storms. To characterize rTEC, we employ 15-day median-average sliding-window during the storm. Both storms lasted 18 h with Dst minima -139 nT for July 15 and -145 nT for March 9, when solar plasma wind speed recorded 545 km/s and 712 km/s respectively. The recovery phase lasted 48 h for -139 nT storm and 46 h for -145 nT when solar plasma wind speed recorded 485 km/s and 428 km/s respectively. It may be attributed that storm recovery phases do not depend on storm severity but the response of ionosphere during storms. Results show Positive storm dominates during the recovery phase and interplanetary electric field and solar plasma wind speed contribute to storm enhanced density. Ionospheric disturbances observed due to prompt penetration electric field shaped the magnetic field and prompted pre-storm rTEC enhancement. Plasma convection at mid-latitudes of African sector observed rTEC enhancements which did not appear in other studied sector results. Further observations should be carried out using other storms.
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Fujii, M., and Y. Yamanaka. "Effects of storms on primary productivity and air-sea CO<sub>2</sub> exchange in the subarctic western North Pacific: a modeling study." Biogeosciences Discussions 5, no. 1 (January 4, 2008): 65–81. http://dx.doi.org/10.5194/bgd-5-65-2008.
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Abstract. Biogeochemical responses of the open ocean to storms and their feedback to climate are still poorly understood. Using a marine ecosystem model, we examine biogeochemical responses to the storms in the subarctic western North Pacific. The storms in summer through early autumn enhance primary production by wind-induced nutrient injections into the surface waters while the storms in the other seasons reduce primary production by intensifying light limitation on the phytoplankton growth due to vertical dilution of the phytoplankton. The two compensating effects diminish the storm-induced annual change of primary production to only 1%. On the contrary, the storms enhance the annual sea-to-air CO2 efflux by no less than 34%, resulting from storm-induced strong winds. Our results suggest that previous studies using climatological wind and CO2 data probably underestimated the sea-to-air CO2 efflux during storms in the subarctic western North Pacific, and therefore, that continuous observations are required to reduce uncertainties in the global oceanic CO2 uptake.
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Weisse, Ralf, Hans von Storch, and Frauke Feser. "Northeast Atlantic and North Sea Storminess as Simulated by a Regional Climate Model during 1958–2001 and Comparison with Observations." Journal of Climate 18, no. 3 (February 1, 2005): 465–79. http://dx.doi.org/10.1175/jcli-3281.1.
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Abstract An analysis of the storm climate of the northeast Atlantic and the North Sea as simulated by a regional climate model for the past 44 yr is presented. The model simulates the period 1958–2001 driven by the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis. Comparison with observations shows that the model is capable of reproducing impact-related storm indices such as the number of severe and moderate storms per year or the total number of storms and upper intra-annual percentiles of near-surface wind speed. The indices describe both the year-to-year variability of the frequency, as well as changes in the average intensity of storm events. Analysis of these indices reveals that the average number of storms per year has increased near the exit of the North Atlantic storm track and over the southern North Sea since the beginning of the simulation period (1958), but the increase has attenuated later over the North Sea and the average number of storms per year has been decreasing over the northeast Atlantic since about 1990–95. The frequency of the most severe storms follows a similar pattern over the northeast North Atlantic while too few severe storms occurred in other areas of the model domain, preventing a statistical analysis for these areas.
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Shisler, Matthew P., and David R. Johnson. "Comparison of Methods for Imputing Non-Wetting Storm Surge to Improve Hazard Characterization." Water 12, no. 5 (May 16, 2020): 1420. http://dx.doi.org/10.3390/w12051420.
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Joint probability methods for characterizing storm surge hazards involve the use of a collection of hydrodynamic storm simulations to fit a response surface function describing the relationship between storm surge and storm parameters. However, in areas with a sufficiently low probability of flooding, few storms in the simulated storm suite may produce surge, resulting in a paucity of information for training the response surface fit. Previous approaches have replaced surge elevations for non-wetting storms with a constant value or truncated them from the response surface fitting procedure altogether. The former induces bias in predicted estimates of surge from wetting storms, and the latter can cause the model to be non-identifiable. This study compares these approaches and improves upon current methodology by introducing the concept of “pseudo-surge,” with the intent to describe how close a storm comes to producing surge at a given location. Optimal pseudo-surge values are those which produce the greatest improvement to storm surge predictions when they are used to train a response surface. We identify these values for a storm suite used to characterize surge hazard in coastal Louisiana and compare their performance to the two other methods for adjusting training data. Pseudo-surge shows potential for improving hazard characterization, particularly at locations where less than half of training storms produce surge. We also find that the three methods show only small differences in locations where more than half of training storms wet.
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Köklü, Kevser. "Mathematical Analysis of the 08 May 2014 Weak Storm." Mathematical Problems in Engineering 2021 (September 15, 2021): 1–12. http://dx.doi.org/10.1155/2021/9948745.
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Since the time scale of weak storms is about half the time scale of intense storms, it is troublesome and important to examine the solar wind parameters/interplanetary magnetic field (IMF) (E, v , P , T, N, and Bz) to evolve and affect to zonal geomagnetic indices (Kp, Dst, AE, and ap). In a severe storm, which usually has two main phases, solar parameters have enough time to react, but weak storms cannot find this time. They have to yield their reaction in a short time. One can find a weak storm in order to reveal and discuss the consistency of models that have proven themselves in severe and moderate storms in this study. I discuss weak storm (Dst = −46) on May 8, 2014, via solar wind parameters and zonal geomagnetic indices. The goal of the work is to realize the models applicable to the moderate and the strong storms for a weak storm. Hereby, all possible correlations between solar parameters and zonal indices are discussed in depth. I tried to obey the cause-effect relationship while creating mathematical models while not ignoring the physical principles. Therefore, the physical principles govern the study. The results are visualized with tables and graphs for the understanding of the dynamic structure of the storm.
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Золотухина, Нина, Nina Zolotukhina, Владимир Куркин, Vladimir Kurkin, Неля Полех, and Nelya Polekh. "Ionospheric disturbances over East Asia during intense December magnetic storms of 2006 and 2015: similarities and differences." Solar-Terrestrial Physics 4, no. 3 (September 28, 2018): 28–42. http://dx.doi.org/10.12737/stp-43201805.
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Using data from ionosondes, located in East Asia, and total electron content maps, we have made a comparative analysis of ionospheric disturbances associated with the intense geomagnetic storms of December 14–16, 2006 and December 19–22, 2015. These storms had almost equal peak intensities (Dstmin=–162 and –155 nT), but different durations of the main phases (2.5 and 19 hr). At the beginning of both the storms, the region under study was located in the vicinity of the midnight meridian. Ionospheric responses to magnetic storms differed in: i) an increase in the F2-layer critical frequency at subauroral latitudes, caused by an increase in auroral precipitation, during the initial phase of the former storm and the absence of this effect in the latter; (ii) a sharp drop in the critical frequency in the evening hours of the main phase of the latter storm, caused by a shift of the main ionospheric trough to lower latitudes, and the absence of this effect during the former storm; (iii) generation of a short-term positive disturbance observed at subauroral latitudes only in the early recovery phase of the former storm after the negative ionospheric disturbance. During both the storms at middle latitudes there were positive disturbances and wave-like fluctuations of the critical frequency which increased in the vicinity of the dawn meridian. The main causes of the differences between the ionospheric storms are shown to be the differences between the initial conditions of the magnetosphere–ionosphere system and durations of the main phases of magnetic storms.
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Золотухина, Нина, Nina Zolotukhina, Владимир Куркин, Vladimir Kurkin, Неля Полех, and Nelya Polekh. "Ionospheric disturbances over East Asia during intense December magnetic storms of 2006 and 2015: similarities and differences." Solnechno-Zemnaya Fizika 4, no. 3 (September 28, 2018): 39–56. http://dx.doi.org/10.12737/szf-43201805.
Full textAbstract:
Using data from ionosondes, located in East Asia, and total electron content maps, we have made a comparative analysis of ionospheric disturbances as-sociated with the intense geomagnetic storms of De-cember 14–16, 2006 and December 19–22, 2015. These storms had almost equal peak intensities (Dstmin=–162 and –155 nT), but different durations of the main phases (2.5 and 19 hr). At the beginning of both the storms, the region under study was located in the vicinity of the midnight meridian. Ionospheric re-sponses to magnetic storms differed in: i) an increase in the F2-layer critical frequency at subauroral latitudes, caused by an increase in auroral precipitation, during the initial phase of the former storm and the absence of this effect in the latter; (ii) a sharp drop in the critical frequency in the evening hours of the main phase of the latter storm, caused by a shift of the main ionospheric trough to lower latitudes, and the absence of this effect during the former storm; (iii) generation of a short-term positive disturbance observed at subauroral latitudes only in the early recovery phase of the former storm after the negative ionospheric disturbance. During both the storms at middle latitudes there were positive dis-turbances and wave-like fluctuations of the critical fre-quency which increased in the vicinity of the dawn me-ridian. The main causes of the differences between the ionospheric storms are shown to be the differences be-tween the initial conditions of the magnetosphere-ionosphere system and durations of the main phases of magnetic storms.
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Knowland, K. E., R. M. Doherty, and K. I. Hodges. "The effects of springtime mid-latitude storms on trace gas composition determined from the MACC reanalysis." Atmospheric Chemistry and Physics 15, no. 6 (March 31, 2015): 3605–28. http://dx.doi.org/10.5194/acp-15-3605-2015.
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Abstract. The relationship between springtime air pollution transport of ozone (O3) and carbon monoxide (CO) and mid-latitude cyclones is explored for the first time using the Monitoring Atmospheric Composition and Climate (MACC) reanalysis for the period 2003–2012. In this study, the most intense spring storms (95th percentile) are selected for two regions, the North Pacific (NP) and the North Atlantic (NA). These storms (∼60 storms over each region) often track over the major emission sources of East Asia and eastern North America. By compositing the storms, the distributions of O3 and CO within a "typical" intense storm are examined. We compare the storm-centered composite to background composites of "average conditions" created by sampling the reanalysis data of the previous year to the storm locations. Mid-latitude storms are found to redistribute concentrations of O3 and CO horizontally and vertically throughout the storm. This is clearly shown to occur through two main mechanisms: (1) vertical lifting of CO-rich and O3-poor air isentropically, from near the surface to the mid- to upper-troposphere in the region of the warm conveyor belt; and (2) descent of O3-rich and CO-poor air isentropically in the vicinity of the dry intrusion, from the stratosphere toward the mid-troposphere. This can be seen in the composite storm's life cycle as the storm intensifies, with area-averaged O3 (CO) increasing (decreasing) between 200 and 500 hPa. The influence of the storm dynamics compared to the background environment on the composition within an area around the storm center at the time of maximum intensity is as follows. Area-averaged O3 at 300 hPa is enhanced by 50 and 36% and by 11 and 7.6% at 500 hPa for the NP and NA regions, respectively. In contrast, area-averaged CO at 300 hPa decreases by 12% for NP and 5.5% for NA, and area-averaged CO at 500 hPa decreases by 2.4% for NP while there is little change over the NA region. From the mid-troposphere, O3-rich air is clearly seen to be transported toward the surface, but the downward transport of CO-poor air is not discernible due to the high levels of CO in the lower troposphere. Area-averaged O3 is slightly higher at 1000 hPa (3.5 and 1.8% for the NP and NA regions, respectively). There is an increase of CO at 1000 hPa for the NP region (3.3%) relative to the background composite and a~slight decrease in area-averaged CO for the NA region at 1000 hPa (-2.7%).