Meteorology Commons^™

The Impact Of Sea-Level Rise In Numerically Modeled Landfalling Hurricanes: Katrina And The Gulf Coast., Serenity Nadirah Mercuri

Electronic Theses and Dissertations

With climate change, landfalling hurricanes become an increasing threat to coastal regions. However, the interactions between the coastal landscape and landfalling hurricanes are often overlooked when addressing sea-level rise outside of inundation and independent of sea surface temperature. This study analyzed the potential impacts regarding structure and intensity as a result of sea-level rise in the Gulf of Mexico using the WRF-ARW numerical model coupled with a 1D ocean model. Analysis showed that 10 m windspeed from landfall forward was higher in modified coastlines, and minimum sea-level pressure post-landfall was consistently lower for modified runs where storms maintain a higher …

High-Resolution Downscaling And Bias-Correction Of Temperature And Precipitation: Advances In Statistical Methods, Maike Holthuijzen

Graduate College Dissertations and Theses

High-resolution, bias-corrected climate data is necessary for climate impact studies and modeling efforts at local scales. General circulation models (GCMs) provide important information about historical and future larger-scale climate trends, but their spatial resolution is too coarse to investigate localized effects of climate processes. Additionally, raw GCM output is characterized by some degree of bias. Two post-processing procedures known as downscaling and bias-correction are typically applied to raw climate model output prior to its use in further modeling applications. Downscaling is the process in which data at a coarse spatial scale is transformed to a fine spatial scale. Bias-correction refers …

Adaptive Monte Carlo Sampling For Cloud And Microphysics Calculations, Thomas Franz-Peter Roessler

Theses and Dissertations

An important problem in large-scale modeling of the atmosphere is the parametrization of clouds and microphysics on subgrid scales. The framework Cloud Layers Unified By Binormals (CLUBB) was developed to improve the parametrization of subgrid variability. Monte Carlo sampling is used to couple the different physical processes, which improves the grid average of subgrid tendencies.

In this Thesis we develop an adaptive Monte Carlo sampling algorithm that re-uses sample points of the previous time step by re-weighting them according to the change of the underlying distribution. This process is called 'what-if sampling' and is an application of importance sampling. An …

Using A Semiprognostic Test To Elucidate Key Model Errors Of Warm Rain Processes Within A Unified Parameterization Of Clouds And Turbulence, Justin Kyle Weber

Theses and Dissertations

The representation of clouds and turbulence remains one of the foremost challenges in modeling earth's climate system and continues to remain one of the greatest sources of uncertainty in future climate projections. Increased attention has been given to unifying cloud and turbulence parameterizations in order to avoid the artificial categorization of cloud and turbulence regimes. One such unified parameterization is known as the Cloud Layers Unified by Binormals (CLUBB). CLUBB is a single column model of clouds and turbulence that assumes subgrid scale variability can be represented by a joint probability density function (PDF) of temperature, moisture, momentum, and hydrometeors. …

The Simulation & Evaluation Of Surge Hazard Using A Response Surface Method In The New York Bight, Michael H. Bredesen

UNF Graduate Theses and Dissertations

Atmospheric features, such as tropical cyclones, act as a driving mechanism for many of the major hazards affecting coastal areas around the world. Accurate and efficient quantification of tropical cyclone surge hazard is essential to the development of resilient coastal communities, particularly given continued sea level trend concerns. Recent major tropical cyclones that have impacted the northeastern portion of the United States have resulted in devastating flooding in New York City, the most densely populated city in the US. As a part of national effort to re-evaluate coastal inundation hazards, the Federal Emergency Management Agency used the Joint Probability Method …

A Crowdsourced Hail Dataset: Potential, Biases, And Inaccuracies, Joseph Robert Pehoski

Theses and Dissertations

Hail is a substantial severe weather hazard in the USA, with significant damage to property and

crops occurring annually. Traditional methods of forecasting hail size have limited accuracy, and despite

improvements in remote sensing of precipitation, the fall characteristics of hail make quantification of

hail imprecise. Research into hail is ongoing, but traditional hail datasets have known biases and low

spatiotemporal resolution. The increased usage of smartphones creates the opportunity to use a

crowdsourced dataset provided by the Precipitation Identification Near the Ground (PING) program, a

program developed by the National Severe Storms Laboratory. PING data is compared to approximate …