Thesis (M.S.) Massachusetts Institute of Technology. Dept. of Meteorology, 1946. / Bibliography: leaf 30. / by Marion G. Hogan. / M.S.

Organized convection is of critical importance in the tropical atmosphere. Recent advances in numerical modeling have revealed that moist convection can interact with its environment to transition from a quasi-random to organized state. This phenomenon, known as convective self-aggregation, is aided by feedbacks involving clouds, water vapor, and radiation that increase the spatial variance of column-integrated frozen moist static energy. Prior studies have shown self-aggregation to take several different forms, including that of spontaneous tropical cyclogenesis in an environment of rotating radiative-convective equilibrium (RCE). This study expands upon previous work to address the processes leading to tropical cyclogenesis in this rotating RCE framework. More specifically, a 3-D, cloud-resolving numerical model is used to examine the self-aggregation of convection and potential cyclogenesis, and the background planetary vorticity is varied on an f-plane across simulations to represent a range of deep tropical and near-equatorial environments. Convection is initialized randomly in an otherwise homogeneous environment, with no background wind, precursor disturbance, or other synoptic-scale forcing. All simulations with planetary vorticity corresponding to latitudes from 10° to 20° generate intense tropical cyclones, with maximum wind speeds of 80 m/s or above. Time to genesis varies widely, even within a 5-member ensemble of 20° simulations, reflecting a potential degree of stochastic variability based in part on the initial random distribution of convection. Shared across this so-called “high-f” group is the emergence of a midlevel vortex in the days leading to genesis, which has dynamic and thermodynamic implications on its environment that facilitate the spinup of a low-level vortex. Tropical cyclogenesis is possible in this model even at values of Coriolis parameter as low as that representative of 1°. In these experiments, convection self-aggregates into a quasi-circular cluster, which then begins to rotate and gradually strengthen into a tropical storm, aided by near-surface inflow and shallow overturning radial circulations aloft within the aggregated cluster. Other experiments at these lower Coriolis parameters instead self-aggregate into an elongated band and fail to undergo cyclogenesis over the 100-day simulation. A large portion of this study is devoted to examining in greater detail the dynamic and thermodynamic evolution of cyclogenesis in these experiments and comparing the physical mechanisms to current theories. / 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. / Spring Semester 2019. / April 1, 2019. / Convection, Numerical modeling, Self-aggregation, Tropical cyclones / Includes bibliographical references. / Allison A. Wing, Professor Directing Thesis; Robert E. Hart, Committee Member; Jeffrey M. Chagnon, Committee Member.

The objective of this study is to quantify barrier layer development due to tropical cyclone (TC) passage using Argo float observations of temperature and salinity. To accomplish this objective, a climatology of Argo float measurements is developed from 2001-2014 for the Atlantic, eastern Pacific, and central Pacific basins. Each Argo float sample consists of a pre-storm and post-storm temperature and salinity profile pair. In addition, a no-TC Argo pair dataset is derived for comparison to account for natural ocean state variability and instrument sensitivity. The Atlantic basin shows a statistically significant increase in post-TC barrier layer thickness (BLT) and barrier layer potential energy (BLPE) that is largely attributable to an increase of 2.6 m in the post-TC isothermal layer depth (ITLD). The eastern Pacific basin shows no significant changes to any barrier layer characteristic, likely due to a shallow and highly stratified pycnocline. However, the near-surface layer freshens in the upper 30 m after TC passage, which increases static stability. Finally, the central Pacific has a statistically significant freshening in the upper 20-30 m that increases upper-ocean stratification by ~35%. The mechanisms responsible for increases in BLPE vary between the Atlantic and both Pacific basins; the Atlantic is sensitive to ITLD deepening, while the Pacific basins show near-surface freshening to be more important in barrier layer development. In addition, Argo data subsets are used to investigate the physical relationships between the barrier layer and TC intensity, TC translation speed, radial distance from TC center, and time after TC passage. ROMS model hindcasts of Hurricange Gonzalo (2014) characterize the upper-ocean response to TC precipitation forcing. Several different vertical mixing parameterizations are tested to determine their sensitivity to precipitation. For all mixing schemes, TC precipitation accounts for ocean surface freshening of about 0.3 PSU. The dominant terms in the near-surface salinity budget are the total advection and vertical diffusivity. The influence of precipitation-induced changes to the SST response is more complicated. In some areas, increased upper-ocean stratification mutes the SST cooling response. However, in other areas, cooling can be stronger when precipitation is prescribed. Dynamical changes in upper-ocean currents and the curl of the surface stress can induce a stronger cooling response in these regions. / 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. / Fall Semester 2018. / December 5, 2018. / Air-Sea Interaction, Oceanic Barrier Layer, Tropical Cyclones / Includes bibliographical references. / Mark Bourassa, Professor Directing Dissertation; James Elsner, University Representative; Robert Hart, Committee Member; Jeff Chagnon, Committee Member; Allan Clarke, Committee Member.

Surface ozone (O3) is a toxic air pollutant. In the United States and Europe, among other places, policies and technology have reduced emissions of O3 precursors the last couple decades. As a result, peak levels of O3, quantified by concentration metrics such as maximum daily average over 8 hours (MDA8), the accumulated O3 exposure over a threshold of 40 ppb (AOT40), and the weighted cumulative exposure index (W126) have fallen. Influential past studies have assumed that these improvements in AOT40 and W126 imply reductions in plant injury, even though it is widely recognized that O3 flux into leaves is a better predictor of plant damage than ambient concentration in air. Concentration metrics remain widely used because O3 concentration measurements are more common and because concentration and flux are correlated when the variability of stomatal conductance is limited. We use a new dataset of O3 flux into plants to quantify decadal trends in the cumulative uptake of O3 (CUO) into leaf stomata for the first time. We examine 32 sites in the United States and Europe over 2005-2014 and find that the AOT40 and W126 concentration metrics decreased at 25 and 28 sites, respectively, whereas CUO increased at a majority of sites (18). The divergent trends are due to stomatal control of flux, which is shaped by environmental variability. As a result, there has been no widespread, clear improvement in CUO over 2005-2014 at the sites we can assess. We use several statistical tests to show that temporal trends and variability in CUO are uncorrelated with AOT40, W126, and mean concentration (R2 ≤ 0.15). Decreases in concentration metrics, therefore, give a falsely optimistic picture of the direction and magnitude of O3 impacts on vegetation. Because of this lack of relation between flux and concentration, flux metrics should be preferred over concentration metrics in assessments of plant injury from O3. GEOS-Chem is a 3-D global atmospheric chemistry model that uses meteorological input to simulate atmospheric composition. We evaluate the model’s ability to estimate O3 deposition velocity (V_d) by running a simulation during the same period as the surface O3 trend analysis. By comparing monthly output of V_d from GEOS-Chem to our observations using the SynFlux dataset, we find that GEOS-Chem consistently underestimates V_d. The degree of the underestimation depends on the land class type as well as the time of year. We attempt to improve the model output by prescribing the land class type within the model to match the plant functional types at the FLUXNET sites. This did not lead to a significant improvement and in many cases, this led to a wider gap between the model and observations. We discuss possible reasons for the discrepancy between the model and observations. Improving V_d in the model would better estimate dry deposition of O3, which is important for simulating air quality, and its impacts to humans and plants. / 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. / Spring Semester 2019. / April 3, 2019. / Includes bibliographical references. / Christopher D. Holmes, Professor Directing Thesis; Allison Wing, Committee Member; Mark Bourassa, Committee Member.

Many tropical cyclone studies have been conducted on basin-averaged potential intensity trends and the influence of sea surface temperatures (SSTs) on tropical cyclone intensity, but there is less research on along-track potential intensity (PI) and lifetime maximum intensity (referred to here as actual intensity or AI) and the factors that influence their variability. Potential intensity is a theory that predicts the maximum intensity that a tropical cyclone can achieve given certain large-scale environmental variables. Understanding interannual variability in PI and its relation to AI interannual variability is of great importance for assessing the impact of future climate conditions on tropical cyclones. Theoretically, warmer SSTs and cooler outflow temperatures would cause an increase in overall PI which in turn would lead to an increase in AI. This thesis examined the relationship between PI and AI on interannual time scales and the factors affecting PI variability: thermodynamic efficiency and air-sea enthalpy disequilibrium. Using best-track data and three reanalysis products, variability in PI and AI was examined for the North Atlantic, North Indian, South Indian, South Pacific, Eastern North Pacific, and Western North Pacific basins from 1980-2013. Overall, the Western North Pacific was the only basin that yielded high and consistently significant correlations between AI and PI. Despite the expectation from a previous study, the North Atlantic did not yield robust significant correlations. Multiple tests were then conducted to determine the sensitivity of the North Atlantic correlations to different datasets and time periods. Ultimately, it was determined that the North Atlantic AI vs. PI correlation results were very dependent upon the time period and the individual years within the time period. In the comparison of all contributors, air-sea disequilibrium was the dominant contributor to PI variability. When AI variability was correlated with PI variability, disequilibrium (which is largely controlled by SSTs) was also the dominant contributor to AI variability. Although disequilibrium was the dominant factor in PI and AI interannual variability, efficiency also played a role. In fact, this study found that variances in efficiency explained 13-93% of PI interannual variability, indicating that variability in outflow temperatures (which cause much of the variability in efficiency) must be taken into account. / 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. / Spring Semester 2019. / April 2, 2019. / actual intensity, disequilibrium, efficiency, interannual variability, lifetime maximum intensity, potential intensity / Includes bibliographical references. / Allison Wing, Professor Directing Thesis; Robert Hart, Committee Member; Philip Sura, Committee Member.

Snow, another precipitation form besides rain, affects the Earth’s climate distinctly by modifying hydrological and radiative processes. The radiative properties of nonspherical snowflakes are much more complicated than their spherical counterparts, raindrops. Snowflakes with different structures tend to have different scattering properties. Thus it is important for us to enhance the knowledge in falling snow. However, only a few sensors have been available so far that can provide global snowfall measurements including those onboard he Global Precipitation Measurement (GPM) core observatory and the CloudSat satellites. The GPM satellite carries two important instruments for studying snow precipitations, i.e., the Dual–frequency Precipitation Radar (DPR) and the GPM Microwave Imager (GMI). By combining the GPM instruments with another active sensor onboard the CloudSat satellite, the Cloud Profiling Radar (CPR), an unprecedented opportunity arises for understanding the microphysics of snowflakes and the physical processes of snow precipitation. Seizing this opportunity, in this study, we firstly investigate the microphysical properties of snow particles by analyzing their backscattered signatures at different frequencies. Then, the accuracy of simulating passive microwave brightness temperatures at high frequencies is examined under snowfall conditions using the CPR derived snow water content profiles as radiative transfer model inputs. Lastly, a passive microwave snowfall retrieval method is developed in which the a priori database is optimized by tuning snow water content profiles to be consistent with the GMI observations. To understand the microphysical properties of snow clouds, the triple-frequency radar signatures derived from the DPR and CPR collocated measurements are analyzed. It is noticed that there is a clear difference in triple-frequency radar signatures between stratiform and convective clouds. Through modeling experiments, it is found that the triple-frequency radar signatures are closely related to the size and bulk density of snow particles. The observed difference in triple-frequency radar signatures are mainly attributed to the difference in prevalent particle modes between stratiform and convective clouds, i.e., stratiform snow clouds contain abundant large unrimed particles with low density, while dense small rimed particles are prevalent in convective clouds. To assess the accuracy of radiative transfer simulation for passive microwave high frequency channels under snowfall conditions, we evaluate the biases between observed and simulated brightness temperatures for GMI channels at 166 and 183 GHz. A radiative transfer model is used, which is capable to handle the scattering properties of nonspherical snowflakes. As inputs to the radiative transfer model, the snow water content profiles are derived from the CPR measurements. The results indicate that the overall biases of observed minus simulated brightness temperatures are generally smaller than 1 K except for the 166 GHz horizontal polarization (166H) channel. Large biases for GMI channels are found under scenes of low brightness temperatures. Further investigations indicate that the remaining biases for GMI channels are associated with specific cloud types. In shallow clouds, errors in cloud liquid water profiles are likely responsible for the large positive bias at the 166H channel. In deep convective clouds, strong attenuation in CPR radar reflectivities and possible sampling bias both contribute to the GMI remaining negative biases. A snowfall retrieval algorithm is then developed for GMI observations. The data sources and processing methods are adopted from the above study of GMI bias characterization. First, an a priori database is created which contains the snow water content profiles and their corresponding brightness temperatures simulated for GMI channels. A one–dimensional variational (1D–Var) method is employed to optimize the CPR derived snow water content profiles. The so developed a priori database is applied in a Bayesian retrieval algorithm. The retrieval results show that the 1D–Var optimization can improve the vertical structure of retrieved snow water content. Additionally, this method can bring the global mean distribution of GMI retrieved surface snow water closer to the CPR estimates. This research explores the application of spaceborne microwave measurements to snowfall studies by combining CloudSat and GPM instruments. It provides new knowledge on snowflake microphysics and applicable methods in retrieving three–dimensional snow water distribution from passive high frequency microwave measurements. / 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. / Spring Semester 2019. / March 7, 2019. / Includes bibliographical references. / Guosheng Liu, Professor Directing Dissertation; Eric Chicken, University Representative; Jon E. Ahlquist, Committee Member; Mark A. Bourassa, Committee Member; Ming Cai, Committee Member.

This study explores sensitivity of the Atlantic subtropical anticyclone and the tracks of tropical cyclones traveling around the subtropical anticyclone to radiative transfer. The data sets for these experiments are derived from 120-hours forecasts generated using the T126 version of the Florida State University Global Spectral Model (FSUGSM). The subtropical anticyclone owes its origin, maintenance, and its asymmetrical nature over the Atlantic Ocean mainly due to radiative cooling over the eastern ocean. This being the case, it follows that the way radiative properties are modeled will play a crucial role in determining the reliability of a forecast. In order to examine this, the full FSUGSM is compared to a version with no radiative properties. This represents the most extreme case and shows the significance of radiative properties on not only the subtropical anticyclone, but also the flow associated with it, and thus the tracks of tropical cyclones traversing the Atlantic Ocean. Since the subtropical anticyclone is the dominant factor in the steering flow, it follows that changes in the tropical cyclones' tracks occur in concert with changes seen in the anticyclone under different radiative conditions. The effects of (no) radiation take about three days to manifest themselves. The subtropical high weakens, and broadens westward without radiative cooling to maintain it. In turn, the orientation of the subtropical high changes as does the steering pattern. Due to this there is a change seen in the tracks of the tropical cyclones. The cyclones are more to the west and south compared to the normal model. Thus, radiation is an important factor in the forecasts of tropical cyclones and their steering environment three days or greater. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Degree Awarded: Fall Semester, 2007. / Date of Defense: October 25, 2007. / Azores High, Subtropical High, Florida State University Global Spectral Model, FSUGSM, Bermuda High, Tropical Cyclone, Tropical Cyclone Steering / Includes bibliographical references. / T. N. Krishnamurti, Professor Directing Thesis; Robert E. Hart, Committee Member; Guosheng Liu, Committee Member.

Improved knowledge of thunderstorm behavior near the end of its lifecycle is essential to improving the prediction of lightning cessation. This study documents the characteristics of decaying storms near the end of their lightning activity at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). Total lightning data were obtained by combining information from the Lightning Detection and Ranging (LDAR) network with the Cloud-to-Ground-Surveillance System (CGLSS) and the National Lightning Detection Network (NLDN). The lightning data were used in conjunction with WSR-88D radar data and Rapid Update Cycle (RUC) model analyses. The study focuses on a dataset of 116 isolated unicellular and multicellular storms during the warm-seasons (May-September) of 2000-2005. Twenty of the 116 storms were tracked through lightning cessation using the K-Means storm clustering and tracking algorithm within the Warning Decision Support System – Integrated Information (WDSS-II). This tracking yielded time-series of radar-derived, RUC-derived, and lightning parameters. Flash characteristics of the 116 storms showed trends during storm growth and dissipation; however, none exhibited clear relationships with the final flash. Although most storms experienced gradually decaying flash rates until cessation, two other cessation behaviors also were observed, making flash activity an unreliable indicator of cessation. Trends in composite reflectivity, reflectivity at three temperatures crucial to storm electrification (i.e., 0°C, -10°C, -20°C), storm thickness of 30 dBZ above -10°C, and vertical gradients of reflectivity were analyzed for 20 storms during the 8 min period prior to cessation to determine if any indicated imminent cessation. Results showed substantial variability in the decaying storms. Although these parameters decreased in most storms during the 8 min period, some increased. Distributions of the parameters at the last flash also were considered, but no clearly preferred value was evident at the last flash. Neither the inversion of lightning initiation criteria (e.g., 40 dBZ at -10°C) nor the descent of 45 dBZ below -10°C were found to be a useful indicator of cessation. Previously-documented lightning "bubbles" of LDAR sources were observed and were consistent with pulses in the intensifying updrafts. The last lightning "bubble" signatures were found to precede lightning cessation by ~35 min. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Degree Awarded: Spring Semester, 2010. / Date of Defense: December 9, 2009. / Lightning Cessation, Total Lightning, LDAR, WDSS-II, NASA, Forcasting / Includes bibliographical references. / Henry E. Fuelberg, Professor Directing Thesis; Paul H. Ruscher, Committee Member; Robert E. Hart, Committee Member.

Extensive analysis has been conducted over past decades showing the impacts of El Niño-Southern Oscillation (ENSO) on various regions throughout the world. However, these studies have not analyzed data from many stations in Panama, or they have not analyzed long periods of observations. For these reasons, they often miss climatological differences within the region induced by topography, or they do not possess enough observations to adequately study its climatology. Accordingly, the current study focuses on ENSO impacts on precipitation specific to the Isthmus of Panama. Results will be useful for agricultural and water resources planning and Panama Canal operations. Monthly total precipitation data were provided by Empresa de Transmisión Eléctrica S.A., which includes 32 stations with records from 1960 to 2004. The year is split into three seasons: two wet seasons (Early and Late Wet), one dry season (Dry). The country is also divided into regions according to similarities in the stations' climatology and geographic locations. Upper and lower precipitation extremes are associated with one of the three ENSO phases (warm, cold or neutral) to estimate their percentages of occurrences. The differences between each ENSO phases' seasonal precipitation distributions are statistically examined. Statistical analyses show effects of ENSO phases that vary by season and geographical region. Cold and warm ENSO years affect the southwestern half of the country considerably during the Late Wet season. Cold ENSO phases tend to increase rainfall, and the warm phase tends to decrease it. The opposite is true for the Caribbean coast. The Dry season experiences drier conditions in warm ENSO years, and the Early Wet season does not show any statistically significant difference between ENSO years' rainfall distributions. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Degree Awarded: Summer Semester, 2006. / Date of Defense: October 13, 2005. / Extreme Events Central America, Low Level Circulation / Includes bibliographical references. / James J. O'Brien, Professor Directing Thesis; Paul Ruscher, Committee Member; Robert Hart, Committee Member.

Daily maximum and minimum temperature data from 758 COOP stations in nineteen states are used to create temperature decile maps. All stations used contain records from 1948 through 2004 and could not be missing more than 5 consecutive years of data. Missing data are replaced using a multiple linear regression technique from surrounding stations. For each station, the maximum and minimum temperatures are first sorted in ascending order for every two years (to reduce annual variability) and divided into ten equal parts (or deciles). The first decile represents the coldest temperatures, and the last decile contains the warmest temperatures. Patterns and trends in these deciles can be examined for the 57-year period. A linear least-squares regression method is used to calculate best-fit lines for each decile to determine the long-term trends at each station. Significant warming or cooling is determined using the Student's t-test, and bootstrapping the decile data will further examine the validity of significance. Two stations are closely examined. Apalachicola, Florida shows significant warming in its maximum deciles and significant cooling in its minimum deciles. The maximum deciles seem to be affected by some localized change. The minimum deciles are discontinuous, and the trends are a result of a minor station move. Columbus, Georgia has experienced significant warming in its minimum deciles, and this appears to be the result of an urban heat-island effect. The discontinuities seen in the Apalachicola case study illustrate the need for a quality control method. This method will eliminate stations from the regional analysis that experience large changes in the ten-year standard deviations within their time series. The regional analysis shows that most of the region is dominated by significant cooling in the maximum deciles and significant warming in the minimum deciles, with more variability in the lower deciles. Field significance testing is performed on subregions (based on USGS 2000 land cover data) and supports the findings from the regional analysis; it also isolates regions, such as the Florida peninsula and the Maryland/Delaware region, that appear to be affected by more local forcings. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Degree Awarded: Summer Semester, 2007. / Date of Defense: May 31, 2007. / Long term temperature trends, Climate change, Statistical analysis, Climatology / Includes bibliographical references. / James J. O'Brien, Professor Directing Thesis; Mark A. Bourassa, Committee Member; Paul H. Ruscher, Committee Member.