Download or read book Statistical and Model driven Analyses of North Atlantic Tropical Cyclone Activity written by Michael E. Kozar and published by . This book was released on 2011 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hurricane Climatology written by James B. Elsner and published by Oxford University Press. This book was released on 2013-03-28 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hurricane Climatology explains how to analyze and model hurricane data to better understand and predict present and future hurricane activity
Download or read book Hurricanes and Climate Change written by Jennifer M. Collins and published by Springer. This book was released on 2017-02-20 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides research that shows tropical cyclones are more powerful than in the past with the most dramatic increases occurring over the North Atlantic and with the strongest hurricanes. Although such increases are correlated with warming oceans and are consistent with the thermodynamic theory of hurricane intensity, there remains doubt about the interpretation, integrity, and meaning of these results. Arising from the 5th International Summit on Hurricanes and Climate Change, this book contains new research on topics related to hurricanes and climate change. Bringing together international leading academics and researchers on various sides of the debate, the book discusses new research and expresses opinions about what is happening and what might happen in the future with regard to regional and global hurricane (tropical cyclone) activity.
Download or read book Hurricanes of the North Atlantic written by James B. Elsner and published by Oxford University Press. This book was released on 1999-06-10 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: Called the greatest storms on the planet, hurricanes of the North Atlantic Ocean often cause tremendous social and economic upheaval in the United States, Mexico, and the Caribbean. And with the increasing development of coastal areas, the impact of these storms will likely increase. This book provides a comprehensive analysis of North Atlantic hurricanes and what they mean to society. It is intended as an intermediary between hurricane climate research and the users of hurricane information. Topics include the climatology of tropical cyclones in general and those of the North Atlantic in particular; the major North Atlantic hurricanes, focusing on U.S. landfalling storms; the prediction models used in forecasting; and societal vulnerability to hurricanes, including ideas for modeling the relationship between climatological data and analysis in the social and economic sciences.
Download or read book Uncertainties and Limitations in Simulating Tropical Cyclones written by Asuka Suzuki-Parker and published by Springer Science & Business Media. This book was released on 2012-01-05 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thesis work was in two major parts: development and testing of a new approach to detecting and tracking tropical cyclones in climate models; and application of an extreme value statistical approach to enable assessment of changes in weather extremes from climate models. The tracking algorithm applied a creative phase-space approach to differentiate between modeled tropical cyclones and their mid-latitude cousins. A feature here was the careful attention to sensitivity to choice of selection parameters, which is considerable. The major finding was that the changes over time were relatively insensitive to these details. This new approach will improve and add confidence to future assessments of climate impacts on hurricanes. The extremes approach utilized the Generalized Pareto Distribution (one of the standard approaches to statistics of extremes) applied to present and future hurricane distributions as modeled by a regional climate model, then applied the changes to current observations to extract the changes in the extremes. Since climate models cannot resolve these extremes directly, this provides an excellent method of determining weather extremes in general. This is of considerable societal importance as we are most vulnerable to such extremes and knowledge of their changes enables improved planning and adaptation strategies.
Download or read book A Statistical Analysis of the Aviation Model s Tropical Cyclone Forecasts During the 1995 North Atlantic Tropical Cyclone Season written by Rodney Clint Keele and published by . This book was released on 1997 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Statistical Model for the Prediction of Western North Pacific Tropical Cyclone Motion WPCLPR written by Xu Yiming and published by . This book was released on 1985 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Cryosphere and North Atlantic Tropical Cyclone Activity written by Johannes Mack and published by . This book was released on 2013 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: The components of the northern hemisphere cryosphere and their relationship to Atlantic tropical cyclone activity are investigated in this study. Multiple ordinary least-squares regression with a stepwise selection procedure is used to develop a new statistical forecasting scheme for 13 seasonal tropical cyclone parameters at four lead times for the period 1980-2010. Sea ice area and sea ice extent in 10 geographic regions, snow cover extent in three geographic regions and five indices reflecting major modes of climate variability were analyzed as possible predictors. Three model groups, based on predictors, were constructed and evaluated: 1) only climate mode predictors, 2) only cryosphere predictors, and 3) both cryosphere and climate mode predictors. Models using only climate mode predictors showed poor predictability of the tropical cyclone parameters across all four lead times while the models using only cryosphere predictors and those using both sets of predictors showed improved predictability. Baffin Bay and Hudson Bay sea ice area were found to be the most significant predictors, exhibiting an inverse relationship with overall tropical cyclone activity. The developed models were also compared to current operational statistical models of tropical cyclone activity. While the operational models were generally more skillful, June hindcasts of major hurricanes outperformed the operational models by as much as 20%.
Download or read book Prediction of North Atlantic Tropical Cyclone Activity and Rainfall written by Beda Nidhi Luitel and published by . This book was released on 2016 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Among natural disasters affecting the United States, North Atlantic tropical cyclones (TCs) and hurricanes are responsible for the highest economic losses and are one of the main causes of fatalities. Although we cannot prevent these storms from occurring, skillful seasonal predictions of the North Atlantic TC activity and associated impacts can provide basic information critical to our improved preparedness. Unfortunately, it is not yet possible to predict heavy rainfall and flooding associated with these storms several months in advance, and the lead time is limited to few days at the most. On the other hand, overall North Atlantic TC activity can be potentially predicted with a six- to nine-month lead time. This thesis focuses on the evaluation of the skill in predicting basin-wide North Atlantic TC activity with a long lead time and rainfall with a short lead time. For the seasonal forecast of TC activity, we develop statistical-dynamical forecasting systems for different quantities related to the frequency and intensity of North Atlantic TCs using only tropical Atlantic and tropical mean sea surface temperatures (SSTs) as covariates. Our results show that skillful predictions of North Atlantic TC activity are possible starting from November for a TC season that peaks in the August-October months. The short term forecasting of rainfall associated with TC activity is based on five numerical weather prediction (NWP) models. Our analyses focused on 15 North Atlantic TCs that made landfall along the U.S. coast over the period of 2007-2012. The skill of the NWP models is quantified by visual examination of the distribution of the errors for the different lead-times, and numerical examination of the first three moments of the error distribution. Based on our results, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead times up to 48 hours, without a consistently best or worst NWP model.
Download or read book Analysis and Prediction of Atlantic Tropical Cyclone Activity written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This work begins with the development of a statistical prediction model of numbers of tropical storms, hurricanes and major hurricanes per year in several regions of the Atlantic: the entire Atlantic, the Caribbean Sea and the Gulf of Mexico, as well as landfalling storms along the US Gulf of Mexico, Southeast and Northeast coasts. The methodology involves of cross-correlating variables against Empirical Orthogonal Functions (EOFs) of the Hurricane Track Density Function (HTDF) to select predictors. The model performs well in the basin-wide predictions over the entire Atlantic and Caribbean, with the predictions showing an improvement over climatology and random chance at a 95% confidence level. Over the Gulf of Mexico, only named storms showed that level of predictability. Predicting landfalls proves more difficult, and only the prediction of named storms along the US Southeastern and Gulf Coasts shows an improvement over random chance at the 95% confidence level. Tropical cyclone activity along the U.S. Northeastern Coast is found to be unpredictable in this model; with the rarity of events, the model is unstable. In order to provide some physical basis for many of the connections found statistically, the second section is a case study of the 2004-07 Atlantic hurricane seasons. It is found that 2005 had the most favorable SST and vertical wind shear conditions over the main development region. 2004 and 2006 had intermediate levels of SST and wind shear and, outside of the month of August, similar levels of activity. Activity in 2007 was generally suppressed: although more tropical storms formed than in 2006, they were very short-lived. On average, tropical storms in 2007 survived less than 2.5 days. The strength of the subtropical anticyclone is a very important factor: in 2005, a weak subtropical high allowed for unusually high SST in the main development region, while in 2007 a strong subtropical high over the east Atlantic cooled SST and increased vertical wind.
Download or read book Tropical Cyclones of the North Atlantic Ocean written by George W. Cry and published by . This book was released on 1965 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Climate Variability and Tropical Cyclone Activity written by Pao-Shin Chu and published by Cambridge University Press. This book was released on 2022-03-10 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive summary of research on tropical cyclone variability at various time scales, from intraseasonal and interannual to interdecadal and centennial. It covers the fundamental theory, statistics and numerical modelling techniques used when considering climate variability in relation to tropical cyclone activity. Major climate oscillations including the Madden-Julian, El Niño, Atlantic Meridional Mode, and Pacific Decadal oscillations are covered, and their impacts on tropical cyclone activity in the Pacific and Atlantic oceans are discussed. Hurricane landfalls in the United States, Caribbean and East Asia are also considered. Climate models and numerical simulations are used to show how prediction models of tropical cyclones are developed, while looking to the future, particular attention is paid to predicting how tropical cyclones will change in response to increased concentrations of greenhouse gases. This book ideal for researchers and practitioners in atmospheric science, climatology, oceanography and civil and environmental engineering.
Download or read book Tropical Cyclone Origin Movement and Intensity Characteristics Based on Data Compositing Techniques written by W. M. Gray and published by . This book was released on 1979 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Up-to-date results of recent tropical cyclone research at Colorado State University are presented. Particular attention is paid to new findings which impact on tropical cyclone analysis and forecasting efforts. Observational studies using large amounts of composited rawinsonde, satellite, and aircraft flight data have been performed to analyze global aspects of tropical cyclone occurrences, physical processes of tropical cyclone genesis, tropical cyclone intensity change, environmental factors influencing tropical cyclone turning motion 24-36 hours before the turn takes place, tropical cyclone intensity determination from upper tropospheric reconnaissance, and the diurnal variations of vertical motion in tropical weather systems. (Author).
Download or read book Using Downscaled Global Climate Models to Perform a Long Term Analysis of North Atlantic Tropical Cyclones and Their Impacts on Coastal Inundation to New York City written by Andra Reed and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In a changing climate, the impact of tropical cyclones on the United States Atlantic and Gulf Coasts will be affected by both how intense and how frequent these storms become. The observational record of tropical cyclones in the North Atlantic basin is too short (1851 CE present) to accurately assess long-term trends of low-frequency variability in storm activity. To overcome this limitation, I use synthetic tropical cyclone data sets for the North Atlantic basin downscaled from Coupled Model Intercomparison Project Phase 5 (CMIP5) models; driving climate conditions span 850 CE 2005 CE. Using these long-term synthetic tropical cyclone data sets, I investigate the relationship between power dissipation and ocean temperature metrics, as well as the relationship between basin-wide and landfalling tropical cyclone count statistics over the past millennium. Contrary to previous studies, I find only a very weak relationship between power dissipation and main development region sea surface temperature in the Atlantic basin. Consistent with previous studies, I find that basin-wide and landfalling tropical cyclone counts are significantly correlated with one another, lending further support for the use of paleohurricane landfall records to infer long-term basin-wide tropical cyclone trends. Additionally, I investigate the changing risk of inundation to the United States Atlantic coast, dependent upon both storm surges during tropical cyclones, and the rising sea levels on which those surges occur. Focusing our study on New York City, I compare pre-anthropogenic era (850 CE 1800 CE) and anthropogenic era (1970 CE 2005 CE) storm-surge model results, exposing links between increased rates of sea-level rise and storm flood heights. I find that mean flood heights increased by ~1.24 m at The Battery in New York City (due mainly to sea level rise) from ~AD 850 to the anthropogenic era, a result that is significant at the 99% confidence level. Additionally, changes in tropical cyclone characteristics have led to increases in the extremes of the types of storms that create the largest storm surges for New York City. As a result, flood risk has greatly increased for the region; for example, the 500 year return period for a ~2.25 m flood height during the pre-anthropogenic era has decreased to less than 25 years in the anthropogenic era. Finally, as sea levels continue to rise over the next several centuries, we expect additional risk of coastal flooding for the United States Atlantic Coast in general, and for New York City in particular, associated with storm surge events. I thus turn to an analysis of future projections of storm surge heights in New York City through the year 2300 in the context of my long-term historical analysis. Using CMIP5 model projections that extend to 2300 CE, I generate large datasets of downscaled tropical cyclones. Combining storm surge model results with several potential sea level rise scenarios for the New York City region through the year 2300, I find greatly increased risk of flooding for the metropolitan area. I show that mean flood heights are projected to increase by ~0.24 to ~0.97 meters across three CMIP5 models through the year 2100. By 2300, mean flood heights could increase by as much as ~2.85- ~4.99 meters. These results are significant at the 99% confidence level. I show that, although it is possible that shifting storm tracks could spare NYC from increases in severe storm surge heights in coming centuries, rising relative sea levels are likely to greatly increase overall flood heights, regardless of changes in TCs and their resultant storm-surge heights. Results from this research indicate the impacts of climate change on coastal inundation, and call for advanced risk management strategies in our coastal communities, especially in the New York City region.
Download or read book Prediction Enhancement Through Machine Learning of North Atlantic Tropical Cyclone Rapid Intensification written by Alexandria Danielle Grimes and published by . This book was released on 2019 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting rapid intensification (RI) of tropical cyclones (TCs) is considered one of the most challenging problems for the TC operational and research communities and remains a top priority for the National Hurricane Center. Upon landfall, these systems can have detrimental impacts to life and property. To support continued improvement of TC RI forecasts, this study investigated large-scale TC environments undergoing RI in the North Atlantic basin, specifically identifying important diagnostic variables in three-dimensional space. These results were subsequently used in the development of prognostic machine learning algorithms designed to predict RI 24 hours prior to occurrence. Using three RI definitions, this study evaluated base-state and derived meteorological parameters through S-mode and T-mode rotated principal component analysis, hierarchical compositing analysis, and hypothesis testing. Additionally, nine blended intelligence ensembles were developed using three RI definitions trained on data from the Statistical Hurricane Intensity Prediction Scheme- Rapid Intensification Index, Global Ensemble Forecast System Reforecast, and Final Operational Global Analysis. Performance metrics for the intelligence ensembles were compared against traditional linear methods. Additionally, a tenth ensemble was created using forecast data generated from Weather Research and Forecasting model simulations of TC RI events in the open North Atlantic and compared against linear methods. Results revealed modest classification ability of machine learning algorithms in predicting the onset of RI 24 hours in advance by including TC environmental spatial information of temperature and moisture variables, as well as variables indicative of ambient environmental interactions.
Download or read book Statistical dynamical Forecasting of Tropical Cyclogenesis in the North Atlantic at Intraseasonal Lead Times written by Chad S. Raynak and published by . This book was released on 2009 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: We have created a combined statistical-dynamical model to predict the probability of tropical cyclone (TC) formation at daily, 2.5°̊ horizontal resolution in the North Atlantic (NA) at intraseasonal lead times. Based on prior research and our own analyses, we chose five large scale environmental factors (LSEFs) to represent favorable environments for TC formation. The LSEFs include: 850 mb relative vorticity, sea surface temperature, vertical wind shear, Coriolis, and 200 mb divergence. We used logistic regression to create a statistical model that depicts the probability for TC formation based on these LSEFs. Through verification of zero lead hindcasts, we determined that our regression model performs better than climatology. For example, these hindcasts had a Brier skill score of 0.04 and a relative operating characteristic skill score of 0.72. We then forced our regression model with LSEF fields from the NCEP Climate Forecast System to produce non-zero lead hindcasts and forecasts. We conducted a series of case studies to evaluate and study the predictive skill of our regression model, with the results showing that our model produces promising results at intraseasonal lead times.
Download or read book Empirical statistical Downscaling written by Rasmus E. Benestad and published by World Scientific. This book was released on 2008 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical-statistical downscaling (ESD) is a method for estimating how local climatic variables are affected by large-scale climatic conditions. ESD has been applied to local climate/weather studies for years, but there are few ? if any ? textbooks on the subject. It is also anticipated that ESD will become more important and commonplace in the future, as anthropogenic global warming proceeds. Thus, a textbook on ESD will be important for next-generation climate scientists.
