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Relevant bibliographies by topics / Tropical Cyclone

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Academic literature on the topic 'Tropical Cyclone'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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Journal articles on the topic "Tropical Cyclone"

1

Wu, Liguang, Haikun Zhao, Chao Wang, Jian Cao, and Jia Liang. "Understanding of the Effect of Climate Change on Tropical Cyclone Intensity: A Review." Advances in Atmospheric Sciences 39, no. 2 (January 21, 2022): 205–21. http://dx.doi.org/10.1007/s00376-021-1026-x.

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AbstractThe effect of climate change on tropical cyclone intensity has been an important scientific issue for a few decades. Although theory and modeling suggest the intensification of tropical cyclones in a warming climate, there are uncertainties in the assessed and projected responses of tropical cyclone intensity to climate change. While a few comprehensive reviews have already provided an assessment of the effect of climate change on tropical cyclone activity including tropical cyclone intensity, this review focuses mainly on the understanding of the effect of climate change on basin-wide tropical cyclone intensity, including indices for basin-wide tropical cyclone intensity, historical datasets used for intensity trend detection, environmental control of tropical cyclone intensity, detection and simulation of tropical cyclone intensity change, and some issues on the assessment of the effect of climate change on tropical cyclone intensity. In addition to the uncertainty in the historical datasets, intertwined natural variabilities, the considerable model bias in the projected large-scale environment, and poorly simulated inner-core structures of tropical cyclones, it is suggested that factors controlling the basin-wide intensity can be different from individual tropical cyclones since the assessment of the effect of climate change treats tropical cyclones in a basin as a whole.

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Wang, S. T., Y. X. Lin, W. J. Wang, B. Y. Zhang, and D. H. Zhang. "APPLICATION OF GROUND-BASED GPS WATER VAPOR DATA IN THE ANALYSIS OF TROPICAL CYCLONE SON-TINH HITTING HAINAN ISLAND." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W10 (February 8, 2020): 1049–52. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w10-1049-2020.

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Abstract. Tropical cyclone as a disaster. In addition to bringing abundant precipitation to the island, the huge wind will affect the public facilities in the island. In serious cases, it directly endangers people's lives and property. Every year, the disastrous damage caused by tropical cyclone causes direct or indirect economic losses to Hainan Island.This paper studies this problem. Based on the tropical cyclone data provided by China Typhoon Network and the information provided by GPS satellite observation data and 16 meteorological observatories in Hainan Island, this paper takes the monitoring of tropical cyclone Son-Tinh No. 9 in 2018 as an example to analyze the changes of meteorological elements and precipitation during the influence period of tropical cyclone. The results show that: The changes of atmospheric pressure, temperature and relative humidity at the stations are very obvious for the transit of tropical cyclones. When the island is affected by tropical cyclones, these parameters will change significantly. Among them, the abnormal changes of atmospheric pressure and temperature can effectively express the time and extent of the influence of tropical cyclone. It can be used as one of the important indicators to judge tropical cyclone before and after landfall. Based on these obvious changes, the influence of the parameters of tropical cyclone Son-Tinh before and after landing on Hainan Island is analyzed. It can effectively analyze the disasters caused by tropical cyclones and provide some reference information.

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Lloyd, Ian D., and Gabriel A. Vecchi. "Observational Evidence for Oceanic Controls on Hurricane Intensity." Journal of Climate 24, no. 4 (February 15, 2011): 1138–53. http://dx.doi.org/10.1175/2010jcli3763.1.

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Abstract The influence of oceanic changes on tropical cyclone activity is investigated using observational estimates of sea surface temperature (SST), air–sea fluxes, and ocean subsurface thermal structure during the period 1998–2007. SST conditions are examined before, during, and after the passage of tropical cyclones, through Lagrangian composites along cyclone tracks across all ocean basins, with particular focus on the North Atlantic. The influence of translation speed is explored by separating tropical cyclones according to the translation speed divided by the Coriolis parameter. On average for tropical cyclones up to category 2, SST cooling becomes larger as cyclone intensity increases, peaking at 1.8 K in the North Atlantic. Beyond category 2 hurricanes, however, the cooling no longer follows an increasing monotonic relationship with intensity. In the North Atlantic, the cooling for stronger hurricanes decreases, while in other ocean basins the cyclone-induced cooling does not significantly differ from category 2 to category 5 tropical cyclones, with the exception of the South Pacific. Since the SST response is nonmonotonic, with stronger cyclones producing more cooling up to category 2, but producing less or approximately equal cooling for categories 3–5, the observations indicate that oceanic feedbacks can inhibit intensification of cyclones. This result implies that large-scale oceanic conditions are a control on tropical cyclone intensity, since they control oceanic sensitivity to atmospheric forcing. Ocean subsurface thermal data provide additional support for this dependence, showing weaker upper-ocean stratification for stronger tropical cyclones. Intensification is suppressed by strong ocean stratification since it favors large SST cooling, but the ability of tropical cyclones to intensify is less inhibited when stratification is weak and cyclone-induced SST cooling is small. Thus, after accounting for tropical cyclone translation speeds and latitudes, it is argued that reduced cooling under extreme tropical cyclones is the manifestation of the impact of oceanic conditions on the ability of tropical cyclones to intensify.

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Surinati, Dewi, and Dwi Ayu Kusuma. "KARAKTERISTIK DAN DAMPAK SIKLON TROPIS YANG TUMBUH DI SEKITAR WILAYAH INDONESIA." OSEANA 43, no. 2 (October 30, 2018): 1–12. http://dx.doi.org/10.14203/oseana.2018.vol.43no.2.16.

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CHARACTERISTICS AND IMPACTS OF TROPICAL CYCLONES GROWING AROUND INDONESIAN TERRITORY. Tropical cyclone is a cyclonic originates from tropical oceans and driven principally by heat transfer from the ocean. Tropical cyclone is an atmospheric phenomenon characterized by the emergence of low air pressure that triggers the occurrence of strong winds due to the process of heat transfer from the equator to the latitude. This phenomenon can not be prevented, so that it has great potential to impact on the damage in the area it through. Tropical cyclones can be characterized through their life cycle, scale of power and how it impacts in the area it through. The Cempaka and Dahlia tropical cyclone occuring in 2017 greatly influenced territory of Indonesia. The effect of the cyclone causes extreme weather in Indonesia, especially in areas close to where cyclones are formed.

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Bell, Ray, Kevin Hodges, Pier Luigi Vidale, Jane Strachan, and Malcolm Roberts. "Simulation of the Global ENSO–Tropical Cyclone Teleconnection by a High-Resolution Coupled General Circulation Model." Journal of Climate 27, no. 17 (August 28, 2014): 6404–22. http://dx.doi.org/10.1175/jcli-d-13-00559.1.

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Abstract This study assesses the influence of the El Niño–Southern Oscillation (ENSO) on global tropical cyclone activity using a 150-yr-long integration with a high-resolution coupled atmosphere–ocean general circulation model [High-Resolution Global Environmental Model (HiGEM); with N144 resolution: ~90 km in the atmosphere and ~40 km in the ocean]. Tropical cyclone activity is compared to an atmosphere-only simulation using the atmospheric component of HiGEM (HiGAM). Observations of tropical cyclones in the International Best Track Archive for Climate Stewardship (IBTrACS) and tropical cyclones identified in the Interim ECMWF Re-Analysis (ERA-Interim) are used to validate the models. Composite anomalies of tropical cyclone activity in El Niño and La Niña years are used. HiGEM is able to capture the shift in tropical cyclone locations to ENSO in the Pacific and Indian Oceans. However, HiGEM does not capture the expected ENSO–tropical cyclone teleconnection in the North Atlantic. HiGAM shows more skill in simulating the global ENSO–tropical cyclone teleconnection; however, variability in the Pacific is overpronounced. HiGAM is able to capture the ENSO–tropical cyclone teleconnection in the North Atlantic more accurately than HiGEM. An investigation into the large-scale environmental conditions, known to influence tropical cyclone activity, is used to further understand the response of tropical cyclone activity to ENSO in the North Atlantic and western North Pacific. The vertical wind shear response over the Caribbean is not captured in HiGEM compared to HiGAM and ERA-Interim. Biases in the mean ascent at 500 hPa in HiGEM remain in HiGAM over the western North Pacific; however, a more realistic low-level vorticity in HiGAM results in a more accurate ENSO–tropical cyclone teleconnection.

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Nakajo, Sota, Jinji Umeda, and Nobuhito Mori. "APPLICABILITY OF D4PDF DATASET TO GLOBAL STOCHASTIC TROPICAL CYCLONE MODEL." Coastal Engineering Proceedings, no. 36v (December 31, 2020): 26. http://dx.doi.org/10.9753/icce.v36v.papers.26.

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Disaster damage caused by tropical cyclone has grown every year. However, our experience of tropical cyclone is not enough to evaluate very low frequent and catastrophic disaster event. Stochastic tropical cyclone model has been used for assessment of tropical cyclone disaster. Global stochastic model was improved by using a lot of ensemble Global Climate Model simulation data (d4PDF) instead of limited number of observation data. The model bias included d4PDF was corrected by each regional grid by simple statistical method and interpolation. The accuracy of new model was verified at representative regional area in different basins. Generally, the improvement is remarkable where tropical cyclones rarely passed. The variation of joint PDF of tropical cyclone change rate between previous model and present model agree with model improvement. As an example of application, the frequencies of strong tropical cyclone events of two cases were estimated.

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Zy Misa Harivelo, Rakotoarimanana, Rakotoarimanana Zy Harifidy, Pandin Moses Glorino Rumambo, and Waloejo Christrijogo Sumartono. "Analysis of tropical cyclones 2000-2020 in Madagascar." Disaster Advances 15, no. 3 (February 25, 2022): 13–20. http://dx.doi.org/10.25303/1503da1320.

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Madagascar is among the ten countries most exposed to cyclonic disasters in the world due to its geographical position. The country faces serious problems directly related to tropical cyclones every year. This research aims to analyze the cyclones in Madagascar from 2000 to 2020 focusing on the impact of the cyclone based on human losses and costs. The findings showed that during the past 20 years, 39 significant cyclones have affected Madagascar. On an average, 02 cyclones per year hit the country but its frequency has been decreasing since 2014. Cyclone Eline, Gafilo and Ivan were considered the most dangerous and have caused serious damages to the country. The number of victims caused by the cyclone, Eline, in 2000 were numerous while the cyclone Ivan in 2008 led many people to homelessness. In addition, the cyclone Gafilo in 2004 was recorded as the deadliest, costliest and has provoked many injuries including missing people. The number of victims, homeless, injured, missing and the cost of damage increase depending on the intensity of the cyclone. The East, North-East, West and Southwest coasts are most often hit by cyclones. Despite the frequency and damage of cyclones in the country, the actions carried out to reduce or mitigate the impacts of cyclones are still not sustainable, which makes the populations more vulnerable.

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Dare, Richard A., and John L. McBride. "Sea Surface Temperature Response to Tropical Cyclones." Monthly Weather Review 139, no. 12 (December 1, 2011): 3798–808. http://dx.doi.org/10.1175/mwr-d-10-05019.1.

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Abstract The response of sea surface temperature (SST) to tropical cyclones is studied using gridded SST data and global cyclone tracks from the period 1981–2008. A compositing approach is used whereby temperature time series before and after cyclone occurrence at individual cyclone track positions are averaged together. Results reveal a variability of several days in the time of maximum cooling with respect to cyclone passage, with the most common occurrence 1 day after cyclone passage. When compositing is carried out relative to the day of maximum cooling, the global average response to cyclone passage is a local minimum SST anomaly of −0.9°C. The recovery of the ocean to cyclone passage is generally quite rapid with 44% of the data points recovering to climatological SST within 5 days, and 88% of the data points recovering within 30 days. Although differences exist between the mean results from the separate tropical cyclone basins, they are in broad agreement with the global mean results. Storm intensity and translation speed affect both the size of the SST response and the recovery time. Cyclones occurring in the first half of the cyclone season disrupt the seasonal warming trend, which is not resumed until 20–30 days after cyclone passage. Conversely, cyclone occurrences in the later half of the season bring about a 0.5°C temperature drop from which the ocean does not recover due to the seasonal cooling cycle.

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Fang, Wei, Wenhe Lu, Jiaxin Li, and Liyao Zou. "A Novel Tropical Cyclone Track Forecast Model Based on Attention Mechanism." Atmosphere 13, no. 10 (September 30, 2022): 1607. http://dx.doi.org/10.3390/atmos13101607.

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Tropical cyclones are one of the most powerful and destructive weather systems on Earth. Accurately forecasting the landing time, location and moving paths of tropical cyclones are of great significance to mitigate the huge disasters it produces. However, with the continuous accumulation of meteorological monitoring data and the application of multi-source data, traditional tropical cyclone track forecasting methods face many challenges in forecasting accuracy. Recently, deep learning methods have proven capable of learning spatial and temporal features from massive datasets. In this paper, we propose a new spatiotemporal deep learning model for tropical cyclone track forecasting, which adopts spatial location and multiple meteorological factors to forecast the tracks of tropical cyclones. The model proposes a multi-layer ConvGRU to extract the nonlinear spatial features of tropical cyclones, while Spatial and Channel Attention Mechanism (CBAM) is adopted to overcome the large-scale problem of high response isobaric surface affecting the tropical cyclones. Meanwhile, this model utilizes a Deep and Cross framework to combine the traditional CNN model with the multi-ConvGRU model. Experiments were conducted on the China Meteorological Administration Tropical Cyclone Best Track Dataset (CMA) from 2000 to 2020, and the EAR-Interim dataset provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The experimental results show that the proposed model is superior to the deep learning tropical cyclone forecasting methods.

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Koh, J. H., and C. M. Brierley. "Tropical cyclone genesis across palaeoclimates." Climate of the Past Discussions 11, no. 1 (February 6, 2015): 181–220. http://dx.doi.org/10.5194/cpd-11-181-2015.

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Abstract. Tropical cyclone genesis is investigated for the Pliocene, Last Glacial Maximum (LGM) and the mid-Holocene through analysis of five climate models. The genesis potential index is used to estimate this from large scale atmospheric properties. The mid-Pliocene and LGM characterise periods where carbon dioxide levels were higher and lower than pre-industrial respectively, while the mid-Holocene differed primarily in its orbital configuration. The number of tropical cyclones formed each year is found to be fairly consistent across the various palaeoclimates. Although there is some model uncertainty in the change of global annual tropical cyclone frequency, there are coherent changes in the spatial patterns of tropical cyclogenesis. During the Pliocene and LGM, changes in carbon dioxide led to sea surface temperature changes throughout the tropics, yet the potential intensity of tropical cyclones appears relatively insensitive to these variations. Changes in tropical cyclone genesis during the mid-Holocene are observed to be asymmetric about the Equator: genesis is reduced in the Northern Hemisphere, but enhanced in the Southern Hemisphere. This is clearly driven by the altered seasonal insolation. Nonetheless, the enhanced seasonality may have driven localised effects on tropical cyclone genesis, through changes to the strength of monsoons and shifting of the inter-tropical convergence zone. Trends in future tropical cyclone genesis are neither consistent between the five models studied, nor with the palaeoclimate results. It is not clear why this should be the case.

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Dissertations / Theses on the topic "Tropical Cyclone"

1

Budzko, David C. "North Pacific tropical cyclones and teleconnections." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://handle.dtic.mil/100.2/ADA432435.

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Blackerby, Jason S. "Accuracy of Western North Pacific tropical cyclone intensity guidance /." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FBlackberry.pdf.

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Vogl, Stefanie. "Tropical Cyclone Boundary-Layer Models." Diss., lmu, 2009. http://nbn-resolving.de/urn:nbn:de:bvb:19-102740.

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Fu, Bing. "An observational analysis of tropical cyclogenesis in the Western North Pacific." Thesis, University of Hawaii at Manoa, 2003. http://hdl.handle.net/10125/7030.

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Stenger, Robert A. "Assessment of tropical cyclone structure variability." Thesis, Monterey, California: Naval Postgraduate School, 2013. http://hdl.handle.net/10945/37723.

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Approved for public release; distribution is unlimited
The landfall of large hurricanes in densely populated areas has increased the awareness that tropical cyclone struc-ture plays an important role in the destructive potential of a storm. A unique set of H*Wind analyses of Atlantic tropical cyclones during the 2003-2005 seasons is studied to better understand the internal and external mechanisms that lead to significant variability in surface wind structure. Secondary eyewall formation, asymmetric convection, land interaction, and environmental vertical wind shear were generally found to be mechanisms for radius of maximum wind increases, intensity decreases, and size of the radius of 34-kt wind increases. Two modes of size changes were documented that may lead to 100 km increases in 12-24 h, or near-zero size changes when a sharper than average outer wind structure profi les are generated. The statistical relationships among the radius of maximum wind, intensity, and outer-core wind structure from this sample may provide perturbed vortex initial conditions for an ensemble model to predict structure changes.

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Ramstrom, William D. (William Douglas). "Tropical cyclone momentum and energy fluxes." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/59095.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2001.
Includes bibliographical references (leaves 82-84).
Many modeling studies of tropical cyclones use the bulk aerodynamic formulae to determine angular momentum and enthalpy fluxes at the sea surface. These results show that the intensification of a hurricane is very sensitive to the values of the coefficients defined in these formulae (Emanuel, 1995). Using these formulae allows the model to make bulk estimates of these fluxes as a function of wind speed, without having to consider the full complexity of the physics of the air-sea interface. Generally, a complete treatment of fluxes would require modeling a number of small-scale physical processes, e.g. wave field response to the duration and fetch of the wind, sea spray processes, and convective stability of the boundary layer. The coefficients to these equations, Cd and Ck, have been empirically determined in previous studies, either by direct measurements on platforms and ships (Large and Pond, 1981), or by budget analyses from airborne data. However, these studies do not provide results for the high winds speeds encountered in strong hurricanes. Previous work has suggested that the coefficients do not remain constant, but rather are a function of wind speed. Producing values for these coefficients at high wind speeds will improve the accuracy of the numerical models. Recent advances in dropsonde technology (Hock and Franklin, 1999) provide improved range and accuracy from earlier methods, with reliable measurements of wind and thermodynamic variables down to within 10m of the surface. Three cases of strong hurricanes have been selected for this study, allowing analysis of these coefficients for conditions with up to 65 ms- 1 surface winds. The values of the drag coefficient, Cd, are demonstrated to reach a maximum value at about hurricane force, then maintain that value with higher wind speeds. The values of Ck, the heat flux coefficient, do not show variation with wind speed. These coefficients are calculated both at the standard 10m, so that they may be compared with existing literature, and at the top of the boundary layer, so that models which do not explicitly resolve the physics of the boundary layer may nonetheless make use of this data. The budget calculations in this study have shown that the 10m drag coefficient has a value of 0.0026 to 0.0030 for wind speeds in the 40-60 ms- 1 range. Eddy fluxes of total energy and entropy are also shown to be significant. With this effect added, budget calculations have shown that the 10m enthalpy transfer coefficient ranges from 0.0029 to 0.0036 under these conditions for Floyd and Georges. Thus, the ratio of Ck/Cd is slightly larger than 1.0. At the gradient wind level, Cd is 0.0019 ± 0.0010 and Ck is approximately 0.0018.
by William Douglas Ramstrom.
S.M.

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Sippel, Jason Allen. "The multiple vortex nature of tropical cyclogenesis." Texas A&M University, 2004. http://hdl.handle.net/1969.1/1424.

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This thesis contains an observational analysis of the genesis of Tropical Storm Allison (2001). Using a paradigm of tropical cyclone formation as the superposition of potential vorticity (PV) anomalies, the importance of different scales of PV merger to various aspects of Allisons formation is discussed. While only the case of Allison is discussed in great detail, other studies have also documented PV superposition on various scales, and superposition could be important for most tropical cyclones. Preceding Allisons genesis, PV superposition on the large scale destabilized the atmosphere and increased low-level cyclonic vorticity. This presented a more favorable environment for the formation of MCV-type PV anomalies and smaller, surface-based, meso-β-scale vortices. Although these vortices eventually merged to form a more concentrated vortex with stronger surface pressure gradients, the merger happened well after landfall of Allison and no strengthening ensued. The unstable, vorticity-rich environment was also favorable for the development of even smaller, meso-γ-scale vortices that accompanied deep convective cells within one of Allisons meso-β-scale vortices. The observations herein suggest that the meso-γ- scale convective cells and vortices are the respective source of PV production and building blocks for the meso-β-scale vortices. Finally, this thesis discusses issues related to the multiple vortex nature of tropical cyclone formation. For instance, the tracking of developing tropical cyclones is greatly complicated by the presence of multiple vortices. For these cases, the paradigm of a single cyclone center is inappropriate and alternative tracking methods are introduced.

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Zhu, Hongyan. "A minimal three-dimensional tropical cyclone model." Diss., [S.l. : s.n.], 2002. http://edoc.ub.uni-muenchen.de/archive/00000260/.

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Shin, Seol Eun. "Convective instability changes and tropical cyclone intensification." Diss., lmu, 2007. http://nbn-resolving.de/urn:nbn:de:bvb:19-72966.

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Sherman, Brett T. "Synoptic patterns related to tropical cyclone recurvature/." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/23131.

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Relative vorticity fields calculated from the U. S. Navy operational Global Band Analysis are used to relate synoptic and storm parameters to the track of tropical cyclones in the western North Pacific Ocean. In this preliminary study, synoptic patterns are developed, described and discussed from the perspective of a pattern recognition technique to assist the forecasters at the Joint Typhoon Warning Center, Guam. The focus is on track turning motions to the left and right of the persistence track and on trying to accurately predict the point of the turn or recurvature in relation to the time evolution of the vorticity patterns. The developmental sample of storms indicates that there is potential for using synoptic patterns in the Global Band Analysis to guide the selection of the appropriate track aid in the 48-60 hour time range. (Author)

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Books on the topic "Tropical Cyclone"

1

Blake, Eric S. Tropical cyclones of the eastern North Pacific Basin, 1949-2006. Ashville, North Carolina: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service-National Environmental Satellite, Data, and Information Service, 2009.

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Blake, Eric S. Tropical cyclones of the eastern North Pacific Basin, 1949-2006. Ashville, North Carolina: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service-National Environmental Satellite, Data, and Information Service, 2009.

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Elsberry, Russell L. ONR tropical cyclone motion research initiative: Field experiment planning workshop. Monterey, Calif: Naval Postgraduate School, 1989.

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Chan, Johnny C. L. Tropical cyclone spinup and intensity change. Kowloon, Hong Kong: Royal Observatory, 1988.

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Australia, Western. State tropical cyclone emergency management plan. [Perth]: Fire & Emergency Services Authority, 2004.

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Elsberry, Russell L. Recent advances in understanding tropical cyclone motion. Monterey, Calif: Naval Postgraduate School, 1991.

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National Climatic Data Center (U.S.), National Hurricane Center (1965-1995), and United States. National Environmental Satellite, Data, and Information Service, eds. Tropical cyclones of the North Atlantic Ocean, 1851-2006: With 2007 and 2008 track maps included. 6th ed. Asheville, N.C: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, National Environmental Satellite, Data, and Information Service, 2009.

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Carr, Lester E. Condensed and updated version of the Systematic Approach meteorological knowledge base Southern Hemisphere. Monterey, Calif: Naval Postgraduate School, 1999.

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Sherman, Brett T. Synoptic patterns related to tropical cyclone recurvature. Monterey, California: Naval Postgraduate School, 1988.

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Carr, Lester E. Systematic and integrated approach to tropical cyclone track forecasting, part II: Climatology, reproducibility, and refinement of meteorological knowledge base. Monterey, Calif: Naval Postgraduate School, 1995.

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Book chapters on the topic "Tropical Cyclone"

1

Done, Terry. "Tropical Cyclone/Hurricane." In Encyclopedia of Modern Coral Reefs, 1092–96. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-2639-2_159.

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Li, Tim, and Pang-chi Hsu. "Tropical Cyclone Formation." In Springer Atmospheric Sciences, 107–47. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59597-9_4.

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Harriman, Lindsey M. "Tropical Cyclone Activities." In Exploring Natural Hazards, 141–58. Boca Raton, FL : CRC Press, 2018.: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315166858-6.

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Sharkov, Eugene A. "Ionosphere and tropical cyclone activity." In GLOBAL TROPICAL CYCLOGENESIS, 315–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-13296-4_6.

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Holland, Greg J., James M. Done, Rowan Douglas, Geoffrey R. Saville, and Ming Ge. "Global Tropical Cyclone Damage Potential." In Hurricane Risk, 23–42. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-02402-4_2.

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Najar, Khalid Ahmad Al, and P. S. Salvekar. "Understanding the Tropical Cyclone Gonu." In Indian Ocean Tropical Cyclones and Climate Change, 359–69. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3109-9_40.

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Rao, P. Krishna, Susan J. Holmes, Ralph K. Anderson, Jay S. Winston, and Paul E. Lehr. "Tropical Cyclone Analysis and Forecasting." In Weather Satellites: Systems, Data, and Environmental Applications, 274–84. Boston, MA: American Meteorological Society, 1990. http://dx.doi.org/10.1007/978-1-944970-16-1_27.

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Roy, Chandan, and Rita Kovordanyi. "Tropical Cyclone and Track Forecasting." In Exploring Natural Hazards, 1–48. Boca Raton, FL : CRC Press, 2018.: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315166858-1.

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Suzuki-Parker, Asuka. "Simulated Tropical Cyclone Climatology in the Tropical Channel Experiments." In An assessment of uncertainties and limitations in simulating tropical cyclone climatology and future, 27–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25029-3_3.

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Krishnamurti, T. N., A. Jaya Kumar, Y. E. A. Raj, and S. B. Thampi. "Physical Initialization in Tropical Cyclone Forecasting." In Advanced Numerical Modeling and Data Assimilation Techniques for Tropical Cyclone Prediction, 397–406. Dordrecht: Springer Netherlands, 2016. http://dx.doi.org/10.5822/978-94-024-0896-6_15.

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Conference papers on the topic "Tropical Cyclone"

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Sheng, Y. Peter, and Sherman S. Chiu. "Tropical Cyclone Generated Currents." In 20th International Conference on Coastal Engineering. New York, NY: American Society of Civil Engineers, 1987. http://dx.doi.org/10.1061/9780872626003.056.

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Tao, Shanshan, Jialing Song, Zhifeng Wang, Yong Liu, and Sheng Dong. "Statistical Analysis for the Duration and Time Intervals of Tropical Cyclones, Hong Kong." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95791.

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Abstract Hong Kong is impacted by tropical cyclones from April to December each year. The duration of tropical cyclones is one key factor to impact the normal operation of port or coastal engineering, and longer time interval between two tropical cyclones can provide longer operation or construction time. Therefore, it is quite important to study on the long-term laws of the duration and time intervals of tropical cyclones which attacked Hong Kong. The Hong Kong Observatory issues the warning signals to warn the public of the threat of winds associated with a tropical cyclone. Choose the tropical cyclones with warning signal No. 3 or above as the research object. A statistical study was conducted on the duration of each tropical cyclone, the time interval between every two continuous tropical cyclones during the year, and the time interval between the last cyclone of each year and the first cyclone of the following year. Poisson compound extreme value distributions are constructed to calculate the return values, which can make people know how long a tropical cyclone with a fixed duration or time interval occurs once in statistical average sense. Based on bivariate copulas, the joint probability distribution of duration and time intervals of tropical cyclones are presented. Then when the duration of a tropical cyclone is known, the conditional probability that the time interval before the next tropical cyclone occurs is greater than a certain value can be calculated. The results provide corresponding conditional probability distributions. Similarly, for the sum of the duration of tropical cyclones each year, and the time interval between the last cyclone of each year and the first cyclone of the following year, their joint probability distribution and conditional probability distributions are also presented. The conditional probability can provide the probabilistic prediction of the length of the stationary period (with no impact of tropical cyclones).

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Naugolnykh, K., S. Rybak, Bengt Enflo, Claes M. Hedberg, and Leif Kari. "Infrasonic Precursor of Tropical Cyclone." In NONLINEAR ACOUSTICS - FUNDAMENTALS AND APPLICATIONS: 18th International Symposium on Nonlinear Acoustics - ISNA 18. AIP, 2008. http://dx.doi.org/10.1063/1.2956245.

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Hawkins, Jeffrey, Kim Richardson, Joe Turk, Chris Velden, Gene Poe, and Marla Helveston. "Tropical cyclone satellite remote sensing." In 34th Aerospace Sciences Meeting and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1996. http://dx.doi.org/10.2514/6.1996-943.

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Young, I. R., and J. Vinoth. "A Parametric Model for Tropical Cyclone Waves." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-10022.

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One of the major challenges in fully understanding the complex wave fields produced by intense tropical cyclones is having sufficient data to fully define the spatial wave field in such systems. Although the in situ data set is increasing, it is still quite limited and does not cover the full range of possible tropical cyclone parameters. One way to address this problem is to use remote sensing data obtained from satellites. Radar altimeters on such satellites have now been in operation for more than 25 years. Such a data set is used to investigate the wave field within tropical cyclones. The full data set consists of the over flight by an altimeter of a total of 440 tropical cyclones. As such, the data set is the most extensive ever obtained under tropical cyclone conditions. Using this data set, a parametric model for the wave field is developed. The analysis confirms that the most extreme waves are generated to the right (northern hemisphere) of the storm, where the waves generated tend to move forward with the storm. As such, they experience an extended fetch. This concept is used in conjunction with JONSWAP scaling to develop a parametric model which can be used to predict the tropical cyclone wave field. This model is then used in conjunction with in situ data to provide an estimate of the wave spectrum at any point in the spatial wave field. This approach provides a very valuable approach for preliminary design and extreme value studies.

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Grey, Stephen, and Ye Liu. "A Probabilistic Approach to Tropical Cyclone Modelling." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-96245.

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Abstract Tropical cyclones are highly variable and, in many areas of the world, are the main cause of extreme wind and associated waves, surge and current conditions. At a given location, cyclones that cause a significant impact are relatively rare but severe events, which means that the number of historical events for which data are available is often quite small. In addition, the effects, particularly surge, can be relatively localized and affected by the local bathymetry and topography. This causes considerable difficulty in making quantitative predictions of extreme events for design of offshore or coastal structures in areas affected by tropical cyclones. A new probabilistic method has been developed to increase the sample of tropical cyclones by producing 10,000 years of synthetic cyclone tracks with a range of paths, intensities and sizes based on Hall and Jewson [1] and Casson and Coles [2]. From this set of synthetic tracks, those tropical cyclones most likely to affect the site of interest are modelled using time-varying wind fields based on the Holland model [3] with surge, current and waves then modelled using the hydrodynamic model TELEMAC-2D coupled to the SWAN wave model. As it is impractical to model 10,000 years of tropical cyclones, a Gaussian process emulator is employed to relate the resultant conditions to parameters defining the cyclones, such as track position, heading, intensity and radius to maximum wind. The result is a synthesized 10,000 years of cyclone events from which design conditions for a range of return periods can be predicted with a greater degree of certainty than by extrapolating from historical events.

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Zhang, Lai, and Sun. "Intelligent Location of Tropical Cyclone Center." In Proceedings of 2005 International Conference on Machine Learning and Cybernetics. IEEE, 2005. http://dx.doi.org/10.1109/icmlc.2005.1526984.

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Peterson, RIchard E., and Thomas E. Warner. "Tropical cyclone frequency and global warming." In The world at risk: Natural hazards and climate change. AIP, 1992. http://dx.doi.org/10.1063/1.43886.

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Bock, David. "Visualization of Tropical Cyclone-Ocean Interactions." In PEARC17: Practice and Experience in Advanced Research Computing 2017. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3093338.3104149.

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Jiang, Han, Yinfei Zhou, Gang Zheng, Xiaofeng Li, Bin Liu, Lizhang Zhou, and Peng Chen. "Tropical Cyclone Rainbands in SAR Images." In 2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS). IEEE, 2022. http://dx.doi.org/10.1109/icgmrs55602.2022.9849265.

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Reports on the topic "Tropical Cyclone"

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Sampson, C. R., R. A. Jeffries, C. J. Neumann, and J.-H. Chu. Tropical Cyclone Forecasters Reference Guide 6. Tropical Cyclone Intensity. Fort Belvoir, VA: Defense Technical Information Center, October 1995. http://dx.doi.org/10.21236/ada302328.

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Sampson, C. R., R. A. Jeffries, and C. J. Neumann. Tropical Cyclone Forecasters Reference Guide 4. Tropical Cyclone Motion. Fort Belvoir, VA: Defense Technical Information Center, October 1995. http://dx.doi.org/10.21236/ada302329.

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Gray, William M. Tropical Cyclone Propagation. Fort Belvoir, VA: Defense Technical Information Center, November 1994. http://dx.doi.org/10.21236/ada327290.

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Gray, W. M. Tropical Cyclone Propagation. Fort Belvoir, VA: Defense Technical Information Center, May 1991. http://dx.doi.org/10.21236/ada239058.

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Velden, Christopher S. Tropical Cyclone Intensity Change. Fort Belvoir, VA: Defense Technical Information Center, September 2000. http://dx.doi.org/10.21236/ada609789.

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Elsberry, Russell L. Tropical Cyclone Motion Studies. Fort Belvoir, VA: Defense Technical Information Center, September 2000. http://dx.doi.org/10.21236/ada610209.

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Etro, James F., and Peter A. Morse. Tropical Cyclone Report, 1993. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada285097.

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Peng, Melinda S., James Hansen, and Tim Li. Predicting Tropical Cyclone Genesis. Fort Belvoir, VA: Defense Technical Information Center, September 2009. http://dx.doi.org/10.21236/ada531304.

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Peng, Melinda S., James Hansen, and Tim Li. Predicting Tropical Cyclone Genesis. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada541869.

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Elsberry, Russell L. Tropical Cyclone Motion Studies. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada629001.

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