Meteorology Commons^™

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 …

The Influence Of Assimilated Targeted Observations Upon Ensemble Forecasts Of Convection Initiation, Alexandra Marie Keclik

Theses and Dissertations

The influence of assimilating targeted meso-α- to synoptic-scale observations collected in the upstream, pre-convective environment upon subsequent short-range ensemble forecasts of convection initiation (CI) across the central United States for the fifteen aircraft missions conducted by the Mesoscale Predictability Experiment (MPEX) in May and June 2013 is evaluated in this study. Utilizing the ensemble Kalman filter implementation within the Data Assimilation Research Testbed software package as coupled to version 3.4.1 of the Advanced Research version of the Weather Research and Forecasting model, two nearly-identical thirty- member ensembles of short-range forecasts are conducted for each mission. Initial conditions for one ensemble …

Predictability Of Sea Ice Near Bifurcations, Dawn Marie Kopacz

Theses and Dissertations

There is evidence in Earth’s history of relatively stable climate regimes abruptly transitioning to alternative states. It has been argued that the greatest potential for such abrupt transitions in Earth’s system in the near future is located in the Arctic. Here we analyze the Arctic sea ice evolution of two current generation climate models that exhibit critical transitions. We demonstrate the detectability of two early warning signals: increased variance and increased autocorrelation. We introduce another metric that forewarns of abrupt changes in sea ice; a decrease in predictability before the threshold points. Observations of Arctic sea ice extent are searched …

Seasonal Influences Upon And Long-Term Trends In The Length Of The Atlantic Hurricane Season, Juliana Marie Karloski

Theses and Dissertations

Atlantic tropical cyclone (TC) seasons vary yearly in length with some seasons significantly shorter or longer than normal. Kossin (2008) suggested that from 1980 to 2007, the Atlantic TC season increased in length; however, their study only considered a subset of the Atlantic basin south of 30°N and east of 75°W. It is uncertain whether this trend holds over the entire Atlantic basin or continues into the present. It is also unclear as to whether meaningful sub-seasonal variability in the environmental factors necessary for TC formation exists between early- and late-starting and -ending seasons.

Quantile regression is used to evaluate …

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. …

A Preliminary Evaluation Of Advanced Dvorak Technique-Derived Intensity Estimate Errors And Biases During The Extratropical Transition Of Tropical Cyclones Using Synthetic Satellite Imagery, Alex Manion

Theses and Dissertations

Real-time and historical tropical cyclone (TC) intensity estimates during extratropical transition (ET) are derived mainly from satellite-based methods such as the Dvorak Technique (DT) and Advanced Dvorak Technique (ADT). However, the empirical relationships developed between cloud organization patterns and cyclone intensity that underlie the DT and ADT are primarily tropical in nature and thus become less reliable during ET. Preliminary analyses suggest that ADT-derived intensity estimates are weak-biased during ET; however, due to the lack of direct observations of cyclone intensity during ET, the extent to which this is true is unknown. Herein, an attempt to quantify errors during this …

Multi-Periodic Climate Dynamics: Spectral Analysis Of Instrumental, Short- And Long-Length Proxy Temperature Records, Michael David Madsen

Theses and Dissertations

Analyzing 26 short-length (less than 3000 years) instrumental and proxy temperature records and five long-length (greater than 3000 years) proxy temperature records using Discrete Fourier Transform has shown that as the length of significant periods increase in the time domain then so does the power at which the period is observed. A t-test verifies that a positive correlation exist between the length of the significant periods and the power with a confidence level of ∝ >0.05. Significant frequencies with period greater than 30 years are confirmed using Monte Carlo simulations, which were created using a nonlinear approach known as fractional …

Re-Examining An Air Mass-Based Approach To Detecting Structural Climate Change, 1948-2011, Joseph James Larsen

Theses and Dissertations

Air mass-based approaches to observing changes in climate can have considerable value beyond simple trends of temperature and moisture, providing more thorough understanding of structural climate patterns. Few methodologies have adequately characterized recent air mass modification, however. This research seeks to update and improve upon the methods of a prior study, providing new data from 1948-2011, as well as more rigorous statistical analyses. Air mass types were created, and monthly averages of temperature, dewpoint, and relative frequency were calculated for each of the air masses in all four seasons; then the time series were submitted to regression analysis. The results …

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 …

Assessing The Predictability Of Convection Initiation Using An Object-Based Approach, Brock James Burghardt

Theses and Dissertations

Improvements in numerical forecasts of deep, moist convection have been notable in recent years and are in large part due to increased computational power allowing for the explicit numerical representation of convection. Accurately forecasting the timing and location of convection initiation (CI), however, remains a substantial forecast challenge. This is attributed to the inherently limited intrinsic predictability of CI due to its dependence on highly non-linear moist physics and fine-scale atmospheric processes that are poorly represented in observations. Because CI is the starting point of deep, moist convection that grows upscale, even small errors in initial convective development can rapidly …