Simulations of baroclinic wave life cycles are performed in order to illustrate the wave evolution of a cyclone and diagnose possible unbalanced flow associated with the destabilization of an upper-level jet. Development of the baroclinic wave is observed using the multilevel primitive equation Weather Research and Forecasting (WRF) model. A baroclinic system is produced with an initially balanced, zonal baroclinic jet on an f-plane, whereby the geometry of the dynamic tropopause is specified. The change in geometry will result in different initial jet profiles. For each jet profile two numerical simulations comprised of different diffusion parameters are integrated to show the effect that the diffusion has on the simulation. The first simulation consists of a combination of weak horizontal and strong vertical diffusion, while the second simulation includes only strong horizontal diffusion, and is considered to be more consistent with real atmosphere characteristics. For each simulation, the nonlinear stage of the life cycle resembles a cyclonic wave-breaking system. Simulations where the vertical diffusion is strong tend to produce events of secondary cyclogenesis, which are not observed in the case of strong horizontal diffusion. Therefore, these secondary events are in all probability results of numerical instabilities at the triple point of the baroclinic system. The simulations with strong horizontal diffusion produce a crisper version of the baroclinic wave evolution cycle with sharper temperature gradients and deeper surface lows than the strong vertical diffusion case. Diagnostic calculations of the horizontal divergence and the residual of the nonlinear balance equation are shown in order to identify areas of unbalanced flow and subsequent inertia-gravity waves. Banded structures in the horizontal divergence field at the level of maximum wind speed suggest that the unbalanced flow is closely related to the upper level jet streak and possibly generated through geostrophic adjustment processes. The simulations with strong vertical diffusion contain less numerical noise and provide a clearer insight into the possible existence of inertia-gravity waves. A breakdown into the three main components of the residual of the nonlinear balance equation is shown in order to asses the contribution of each term towards the production of unbalanced flow, and indicates that the Laplacian term was the dominant factor as it was an order of magnitude stronger than the Jacobian and vorticity terms. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Spring Semester, 2005. / August 24, 2004. / WRF, Gravity Waves, Baroclinic / Includes bibliographical references. / Philip Cunningham, Professor Directing Thesis; Paul Reasor, Committee Member; T. N. Krishnamurti, Committee Member.

Radiance data obtained from NASA's Advanced Infrared Sounder (AIRS) is used in an attempt to improve the mesoscale prediction of temperature and moisture using one- and four-dimensional variational data assimilation (1D/4D-Var). The joint National Center for Atmospheric Research and Pennsylvania State University fifth-generation mesoscale model (MM5) along with the Stand-alone AIRS Radiative Transfer Algorithm (SARTA) is selected for this project. This work aims to utilize AIRS "clear-channel" radiances to enhance the first-guess analysis regarding the temperature and moisture content as a precursor to improving short-term precipitation forecasts. The adjoint operator for SARTA has been derived and linked to the MM5 adjoint modeling system; a "clear-channel" identification scheme, which is compatible with SARTA, has been developed and verified; and a set of one-dimensional variational data assimilation (1D-Var) experiments have been done in order to determine the impact of AIRS channels on the vertical profiles of temperature and moisture. Lastly, a preliminary 4D-Var experiment is carried out to determine the impact of a limited number of clear-channel AIRS radiances on the prediction of temperature and moisture. An adjoint-sensitivity based forecast verification technique is used to compare the 4D-Var forecast results to a control forecast. / A Dissertation submitted to the Department of Metorology in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester, 2008. / December 19, 2007. / Clear Channels, AIRS, Assimilation, Quality Control / Includes bibliographical references. / Xiaolei Zou, Professor Directing Dissertation; Robert A. van Engelen, Outside Committee Member; Robert Hart, Committee Member; Mark A. Bourassa, Committee Member; Guosheng Liu, Committee Member.

Hurricanes affecting the United States cause severe damage and kill people. The risk of future hurricane activity along the coast is the subject of much scientific and public interest. While considerable work had been done to understand the occurrence of hurricanes along the coast, much less has been done to examine the inter-relationships among the hurricanes. This dissertation concerns the relationships of hurricanes affecting the United States using methods of network analysis. Network analysis has been used in a variety of fields to study relational data, but has yet to be used in the study of hurricane climatology. The present work is largely expository introducing network analysis and showing how it can be applied to possibly better understanding regional hurricane activity as well as hurricane activity overtime. The research is divided into two cases. The first case consists of networks developed based on the relationships of spatial locations of landfalls and the second part consists of networks developed based on the relationships of the temporal occurrence of landfalls. In the first case, the network links coastal locations (termed nodes) with particular hurricanes (termed links). The topology of the network is examined using local and global metrics. Results show that certain regions of the coast (like Louisiana) have high hurricane occurrence rates, but not necessarily high values of network connectivity. Low values of connectivity indicate that hurricanes affecting Louisiana tend not to affect other regions. Regions with the highest values of connectivity include southwest Florida, northwest Florida, and North Carolina. Virginia which has a relatively low occurrence rate is well-positioned in the network having a relatively high value of betweenness. In the second case, the year-to-year variation in U.S. hurricane activity is examined by extending the ideas and concepts of network analysis for time series data. The "visibility" network link years experiencing a hurricane landfall with other hurricane landfall years ``visible" to each other through time. The topology of the visibility network is examined using local and global metrics. Results show that overall the visibility network has few years with many lines of visibility, therefore, many linkages to other years. Years with high hurricane count have more visibility in the network than those years that have less storms. Among years with high counts the years that are surrounded (before and after) with years of low counts will have greater visibility. The years 1886, 1893, 1955 and 2004 are highly visible in the network of U.S. hurricanes. A year is more central if it is a link in more visibility chains between other years in the network. Six conditional networks are constructed for the spatial and temporal networks based on years of below and above average values of important climate variables. Significant differences in the connectivity of the network are noted for different phases of the El Nino-Southern Oscillation. During El Nino years, when the equatorial waters of the eastern Pacific are warm, there tends to be shearing winds and subsidence over large portions of the North Atlantic where hurricanes form. These conditions lead to fewer hurricanes affecting the United States. More work is needed to better understand the details of how climate influences the network of landfalls. The scientific merit of the research is a better understanding of the relationships in the regional risk of hurricane activity. The broader impacts are an introduction of network analysis to hurricane climatology. / A Dissertation submitted to the Department of Geography in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester, 2009. / March 16, 2009. / Robert Har, Hurricane Climatology, Hurricanes / Includes bibliographical references. / James B. Elsner, Professor Directing Dissertation; Robert Hart, Outside Committee Member; J. A. Stallins, Committee Member; Thomas Jagger, Committee Member.

A more versatile and robust technique is developed for determining area averaged surface vorticity based on vector winds from the SeaWinds scatterometer on the QuikSCAT satellite. This improved technique is discussed in detail and compared to two previous studies by Sharp et al. (2002) and Gierach et al. (2007) that focused on early development of tropical systems. The error characteristics of the technique are examined in detail. Specifically, three independent sources of error are explored: random observational error, truncation error and representation error. Observational errors are due to random errors in the wind observations, and determined as a worst-case estimate as a function of averaging spatial scale. The observational uncertainty in vorticity averaged for a roughly circular shape with a 100 km diameter, expressed as one standard deviation, is approximately 0.5 x 10 -5 s-1 for the methodology described herein. Truncation error is associated with the assumption of linear changes between wind vectors. For accurate results, it must be estimated on a case-by-case basis. An attempt is made to determine a lower bound of truncation errors through the use of composites of tropical disturbances. This lower bound is calculated as 10-7 s-1 for the composites, which is relatively small compared to the tropical disturbance detection threshold set at 5 x 10-5 s-1, used in an earlier study. However, in more realistic conditions, uncertainty related to truncation errors is much larger than observational uncertainty. The third type of error discussed is due to the size of the area being averaged. If the wind vectors associated with a vorticity maximum are inside the perimeter of this area (away from the edges), it will be missed. This type of error is analogous to over-smoothing. Tropical and sub-tropical low pressure systems from three months of QuikSCAT observations are used to examine this error. This error results in a bias of approximately 1.5 x 10-5 s-1 for area averaged vorticity calculated on a 100 km scale compared to vorticity calculated on a 25 km scale. The discussion of these errors will benefit future projects of this nature as well as future satellite missions. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Fall Semester, 2008. / August 14, 2008. / Vorticity, Scatterometer, Cyclone Genesis, Rrror Analysis, Tropical Storm / Includes bibliographical references. / Mark Bourassa, Professor Directing Thesis; Paul Reasor, Committee Member; Philip Cunningham, Committee Member.

Accurate knowledge of cloud-top height is important for a range of meteorological applications. Uses include cloud classification and the assignment of height levels to cloud drift winds. Such data may also be useful for monitoring tropical cyclone intensity over observation sparse oceans. A new method to retrieve cloud-top height has been developed in order to improve the temporal and spatial coverage of cloud-top height data compared to currently available sources. The technique is a stereoscopic retrieval algorithm which uses visible wavelength data from the GOES-IM and MODIS instruments. Stereoscopic techniques utilize multiple views of the same cloud feature from different viewing angles to retrieve cloud-top height. Since clouds occur above the surface of the earth, when viewed from distinct angles a cloud will map to different positions creating a location parallax. The magnitude of location parallax is a function of the cloud altitude above the earth's surface and therefore may be used to determine cloud-top height. Data from the CloudSat and the Multiangle Imaging Spectroradiometer (MISR) have been used to validate the algorithm developed by this study. The overall mean and median algorithm bias relative to CloudSat and MISR are significantly different from 0 at the 95% confidence level however the bias are only ~200 m suggesting the algorithm is accurate. The algorithm is also evaluated by binning clouds according to optical thickness and the degree of cloud-top texture. Bias statistics are then calculated for each cloud bin. Results indicate biases are only statistically significantly different from 0 for clouds with little cloud top texture. To test the feasibility of using cloud-top height data to estimate tropical cyclone intensity the algorithm is used to retrieve cloud heights for tropical cyclones Katrina 2005 and Dennis 2005. Some predictive skill is apparent; however, additional work is needed draw definitive conclusions. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Spring Semester, 2009. / January 22, 2009. / Cloud-top Height, Remote Sensing, Satellites / Includes bibliographical references. / Guosheng Liu, Professor Directing Thesis; Robert G. Ellingson, Committee Member; Robert Hart, Committee Member.

A mesoscale budget analysis of absolute angular momentum (AAM) in the hurricane eyewall is presented using airborne dual-Doppler wind data from Hurricane Guillermo (1997). Multiple consecutive passes were made through the storm, allowing observed and budget-estimated changes to be directly assessed. Although the budget-estimated tendency is not in agreement with the observed tendency, the individual budget terms do show consistency with previous numerically based AAM budgets. The accuracy of the Doppler-derived wind field impacts the budget analysis; errors associated with the Doppler data are analyzed in depth. Aspects of the data processing and Doppler synthesis procedure that most directly impact the budget are identified (e.g., interpolation, mass continuity constraint, and sampling strategy). In order to more directly compare the Doppler-based budget with numerically based results, the Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) fifth generation non-hydrostatic Mesoscale Model (MM5) is used to perform an AAM budget analysis of a simulated hurricane. The numerically based budget is used to examine the impact of temporal resolution of the data on the budget, and to provide an additional context for examining the role of eddies in the Doppler-based budget. Consistent with recent mesoscale numerical budget studies, the eddy terms in the Doppler-based and numerically based AAM budgets are important in the eyewall and cannot be neglected. Contributions to the eddy flux convergence, and thus local changes in symmetric AAM, appear to be related to internal processes like mixing between the eye and eyewall, as well as the interaction of eyewall vorticity asymmetry with the environmental flow. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Fall Semester, 2008. / October 23, 2008. / Airborne Doppler Radar Data, Absolute Angular Momentum Budget, Tropical Cyclone / Includes bibliographical references. / Paul D. Reasor, Professor Directing Thesis; Philip Cunningham, Committee Member; Robert Hart, Committee Member.

At the polar latitudes, maritime mesocyclones form throughout the year, often near or embedded within cloud streets associated with massive cold air outbreaks. Such storms appear on the 100–1000 km horizontal scale. However, polar mesocyclones tend to exist on the lesser end of the horizontal scale. As a storm's size decreases, the likelihood that they will be well-represented in data also decreases. Underrepresentation of polar mesocyclones in reanalyses will affect climatological forecasts and research that utilize such data. Namely, the air-sea interactions associated with polar mesocyclones will be undercut, thereby impacting estimates of ocean circulation. Additionally, many reanalyses underestimate near-surface wind speeds, which is linked to but not exclusively dependent upon the problems associated with data resolution. Harsh polar conditions make regions of scientific interest unfavorable for in situ data collection, which compounds the aforementioned issues. This research examines the relatively new Arctic System Reanalysis (ASRv1) and its ability to represent three polar mesocyclonic systems of differing size. Should ASRv1 represent polar mesocyclones effectively, it could be a prime candidate in establishing an arctic atmospheric state for air-sea modeling. The product is compared to high-resolution Weather Research and Forecasting (WRF) model simulations, with ERA-Interim information providing the initial and boundary conditions. Simulation results are checked against available 10m equivalent neutral wind data from QuikSCAT to ensure that the model is producing reasonable atmospheric conditions. Comparisons are drawn for near-surface wind fields and surface turbulent fluxes to focus on ASRv1's depictions of air-sea interactions for polar mesocyclones. Differences betwixt ASRv1 and the WRF simulations are given with the likely explanations—physical, dynamical, and data-based (e.g., resolution, model options)—behind such differences. / A Thesis submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester 2015. / July 10, 2015. / arctic, cyclone, low, model, polar, reanalysis / Includes bibliographical references. / Mark A. Bourassa, Professor Directing Thesis; Robert E. Hart, Committee Member; Henry E. Fuelberg, Committee Member.

The diurnal variations from a high-resolution regional climate model (Regional Spectral Model; RSM) are analyzed from 6 independent decade long integrations using lateral boundary forcing data separately from the National Centers for Environmental Prediction Reanalysis 2 (NCEPR2), and European Center for Medium-Range Weather Forecasts (ECMWF) 40-year Reanalysis (ERA40) and the 20th Century Reanalysis (20CR). With each of these lateral boundary forcing data, the RSM is integrated separately using two convection schemes: the Relaxed Arakawa-Schubert (RAS) and Kain-Fritsch (KF) schemes. The results show that RSM integrations forced with 20CR have the least fidelity in depicting the seasonal cycle and diurnal variability of precipitation and surface temperature over the Southeastern United States (SEUS). The remaining four model simulations show comparable skills. The differences in the diurnal amplitude of rainfall during the summer months of the 20CR forced integration from the corresponding NCEPR2 forced integration, for example, is found to be largely from the transient component of the moisture flux convergence. The root mean square error (RMSE) of the seasonal cycle of precipitation and surface temperature of the other four simulations (not forced by 20CR) were comparable to each other and highest in the summer months. But the RMSE of the diurnal amplitude of precipitation and the timing of its diurnal zenith were largest during winter months and least during summer and fall months in the four model simulations (not forced by 20CR). The diurnal amplitude of surface temperature in comparison showed far less fidelity in all models. The phase of the diurnal maximum of surface temperature however showed significantly better validation with corresponding observations in all of the 6 model simulations The impacts of irrigation on SEUS diurnal climate are then investigated. An extreme case is assumed, wherein irrigation is set to 100% of field capacity over the growing season of May through October (IRR100). Irrigation is applied to the root zone layers of 10-40cm and 40-100cm soil layers only. It is found that in this regime there is a pronounced decrease in monthly averaged temperatures in irrigated regions across all months. In non-irrigated areas a slight warming is simulated. Diurnal maximum temperatures in irrigated areas warm, while diurnal minimum temperatures cool. The daytime warming is attributed to an increase in shortwave flux at the surface owing to diminished low cloud cover. Nighttime cooling results as a consequence of higher net downward ground heat flux. Both diurnal and monthly average precipitations are reduced over irrigated areas at a magnitude and spatial pattern similar to one another. Due to the excess moisture availability, evaporation is seen to increase, but this is balanced by a corresponding reduction in sensible heat flux. Concomitant with additional moisture availability is an increase in both transient and stationary moisture flux convergences. However, despite the increase, there is a large-scale stabilization of the atmosphere stemming from a cold surface and a warmed vertical column. Three additional regional climate model runs centered on the SEUS assume a crop growing season of May through October and are irrigated at 25%, 50%, 75% (IRR25, IRR50, IRR75, respectively) of the root zone field capacity to assess the sensitivity of the SEUS climate to irrigation. A fifth run, assuming no irrigation (CTL), is used as the basis for comparison. Across all IRR runs, it is found that there is a general reduction in monthly mean precipitation over the irrigated cells relative to CTL, with much of the change occurring in the sub-diurnal scales. This manifests as an increase dry days and reduction in > 1 mm/day rainfall events. IRR25 is seen to have the lowest change in both, while IRR100 is seen to have the greatest change. Area-averaged precipitation over the irrigated cells reveals a strong reduction in precipitation in IRR100 (on the order of 0.4 mm/hr) with a much weaker reduction in IRR25. Vertically integrated moisture convergence is seen to have the most pronounced sensitivity pattern across all runs. Monthly averaged temperatures are reduced over irrigated areas, with the intensity of the reduction increasing as irrigation vigor increases. This is attributed to a systematic change in ground heat flux that transports heat into the subsurface soil layers in the irrigated cells. The precipitation ahead of the transient cold fronts is reduced by irrigation as it passes over the irrigated cells. The intensity of the net precipitation reduction becomes more intense as irrigation vigor increases. Lastly, heat waves in the SEUS are reduced in intensity just over the irrigated cells, though likely increasing in frequency due to lowered temperature thresholds for heat wave definition. / A Dissertation submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2015. / July 9, 2015. / climate, irrigation, precipitation, regional model, temperature / Includes bibliographical references. / Vasubandhu Misra, Professor Directing Dissertation; Sachin Shanbhag, University Representative; Mark A. Bourassa, Committee Member; Guosheng Liu, Committee Member; Zhaohua Wu, Committee Member.

While a number of research groups offer quantitative diagnostic indices of aggregate annual Atlantic Basin tropical cyclone (TC) activity, the literature is comparatively thin concerning methods to similarly quantify seasonal U.S. landfall risks. An accurate diagnostic assessment of annual TC risk would be of great public utility and economic value, but the methods used to assess yearly activity demonstrate little skill in evaluating count or severity of TCs making landfall in the continental United States. As existing models are optimized to capture variability in cumulative seasonal TC activity, they are suboptimal statistical diagnostic tools for assessing the potential for sensible impacts of storms on populated areas. This project aims to address this utility gap in existing seasonal aggregate TC potential indices by taking a broader view of the factors that influence where TCs develop and move in the Atlantic Basin, shifting the focus to the physical parameters most closely linked to the historical conditions associated with U.S. landfall events. Using an extended record of Atlantic TC activity and reanalysis model datasets, characteristic atmospheric and oceanic traits of elevated U.S. TC landfall risk are identified, with the aim of quantifying the internal variance and predictability of these risks using empirical Poisson regression models. The resulting product, the Landfall Diagnostic Index (LDI), incorporates spatially and temporally averaged measures of relative sea surface temperature, layer-averaged steering winds, zonal shear vorticity, and upper-level divergence to yield a seasonal TC activity metric that has significant fidelity to the interannual and seasonal cycle variability of continental U.S. hurricane landfalls. The LDI offers physical insight into the causes and nature of TC risk on each of these scales, in particular highlighting a potential inherent tension between the conditions most favorable for elevated TC counts and those favoring steering currents directed towards the continental United States. / A Dissertation submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2015. / July 9, 2015. / climate, climatology, diagnostic methods, hurricanes, risk management, tropical cyclones / Includes bibliographical references. / Robert E. Hart, Professor Directing Dissertation; James Elsner, University Representative; Philip Sura, Committee Member; Vasu Misra, Committee Member; Mark Bourassa, Committee Member.

The availability of high resolution temperature and water vapor data is critical for the study of mesoscale scale weather phenomena (e.g., convective initiations, and tropical cyclones). As hyperspectral infrared sounders, the Atmospheric Infrared Sounder (AIRS) and Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) could provide high resolution atmospheric profiles by measuring radiations in many thousands of different channels. This work focuses on the assessment of the potential values of satellite hyperspectral radiance data on the study of convective initiations (CI) and the assimilation of AIRS radiance observations within tropical storms. First, the potential capability of hyperspectral infrared measurements (GIFTS) to provide convective precipitation forecasts has been studied and assessed. Using both the observed and the model-predicted profiles as input to the GIFTS radiative transfer model (RTM), it is shown that the simulated GIFTS radiance could capture the high vertical and temporal variability of the real and modeled atmosphere prior to a convective initiation, as well as the differences between observations and model forecasts. This study suggests the potential for hyperspectral infrared radiance data to make an important contribution to the improvement of the forecast skill of convective precipitation. Second, as the first step toward applying AIRS data to tropical cyclone (TC) prediction, a set of dropsonde profiles during Hurricane Rita (2005) is used to simulate AIRS radiance data and to assess the ability of AIRS data in capturing the vertical variability within TCs through one-dimensional variational (1D-Var) twin experiments. The AIRS observation errors and background errors are first estimated. Five sets of 1D-Var twin experiments are then performed using different combinations of AIRS channels. Finally, results from these 1D-Var experiments are analyzed. Major findings are: (1) AIRS radiance data contain useful information about the vertical variability of the temperature and water vapor within hurricanes; (2) assimilation of AIRS radiances significantly reduced errors in background temperature in the lower troposphere and relative humidity in the upper troposphere; (3) the near-real time (NRT) channel set provided by NOAA/NESDIS seems sufficient for capturing the vertical variability of the atmosphere in the upper troposphere of TCs, but not in the lower troposphere; and (4) the channels with weighting functions peak within the layer between 500-700 hPa could provide useful information to the atmospheric state below 700 hPa. A channel selection method is proposed to capture most vertical variability of temperature and water vapor within TCs contained in AIRS data. Finally, AIRS radiance data within TCs have been assimilated in the 1D-Var experiments with comparisons of the retrieval temperature and water vapor profiles with co-located Global Positioning System (GPS) radio occultation (RO) soundings and dropsonde profiles. The comparisons of AIRS 1D-Var retrieval profiles with GPS RO sounding show that AIRS data can greatly improve the analysis of temperature and water vapor profiles within TCs. The comparisons of retrieval profiles with dropsonde data during Hurricane Rita, however, showed some discrepancies partly due to the difference of these two measurements and the uncertainties of the AIRS errors. / A Dissertation submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester, 2010. / March 25, 2010. / 1D-Var, AIRS, Vertical Variability / Includes bibliographical references. / Xiaolei Zou, Professor Directing Dissertation; Xufeng Niu, University Representative; Robert G. Ellingson, Committee Member; Guosheng Liu, Committee Member; Robert Hart, Committee Member.