During July 2005, Typhoon Banyan recurved and underwent tropical transition over the western North Pacific. Coincident with the extratropical transition of Banyan, a large mid-tropospheric anticyclone developed immediately east of the recurving typhoon. The anticyclone was associated with a high-amplitude Rossby wave-like pattern that developed downstream of the anticyclone and extended across the North Pacific. Development of the anticyclone is examined with respect of the interaction between the outflow from Banyan and the midlatitude jet streak. During the poleward movement of TY Banyan, an anticyclonically-curved jet streak was forced by the merger of the upper-level outflow from Banyan and a jet streak associated with an upstream trough. The anticyclonic curvature was accentuated by the presence of a mid-tropospheric cyclone east of Banyan. The anticyclonic curvature increased as Banyan moved poleward and the mid-tropospheric cyclone moved equatorward. Thermodynamic forcing of the mid-tropospheric anticyclone is examined with respect to the poleward movement of warm moist air that ascends as it is advected around the eastern side of the decaying typhoon. The combination of dynamic and thermodynamic factors is examined in a potential vorticity framework to identify the development of the anticyclone east of Banyan and the transformation of Banyan into a midlatitude cyclone.

CIVINS / The understanding of large and rare waves in the ocean is becoming more important as these rare events are turning into more common observances. In order to design a marine structure or vehicle to withstand such a potentially devastating phenomenon, the designer must have knowledge of extreme waves with return periods of 50 and 100 years. Based on satellite radar altimeter data, researchers have successfully predicted extreme significant wave heights with the return periods of 50 and 100 years. This thesis extends their research further by estimating the most probable extreme wave heights and other wave statistics based on spectral analysis. The same technique used for extreme significant wave height prediction is applied to extrapolation of corresponding mean wave periods, and they are used to construct two parameter spectra representing storm sea conditions. The prediction of the most probable extreme wave heights as well as other statistical data is based on linear theory and short term order statistics. There exists sufficient knowledge of second order effects on wave generation, and it could be applied to a logical progression of the simulation approach in this thesis. However, because this greatly increases computation time, and the kinematics of deep sea spilling breakers are not yet fully understood for which substantial new research is required, the nonlinear effects are not included in this thesis. Spectral analysis can provide valuable statistical information in addition to extreme wave height data, and preliminary results show good agreement with other prediction methods including wave simulation based on the Pierson-Moskowitz spectrum. / Contract number: N662271-97-G-0025 / CIVINS / US Navy (USN) author

Ahvaz, Iran ranks as the most polluted city of the world in terms of PM10 concentrations that lead to deleterious effects on its inhabitants. This study examines diurnal, weekly, monthly and annual fluctuations of PM10 between 2009 and 2014 in Ahvaz. Health effects of PM10 levels are also assessed using the World Health Organization AirQ software. Over the study period, the mean PM10 level in Ahvaz was 249.5 mu g m(-3), with maximum and minimum values in July (420.5 mu g m(-3)) and January (154.6 mu g m(-3)), respectively. The cumulative diurnal PM10 profile exhibits a dominant peak between 08:00-11:00 (local time) with the lowest levels in the afternoon hours. While weekend PM10 levels are not significantly reduced as compared to weekdays, an anthropogenic signature is instead observed diurnally on weekdays, which exhibit higher PM10 levels between 07:00-17:00 by an average amount of 14.2 mu g m(-3) as compared to weekend days. PMio has shown a steady mean-annual decline between 2009 (315.2 mu g m(-3)) and 2014 (143.5 mu g m(-3)). The AirQ model predicts that mortality was a health outcome for a total of 3777 individuals between 2009 and 2014 (i.e., 630 per year). The results of this study motivate more aggressive strategies in Ahvaz and similarly polluted desert cities to reduce the health effects of the enormous ambient aerosol concentrations. (C) 2016 Elsevier B.V. All rights reserved.

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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.

As climate change impacts a growing number of aspects of economic activity, it is becoming ever more vital to understand how these effects will manifest. This work advances the study of the impacts of environmental change. First, I provide a panel analysis at the country level that identifies the effects of dust storms on economic activity in West Africa. I also find some evidence in the agricultural sector to support the finding of damaging effects. Second, I examine the extent to which dust storms and climate shocks affect migration in the same region. While temperatures and precipitation are found to play important roles, dust storms do not appear to have a significant influence. Third, I consider the role of adaptation to climate change in the United States. I build a model that predicts the locations most likely to be used in agriculture in the future, allowing for better forecasting of shifts in the areas used for agricultural production.

Severe weather events that accompany climatic changes have been the main focus of many studies that want to highlight the large processes that surround us every day. These studies are based on years of data collection and other studies to help aid their pursuits. An area of major focus is identifying proxies and supplementary materials that help refine climate records of the geologic past. This study aims to identify reliable proxies for obtaining a record of severe weather events. The research consists of studying a coral species Pseudodiploria strigosa colonies with the goal to document, interpret, and describe the burial and re-exposure of massive coral colonies by severe storm or hurricane events, as recorded in coral growth patterns through density patterns and the analysis of CT-scanned coral specimens. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

Rainfall data are usually gathered at daily timescales due to the availability of daily rain-gauges throughout the world. However, rainfall data at fine timescale are required for certain hydrologic modellings such as crop simulation modelling, erosion modelling etc. Limited availability of such data leads to the option of daily rainfall disaggregation. This research investigates the use of a stochastic rainfall disaggregation model on a regional basis to disaggregate daily rainfall into any desired fine timescale in the State of Queensland, Australia. With the incorporation of seasonality into the variance relationship and capping of the fine timescale maximum intensities, the model was found to be a useful tool for disaggregating daily rainfall in the regions of Queensland. The degree of model complexity in terms of binary chain parameter calibration was also reduced by using only three parameters for Queensland. The resulting rainfall Intensity-Frequency-Duration (IFD) curves better predicted the intensities at fine timescale durations compared with the existing Australian Rainfall and Runoff (ARR) approach. The model has also been linked to the SILO Data Drill synthetic data to disaggregate daily rainfall at sites where limited or no fine timescale observed data are available. This research has analysed the fine timescale rainfall properties at various sites in Queensland and established sufficient confidence in using the model for Queensland.

In this study, it is hypothesized that the mesoscale environment can indirectly control the cloud-to-ground (CG) lightning polarity of severe storms by directly affecting their structural, dynamical, and microphysical properties, which in turn directly control cloud electrification and CG flash polarity. A more specific hypothesis, which has been supported by past observational and laboratory charging studies, suggests that broad, strong updrafts and associated large liquid water contents in severe storms lead to enhanced positive charging of graupel and hail via the noninductive charging mechanism, the generation of an inverted charge structure, and increased positive CG lightning production. The corollary is that environmental conditions favoring these kinematic and microphysical characteristics should support severe storms generating an anomalously high (> 25%) percentage of positive CG lightning (i.e., positive storms), while environmental conditions relatively less favorable should sustain storms characterized by a typical (≤ 25%) percentage of positive CG lightning (i.e., negative storms). Forty-eight inflow proximity soundings were analyzed to characterize the environments of nine distinct mesoscale regions of severe storms (four positive and five negative) on six days during May – June 2002 over the central United States. This analysis clearly demonstrated significant and systematic differences in the mesoscale environments of positive and negative storms, which were consistent with the stated hypothesis. When compared to negative storms, positive storms occurred in environments associated with a drier low to midtroposphere, higher cloud base height, smaller warm cloud depth, stronger conditional instability, larger 0-3 km AGL wind shear, stronger 0-2 km AGL storm-relative wind speed, and larger buoyancy in the mixed-phase zone, at a statistically significant level. Differences in the warm cloud depth of positive and negative storms were by far the most dramatic, suggesting an important role for this parameter in controlling CG lightning polarity. Subjective visual inspection of radar imagery revealed no strong relationship between convective mode and CG lightning polarity, and also illustrated that positive and negative severe storms can be equally intense.

In this study, it is hypothesized that the mesoscale environment can indirectly control the cloud-to-ground (CG) lightning polarity of severe storms by directly affecting their structural, dynamical, and microphysical properties, which in turn directly control cloud electrification and CG flash polarity. A more specific hypothesis, which has been supported by past observational and laboratory charging studies, suggests that broad, strong updrafts and associated large liquid water contents in severe storms lead to enhanced positive charging of graupel and hail via the noninductive charging mechanism, the generation of an inverted charge structure, and increased positive CG lightning production. The corollary is that environmental conditions favoring these kinematic and microphysical characteristics should support severe storms generating an anomalously high (> 25%) percentage of positive CG lightning (i.e., positive storms), while environmental conditions relatively less favorable should sustain storms characterized by a typical (≤ 25%) percentage of positive CG lightning (i.e., negative storms). Forty-eight inflow proximity soundings were analyzed to characterize the environments of nine distinct mesoscale regions of severe storms (four positive and five negative) on six days during May - June 2002 over the central United States. This analysis clearly demonstrated significant and systematic differences in the mesoscale environments of positive and negative storms, which were consistent with the stated hypothesis. When compared to negative storms, positive storms occurred in environments associated with a drier low to midtroposphere, higher cloud base height, smaller warm cloud depth, stronger conditional instability, larger 0-3 km AGL wind shear, stronger 0-2 km AGL storm-relative wind speed, and larger buoyancy in the mixed-phase zone, at a statistically significant level. Differences in the warm cloud depth of positive and negative storms were by far the most dramatic, suggesting an important role for this parameter in controlling CG lightning polarity. Subjective visual inspection of radar imagery revealed no strong relationship between convective mode and CG lightning polarity, and also illustrated that positive and negative severe storms can be equally intense.