Through methodology unique for tropical cyclones in peer-reviewed literature, this study explores how the dynamics of moist convection affects the predictability of tropical cyclogenesis. Mesoscale models are used to perform short-range ensemble forecasts of a non-developing disturbance in 2004 and Hurricane Humberto in 2007; both of these cases were highly unpredictable. Taking advantage of discrepancies between ensemble members in short-range ensemble forecasts, statistical correlation is used to pinpoint sources of error in forecasts of tropical cyclone formation and intensification. Despite significant differences in methodology, storm environment and development, it is found in both situations that high convective instability (CAPE) and mid-level moisture are two of the most important factors for genesis. In the gulf low, differences in CAPE are related to variance in quasi-geostrophic lift, and in Humberto the differences are related to the degree of interaction between the cyclone and a nearby front. Regardless of the source of CAPE variance, higher CAPE and mid-level moisture combine to yield more active initial convection and more numerous and strong vortical hot towers (VHTs), which incrementally contribute to a stronger vortex. In both cases, strength differences between ensemble members are further amplified by differences in convection that are related to oceanic heat fluxes. Eventually the WISHE mechanism results in even larger ensemble spread, and in the case of Humberto, uncertainty related to the time of landfall drives spread even higher. It is also shown that initial condition differences much smaller than current analysis error can ultimately control whether or not a tropical cyclone forms. Furthermore, even smaller differences govern how the initial vortex is built. Differences in maximum winds and/or vorticity vary nonlinearly with initial condition differences and depend on the timing and intensity of small mesoscale features such as VHTs and cold pools. Finally, the strong sensitivity to initial condition differences in both cases exemplifies the inherent uncertainties in hurricane intensity prediction. This study illustrates the need for implementing advanced data analysis schemes and ensemble prediction systems to provide more accurate and event-dependent probabilistic forecasts.

Paleotempestology, the study of past tropical cyclones (TCs) using geological proxy techniques, is a growing discipline that utilizes data from a broad range of sources. Most paleotempestological studies have been conducted using “established proxies”, such as grain-size analysis, loss-on-ignition, and micropaleontological indicators. More recently researchers have been applying more advanced geochemical analyses, such as X-ray fluorescence (XRF) core scanning and stable isotopic geochemistry to generate new paleotempestological records. This is presented as a four article-type thesis that investigates how changing climate conditions have impacted the frequency and paths of tropical cyclones in the western North Atlantic basin on different spatial and temporal scales. The first article (Chapter 2; Oliva et al., 2017, Prog Phys Geog) provides an in-depth and up-to-date literature review of the current state of paleotempestological studies in the western North Atlantic basin. The assumptions, strengths and limitations of paleotempestological studies are discussed. Moreover, this article discusses innovative venues for paleotempestological research that will lead to a better understanding of TC dynamics under future climate change scenarios. The second article (Chapter 3; Oliva et al., submitted, The Holocene) presents the development of the first database summarizing the most up-to-date paleotempestological proxy data available for TC reconstructions for the western North Atlantic basin. Subsets of this new database are then used to reconstruct TC variability in the western North Atlantic basin. Using our new developed subsets, we investigate a key hypothesis, the Bermuda High Hypothesis that has been proposed to have influenced TC paths over centennial to millennial timescales. Results show an oscillation in the distribution of TC landfalls along the North American coast, suggesting a centennial oscillation in the mean summer position of the high pressure system. We suggest that a more serious, millennial scale shift in the Bermuda High to a northeastern (NE position) may have occurred at ~3000 and ~1000 cal yr BP. The third article (Chapter 4; Oliva et al., under review, Marine Geology) presents a local multi-proxy reconstruction of TC activity during the past 800 years from Robinson Lake, Chezzetcook Inlet in Nova Scotia, Canada. Here, we are testing the more recent use of the XRF scanning approach to paleotempestology at a local scale. Two sediment cores were extracted from Robinson Lake that were dated by 210Pb and 14C, analyzed for organic matter content, benthic foraminifera and thecamoebians, sediment grain size, and a range of elements and elemental ratios determined by XRF core scanning. Results show two periods of low TC activity based on multiple proxies including XRF technology: one from ~1150 to 1475 CE (800 – 475 cal yr BP) and the other from 1670 CE (280 cal yr BP) to the present, with the intervening period from ~1475 to 1670 CE (475 – 280 cal yr BP) as a time of more frequent and possibly higher magnitude TC activity. The fourth article (Chapter 5. Oliva et al., in preparation, Canadian Journal of Earth Sciences) explores the potential use of stable oxygen isotopes in tree ring α-cellulose to reconstruct past local TC activity surrounding areas of known TC strikes. Cores of 12 Picea mariana trees were extracted adjacent to Robinson Lake, Chezzetcook Inlet, Nova Scotia in order to test more contemporary and historically documented records of TC activity in this region as per Chapter 4. TCs precipitate 18O-depleted rain, leaving a unique signature in the source water that trees use to form cellulose. Using an autoregressive integrated moving average (ARIMA AR-1) model to detrend the data, local and regional time series were reconstructed. Local reconstructions led to most (> 95%) hurricanes and all major hurricane (± 1 year) being recorded in the isotope record, whereas the regional reconstruction shows no major hurricane, only a few hurricanes (< 40%) and one signal with a higher error (> 1 year). This thesis contributes to advancing our knowledge in paleotempestology of the western North Atlantic basin by: 1) bringing an up-to-date current status on paleotempestology, 2) the development and ongoing use of a new paleotempestology database for the western North Atlantic basin publicly available, 3) a local scale study using new XRF core elemental technology and 4) the exploratory use of tree-ring α-cellulose oxygen isotopic analysis based on contemporary and historical documents at local sites.

The interplay between convective processes and the stabilizing effects of largescale systems remains debated, especially for warmer climates. We study sets of simulations of past and present climates in which carbon dioxide (CO2) concentrations vary over a wide range: from pre-industrial era levels of 280 ppm to an exceedingly high value of 8960 ppm. This allows us to assess the importance of convective processes relative to middle latitude thermal stratification and changes to the general circulation in progressively warmer climate states. As a tool to assess the stability of the atmosphere, we calculate a thermodynamic variable called saturation potential vorticity (P*), which has the property of being identically zero wherever lapse rates are neutral with respect to moist convection, and large where lapse rates are stable. Using P* allows us to examine convective motions arising from both gravitational accelerations as well as symmetric instabilities. We assess the ability of current models (of varying spectral resolutions) in resolving conditions unstable to slantwise convection. We show that the coarse resolution reanalysis data captures instances of observed slantwise convection. Our results show examples of vertically stable lapse rates, while being conditionally unstable along slanted angular momentum surfaces. This suggests the need for model parameterizations of convection to include instabilities arising from symmetric displacements. Tropical regions are neutral with respect to moist convection while higher latitudes most often have stable lapse rates, especially during the winter months. In the warmer climate simulations, the frequency of convectively neutral air masses increases in both middle latitude and polar regions, especially during the summer months. These simulations also show expansion of the Hadley cell and shifting of middle latitude storm tracks. Using Maximum Potential Intensity (MPI) as a tool to assess the upper bound of hurricane strength, we show sustainment of intense tropical cyclones in regions they cannot in our present climate.

No description available.

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%.

Myanmar remained largely closed to the world through political instability for several years, when it continued to suffer terribly at the hands of nature that remained largely unknown. Of note is the period between 2008 and 2013, during which the country suffered at least eight major natural calamities that killed more than 141,000 people and affected 3.2 million. The worst of these was Cyclone Nargis in May 2008 that killed more than 130,000. With an estimated $4 billion in damages, Nargis remains the deadliest and most destructive named cyclone ever to have occurred in the North Indian Ocean. Recent studies have shown that, due to increased greenhouse gases and aerosol loading in the atmosphere, more and stronger tropical cyclones (TCs) in the last three decades are tracking eastwards toward the Indochina peninsula. Unfortunately, the Burmese lack the capacity to deal with the impacts of such storms. Myanmar was left behind as the world made significant technological and industrial advancement; but agriculture, which employs at least 65% of the active labor force, has remained the backbone of the Myanmar economy – an industry that is heavily reliant on monsoon rainfall. The pre-monsoon TC season in the Bay of Bengal (BoB) precedes the onset of the Myanmar monsoon but sometimes the two (i.e.TC formation and the monsoon onset) occur in unison. This work studied the mechanism by which the Madden Julian Oscillation (MJO) modulates the Myanmar monsoon onset and TC activity collectively (i.e. ISO-Onset-TC connection). Avoiding TC destruction at the beginning of the planting season is crucial, so is the monsoon onset date critical for planning. Additional understanding of the aforementioned ISO-Onset-TC connection could provide further insight into predicting the Myanmar monsoon onset and aid in disaster planning for TC impact. This research is part of a two-year NASA funded project to study extreme climate and weather events.

Estuaries are dynamic on many spatial and temporal scales. Distinguishing effects of unpredictable events from cyclical patterns can be challenging but important to predict the influence of press and pulse drivers in the face of climate change. Diatom assemblages respond rapidly to changing environmental conditions and characterize change on multiple time scales. The goals of this research were to 1) characterize diatom assemblages in the Charlotte Harbor watershed, their relationships with water quality parameters, and how they change in response to climate; and 2) use assemblages in sediment cores to interpret past climate changes and tropical cyclone activity. Diatom assemblages had strong relationships with salinity and nutrient concentrations, and a quantitative tool was developed to reconstruct past values of these parameters. Assemblages were stable between the wet and dry seasons, and were more similar to each other than to assemblages found following a tropical cyclone. Diatom assemblages following the storm showed a decrease in dispersion among sites, a pattern that was consistent on different spatial scales but may depend on hydrological management regimes. Analysis of sediment cores from two southwest Florida estuaries showed that locally-developed diatom inference models can be applied with caution on regional scales. Large-scale climate changes were suggested by environmental reconstructions in both estuaries, but with slightly different temporal pacing. Estimates of salinity and nutrient concentrations suggested that major hydrological patterns changed at approximately 5.5 and 3 kyrs BP. A highly temporally-resolved sediment core from Charlotte Harbor provided evidence for past changes that correspond with known climate records. Diatom assemblages had significant relationships with the three-year average index values of the Atlantic Multidecadal Oscillation and the El Niño Southern Oscillation. Assemblages that predicted low salinity and high total phosphorus also had the lowest dispersion and corresponded with some major storms in the known record, which together may provide a proxy for evidence of severe storms in the paleoecological record.

An analysis to determine physical and spatial patterns of the surface latent heat flux (LHF) and near surface (5m) salinity (NSS) beneath tropical cyclones (TCs) in the North Atlantic and eastern North Pacific basins during the first 24 hours of rapid intensification (RI) was conducted using empirical orthogonal function (EOF) analysis. To determine if these patterns were unique to RI, TC RI cases were compared to three non-RI intensification thresholds, 10 kt, 15 kt and 20 kt, for both LHF and NSS. Though similarities exist between non-RI and RI cases physical and spatial patterns unique to the RI cases did exist. Sea surface temperatures associated with statistically identified TC groups were assessed for their potential influence on RI. While inconclusive in the eastern North Pacific, NSS in the Atlantic may play a role for RI TCs in areas affected by river discharge from South America.

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.

Thesis (MEng (Civil Engineering))--University of Stellenbosch, 1999. / 100 leaves single printed pages, preliminary pages and numberd pages 1.1-9.1.Includes bibliography. List of figures, tables, symbols and acronyms. Scanned with a HP Scanjet 8250 Scanner to pdf format (OCR). / ENGLISH ABSTRACT: A tropical cyclone is a non-frontal, synoptic scale, low-pressure system over tropical or subtropical waters with organised convection and a definite cyclonic surface wind circulation. The system varies in size between a hundred and a few thousand kilometres in diameter with high winds circulating around a central low pressure. The process of bringing the lower atmospheric layers into thermodynamic equilibrium with the warm tropical waters add the energy to the atmosphere and lower the surface pressure. If favourable climatic conditions exist this leads to the formation of a warm core vortex, which can develop into a tropical cyclone. The occurrence of tropical cyclones follows seasonal variations, the tropical cyclone season for the Southwest Indian Ocean being between November and March. The occurrences peak along the Southern African East Coast between Mid-January and Mid-February. The data on the location and intensity of tropical cyclones along the Southeast Africa coastline were obtained from the Joint Typhoon Warning Centre and span the period between 1848 and 1999. The available data before 1945 consist of tropical cyclone tracks that influenced populated areas or were encountered by ships. It was assumed that a number of tropical cyclones before 1945 were not recorded and therefore data collected before 1945 were disregarded in the analysis. The development of radar in 1945 significantly improved the detection of tropical cyclones. Some of the tropical cyclone tracks recorded between 1945 and 1956 contain information about the intensity of the tropical cyclone. Since the dawn of the satellite age in the mid 1980's, the detection of tropical cyclones and intensity measurements have improved vastly. Monte Carlo simulation techniques were used to create long term data series based on the available measured data. Statistical distributions were fitted for each characteristic describing the tropical cyclone at its nearest position to the site under investigation. Tropical cyclones frequently occur along the Southern African East Coast. The region where more than one tropical cyclone per 100 years can be expected is bordered by latitudes 2.5°S to 32.5°S. The design parameters for structures in these regions should provide for the influence that a tropical cyclone will have on the site. The occurrence rate and expected maximum intensity of tropical cyclones with a 1DO-year return period vary with latitude along the Southern African East Coast. The maximum number of tropical cyclones in a 1DO-year period occurs at latitude 15°S with an expected number of tropical cyclones of 157.2 per 100 years. The maximum expected tropical cyclone intensity in a 100-year period is 143.5 knots at latitude 17.5°S. / AFRIKAANSE OPSOMMING: Tropiese siklone is nie-frontale laagdrukstelsels wat hulle ontstaan het oor tropiese en subtropiese oseane. 'n Stelsel bestaan uit 'n sentrale laagdrukstelsel met sirkulerende winde daar om. 'n Sikloon se deursnee kan wissel van 'n honderd tot 'n paar duisend kilometer. 'n Laagdrukstelsel ontstaan as gevolg van 'n termodinamiese wanbalans tussen die atmosfeer en die warm oseaanwater in die trope. Indien die benodigde atmosferiese toestande heers kan die laagdrukstelsel in 'n tropiese sikloon ontwikkel. In die Suidwestelike Indiese Oseaan vorm tropiese siklone tussen November en Maart. Die meeste siklone kom hier voor vanaf middel Januarie tot middel Februarie. Data is verkry vanaf die "Joint Typhoon Warning Centre" vir die Suidwestelike Indiese Oseaan en strek vanaf 1848 tot 1999. Die data voor 1945 verteenwoordig slegs die tropiese siklone wat bewoonde areas of skeepsvaart beinvloed het. Daar is aangeneem dat 'n betekenisvolle getal van die tropiese siklone voor 1945 nie gedokumenteer is nie en derhalwe is slegs data van sikloon voorkomste na 1945 gebruik in die studie. Vanaf 1945 het die ontwikkeling van radar die opsporing van siklone in onbewoonde areas moontlik gemaak. Die gebruik van weersatelliete vanaf die middel 1980's het die kwaliteit van die data nog verder verbeter. Monte Carlo simulasie tegnieke is gebruik om langtermyn data vir spesifieke posisies langs die kus te genereer. Statistiese verdelings is gepas op die eienskappe wat die sikloon beskryf wanneer dit die naaste posisie aan die terrein bereik. Die passing van die verdelings is gedoen op die beskikbare historiese data. Die verdelings is dan gebruik om langtermyn data stelle te skep vir die terrein. Tropiese siklone kom gereeld in die Suidwestelike Indiese Oseaan voor en beinvloed die Suid-Afrikaanse Ooskus. Meer as een tropiese sikloon kan elke 100 jaar verwag word in kusgebiede tussen breedtegrade 2.5° S en 32.5° S. Die ontwerpe vir strukture in die gebied moet dus voorsiening maak vir die invloed van tropiese siklone. Die voorkoms en intensiteit van tropiese siklone varieer met breedtegraad langs die Suid-Afrikaanse Ooskus. Die meeste siklone word verwag by breedtegraad 15°S met 'n gemiddelde van 157.2 siklone per 100 jaar. Die mees intensiewe siklone kom voor by breedtegraad 17.5°S met 'n verwagte 1:100 jaar intensiteit van 143.5 knope.