Special Issue "Tropical Cyclones and Their Impacts"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology and Meteorology".

Deadline for manuscript submissions: closed (15 May 2018).

Special Issue Editor

Guest Editor
Assoc. Prof. Corene Matyas

Department of Geography, University of Florida, Gainesville, FL 32611, USA
Website | E-Mail
Interests: tropical cyclones; remote sensing of rainfall; climatology of the tropics; natural hazards

Special Issue Information

Dear Colleagues,

On an annual basis, tropical cyclones affect thousands of people. Efforts of physical scientists are needed to help improve our ability to predict the location, intensity, and extent of these systems and their impacts, while the work of social scientists is vital to better communicate warning messages, assess risk and evaluate strategies for recovery after the event. This Special Issue of Atmosphere focuses on tropical cyclones. We seek research studies that examine tropical cyclones in all ocean basins from formation to dissipation, including interactions with the surrounding atmosphere and underlying ocean and/or land surface. Both observational and modeling approaches are welcomed. Manuscripts may also focus on the impacts of these systems such as rainfall and associated flooding, storm surge and coastal erosion, and/or wind-related damage including tornadoes. We invite manuscripts incorporating data from paleoclimatological investigations to future scenarios under changing climatic conditions. We also wish to include studies that examine the impacts of tropical cyclones on people and the environment. This may include risk communication and evacuation, vulnerability and recovery, and impacts to ecosystems, infrastructure, and health.

Assoc. Prof. Corene Matyas
Guest Editor

Manuscript Submission Information

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Keywords

  • Tropical Cyclone Meteorology

  • Tropical Cyclone Climatology

  • Atmosphere, Ocean, Land Conditions

  • Tropical Cyclone Impacts on Humans

  • Tropical Cyclone Impacts on the Environment

Published Papers (17 papers)

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Research

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Open AccessCommunication
Snow Level Characteristics and Impacts of a Spring Typhoon-Originating Atmospheric River in the Sierra Nevada, USA
Atmosphere 2018, 9(6), 233; https://doi.org/10.3390/atmos9060233
Received: 24 May 2018 / Revised: 11 June 2018 / Accepted: 13 June 2018 / Published: 15 June 2018
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Abstract
On 5–7 April 2018, a landfalling atmospheric river resulted in widespread heavy precipitation in the Sierra Nevada of California and Nevada. Observed snow levels during this event were among the highest snow levels recorded since observations began in 2002 and exceeded 2.75 km [...] Read more.
On 5–7 April 2018, a landfalling atmospheric river resulted in widespread heavy precipitation in the Sierra Nevada of California and Nevada. Observed snow levels during this event were among the highest snow levels recorded since observations began in 2002 and exceeded 2.75 km for 31 h in the northern Sierra Nevada and 3.75 km for 12 h in the southern Sierra Nevada. The anomalously high snow levels and over 80 mm of precipitation caused flooding, debris flows, and wet snow avalanches in the upper elevations of the Sierra Nevada. The origin of this atmospheric river was super typhoon Jelawat, whose moisture remnants were entrained and maintained by an extratropical cyclone in the northeast Pacific. This event was notable due to its April occurrence, as six other typhoon remnants that caused heavy precipitation with high snow levels (mean = 2.92 km) in the northern Sierra Nevada all occurred during October. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
Statistical Analysis of Tropical Cyclones in the Solomon Islands
Atmosphere 2018, 9(6), 227; https://doi.org/10.3390/atmos9060227
Received: 8 May 2018 / Revised: 7 June 2018 / Accepted: 8 June 2018 / Published: 12 June 2018
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Abstract
This study examines tropical cyclone (TC) activity around the Solomon Islands (SIs) using best track data from the Tropical Cyclone Warning Centre, Brisbane, and the Regional Specialized Meteorological Centre, Nadi. Analysis of long-term trends showed that the frequency of TCs has decreased in [...] Read more.
This study examines tropical cyclone (TC) activity around the Solomon Islands (SIs) using best track data from the Tropical Cyclone Warning Centre, Brisbane, and the Regional Specialized Meteorological Centre, Nadi. Analysis of long-term trends showed that the frequency of TCs has decreased in this region, while the average TC intensity has increased. Datasets were classified according to the phase of Madden–Julian Oscillation (MJO) and the index of El Niño Southern Oscillation (ENSO), provided by Bureau of Meteorology. The MJO significantly influenced TC activity in the SIs, with TC genesis occurring most frequently in phases 6–8. In contrast, TC genesis occurred less frequently in phase 5. ENSO also influenced TC genesis; more TCs were generated in El Niño periods. The TC genesis locations during El Niño (La Niña) periods were significantly displaced to the north (south) over the SIs. TCs generated during El Niño conditions tended to be strong. This study also explores the modulation of TCs in terms of the seasonal climatic variability of large-scale environmental variables such as sea surface temperature (SST), low-level relative vorticity, vertical wind shear, and upper level divergence. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
A Nowcasting Model for Tropical Cyclone Precipitation Regions Based on the TREC Motion Vector Retrieval with a Semi-Lagrangian Scheme for Doppler Weather Radar
Atmosphere 2018, 9(5), 200; https://doi.org/10.3390/atmos9050200
Received: 4 April 2018 / Revised: 17 May 2018 / Accepted: 18 May 2018 / Published: 21 May 2018
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Abstract
Accurate observational data and reliable prediction models are both essential to improve the quality of precipitation forecasts. The spiraling trajectories of air parcels within a tropical cyclone (TC) coupled with the large sizes of these systems brings special challenges in making accurate short-term [...] Read more.
Accurate observational data and reliable prediction models are both essential to improve the quality of precipitation forecasts. The spiraling trajectories of air parcels within a tropical cyclone (TC) coupled with the large sizes of these systems brings special challenges in making accurate short-term forecasts, or nowcasts. Doppler weather radars are ideal instruments to observe TCs when they move over land, and traditional nowcasts incorporate radar data. However, data from dozens of radars must be mosaicked together to observe the entire system. Traditional single-radar-based reflectivity tracking methods commonly employed in nowcasting are not suitable for TCs as they are not able to capture the circular motion of these systems. Thus, this paper focuses on improving short-term predictability of TC precipitation with Doppler weather radar observations based on: a multi-scale motion vector retrieval algorithm, an optimization technique and a semi-Lagrangian advection scheme. Motion fields of precipitation regions are obtained by a multi-level motion vector retrieval algorithm, then corrected and smoothed by the optimization technique using mass and smooth constraints. Predicted precipitation regions are then extrapolated using the semi-Lagrangian advection scheme. A case study of Hurricane Isabel (2003) shows that the combination of these methods may increase reliable rainfall prediction to about 5 h as the TC moves over land. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
Event-Based Climatology of Tropical Cyclone Rainfall in Houston, Texas and Miami, Florida
Atmosphere 2018, 9(5), 170; https://doi.org/10.3390/atmos9050170
Received: 30 March 2018 / Revised: 25 April 2018 / Accepted: 27 April 2018 / Published: 3 May 2018
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Abstract
Tropical cyclone (TC) rainfall amounts are compared from 1950–2017 for Houston, Texas and Miami, Florida to estimate the risk of TC rain in both cities. Following the wake of Hurricanes Harvey and Irma in 2017, concern has risen over the future of raininess [...] Read more.
Tropical cyclone (TC) rainfall amounts are compared from 1950–2017 for Houston, Texas and Miami, Florida to estimate the risk of TC rain in both cities. Following the wake of Hurricanes Harvey and Irma in 2017, concern has risen over the future of raininess in these locations. Per-event rainfall amounts are aggregated using tracks taken from HURDAT, time-of-rain gathered from National Weather Service daily weather maps, and rainfall totals taken from airport monitoring stations. Risk analysis tools include descriptive statistics, time series, and return frequencies for Houston and Miami, and spatially interpolated surfaces for Hurricanes Harvey and Irma. The season duration is longer in Miami than in Houston. The uppermost rainfall events in the distribution for Houston show a significant increase through time, suggesting the most intense rainfall events are becoming worse for Houston. The expected return frequency for a Harvey-like event (940 mm) in Houston is every 230 years, on average, and the 90th percentile rain of 286 mm is expected once every 17 years (11–29; 90% significance). The expected return frequency for an Irene-like event (261 mm—maximum for location) in Miami is every 173 years, on average, and the 90th percentile rain of 167 mm is expected once every 11 years (7–17; 90% significance). Results show a substantial difference between Houston and Miami TC rainfall climatologies similar to the differences of Hurricanes Harvey and Irma. Though emergency management must be tailored for each TC, management for inland TC rainfall may be more applicable in Houston than in Miami. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
Regional Forecasting of Wind Speeds during Typhoon Landfall in Taiwan: A Case Study of Westward-Moving Typhoons
Atmosphere 2018, 9(4), 141; https://doi.org/10.3390/atmos9040141
Received: 6 February 2018 / Revised: 6 April 2018 / Accepted: 8 April 2018 / Published: 10 April 2018
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Abstract
Taiwan is located on a route where typhoons often strike. Each year, the strong winds accompanying typhoons are a substantial threat and cause significant damage. However, because the terrains of high mountains in Taiwan vary greatly, when a typhoon passes the Central Mountain [...] Read more.
Taiwan is located on a route where typhoons often strike. Each year, the strong winds accompanying typhoons are a substantial threat and cause significant damage. However, because the terrains of high mountains in Taiwan vary greatly, when a typhoon passes the Central Mountain Range (CMR), the wind speed of typhoons becomes difficult to predict. This research had two primary objectives: (1) to develop data-driven techniques and a powerful artificial neural network (ANN) model to predict the highly complex nonlinear wind systems in western Taiwan; and, (2) to investigate the accuracy of wind speed predictions at various locations and for various durations in western Taiwan when the track of westward typhoons is affected by the complex geographical shelters and disturbances of the CMR. This study developed a typhoon wind speed prediction model that evaluated various typhoon tracks (covering Type 2, Type 3, and Type 4 tracks, as defined by the Central Weather Bureau), and evaluated the prediction accuracy at Hsinchu, Wuqi, and Kaohsiung Stations in western Taiwan. Back propagation neural networks (BPNNs) were employed to establish wind speed prediction models, and a linear regression model was adopted as the benchmark to evaluate the strengths and weaknesses of the BPNNs. The results were as follows: (1) The BPNNs generally had favorable performance in predicting wind speeds and their performances were superior to linear regressions; (2) when absolute errors were adopted to evaluate the prediction performances, the predictions at Hsinchu Station were the most accurate, whereas those at Wuqi Station were the least accurate; however, when relative errors were adopted, the predictions at Hsinchu Station were again the most accurate, whereas those at Kaohsiung were the least accurate; and, (3) regarding the relative error rates for the maximum wind speed of Types 2, 3, and 4 typhoons, Wuqi, Kaohsiung, and Wuqi had the most accurate performance, respectively; as for maximum wind time error (ETM) for Types 2, 3, and 4 typhoons, Kaohsiung, Wuqi, and Wuqi correspondingly performed the most favorably. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
Typhoon Effect on Kuroshio and Green Island Wakes: A Modelling Study
Atmosphere 2018, 9(2), 36; https://doi.org/10.3390/atmos9020036
Received: 5 January 2018 / Revised: 18 January 2018 / Accepted: 20 January 2018 / Published: 23 January 2018
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Abstract
Green Island, located in the typhoon-active eastern Taiwan coastal water, is the potential Kuroshio power plant site. In this study, a high resolution (250–2250 m) shallow-water equations model is used to investigate the effect of typhoon on the hydro-dynamics of Kuroshio and Green [...] Read more.
Green Island, located in the typhoon-active eastern Taiwan coastal water, is the potential Kuroshio power plant site. In this study, a high resolution (250–2250 m) shallow-water equations model is used to investigate the effect of typhoon on the hydro-dynamics of Kuroshio and Green Island wakes. Two typhoon–Kuroshio interactions—typhoon Soulik and Holland’s typhoon model—are studied. Simulation results of typhoon Soulik indicate salient characteristics of Kuroshio, and downstream island wakes seems less affected by the typhoon Soulik, because the shortest distance of typhoon Soulik is 250 km away from Green Island and wind speed near Green Island is small. Moreover, Kuroshio currents increase when flow is in the same direction as the counterclockwise rotation of typhoon, and vice versa. This finding is in favorable agreement with the TOROS (Taiwan Ocean Radar Observing System) observed data. Simulations of Kuroshio and Holland’s typhoon model successfully reproduces the downstream recirculation and vortex street. Numerical results reveal that the slow moving typhoon has a more significant impact on the Kuroshio and downstream Green Island wakes than the fast moving typhoon does. The rightward bias phenomenon is evident—Kuroshio currents increase (decrease) in the right (left) of the moving typhoon’s track, due to the counterclockwise rotation of typhoon. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
Estimate of Hurricane Wind Speed from AMSR-E Low-Frequency Channel Brightness Temperature Data
Atmosphere 2018, 9(1), 34; https://doi.org/10.3390/atmos9010034
Received: 12 November 2017 / Revised: 1 January 2018 / Accepted: 17 January 2018 / Published: 22 January 2018
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Abstract
Two new parameters (W6H and W6V) were defined that represent brightness temperature increments for different low-frequency channels due to ocean wind. We developed a new wind speed retrieval model inside hurricanes based on W6H and W6V using brightness temperature data from AMSR-E. The [...] Read more.
Two new parameters (W6H and W6V) were defined that represent brightness temperature increments for different low-frequency channels due to ocean wind. We developed a new wind speed retrieval model inside hurricanes based on W6H and W6V using brightness temperature data from AMSR-E. The AMSR-E observations of 12 category 3–5 hurricanes from 2003 to 2011 and corresponding data from the H*wind analysis system were used to develop and validate the AMSR-E wind speed retrieval model. The results show that the mean bias and the overall root-mean-square (RMS) difference of the AMSR-E retrieved wind speeds with respect to H*wind (HRD Real-time Hurricane Wind Analysis System) analysis data were −0.01 m/s and 2.66 m/s, respectively. One case study showed that W6H and W6V were less sensitive to rain than the observed AMSR-E C-band and X-band brightness temperature data. The AMSR-E retrieval model was further validated by comparing the retrieved wind speeds against stepped-frequency microwave radiometer (SFMR) measurements. The comparison showed an RMS difference of 3.41 m/s and a mean bias of 0.49 m/s. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
Decision Science Perspectives on Hurricane Vulnerability: Evidence from the 2010–2012 Atlantic Hurricane Seasons
Atmosphere 2018, 9(1), 32; https://doi.org/10.3390/atmos9010032
Received: 1 September 2017 / Revised: 12 January 2018 / Accepted: 17 January 2018 / Published: 20 January 2018
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Abstract
Although the field has seen great advances in hurricane prediction and response, the economic toll from hurricanes on U.S. communities continues to rise. We present data from Hurricanes Earl (2010), Irene (2011), Isaac (2012), and Sandy (2012) to show that individual and household [...] Read more.
Although the field has seen great advances in hurricane prediction and response, the economic toll from hurricanes on U.S. communities continues to rise. We present data from Hurricanes Earl (2010), Irene (2011), Isaac (2012), and Sandy (2012) to show that individual and household decisions contribute to this vulnerability. From phone surveys of residents in communities threatened by impending hurricanes, we identify five decision biases or obstacles that interfere with residents’ ability to protect themselves and minimize property damage: (1) temporal and spatial myopia, (2) poor mental models of storm risk, (3) gaps between objective and subjective probability estimates, (4) prior storm experience, and (5) social factors. We then discuss ways to encourage better decision making and reduce the economic and emotional impacts of hurricanes, using tools such as decision defaults (requiring residents to opt out of precautions rather than opt in) and tailoring internet-based forecast information so that it is local, specific, and emphasizes impacts rather than probability. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
Open AccessArticle
The Use of a Spectral Nudging Technique to Determine the Impact of Environmental Factors on the Track of Typhoon Megi (2010)
Atmosphere 2017, 8(12), 257; https://doi.org/10.3390/atmos8120257
Received: 3 October 2017 / Revised: 7 December 2017 / Accepted: 7 December 2017 / Published: 20 December 2017
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Abstract
Sensitivity tests based on a spectral nudging (SN) technique are conducted to analyze the effect of large-scale environmental factors on the movement of typhoon Megi (2010). The error of simulated typhoon track is effectively reduced using SN and the impact of dynamical factors [...] Read more.
Sensitivity tests based on a spectral nudging (SN) technique are conducted to analyze the effect of large-scale environmental factors on the movement of typhoon Megi (2010). The error of simulated typhoon track is effectively reduced using SN and the impact of dynamical factors is more significant than that of thermal factors. During the initial integration and deflection period of Megi (2010), the local steering flow of the whole and lower troposphere is corrected by a direct large-scale wind adjustment, which improves track simulation. However, environmental field nudging may weaken the impacts of terrain and typhoon system development in the landfall period, resulting in large simulated track errors. Comparison of the steering flow and inner structure of the typhoon reveals that the large-scale circulation influences the speed and direction of typhoon motion by: (1) adjusting the local steering flow and (2) modifying the environmental vertical wind shear to change the location and symmetry of the inner severe convection. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
Spatial and Temporal Trends in the Location of the Lifetime Maximum Intensity of Tropical Cyclones
Atmosphere 2017, 8(10), 198; https://doi.org/10.3390/atmos8100198
Received: 31 August 2017 / Revised: 30 September 2017 / Accepted: 5 October 2017 / Published: 10 October 2017
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Abstract
The climatology of tropical cyclones is an immediate research need, specifically to better understand their long-term patterns and elucidate their future in a changing climate. One important pattern that has recently been detected is the poleward shift of the lifetime maximum intensity (LMI) [...] Read more.
The climatology of tropical cyclones is an immediate research need, specifically to better understand their long-term patterns and elucidate their future in a changing climate. One important pattern that has recently been detected is the poleward shift of the lifetime maximum intensity (LMI) of tropical cyclones. This study further assessed the recent (1977–2015) spatial changes in the LMI of tropical cyclones, specifically those of tropical storm strength or stronger in the North Atlantic and northern West Pacific basins. Analyses of moving decadal means suggested that LMI locations migrated south in the North Atlantic and north in the West Pacific. In addition to a linear trend, there is a cyclical migration of LMI that is especially apparent in the West Pacific. Relationships between LMI migration and intensity were explored, as well as LMI location relative to landfall. The southerly trend of LMI in the North Atlantic was most prevalent in the strongest storms, resulting in these storms reaching their LMI farther from land. The relationship between intensity and LMI migration in the West Pacific was not as clear, but the most intense storms have been reaching LMI closer to their eventual landfall location. This work adds to those emphasizing the importance of understanding the climatology of the most intense hurricanes and shows there are potential human impacts resulting from any migration of LMI. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
An Alternative Multi-Model Ensemble Forecast for Tropical Cyclone Tracks in the Western North Pacific
Atmosphere 2017, 8(9), 174; https://doi.org/10.3390/atmos8090174
Received: 7 June 2017 / Revised: 9 September 2017 / Accepted: 12 September 2017 / Published: 15 September 2017
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Abstract
This study introduces an unequally weighted technique for Multi-model Ensemble (MME) forecasting for western North Pacific Tropical Cyclone (TC) tracks. Weights are calculated by partial least square regression, and members are selected by paired t-test. The performances for shorter forecast time ranges, [...] Read more.
This study introduces an unequally weighted technique for Multi-model Ensemble (MME) forecasting for western North Pacific Tropical Cyclone (TC) tracks. Weights are calculated by partial least square regression, and members are selected by paired t-test. The performances for shorter forecast time ranges, such as 24, 48 and 72 h, are examined in order to improve the MME model, in which the weights for members are equally assigned. For longer forecast time ranges, such as 96 and 120 h, weights for MME members are thought to be less reliable, since the modeling is more likely to be influenced by the climate variability in the data period. A combination of both techniques for the shorter and the longer forecast time ranges is suggested as an alternative MME forecast procedure in operational meteorological agencies. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
Comparing the Spatial Patterns of Rainfall and Atmospheric Moisture among Tropical Cyclones Having a Track Similar to Hurricane Irene (2011)
Atmosphere 2017, 8(9), 165; https://doi.org/10.3390/atmos8090165
Received: 26 July 2017 / Revised: 19 August 2017 / Accepted: 1 September 2017 / Published: 6 September 2017
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Abstract
Irene was the most destructive tropical cyclone (TC) of the 2011 Atlantic hurricane season due to flooding from rainfall. This study used a Geographic Information System to identify TCs with similar tracks and examine the spatial attributes of their rainfall patterns. Storm-total rainfall [...] Read more.
Irene was the most destructive tropical cyclone (TC) of the 2011 Atlantic hurricane season due to flooding from rainfall. This study used a Geographic Information System to identify TCs with similar tracks and examine the spatial attributes of their rainfall patterns. Storm-total rainfall was calculated from the Unified Precipitation Dataset for 11 post-1948 storms and statistics corresponding to the top 10% of rainfall values left of track were computed. Irene-type tracks occur every 6.6 years. Floyd (1999) produced the highest rainfall overall and was the closest analog to Irene, yet Irene produced more rainfall in the northeastern U.S. where higher values of precipitable water existed. Areas of high rainfall expanded as five TCs moved north due to synoptic-scale forcing during extratropical transition. However, Irene and three other TCs did not exhibit this pattern. The amount of moisture in the environment surrounding the TC, rather than storm speed or intensity, exhibited the strongest correlations with rainfall totals and their spatial distribution. These results demonstrate the high variability that exists in the production of rainfall among TCs experiencing similar steering flow, and show that advection of moisture from the tropics is key to higher rainfall totals in the mid-latitudes. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
Spatial Distributions of Tropical Cyclone Tornadoes by Intensity and Size Characteristics
Atmosphere 2017, 8(9), 160; https://doi.org/10.3390/atmos8090160
Received: 9 August 2017 / Revised: 22 August 2017 / Accepted: 25 August 2017 / Published: 28 August 2017
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Abstract
Tropical cyclones that make landfall often spawn tornadoes. Previous studies have shown that these tornadoes are not uniformly distributed in the United States or in the tropical cyclone environment. They show that tornadoes tend to occur relatively close to the coastline and that [...] Read more.
Tropical cyclones that make landfall often spawn tornadoes. Previous studies have shown that these tornadoes are not uniformly distributed in the United States or in the tropical cyclone environment. They show that tornadoes tend to occur relatively close to the coastline and that they tend to cluster to the east-of-center in the tropical cyclone environment, particularly in the northeast and east-of-center quadrants. This study contributes to these studies by analyzing the spatial distributions of tropical cyclone tornadoes by intensity, path length, path width, and the damage potential index. The analyses confirm that most tornadoes occur relatively close to the coastline, but show that stronger tornadoes with larger paths are disproportionately common farther inland. They also confirm that the highest amount of activity is located within the northeast and east-of-center quadrants and show that the most potentially damaging tornadoes cluster in a sub region near the intersection of these two quadrants. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Open AccessArticle
Impacts of the Lower Stratosphere on the Development of Intense Tropical Cyclones
Atmosphere 2017, 8(7), 128; https://doi.org/10.3390/atmos8070128
Received: 12 June 2017 / Revised: 6 July 2017 / Accepted: 15 July 2017 / Published: 19 July 2017
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Abstract
This study examines potential impacts of the lower stratosphere on the development and the inner-core structure of intense tropical cyclones (TCs). By initializing the Hurricane Weather Research and Forecasting (HWRF) model with different monthly averaged sounding profiles in the Northwestern Pacific and the [...] Read more.
This study examines potential impacts of the lower stratosphere on the development and the inner-core structure of intense tropical cyclones (TCs). By initializing the Hurricane Weather Research and Forecasting (HWRF) model with different monthly averaged sounding profiles in the Northwestern Pacific and the North Atlantic basins, it is shown that the lower stratosphere layer (LSL) can impose a noticeable influence on the TC structure and development via formation of an extra warm core near the tropopause along with a thin layer of inflow in the LSL at the high-intensity limit. Specifically, a lower tropopause level allows for higher TC intensity and a more distinct double warm core structure. Likewise, a weaker LSL stratification also corresponds to a warmer upper-level core and higher intensity. Of further significance is that the double warm core formation is more sensitive to tropopause variations in the Northwestern Pacific basin than those in the North Atlantic basin, given the same sea surface temperature. The results suggest that variations in tropopause level and LSL stratification could be an important factor that is responsible for the long-term variability of TC intensity. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Review

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Open AccessReview
A Review of Parametric Descriptions of Tropical Cyclone Wind-Wave Generation
Atmosphere 2017, 8(10), 194; https://doi.org/10.3390/atmos8100194
Received: 18 August 2017 / Revised: 22 September 2017 / Accepted: 28 September 2017 / Published: 5 October 2017
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Abstract
More than three decades of observations of tropical cyclone wind and wave fields have resulted in a detailed understanding of wave-growth dynamics, although details of the physics are still lacking. These observations are presented in a consistent manner, which provides the basis to [...] Read more.
More than three decades of observations of tropical cyclone wind and wave fields have resulted in a detailed understanding of wave-growth dynamics, although details of the physics are still lacking. These observations are presented in a consistent manner, which provides the basis to be able to characterize the full wave spectrum in a parametric form throughout tropical cyclones. The data clearly shows that an extended fetch model can be used to represent the maximum significant wave height in such storms. The shape stabilizing influence of nonlinear interactions means that the spectral shape is remarkably similar to fetch-limited cases. As such, the tropical cyclone spectrum can also be described by using well-known parametric models. A detailed process is described to parameterize the wave spectrum at any point in a tropical cyclone. Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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Other

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Open AccessReply
Reply to “Comments on ‘Spatial and Temporal Trends in the Location of the Lifetime Maximum Intensity of Tropical Cyclones’”
Atmosphere 2018, 9(7), 242; https://doi.org/10.3390/atmos9070242
Received: 19 June 2018 / Accepted: 21 June 2018 / Published: 25 June 2018
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(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
Open AccessComment
Comment on “Spatial and Temporal Trends in the Location of the Lifetime Maximum Intensity of Tropical Cyclones” by Tennille and Ellis
Atmosphere 2018, 9(7), 241; https://doi.org/10.3390/atmos9070241
Received: 29 April 2018 / Accepted: 21 June 2018 / Published: 25 June 2018
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Abstract
The latitude where tropical cyclones (TCs) reach their peak intensity has migrated poleward in some regions [...] Full article
(This article belongs to the Special Issue Tropical Cyclones and Their Impacts)
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