Abstract not available

Tropical cyclones are among the most devastating natural disasters for human beings and the natural and manmade assets near to Atlantic basin. Estimating the current and future intensity of these powerful storms is crucial to protect life and property. Many methods and models exist for predicting the evolution of Atlantic basin cyclones, including numerical weather prediction models that simulate the dynamics of the atmosphere which require accurate measurements of the current state of the atmosphere (NHC, 2019). Often these models fail to capture dangerous aspects of storm evolution, such as rapid intensification (RI), in which a storm undergoes a steep increase in intensity over a short time. To improve prediction of these events, scientists have turned to statistical models to predict current and future intensity using readily collected satellite image data (Pradhan, 2018). However, even the current-intensity prediction models have shown limited success in generalizing to unseen data, a result we confirm in this study. Therefore, building models for the estimating the current and future intensity of hurricanes is valuable and challenging. In this study we focus on to estimating cyclone intensity using Geostationary Operational Environmental Satellite images. These images represent five spectral bands covering the visible and infrared spectrum. We have built and compared various types of deep neural models, including convolutional networks based on long short term memory models and convolutional regression models that have been trained to predict the intensity, as measured by maximum sustained wind speed. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

The spatial and temporal complexity of tropical cyclones (TCs) raises a number of scientific questions regarding their genesis, movement, intensification, and variability. In this dissertation, the principal goal is to determine the current state of predictability for each of these processes. To quantify the current extent of tropical cyclone predictability, we assess probabilistic forecasts from the most advanced global numerical weather prediction system to date, the ECMWF Variable Resolution Ensemble Prediction System (VarEPS). Using a new false alarm clustering technique to maximize the utility of the VarEPS, the ensemble system is shown to provide well-calibrated probabilistic forecasts for TC genesis through a lead-time of one week, and pregenesis track forecasts with similar skill compared to the VarEPS's postgenesis track forecasts. To quantify the predictability of TCs on intraseasonal time scales, forecasts from the ECMWF Monthly Forecast System (ECMFS) are examined for the North Atlantic Ocean. From this assessment, dynamically based forecasts from the ECMFS provide forecast skill exceeding climatology out to weeks three and four for portions of the southern Gulf of Mexico, western Caribbean and the Main Development Region. Forecast skill in these regions is traced to the model's ability to capture correctly the variability in deep-layer vertical wind shear, the relative frequency of easterly waves moving through these regions, and the intraseasonal modulation of the Madden-Julian Oscillation. On interannual time scales, the predictability of TCs is examined by considering their relationship with tropical Atlantic easterly waves. First, a set of easterly wave climatologies for the CFS-R, ERA-Interim, ERA-40, and NCEP/NCAR Reanalysis are developed using a new easterly wave-tracking algorithm. From the reanalysis-derived climatologies, a moderately positive and statistically significant relationship is seen with tropical Atlantic TCs. In relation to large-scale climate modes, the Atlantic Multidecadal Oscillation (AMO) and Atlantic Meridional Mode (AMM) exhibit the strongest positive covariability with Atlantic easterly wave frequency. Besides changes in the number of easterly waves, the intensification efficiency of easterly waves has also been evaluated. These findings offer a plausible physical explanation for the recent increase in the number of NATL TCs, as it has been concomitant with an increasing trend in both the number of tropical Atlantic easterly waves and intensification efficiency. The last component of this dissertation examines how the historical variability in U.S. landfalling TCs has impacted the annual TC tornado record. To reconcile the inhomogeneous, historical tornado record, two statistical tornado models, developed from a set of a priori predictors for TC tornado formation, are used to reconstruct the TC tornado climatology. While the synthetic TC tornado record reflects decadal scale variations in association with the AMO, a comparison of the current warm phase of the AMO with the previous warm phase period shows that the median number of tornadoes per Gulf TC landfall has significantly increased. This change likely reflects the increase in median TC size (by 35%) of Gulf landfalling TCs along with an increased frequency of large TCs at landfall.

Towards advancing the indices of hurricane energetics that are associated with potential damage, we develop a new methodology for calculating integrated kinetic energy (IKE) climatology. A simple, observation and dynamical - based radial wind speed model is used with the Extended Best Track Data Set to calculate IKE for North Atlantic Hurricanes from 1988 to 2008. The method is evaluated against previous methods of tropical cyclone intensity analysis, and the results are compared to traditional indices in terms of characterizing storm energetics and relating to storm surge. It is shown that the traditional indices are inaccurate measurements of hurricane energetics, and the assumptions that they are based on are not valid. Furthermore, in analyzing storm surge, it is possible that tropical cyclone damage is more strongly correlated with IKE rather than maximum wind speed.

Thesis (MScEng)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Tropical cyclones are synoptic scale rotating storms capable of generating intense wind speeds and rainfall with potentially devastating social and economic consequences. In addition to abnormally high winds and rainfall, the associated storm surge and extreme waves can lead to severe coastal erosion, damage to coastal property and inundation. A good understanding of the risk exposure to these events is therefore of great importance to planners and designers of coastal infrastructure in vulnerable regions. Probabilistic approaches have been routinely adopted for the calculation of extreme tropical cyclone induced wind speeds, with significant developments in these techniques over the last few decades. While the application of these approaches has become widely adopted in regions such as the North Atlantic, North Pacific and South Pacific Oceans, relatively little attention has been paid to the South-West Indian Ocean. This thesis focusses on the quantification of the risk exposure to tropical cyclones over the South-West Indian Ocean, using current state-of-the-art techniques. The primary results of the thesis are extreme wind speed maps at various return periods of interest for engineering design. Best track data for the South-West Indian Ocean, as archived by the Joint Typhoon Warning Centre (JTWC), has been used as the primary dataset forming the basis of this study. These data provide estimates of the location and intensity of historical tropical cyclones at six hourly intervals. Location data are provided as estimates of longitude and latitude of the eye, while intensity data are provided as estimates of the maximum sustained surface (10 m elevation) wind speed and/or minimum central pressure. The modelling of tropical cyclone wind fields has been carried out using both the Holland (1980) and the Willoughby et al. (2006) parametric wind field models. Using the limited information available in the best track data as input to the model, surface wind fields which reasonably resemble those of actual storms have been generated. Both considered parametric wind field models have been shown to yield reasonable wind speeds and directions when compared with measurements. Of the two considered models the Willoughby et al. (2006) model has been shown to provide the best fit to historical wind speed measurements. Extreme value analyses of tropical cyclone induced wind speeds based on historical data alone have been shown to lead to potentially large errors, owing to the small sample size of the historical data. This highlights the need to augment the historical database through a probabilistic approach. Largely following the methods described in Powel et al. (2005) and Emanuel et al. (2006), a synthetic track model for the South-West Indian Ocean has been developed. The objective of the synthetic track model is to simulate thousands of years of tropical cyclone tracks, thereby circumventing errors induced by small sample sizes in the available historical best track data. The synthetic track model developed as part of this study is a Markov chain model, capable of simulating track propagation and intensity evolution along the track, from track genesis through to termination. The model is purely statistical, based on properties derived from the historical best track data. Adjustments have however been made to account for physical limitations such as those imposed by the equator and the maximum potential intensity which an event can attain. The statistical characteristics of synthetic tracks have been shown to agree well with those of the historical population. Applying the Willoughby et al. (2006) wind field model along synthetic tracks has enabled the simulation of 5 000 years of tropical cyclone induced wind speeds at any location of interest in the South-West Indian Ocean. Applying calculations on a 1 degree geographical grid, wind speed maps corresponding to return periods of 50, 100, 200 and 500 years have been generated for the South-West Indian Ocean. Extreme wind speeds along coastal regions provide valuable input for the design of coastal infrastructure in the region. / AFRIKAANSE OPSOMMING: Tropiese siklone is sinoptiese orde roterende storms wat in staat is om aansienlike windspoed en reënval, tot gevolg te hê met potensiële vernietigende sosiale en ekonomiese gevolge. Benewens die abnormale sterk winde en hoë reënval kan die verwante stormdeinings en vloedgolwe lei tot ernstige kus-erosie, skade aan kusfront-eiendom en oorstromings. ‘n Goeie begrip van die risiko-blootstelling aan hierdie gebeurtenisse is daarom van groot belang vir die beplanners en ontwerpers van kus-infrastruktuur in kwesbare gebiede. As gevolg van die beduidende ontwikkeling van probabilistiese benadering tot die berekening van windspoed wat veroorsaak word deur ekstreme tropiese siklone, word hierdie tegnieke huidiglike op ‘n roetine basis aangewend. Terwyl die toepassing van hierdie benaderings wyd aanvaar word in gebiede soos die Noord-Atlantiese, Noordelike- en Suidelike Stille Oseaan, word relatief min aandag gegee aan die Suid-Westelike Indiese Oseaan. Hierdie tesis fokus op die kwantifisering van die risiko-blootstelling aan tropiese siklone in die Suid-Westelike Indiese Oseaan met die gebruik van die huidige gevorderdste tegnieke. Die primêre resultaat van die tesis is uiterste wind spoed kaarte vir ‘n verskeindenheid herhaal periodes wat van belang in vir engenieursontwerp. Beste roete-ata vir die Suid-Westelike Indiese Oseaan, soos voorsien deur die Gesametlike Tifoon Waarskuwing Sentrum (JTWC), is gebruik as die primêre data stel wat die basis vorm van hierdie studie. Hierdie data gee die beste skattings van die ligging (lengte- en breedtegraad), en intensiteit (maksimum volgehoue oppervlak (10m hoogte) wind spoed en/of sentrale druk tekort) van historiese tropiese siklone teen ses-uurlikse intervalle. Die modelering van tropiese sikloon windvelde was uitgevoer met die gebruik van die Holland (1980) en die Willoughby et al. (2006) parametriese windveldmodelle. Met die gebruik van beperkte inligting wat beskikbaar is in die beste roete data as invoer vir die model, was oppervlak wind velde gegenereer wat ‘n billike ooreenstemming het met die van werklike storms. Beide tegnieke se parametriese windveldmodelle is al bewys om redelike akkurate windspoed en windrigtings te lewer in vergelyking met waargenome waardes. Van die twee modelle het die Willoughby et al. (2006) model se resultate die beste ooreenstemming gewys met historiese wind spoed metings. Dit is al uitgewys dat uiterste waarde-analises van tropiese sikloon veroorsaakte windspoed moontlik kan lei tot groot foute in die resultate as gevolg van die klein monster-grootte van die historiese data. Dit beklemtoon die noodsaaklikheid om die historiese databasis aan te vul met behulp van probabilistiese metodes. Die metodes soos beskryf deur Powel et al. (2005) en Emanuel et al. (2006) is hoofsaaklik gebruik om ‘n sintetiese roete-model vir die Suid-Westelike Oseaan te ontwikkel. Die doelwit van die sintetiese roete model is om duisende jare se tropiese sikloonroetes te produseer, en in effek foute te vermy as gevolg van die gebruik van klein monster groottes van die beskikbare historiese beste roete data. Die sintetiese roete model wat tydens hierdie studie ontwikkel is, is ‘n Markov kettingmodel wat in staat is om die roete verspreiding asook die evolusie van intensiteit saam die roete te simuleer vanaf die onstaan tot die beëindiging van die sikloon se roete. Die model is suiwer statisties en is gebasseer op die eienskappe soos afgelei vanaf die historiese beste roete data. Aanpassings is gemaak om rekening te hou van die fisiese beperkings soos die wat opgelê word deur die ewenaar en die maksimum potensiële intensiteit wat ‘n sikloon kan bereik. Dit is voorgelê dat die statistiese einskappe van die sintetiese roetes goed saamstem met die van die historiese populasie. Die toepassing van die Willoughby et al. (2006) wind veld model langs die sintetiese roetes het dit moontlik gemaak om 5000 jaar se windspoed, wat veroorsaak is deur tropiese siklone, te genereer by enige ligging wat van belang is in die Suid-Westelike Indiese Oseaan. Met berekeninge wat op ‘n 1 grade geografiese ruitnet gedoen is, is windspoedkaarte vir herhaal periodes van 50, 100, 200 en 500 jaar opgestel vir die Suid-Westelike Indiese Oseaan. Die uiterste wind spoed in kusgebiede gee waardevolle invoer vir die ontwerp van kus-infrastruktuur in die omgewing.

This dissertation will specifically address the issue of improving the quality of satellite scatterometer retrieved ocean surface vector winds (OVW), especially in the presence of strong rain associated with tropical cyclones. A novel active/passive OVW retrieval algorithm is developed that corrects Ku-band scatterometer measurements for rain effects and then uses them to retrieve accurate OVW. The rain correction procedure makes use of independent information available from collocated multi-frequency passive microwave observations provided by a companion sensor and also from simultaneous C-band scatterometer measurements. The synergy of these active and passive measurements enables improved correction for rain effects, which enhances the utility of Ku-band scatterometer measurements in extreme wind events. The OVW retrieval algorithm is based on the next generation instrument conceptual design for future US scatterometers, i.e. the Dual Frequency Scatterometer (DFS) developed by NASA’s Jet Propulsion Laboratory. Under this dissertation research, an end-to-end computer simulation was developed to evaluate the performance of this active/passive technique for retrieving hurricane force winds in the presence of intense rain. High-resolution hurricane wind and precipitation fields were simulated for several scenes of Hurricane Isabel in 2003 using the Weather Research and Forecasting (WRF) Model. Using these numerical weather model environmental fields, active/passive measurements were simulated for instruments proposed for the Global Change Observation Mission- Water Cycle (GCOM-W2) satellite series planned by the Japanese Aerospace Exploration Agency. Further, the quality of the simulation was evaluated using actual hurricane measurements from the Advanced Microwave Scanning Radiometer and iv SeaWinds scatterometer onboard the Advanced Earth Observing Satellite-II (ADEOS-II). The analysis of these satellite data provided confidence in the capability of the simulation to generate realistic active/passive measurements at the top of the atmosphere. Results are very encouraging, and they show that the new algorithm can retrieve accurate ocean surface wind speeds in realistic hurricane conditions using the rain corrected Ku-band scatterometer measurements. They demonstrate the potential to improve wind measurements in extreme wind events for future wind scatterometry missions such as the proposed GCOM-W2.

Indiana University-Purdue University Indianapolis (IUPUI)