Cloud-to-ground lightning data from the National Lightning Detection Network during the 14-year period 1989-2002 are used to create a warm season lightning climatology for the northern Gulf Coast. Days are separated into five flow regimes based on the orientation of the coastline and the low-level flow. Specifically, each day is classified into either a calm (less than 2.5 m s-1) or directional flow category based on the mean 1000-700 hPa vector wind data at Lake Charles and Slidell, Louisiana. Flash densities are calculated, and maps are created for daily, hourly, and nocturnal periods. The composite 24-hour and nocturnal flash density maps indicate an east-to-west decrease in lightning over the region. Flash densities for the 24-hour period are greatest over land, with relative maxima located near the major metropolitan areas of Houston, Lake Charles, Baton Rouge, New Orleans, Biloxi, and Mobile. Flash densities during the nocturnal period are largest over the coastal waters. Land breezes, warm and shallow Gulf of Mexico waters, and advection of land-forming convection are responsible for the nighttime offshore convection. Lightning across the northern Gulf Coast depends largely on the prevailing synoptic flow. The low-level flow controls the sea breeze, the dominant forcing mechanism during the warm season. Southwest flow is the most unstable and humid of the five regimes, and it exhibits the most flashes. In this case, sea breeze induced convection is located slightly inland from the coast. Northeast flow, being the driest and most stable of the regimes, exhibits the least amount of lightning. The large-scale flow holds the sea breeze along the coastline. Flash density maxima over urban areas are examined to determine the relationship between lightning and the low-level flow. Analyses reveal that these maxima result from interactions between the prevailing flow and one or more mesoscale circulations. Urban influences such as frictional convergence, heat island effects, and air pollution also play a role in the enhancements. Geographic features and local mesoscale circulations affect lightning across the northern Gulf Coast. Geographic features, including lakes, bays, marshes, swamps, and coastline orientations, interact with the low-level flow and mesoscale circulations, such as the sea breeze and lake breezes, to produce complex lightning patterns and distributions. This climatology is useful for operational meteorologists faced with the challenge of forecasting summertime convection and its resulting lightning. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Fall Semester, 2003. / November 10, 2003. / Meteorology, Climatology, National Lightning Detection Network, Convection / Includes bibliographical references. / Henry E. Fuelberg, Professor Directing Thesis; Guosheng Liu, Committee Member; Philip Cunningham, Committee Member.

Tornadoes in the southeastern United States frequently occur with quasi-linear convective systems (QLCSs, also referred to as squall lines). Studies have shown that the non-descending mode of tornadogenesis (i.e., when strong rotation with a tornado builds upward through the storm) is especially common with the QLCS. Due to the frequent non-descending mode of tornadogenesis associated with QLCS tornadoes (hereafter referred to as tornadoes), it is difficult to issue timely tornado warnings for them. 86 tornadoes associated with QLCS systems that occurred during 22 separate severe weather episodes were studied using archived Warning Surveillance Radar – 1988 Doppler (WSR-88D) data to recreate mesocyclones and Tornado Vortex Signatures (TVSs) identified by the WSR-88D operational algorithms. Storm Data reports were used to create separate datasets of tornadic, pre-tornadic, and non-tornadic (null) mesocyclone and TVS detections. Selected diagnostics from the Mesocyclone and TVS Detection Algorithms (MDA and TDA, respectively) were compared between the tornadic and non-tornadic datasets. Low Level Delta Velocity (LLDV), Low-Level Rotational Velocity (LLROTV), and Strength Index (SI) showed some skill at discriminating between the tornadic and non-tornadic mesocyclones; however, the remainder of the selected mesocyclone parameters showed no significant skill, and none of the TVS parameters showed significant skill at discriminating between the tornadic, non-tornadic, or pre-tornadic cases. For mesocyclones, a correlation coefficient of 0.803 between LLDV and Maximum Delta Velocity for the pre-tornadic detections suggested that most of the tornadoes followed the non-descending tornadogenesis paradigm. Selected MDA and TDA diagnostics were combined using regression trees to determine whether these combinations would improve the skill at discriminating between tornadic and non-tornadic mesocyclones and TVSs. Ten-fold cross validation tests were performed on the selected diagnostics to ensure that the regression trees would generalize to independent data. Vertically Integrated Rotational Velocity and LLDV most often were selected for the regression trees. Some combinations of predictors produced detection success rates exceeding 30%, thereby exceeding the success rates when single MDA or TDA parameters were used. Various sized arrays of Spectrum Width (SW), Azimuthal Shear (AZ), and Reflectivity (RE) were combined with the MDA and TDA diagnostics to determine if these predictors contributed additional skill at discriminating tornadic mesocyclones and TVSs from the non-tornadic variety. These parameters had not been considered in previous studies. Qualitative analysis showed that the largest values of SW occurred with the non-tornadic dataset, but the differences between this dataset and the tornadic datasets were too small to be useful in an operational setting. Two sample Kolmogorov-Smirnov goodness-of-fit tests revealed that, in general, statistically significant differences did not exist among tornadic, pre-tornadic, and non-tornadic datasets for the different array sizes. Generally, qualitative differences were smallest with the largest arrays. SW arrays were included in the list of selected MDA and TDA diagnostics to create regression trees that would determine whether these combinations would yield predictive skill comparable to the best performing MDA and TDA diagnostics. For the mesocyclone detections, the same predictors (VIROTV and LLDV) dominated every SW array size. For the TVS comparisons, only the larger SW arrays appeared in some trees. This suggests that the larger SW arrays had predictive ability that was comparable to the four TDA predictors used in the regression trees Azimuthal Shear (AZ) frequently was found to exhibit negative values, even at the times of tornado occurrence. This result was unexpected since mesocyclones and TVSs are almost always associated with positive shear. Different array sizes of AZ showed strong correlations with each other, which was expected since the linear least squares derivative that is applied to the Velocity data has an a priori smoothing effect. Two-sample Kolmogorov-Smirnov goodness-of-fit tests showed that the most statistically significant differences in AZ occurred between the non-tornadic mesocyclones (NTM) and both the tornadic mesocyclones (M0) and the tornadic/pretornadic mesocyclones (MALL). Results indicated that AZ exhibited less ability than SW as a sole predictor at discriminating between tornadic and non-tornadic mesocyclones. However, when used in regression trees together with MDA and TDA parameters, AZ exhibited utility comparable to SW for TVS detections and was superior to SW for mesocyclone detections. When both SW and AZ arrays were used to create regression trees, SW always emerged as the dominant predictor. A surprising finding was the preponderance of negative AZ values in the tornadic TVS detections. Increasing array sizes of Reflectivity Variance (REV) appeared to have an upper limit of utility. Contrary to what was hypothesized, pre-tornadic mesocyclone and TVS detections exhibited larger variances than tornadic detections. Based on two-sample Kolmogorov-Smirnov goodness-of-fit tests, only the non-tornadic mesocyclone (NTM) versus pre-tornadic mesocyclone (MPRE) datasets exhibited statistically significant differences. None of the other comparisons was statistically significant. REV did not exhibit skill comparable to the best Severe Storms Analysis Package (SSAP) diagnostics for the mesocyclone detections in the regression trees that were constructed. However, for TVS detections, the larger REV arrays appeared in regression trees for the NTT versus TALL comparisons, and smaller arrays appeared in regression trees for the NTT versus TPRE comparisons. Regression trees combining REV arrays with the best-performing MDA and TDA predictors showed that REV exhibited better predictive ability for the TVS datasets compared to SW and AZ. These results suggest that SW, AZ, and REV all show utility as predictors when used in combination with some of the already existing MDA and TDA diagnostic parameters. Incorporating these additional data sources into the algorithms therefore could improve their performance. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Summer Semester, 2007. / April 5, 2007. / Tornadoes, Quasi-Linear Convective Systems, Algorithms / Includes bibliographical references. / Henry E. Fuelberg, Professor Directing Thesis; Jon E. Ahlquist, Committee Member; Paul H. Ruscher, Committee Member; Andrew I. Watson, Committee Member.

The impact of tropical cyclones on Canadian Provinces is an important issue. From 1994 to 2003, fifty-five tropical cyclones entered the Canadian Hurricane Centre (CHC) Response Zone, or ~42% of all named Atlantic tropical cyclones in this ten-year period, and 2003 was the fourth consecutive year for a tropical cyclone to make landfall in Canada. The CHC forecasts all tropical cyclones that enter the CHC Response Zone and assumes the lead in forecasting once the cyclone enters the CHC Area of Forecast Responsibility. This study acknowledges the challenges of forecasting such tropical cyclones at extratropical latitudes. If a tropical cyclone has been declared extratropical, global models may no longer carry the cyclone, and even if it is modeled, large model errors often result. The purpose of this study is to develop a new version of the FSU hurricane superensemble with greater skill in tracking tropical cyclones, especially at extratropical latitudes. This has been achieved from the development of the synthetic superensemble. The synthetic superensemble is similar to the multi-model superensemble that is used operationally at FSU. The operational superensemble is a statistical linear regression technique that uses real-time forecasts provided by several hurricane models to construct an optimal consensus forecast. The synthetic superensemble differs from the operational version in that it uses a larger set of member models, including the regular member models, synthetic versions of these models, and the operational superensemble and its synthetic version. Synthetic member model forecast tracks are produced by a simple alteration of the original model track. The alteration consists of producing a linear best-fit line through a hurricane track and applying a Fourier curve to the linear best-fit line to artificially generate a new track shape. This synthetic superensemble is being used here to forecast hurricane tracks from the 2001, 2002, and 2003 hurricane seasons. The synthetic superensemble produced forecasts with generally less track error than its member models, the operational superensemble, and the ensemble mean. It also performed exceptionally well for several major Canadian storms including Hurricane Juan of 2003 where the synthetic superensemble outperformed the Official forecast and the operational superensemble by 425-480 km at the longest forecast hour. Forecasting challenges for each season are discussed and it was found that the synthetic superensemble produced forecasts with greatest skill in the 2003 season when there were few major changes made to member models and when member models performed at their best. Overall, this research shows that the synthetic superensemble performs consistently well and would be an asset to operational hurricane track forecasting. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Fall Semester, 2004. / October 26, 2004. / Superensemble, Hurricane Prediction, Canada, Extratropical Cyclone, Hurricane Juan / Includes bibliographical references. / T. N. Krishnamurti, Professor Directing Thesis; Philip Cunningham, Committee Member; Robert Hart, Committee Member.

The two-way interaction between synoptic eddy and low-frequency flow (SELF), has been recognized to be important for the low-frequency variability of the atmosphere circulation. By considering a stochastic basic flow that captures the observed synoptic eddy statistics, we obtained both first and higher order approximations for a linear closure for the SELF feedback. The validity of the first order approximation depends on the intensity of the eddy variance. The first order approximation breaks down only when the level of eddy variance is unrealistically large. Under observed level of the synoptic eddy variance, I demonstrated that the first-order approximation is largely as good as high order approximations. Direct numerical ensemble simulations of the linearized model with stochastic basic state also confirm the validity of the first order approximation. Moreover, forced solutions under idealized external forcing are analyzed to delineate the importance of the SELF feedback in generating the patterns of low-frequency modes. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Summer Semester, 2005. / April 14, 2005. / low-frequency flow, stochastic, synoptic eddy and low-frequency-feedback / Includes bibliographical references. / Feifei Jin, Professor Directing Thesis; T. N.Krishnamurti, Committee Member; Robert G. Ellingson, Committee Member.

This study investigates the space-time evolution of the dominant modes that constitute the Asian summer monsoon (ASM), and, as an ultimate goal, the climate prediction of the ASM rainfall. Precipitation and other synoptic variables during the prominent life cycle of the ASM (May 21 to September 17) are used to show the detailed features of dominant modes, which are identified as the seasonal cycle, the ISO defined by the 40-50 day intraseasonal oscillation including the Madden-Julian oscillation and El Niño mode. The most pronounced feature of the seasonal cycle is the evolution of the sea level pressure anomaly and the ensuing evolution of other variables. The northward migration of a negative pressure anomaly and the accompanying cyclonic vortex over the Indian Ocean and the resulting moisture transport toward the Indian continent by the low-level westerly (Somali jet) depict the mean evolution of the precipitation field over India, the Bay of Bengal, and the Indochina peninsula during the early stage of the ASM. Over the western Pacific, a positive pressure anomaly cell pushes the precipitation band between 25° and 40°N northward, characterizing the onset and the early evolution of the regional monsoons in East Asia (China, Japan and Korea). This positive pressure anomaly, intruding into southern China and further west to the Bay of Bengal from mid June to mid July, accelerates the low-level wind along the eastern coast of the Asian continent, where the pressure gradient is maximum. It provides a favorable condition for moisture transport toward the East Asian countries. Two major sources of moisture, i.e., the Indian Ocean and the western Pacific Ocean, play distinct roles during the varying phases of the monsoon. Precipitation over the Indian region is affected persistently by the Indian Ocean. Influences of the western Pacific Ocean dominate the precipitation over the Indochina peninsula in the early monsoon period followed by the influence from the Indian Ocean (mid June to mid July), and the combined contribution afterward. The East Asian monsoon regions are affected by both sources from the onset of their monsoons. Since late July, the contribution from the western Pacific Ocean is greater due to the development of a strong negative pressure anomaly pattern over the subtropical western Pacific. The present study reveals that the ISO is the second largest component of the ASM rainfall variation. Correlation analysis indicates that ISO explains a larger fraction of the variance of the observed precipitation (without climatology) than the ENSO mode. The dominant ISO signal faithfully explains the northward propagation of the ISO toward the Asian continent causing intraseasonal active/break periods. The interannual variation of the ISO strength suggests that the ENSO exerts some influence on the ISO. The composite convective ISO anomaly and Kelvin-Rossby wave response over the Indian Ocean shows that the ISO tends to be stronger during the early stage of the ASM than normal in El Niño (La Niña) years, indicating greater (smaller) possibility of ISO-related extreme rainfall over India, Bangladesh, and the Bay of Bengal. The ENSO mode reveals that the following factors affect the evolution of the ASM system in El Niño (La Niña) years. (1) The anomalous sea surface temperature and sea level pressure over the Indian Ocean during the early stage of the ASM weaken (enhance) the meridional pressure gradient. (2) As a result, the westerly jet and the ensuing moisture transport toward India and the Bay of Bengal become weak (strong) and delayed (expedited), providing a less (more) favorable condition for regional monsoon onsets. (3) The Walker circulation anomaly results in an enhanced subsidence (ascent) and drought (flood) over the Maritime continent. (4) The Hadley circulation anomaly over the western Pacific drives the wetter (drier) south China monsoon, the weaker (stronger) East Asian monsoon, and the wetter (drier) late July and early August over India, the Bay of Bengal, and the Indochina peninsula. (5) The ASM system appears to exert positive feedback on the El Niño (La Niña) by accelerating the westerly (easterly) anomaly toward the equatorial western Pacific in August. (6) ENSO effects tend to last until the early stage of the ASM in the following year. Based on the modal decomposition of the ASM variability, a new paradigm for climate (one month and longer) prediction is developed and is applied to the 5-day averaged ASM precipitation. The foundation of the method is to predict the amplitude of each climate signal (e.g., seasonal cycle, ISO, etc.) that constitutes the ASM system. Prediction is much facilitated by forecasting the slowly undulating amplitude time series. The present method extends the predictability of the ASM pentad precipitation event to six months in certain regions with correlation greater than 0.4. Also, ISO propagation was successfully predicted 120 days ahead of time with correlation greater than 0.4. / A Dissertation Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy. / Summer Semester, 2004. / May 25, 2004. / Precipitation, Predictability, Climate Prediction, Asian Summer Monsoon, Monsoon Variability, Long-Range Forecast / Includes bibliographical references. / Kwang-Yul Kim, Professor Directing Dissertation; Ruby Krishnamurti, Outside Committee Member; Henry E. Fuelberg, Committee Member; Tiruvalam N. Krishnamurti, Committee Member; Sharon E. Nicholson, Committee Member.

The goal of this study is to further investigate the relationship between the microphysical processes of a tropical cyclone and its intensification. Hydrometeors such as rainwater, cloud ice, cloud water, snow, and graupel play a significant role updraft and downdraft characteristics, precipitation, evaporation, ice concentration, and the distribution of latent heat. These processes are the primary heat sources for tropical cyclones. Therefore, it is expected that cloud microphysics may directly or indirectly influence the intensity of the hurricane. The first objective of this study is to evaluate the impact of different sophisticated explicit cloud microphysics parameterization schemes available in the PSU/NCAR MM5 model, on the hurricane forecast. Of the four microphysical parameterization schemes, the one that exhibited an intensity pattern closely resembling that of the observed values for the hurricane was selected in order to continue onto the next phase of the project. The second objective is to assess the impact of ice hydrometeors (cloud ice), in the overall performance of the hurricane forecast. This phase further investigates the impact of the selected microphysical processes on the overall forecast of the hurricane, with an emphasis on intensity. This is achieved by suppressing some of the microphysical processes that would allow for ice depletion. By doing so, we indirectly increase the amount of ice in the hurricane. This numerical comparison is done in the selected scheme both before and after ice production terms are modified, in order to substantiate the hypothesis whether or not an increased amount of ice in a tropical cyclone would lead to a more intense storm. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Spring Semester, 2005. / December 3, 2004. / hurricane intensity, MM5, ice microphysics / Includes bibliographical references. / T. N. Krishnamurti, Professor Directing Thesis; Robert Hart, Committee Member; Carol Anne Clayson, Committee Member.

Climate feedbacks represent mechanisms that alter the sensitivity of the earth climate system. It has been suggested that the current spread in climate model sensitivity to a CO2 forcing is a result of different treatments of climate feedbacks. The determination of the climate system sensitivity is critical to understanding how the system will respond to a CO2 radiative forcing. The strength of a climate feedback is defined in terms of annual, global mean top of atmosphere (TOA) radiative perturbation. However, contributions to the global, annual mean feedbacks can originate from different geographical regions and vertical layers within the atmosphere. In addition, the contributions to the annual mean TOA radiative perturbation can be disproportionately distributed throughout the annual cycle. This study performs offline, partial radiative perturbation-style, radiative calculations to determine the geographical, vertical, and seasonal distributions of the major climate feedbacks contributing to the TOA radiative energy budget: clouds, water vapor, temperature, and surface albedo. These feedback strengths are diagnosed from NCAR CCSM3.0 model output for the SRESA1B emission scenario simulated for the IPCC AR4. It is found that the tropics and sub-tropical climate responses drive the sign and strength of the water vapor and cloud feedbacks. In addition, a significant annual cycle of the SW cloud and surface albedo feedbacks is found. The inter-seasonal variations of the SW cloud and surface albedo feedbacks found here show a different pattern than previously published results. The radiative perturbations are then used as input into the newly developed Coupled Feedback Response Analysis Method (CFRAM), which uses a total energy based method to isolate partial temperature changes due to individual feedbacks in the atmosphere and at the surface. Many authors have calculated climate feedback radiative perturbations in different manners using seasonal mean, monthly mean, daily mean, and every time step model output. Monthly mean model output is used in this study. A comparison of the global mean clear sky TOA net flux calculation using monthly mean model output with the monthly mean model output TOA net flux reveals a global mean bias in the offline radiation calculations compared to the model simulated TOA net flux of +3.95 Wm-2 with a standard deviation of 3.78 Wm-2. In order to handle complexities associated with cloud overlap, the Monte Carlo Independent Column Approximation (MCICA) technique is uniquely adapted for use in the context of this study. This technique relies on a stochastic cloud generator using a maximum-random overlap rule to sample the monthly mean cloud frequency profile. It is shown that the global mean bias in the calculation of the TOA net flux compared to NCAR CCSM3.0 model output is +1.74 Wm-2 and a standard deviation of 6.71 Wm-2 using this technique. However, the results suggest that the technique provides a very good estimate of all feedback sensitivity parameters despite bias associated with using monthly mean model output. / A Dissertation Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy. / Fall Semester, 2009. / October 20, 2009. / Climate change, Feedback analysis, Climate feedbacks, Climate, Climate sensitivity / Includes bibliographical references. / Robert G. Ellingson, Professor Directing Dissertation; Ruby Krishnamurti, University Representative; Ming Cai, Committee Member; Carol Anne Clayson, Committee Member; Guosheng Liu, Committee Member.

This research identifies dominant modes of annual variability of the marine stratocumulus (MSc) cloud in the eastern tropical Pacific and Atlantic obtained from the International Satellite Cloud Climatology Project (ISCCP) dataset from January 1984 throughout December 2004, and describes the evolution of the macroscopic and radiative properties related with these physical modes. These modes are extracted from observational data using the cyclostationary empirical orthogonal function (CSEOF) technique, which retrieves the evolution of each mode together with its amplitude time series. This, in combination with comprehensive analysis of the many key physical variables (e.g., SST, surface wind, stability, horizontal temperatures advection) associated with the mode enhances us to depict the understanding the dynamic and thermodynamic processes for the formation and dissipation of these low level clouds. Finally, the development of diagnostic and prognostic models for the low cloud amount (CA) is an additional feature of this research, and helps to improve low cloud parameterization by SST in global climate models in the long term. The main scientific objective of this study is to investigate the timing, location, strength, and moving direction of the SST and the cloud throughout the year and gain some insights for parameterization of cloud properties using the evolution of SST and the interaction relationship between SST and cloud over these eastern tropical oceans. The most pronounced features of the evolution of the SST and cloud property anomalies are equatorward expansion along the coastal regions of the eastern tropical Pacific and Atlantic, and westward propagation along the equator. A positive (negative) CA and the accompanying cold (warm) SST anomalies stretch equatorward along the coastal regions during Summer and early Fall (Winter and early Spring) seasons. With the negative correlation between SST and CA anomalies, CA leads SST about one month at latitude 15°-5°S of the coastal regions of the eastern tropical Pacific. In the view of large-scale environment at the surface, the "trough-like" discontinuity of distorted SLP anomaly due to the land-sea distribution causes the persistently strong southerly surface wind anomaly blowing outward from the contour of SLP anomaly. This southerly surface wind anomaly pumps up the coastal upwelling that drags the cold water from the lower depths of the ocean. This describes schematically the surface wind-SST process occurring over the coastal region of the eastern tropical Pacific (equatorward of 20°S). Considering the cloud effect in this region, the southerly wind off the coasts of the coastal region pumps up cold water from the ocean subsurface. The onset of cooling in the region is conducive to more clouds and less surface insolation, which further promotes southerly wind anomalies. This southerly induces locally stronger, more extensive dynamical and evaporative cooling. This cooling expands to northwest via southerly wind. This is a schematic description of the wind-SST-MSc relationship. The lag/lead pattern between variables supports this relationship. The meridional wind component (V) leads SST about one month in the region. The increasing (decreasing) shielding effect of shortwave radiation at the cloud top drives the cold (warm) SST anomaly. CA also leads SST about one month. After equatorward expansions of the SST and CA anomalies reach maximum, westward propagation of the positive (negative) CA and the cold (warm) SST anomalies starts to occur simultaneously along the equator. These propagations advance further east to the dateline in November (May) along the equator, where the SST gradient is maximum. Easterly surface wind plays an important role of westward propagation of cold SST anomaly and zonal gradient SST anomaly. Easterly surface wind starts to blow where zonal gradient of SST anomaly is negative along the western edge of the nearcoastal zone in the eastern tropical Pacific. At this point, it leads the negative zonal gradient of SST anomaly. As the easterly wind strengthens due to redistribution of SLP pattern by the zonal gradient of SST anomaly, it generates the equatorial upwelling, enhancing cold phase of SST anomaly. The cooling in the region generates more cloudiness and more reflection, which further enhances the gradient of SST anomaly and in turns, the resulting easterly wind anomaly becomes strong. This easterly causes locally stronger, more extensive dynamical and evaporative cooling as well. The schematic wind-SST-MSc relationship is described by the interesting lead/lag relationship between physical variables provides. The easterly wind in tropical equatorial Pacific leads the cold SST anomaly about one month due to equatorial upwelling from the ocean subsurface. However, there is no lag/lead relationship between SST (or stability) and CA, that is, their interaction happens simultaneously in this region. This lead/lag relationship is important in understanding any interactions between them (e.g., cloud-SST feedback, wind-SST feedback). Results of this analysis may lead to improvement of diagnostic model/parameterization for the MSc cloud properties in GCMs. Stability is defined as the difference of potential temperature between 700 hPa and the surface. It is reflected in the atmosphere and ocean field. Therefore, it can be better key physical variable to express the MSc CA variability than SST. Two major atmospheric factors to control stability over the eastern tropical Pacific and Atlantic: the vertical structure of the horizontal temperature advection at the surface and lower level, and subsidence at lower and upper levels. They play significant roles during the positive (negative) phase of CA anomaly. The horizontal temperature advection from warm air aloft (brought on by warm advection) coupled with cold air at the surface (caused by nighttime radiative cooling, cold advection, or a cold surface). Subsidence in the subtropics occurs over the MSc clouds and generates the temperature inversion at low troposphere because dry air aloft is compressed and warmed. Mixing between upper and lower level affects instability. Mixing increases warming below and cooling higher up in the atmosphere. This inversion plays to prevent mixing with drier air above the top of the marine atmospheric boundary layer (MABL) and maintain the moisture in the MABL. In this study, we also evaluate a new parameterization that generates the mean LWP, based on the Gaussian distribution of cloud depths, and assumption that internal homogeneity is due to variation of cloud depths. Based on our comparison of the parameterized results to observations, we discuss the possibility of applying the predicted distribution of mean LWP to a GCM. / A Dissertation Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy. / Spring Semester, 2007. / November 30, 2006. / annual cycle, SST, Stratocumulus, feedback / Includes bibliographical references. / Ming Cai, Professor Directing Dissertation; Kaisheng Song, Outside Committee Member; Paul H. Ruscher, Committee Member; Sharon E. Nicholson, Committee Member; Guosheng Liu, Committee Member.

The plane-parallel hypothesis (PPH) used to approximate clouds in global climate models neglects the 3-D effects of clouds. Such effects can contribute as much as 20 Wm-2 to the downward longwave flux at the surface. Several investigators have proposed accounting for longwave 3-D cloud effects by using information on the Probability of Clear Line of Sight (PCLoS) to modify the PPH approximation. This study investigates the PCLoS at the Atmosphere Radiation Measurement (ARM) Program's Tropical Western Pacific (TWP) site and its dependence on cloud properties. PCLoS is determined for single-layer cumulus events over 2-hour intervals using Whole Sky Imager (WSI) data at the Nauru and Manus sites simultaneous to numerous observations of the location of cloud boundaries and the downward longwave flux. The WSI PCLoS is compared to calculations from a set of PCLoS models using measured cloud field statistics as input (e.g., cloud fraction and aspect ratio). A PCLoS climatology is also prepared for the observation periods at both sites, and the results are used to investigate the spatial variability of the PCLoS and effects on the downward longwave flux at the surface. Comparisons to similar data obtained at the ARM Southern Great Plains site will also be made. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Summer Semester, 2006. / June 22, 2006. / Cumulus Clouds, Cloud Radiative Effects, 3D Radiation / Includes bibliographical references. / Guosheng Liu, Professor Co-Directing Thesis; Ezra Takara, Professor Co-Directing Thesis; Xiaolei Zou, Committee Member; Paul Ruscher, Committee Member.

The nature of balance in the atmosphere is of central importance to the dynamics of both the troposphere and the stratosphere, and unbalanced motions such as inertia-gravity waves play a significant role in many aspects of atmospheric behavior. In light of the importance of upper-tropospheric jets for the generation of inertia-gravity waves in the atmosphere, this study examines the evolution of unstable barotropic jets to assess the nature and evolution of balance in these features. This issue is explored using the simplest non-trivial dynamical framework in which balanced and unbalanced flows can coexist, namely the one-layer shallow water equations. In this study, numerical simulations of initially balanced zonal barotropic jets on an f plane are investigated for evidence of the breakdown of balance and the generation of inertia-gravity waves during the life cycles of the instabilities to these jets. In these simulations, the parameters of the basic-state jet (i.e., jet width and speed) are varied systematically in an attempt to elucidate the dependence of balance on the structure and dynamical evolution of the instability. The presence of unbalanced flow, either in numerical simulations or in atmospheric data, is typically inferred via various quantities that provide indirect measures of imbalance, such as the existence of strong ageostrophy, large Rossby and/or Lagrangian Rossby numbers, and large values of horizontal divergence and its material derivative. Along with evaluating these parameters in each simulation, a potential vorticity inversion method is employed to obtain the structure of balanced and unbalanced fields within each simulation. The diagnostic calculations are then compared to the potential vorticity inversion results. Contrasts and comparisons are presented for each of the simulations shown in this study. The simulations consist of an unstable barotropic wave ranging from small (i.e., O(10-1)) Rossby and Froude number to large (i.e., O(1)) Rossby and Froude number. For strong jets, neither the Rossby number nor the Froude number is small compared to unity therefore the applicability of traditional scale analysis is unclear (e.g. Haltiner and Williams, 1980) (i.e., the balance condition is no longer valid and a breakdown of balance should occur). In contrast, the results of the diagnostic calculations and potential vorticity inversions reveal that nonlinear balance is essentially valid for this particular jet profile, even though the Rossby and Froude numbers are O(1) for the strong barotropic jet. Significant inertia-gravity wave structures were not found in any of the cases shown here, which is consistent with the results obtained by several other investigators in their integrations of the shallow-water equations. / A Thesis Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Master of Science. / Summer Semester, 2004. / June 17, 2004. / Balance, Barotropic, Jets, Gravity waves, Potential vorticity inversion / Includes bibliographical references. / Philip Cunningham, Professor Directing Thesis; Albert I. Barcilon, Committee Member; T. N. Krishnamurti, Committee Member.