Browsing by Author "Rutledge, Steven A., committee member"
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Item Open Access A method to combine spaceborne radar and radiometric observations of precipitation(Colorado State University. Libraries, 2010) Munchak, Stephen Joseph, author; Kummerow, Christian Detlef, advisor; Chandrasekhar, V., committee member; Rutledge, Steven A., committee member; Stephens, Graeme L., 1952-, committee memberThis dissertation describes the development and application of a combined radar-radiometer rainfall retrieval algorithm for the Tropical Rainfall Measuring Mission (TRMM) satellite. A retrieval framework based upon optimal estimation theory is proposed wherein three parameters describing the raindrop size distribution (DSD), ice particle size distribution (PSD), and cloud water path (cLWP) are retrieved for each radar profile. The retrieved rainfall rate is found to be strongly sensitive to the a priori constraints in DSD and cLWP; thus, these parameters are tuned to match polarimetric radar estimates of rainfall near Kwajalein, Republic of Marshall Islands. An independent validation against gauge-tuned radar rainfall estimates at Melbourne, FL shows agreement within 2% which exceeds previous algorithms' ability to match rainfall at these two sites. The algorithm is then applied to two years of TRMM data over oceans to determine the sources of DSD variability. Three correlated sets of variables representing storm dynamics, background environment, and cloud microphysics are found to account for approximately 50% of the variability in the absolute and reflectivity-normalized median drop size. Structures of radar reflectivity are also identified and related to drop size, with these relationships being confirmed by ground-based polarimetric radar data from the North American Monsoon Experiment (NAME). Regional patterns of DSD and the sources of variability identified herein are also shown to be consistent with previous work documenting regional DSD properties. In particular, mid-latitude regions and tropical regions near land tend to have larger drops for a given reflectivity, whereas the smallest drops are found in the eastern Pacific Intertropical Convergence Zone. Due to properties of the DSD and rain water/cloud water partitioning that change with column water vapor, it is shown that increases in water vapor in a global warming scenario could lead to slight (1%) underestimates of a rainfall trends by radar but larger overestimates (5%) by radiometer algorithms. Further analyses are performed to compare tropical oceanic mean rainfall rates between the combined algorithm and other sources. The combined algorithm is 15% higher than the version 6 of the 2A25 radar-only algorithm and 6.6% higher than the Global Precipitation Climatology Project (GPCP) estimate for the same time-space domain. Despite being higher than these two sources, the combined total is not inconsistent with estimates of the other components of the energy budget given their uncertainties.Item Open Access A triple-moment bulk hail microphysics scheme to investigate the sensitivities of hail to aerosols(Colorado State University. Libraries, 2012) Loftus, Adrian Matthew, author; Cotton, William R., advisor; Rutledge, Steven A., committee member; van den Heever, Susan C., committee member; Bringi, Viswanathan N., committee memberHail is a frequent occurrence in warm season deep convection in many mid-latitude regions and causes significant damage to property and agricultural interests every year. Hail can also have a substantial impact on the precipitation characteristics of deep convection as well as on the dynamic and thermodynamic properties of convective downdrafts and cold-pools, which in turn can affect storm evolution and propagation. In addition, large and often destructive hail commonly occurs in severe convection, yet most one- (1M) and two-moment (2M) bulk microphysics schemes in cloud-resolving numerical models are incapable of producing large hail (diameter D ≥ 2 cm). The limits imposed by fixing one or two of the distribution parameters in these schemes often lead to particularly poor representations of particles within the tails of size distribution spectra; an especially important consideration for hail, which covers a broad range of sizes in nature. In order to improve the representation of hail distributions in simulations of deep moist convection in a cloud-resolving numerical model, a new triple-moment bulk hail microphysics scheme (3MHAIL) is presented and evaluated. The 3MHAIL scheme predicts the relative dispersion parameter for a gamma distribution function via the prediction of the sixth moment (related to the reflectivity factor) of the distribution in addition to the mass mixing ratio and number concentration (third and zeroeth moments, respectively) thereby allowing for a fully prognostic distribution function. Initial testing of this scheme reveals significant improvement in the representation of sedimentation, melting, and formation processes of hail compared to lower-order moment schemes. The 3MHAIL scheme is verified in simulations of a well-observed supercell storm that occurred over northwest Kansas on 29 June 2000 during the Severe Thunderstorm and Electrification and Precipitation Study (STEPS). Comparisons of the simulation results with the observations for this case, as well as with results of simulations using two different 2M microphysics schemes, suggest a significant improvement of the simulated storm structure and evolution is achieved with the 3MHAIL scheme. The generation of large hail and subsequent fallout in the simulation using 3MHAIL microphysics show particularly good agreement with surface hail reports for this storm as well as with previous studies of hail in supercell storms. On the other hand, the simulation with 2M microphysics produces only small hail aloft and virtually no hail at the surface, whereas a two-moment version of the 3MHAIL scheme (with a fixed relative dispersion parameter) produces unrealistically high amounts of large hail at low levels as a result of artificial shifts in the hail size spectra towards larger diameter hail during the melting process. The 3MHAIL scheme is also used to investigate the impact of changing the concentrations of aerosols that act as cloud condensation nuclei (CCN) on hail for the 29 June 2000 supercell case. For the simulated supercells in the particular environment examined, an increase in CCN from 100 to 3000 cm-3 leads to an increase in the numbers and a decrease in the sizes of cloud droplets, as expected, yet the overall storm dynamics and evolution are largely unaffected. Increases in CCN lead to non-monotonic responses in the bulk characteristics of nearly all hydrometeor fields, surface precipitation, and cold-pool strength. However, higher concentrations of CCN also result in larger hail sizes and greater amounts of large diameter (≥ 2 cm) hail both aloft as well as at the surface. Analyses of the hail formation and growth mechanisms for these simulations suggest that the combination of increased sizes of new hail particles and localized reductions in numbers of new hailstones forming near maximum growth regions with increasing CCN tends to promote conditions that lead to increased hail sizes and amounts of large hail.Item Open Access Aqueous phase sulfate production in clouds at Mt. Tai in eastern China(Colorado State University. Libraries, 2011) Shen, Xinhua, author; Collett, Jeffrey L., advisor; Kreidenweis, Sonia M., committee member; Rutledge, Steven A., committee member; Reynolds, Stephen J., committee memberClouds play an important role in the oxidation of sulfur dioxide to sulfate, since aqueous phase sulfur dioxide oxidation is typically much faster than oxidation in the gas phase. Important aqueous phase oxidants include hydrogen peroxide, ozone and oxygen (catalyzed by trace metals). Because quantities of emitted sulfur dioxide in China are so large, however, it is possible that they exceed the capacity of regional clouds for sulfate production, leading to enhanced long-range transport of emitted SO2 and its oxidation product, sulfate. In order to assess the ability of regional clouds to support aqueous sulfur oxidation, four field campaigns were conducted in 2007 and 2008 at Mt. Tai in eastern China. Single and 2-stage Caltech Active Strand Cloudwater Collectors were used to collect bulk and drop size-resolved cloudwater samples, respectively. Key species that determine aqueous phase sulfur oxidation were analyzed, including cloudwater pH, S(IV), H2O2, Fe, and Mn. Gas phase SO2, O3, and H2O2 were also measured continuously during the campaigns. Other species in cloudwater, including inorganic ions, total organic carbon (TOC), formaldehyde, and organic acids were also analyzed to provide a fuller view of cloud chemistry in the region. Numerous periods of cloud interception/fog occurred during the four Mt. Tai field campaigns; more than 500 cloudwater samples were collected in total. A wide range of cloud pH values was observed, from 2.6 to 7.6. SO42-, NO3-, and NH4+ were the major inorganic species for all four campaigns. TOC concentrations were also very high in some samples (up to 200 ppmC), especially when clouds were impacted by emissions from agricultural biomass burning. Back-trajectory analysis also indicated influence by dust transport from northern China in a few spring cloud events. Differences between the compositions of small and large cloud droplets were observed, but generally found to be modest for major solute species and pH. Mt. Tai clouds were found to interact strongly with PM2.5 sulfate, nitrate, and ammonium with average scavenging efficiencies of 80%, 75%, and 78%, respectively, across 7 events studied. Scavenging efficiencies for total sulfur (PM2.5 sulfate plus gaseous sulfur dioxide), however, averaged only 43%, indicating the majority of gaseous sulfur dioxide remained unprocessed in these cloud events. H2O2 was found to be the most important oxidant for aqueous sulfate production 68% of the time. High concentrations of residual H2O2 were measured in some samples, especially during summertime, implying a substantial capacity for additional sulfur oxidation. The importance of ozone as a S(IV) oxidant increased substantially as cloud pH climbed above pH 5 to 5.3. Overall, ozone was found to be the most important aqueous S(IV) oxidant in 21% of the sampling periods. Trace metal-catalyzed S(IV) autooxidation was determined to be the fastest aqueous sulfate production pathway in the remaining 11% of the cases. Complexation with formaldehyde was also found to be a potentially important fate for aqueous S(IV) and should be examined in more detail in future studies. Observed chemical heterogeneity among cloud drop populations was predicted to enhance rates of S(IV) oxidation by ozone and enhance or slow metal-catalyzed S(IV) autooxidation rates in some periods. These effects were found to be only of minor importance, however, as H2O2 was the dominant S(IV) oxidant most of the time.Item Open Access Cold pool processes in different environments(Colorado State University. Libraries, 2018) Grant, Leah Danielle, author; van den Heever, Susan C., advisor; Randall, David A., committee member; Rutledge, Steven A., committee member; Niemann, Jeffrey D., committee memberCold pools are localized regions of dense air near Earth's surface. They form in association with precipitating clouds in many environments ranging from moist tropical to semi-arid continental conditions, and they play important roles in weather in climate. The overarching goal of this dissertation research is to improve our process-level understanding of cold pool interactions with different components of the Earth system, focusing on two key knowledge gaps: (1) interactions with Earth's surface in continental environments; and (2) interactions with organized convective systems in tropical oceanic environments. The primary goal of the first study conducted in this dissertation is to evaluate how surface sensible heat fluxes impact cold pool dissipation in dry continental environments via two pathways: (a) by directly heating the cold pool, and (b) by changing mixing rates between cold pool air and environmental air through altering turbulence intensity. Idealized 2D simulations of isolated cold pools are conducted with varying sensible heat flux formulations to determine the relative importance of these two mechanisms. The results demonstrate that the impact of sensible heat fluxes on mixing, i.e. mechanism (b), contributes most significantly to cold pool dissipation. Cold pool – land surface interactions in semi-arid continental conditions are investigated in the second study. Two questions are addressed: (1) how does the land surface respond to the cold pool; and (2) to what extent do land surface feedbacks modulate the cold pool evolution? Idealized 3D simulations of a cold pool evolving in a turbulent boundary layer are conducted to answer these questions. The land surface cools in response to the cold pool, resulting in suppressed sensible heat fluxes in the center of the cold pool. However, sensible heat fluxes are enhanced near the edge of the cold pool in association with higher wind speeds, leading to cold pool dissipation from the edge inwards. The land surface interactions are shown to strongly affect the cold pool, reducing its lifetime, size, and intensity by up to 50%. Preliminary analysis of a cold pool that was observed in northeastern Colorado on 17 May 2017 ("The Bees Day") during the C3LOUD-Ex field campaign is presented in the third study. The observed case exhibits similar environmental and cold pool characteristics to the first two numerical studies, thereby providing observational context for their hypotheses and conclusions. The objective of the fourth study presented in this dissertation is to determine the role of cold pools in organized tropical oceanic convective systems. To address this goal, two convective systems embedded in a weakly sheared cloud population approaching radiative-convective equilibrium are simulated at high resolution. The cold pools are weakened in the sensitivity tests by suppressing evaporation rates below cloud base. Both of the convective systems respond in a consistent manner as follows: (a) when cold pools are weakened, the convective intensity increases; and (b) the mesoscale structure, propagation speeds, and system lifetimes are insensitive to the changes in the cold pools, in contrast to the prevailing (RKW) theory that cold pools are critical to the mesoscale organization of convective systems. In summary, these high-resolution modeling and observational studies demonstrate new insights into cold pool – surface – convection interactions. The results suggest that cold pool interactions with different components of the Earth system are not all created equally; rather, these interactions depend on the environment in which the cold pools find themselves.Item Open Access Estimation and correction of wet ice attenuation for x-band radar(Colorado State University. Libraries, 2010) Leon Colon, Leyda V., author; Bringi, V. N., 1949-, advisor; Chandrasekar, V., committee member; Reising, Steven C., committee member; Rutledge, Steven A., committee memberIn the past, single polarized X-band radars were primarily used (along with S-band radars) for hail detection, first by the Russians and then later for the National Hail Research Experiment (NHRE). But X-band radars were not used alone because of the large attenuation at frequencies around 10 GHz and higher, until dual-polarized radars were developed. This fact has brought attention to development and evaluation of correction techniques for rain attenuation in order to exploit the advantages of dual-polarized data. Past developed methods make use of the close relation between the differential propagation phase ΦDP and path attenuation PIA. Their use is known to be successful in rain events, but in the presence of wet ice, these methods are no longer useful because the differential propagation phase is not affected by the isotropic wet ice. This factor was the basis to develop herein two different techniques for estimating the attenuation due to rain and wet ice separately and correct for the wet ice induced attenuation. In this dissertation, two methods are investigated and evaluated. The first method uses the Surface Reference Technique (SRT) α-adjustment method to correct for the attenuation. This method was first developed for the Tropical Rainfall Measuring Mission (TRMM) precipitation radar. We assume that S-band data is un-attenuated and is used as a reference. The difference in reflectivities at the end of the beam (defined as the average of the last ten gates with 'good' data) is attributed to the total attenuation (sum of rain and any wet ice) along the propagation path. The attenuation due to the rain component, if any, is corrected for using the differential propagation phase. Then the α value in the Ah(X)wet ice-Zh(X) power law relationship (with fixed exponent β) is adjusted such that the reflectivities at S-band and the rain-corrected reflectivity at X-band at the end of the beam are forced to match. This adjusted α is used to apportion the reflectivity backwards, which assumes the α parameter is constant along the beam. Using the adjusted value, the attenuation due to wet ice is estimated separately from that of rain. This method is termed here as the SRT-modified correction method. This method has been applied to different datasets. It was evaluated in both simulated and measured radar data. Using the Regional Atmospheric Modeling System (RAMS) model a supercell was simulated by Professor's Cotton's group at Colorado State University (CSU). A radar emulator was used to simulate radar measurements from this supercell at both X-band and S-bands. Results showed good agreement of both corrected reflectivity profiles and wet ice specific attenuation estimation. A dataset from the International H2O Project (IHOP) that had rain mixed with wet ice particles (mixed phase region) was analyzed too. It showed good agreement also, when comparing profiles; moreover wet ice attenuation contours showed agreement with high values of reflectivity as expected in wet ice regions. Data collected by the Center for Adaptive Sensing of the Atmosphere (CASA) radar network was analyzed along with both Next Generation Radars (NEXRAD) KTLX and KOUN data. For the light rain event (CASA/KTLX), the dual wavelength ratio at the maximum range was close to unity as expected for Rayleigh scattering. When corrected for wet ice, the specific attenuation showed agreement with high values in reflectivity at both bands. Finally, this method was applied to two different Cloud Physics Radar (CP2) radar data sets. In the CP2 data analysis, Mie hail signals were eliminated for the purpose of this research. Results from both datasets showed that resulting corrected reflectivity was comparable to the un-attenuated S-band data. Given that an un-attenuated reference signal, like the one described before, might not always be available, a second method was developed without this assumption. This second method estimates the wet ice specific attenuation using a Ah(X)wet ice-Zh(X) power law relation with fixed coefficients. These fixed coefficients were retrieved using the same CP2 datasets and compared with previous findings. Then, assuming that the reflectivity is already corrected for rain attenuation, the Hitschfeld-Bordan forward correction method is used. To determine the areas where the correction method will be applied the Hydrometeor Identification (HID) algorithm was used. The HID data is used here to locate the first 'good' range gate of the mixed phase region containing the wet ice. This method is termed as the Piece-Wise Forward correction method (PWF). Similar to the first method, this second method was applied to different datasets. First it was applied to one of the two CP2 datasets available, where the Mie 'hail' signal was eliminated. The resulting corrected reflectivity showed good agreement compared with the S-band un-attenuated reflectivity. Also this method was applied to the same convective dataset (from CASA) as the one previously analyzed with the SRT-modified method. It presented higher reflectivity values in wet ice identified areas, but lower values than those presented by the SRT-modified method. The results were also compared with the Networked Based (NB) method.Item Open Access Examination of the potential impacts of dust and pollution aerosol acting as cloud nucleating aerosol on water resources in the Colorado River Basin(Colorado State University. Libraries, 2016) Jha, Vandana, author; Cotton, William R., advisor; Rutledge, Steven A., committee member; Pierce, Jeffrey, committee member; Ramirez, Jorge, committee memberIn this study we examine the cumulative effect of dust acting as cloud nucleating aerosol (cloud condensation nuclei (CCN), giant cloud condensation nuclei (GCCN), and ice nuclei (IN)) along with anthropogenic aerosol pollution acting primarily as CCN, over the entire Colorado Rocky Mountains from the months of October to April in the year 2004-2005; the snow year. This ~6.5 months analysis provides a range of snowfall totals and variability in dust and anthropogenic aerosol pollution. The specific objectives of this research is to quantify the impacts of both dust and pollution aerosols on wintertime precipitation in the Colorado Mountains using the Regional Atmospheric Modeling System (RAMS). In general, dust enhances precipitation primarily by acting as IN, while aerosol pollution reduces water resources in the CRB via the so-called “spill-over” effect, by enhancing cloud droplet concentrations and reducing riming rates. Dust is more episodic and aerosol pollution is more pervasive throughout the winter season. Combined response to dust and aerosol pollution is a net reduction of water resources in the CRB. The question is by how much are those water resources affected? Our best estimate is that total winter-season precipitation loss for for the CRB the 2004-2005 winter season due to the combined influence of aerosol pollution and dust is 5,380,00 acre-feet of water. Sensitivity studies for different cases have also been run for the specific cases in 2004-2005 winter season to analyze the impact of changing dust and aerosol ratios on precipitation in the Colorado River Basin. The dust is varied from 3 to 10 times in the experiments and the response is found to be non monotonic and depends on various environmental factors. The sensitivity studies show that adding dust in a wet system increases precipitation when IN affects are dominant. For a relatively dry system high concentrations of dust can result in over-seeding the clouds and reductions in precipitation. However, when adding dust to a system with warmer cloud bases, the response is non-monotonical, and when CCN affects are dominant, reductions in precipitation are found.Item Open Access Exploring the limits of variational passive microwave retrievals(Colorado State University. Libraries, 2017) Duncan, David Ian, author; Kummerow, Christian D., advisor; Boukabara, Sid-Ahmed, committee member; O'Dell, Christopher W., committee member; Reising, Steven C., committee member; Rutledge, Steven A., committee member; Schumacher, Russ S., committee memberPassive microwave observations from satellite platforms constitute one of the most important data records of the global observing system. Operational since the late 1970s, passive microwave data underpin climate records of precipitation, sea ice extent, water vapor, and more, and contribute significantly to numerical weather prediction via data assimilation. Detailed understanding of the observation errors in these data is key to maximizing their utility for research and operational applications alike. However, the treatment of observation errors in this data record has been lacking and somewhat divergent when considering the retrieval and data assimilation communities. In this study, some limits of passive microwave imager data are considered in light of more holistic treatment of observation errors. A variational retrieval, named the CSU 1DVAR, was developed for microwave imagers and applied to the GMI and AMSR2 sensors for ocean scenes. Via an innovative method to determine forward model error, this retrieval accounts for error covariances across all channels used in the iteration. This improves validation in more complex scenes such as high wind speed and persistently cloudy regimes. In addition, it validates on par with a benchmark dataset without any tuning to in-situ observations. The algorithm yields full posterior error diagnostics and its physical forward model is applicable to other sensors, pending intercalibration. This retrieval is used to explore the viability of retrieving parameters at the limits of the available information content from a typical microwave imager. Retrieval of warm rain, marginal sea ice, and falling snow are explored with the variational retrieval. Warm rain retrieval shows some promise, with greater sensitivity than operational GPM algorithms due to leveraging CloudSat data and accounting for drop size distribution variability. Marginal sea ice is also detected with greater sensitivity than a standard operational retrieval. These studies ultimately show that while a variational algorithm maximizes the effective signal to noise ratio of these observations, hard limitations exist due to the finite information content afforded by a typical microwave imager.Item Open Access Improving the quality of extreme precipitation estimates using satellite passive microwave rainfall retrievals(Colorado State University. Libraries, 2017) Petković, Veljko, author; Kummerow, Christian D., advisor; Vonder Haar, Thomas H., committee member; Rutledge, Steven A., committee member; Niemann, Jeffrey D., committee memberSatellite rainfall estimates are invaluable in assessing global precipitation. As a part of the Global Precipitation Measurement (GPM) mission, a constellation of orbiting sensors, dominated by passive microwave imagers, provides a full coverage of the planet approximately every 2-3 hours. Several decades of development have resulted in passive microwave rainfall retrievals that are indispensable in addressing global precipitation climatology. However, this prominent achievement is often overshadowed by the retrieval's performance at finer spatial and temporal scales, where large variability in cloud morphology poses an obstacle for accurate rainfall measurements. This is especially true over land, where rainfall estimates are based on an observed mean relationship between high frequency (e.g., 89 GHz) brightness temperature (Tb) depression (i.e., the ice-scattering signature) and rainfall rate. In the first part of this study, an extreme precipitation event that caused historical flooding over south-east Europe is analyzed using the GPM constellation. Performance of the rainfall retrieval is evaluated against ground radar and gage reference. It is concluded that satellite observations fully address the temporal evolution of the event but greatly underestimate total rainfall accumulation (by factor of 2.5). A primary limitation of the rainfall algorithm is found to be its inability to recognize variability in precipitating system structure. This variability is closely related to the structure of the precipitation regime and the large-scale environment. To address this influence of rainfall physics on the overall retrieval bias, the second part of this study utilizes TRMM radar (PR) and radiometer (TMI) observations to first confirm that the Tb-to-rain-rate relationship is governed by the amount of ice in the atmospheric column. Then, using the Amazon and Central African regions as testbeds, it demonstrates that the amount of ice aloft is strongly linked to a precipitation regime. A correlation found between the large-scale environment and precipitation regimes is then further examined. Variables such as Convective Available Potential Energy (CAPE), Cloud Condensation Nuclei (CCN), wind shear, and vertical humidity profiles are found to be capable of predicting a precipitation regime and explaining up to 40% of climatological biases. Dry over moist air conditions are favorable for developing intense, well organized systems such as MCSs in West Africa and the Sahel. These systems are characterized by strong Tb depressions and above average amounts of ice aloft. As a consequence, microwave retrieval algorithms misinterpret these non-typical systems assigning them unrealistically high rainfall rates. The opposite is true in the Amazon region, where observed raining systems exhibit relatively little ice while producing high rainfall rates. Based on these findings, in the last part of the study, the GPM operational retrieval (GPROF) for the GMI sensor is modified to offer additional information on atmospheric conditions to its Bayesian-based algorithm. When forming an estimate, the modified algorithm is allowed to use this ancillary information to filter out a priori states that do not match the general environmental condition relevant to the observation and thus reduce the difference between the assumed and observed variability in ice-to-rain ratio. The results are compared to the ground Multi-Radar Multi-Sensor (MRMS) network over the US at various spatial and temporal scales demonstrating outstanding potentials in improving the accuracy of rainfall estimates from satellite-borne passive microwave sensors over land.Item Open Access Multi-scale interactions leading to tropical cyclogenesis in sheared environments(Colorado State University. Libraries, 2021) Nam, Chaehyeon Chelsea, author; Bell, Michael M., advisor; Rutledge, Steven A., committee member; Maloney, Eric D., committee member; Reising, Steven C., committee memberTo be, or not to be, that is the question of tropical cyclogenesis. Only a small fraction of tropical disturbances eventually develop into tropical cyclones (TCs). Accurate forecasts of tropical cyclogenesis are difficult because TC development involves a wide range of scales from the stochastic convective scale to a quasi-balanced large-scale flow. This dissertation examines the factors that increase uncertainty around the multi-scale tropical cyclogenesis problem, namely, vertical wind shear (VWS), environmental humidity, and convective organization. These factors were explored using multiple data sources including observations such as dual-Doppler radar, dropsonde soundings, and satellite data for mesoscale case studies, reanalyses data for synoptic and climatological analysis, and extensive ensemble mesoscale modeling for controlled experiments. First, this dissertation presents a detailed observational analysis for multi-scale processes around an incipient wave pouch of Hagupit (2008) that survived through strong VWS and underwent TC genesis. The strong deep-layer VWS (> 20 m s-1) had a negative impact on the development through misalignment of the low and mid-level circulations and dry air intrusion. However, the low-level circulation persisted and the system ultimately formed into a tropical cyclone after it had left the high-shear zone. Here we propose that a key process that enabled the pre-depression to survive through the upper-tropospheric trough interaction was persistent vorticity amplification on the meso-γ scale that was aggregated on the meso-α scale within the wave pouch. In the second part, twelve sets of Weather Research and Forecasting ensemble simulations were created to examine the combined impacts of VWS, environmental moisture, and the structure of the precursor vortex on the uncertainty of TC genesis. Here we hypothesized that the combination of moderate shear and dry air makes an unstable condition for a vortex to intensify or decay, which implies that TC genesis in such environments may be intrinsically unpredictable in a deterministic sense. Based on the close examination of selected ensemble members and statistical analysis of geometric probability distribution and time-lagged correlations for all ensemble sets, we propose a theoretical pyramid diagram of the five processes leading to TC genesis in sheared and dry environments. First, inside their low-level circulations, deep convection emerged over a wider area. Second, a new smaller scale mid-level vortex formed inside the deep convection where the pre-existing mid-level vortex was carried away by VWS. Third, the mid-level vortex and low-level vortex went through a vertical alignment process. Fourth, with sustained vortex alignment, convection organized near the low-level center. Fifth, central pressure fell and wind speed increased; and the system reached tropical cyclone intensity. The results suggest that all successfully developing TCs share a common set of precursor events that lead to TC genesis, while a deficiency in any of the precursor events leads to a failure of genesis. In the third part, we investigated the likelihood of subsequent TC genesis from the "monsoon tail" rainband for TCs in the monsoonal area of the western North Pacific (WNP). The monsoon tail rainband—an elongated rainband in the southwestern quadrant of the TC—is shown to be a common feature for TCs in the WNP due to the climatological northeasterly VWS. Variations in the convective activity are shown to be related to the strength of the low-level and upper-level monsoonal flow on synoptic and seasonal timescales, with VWS having the highest correlation to cold cloud tops in the southwest quadrant. Some monsoon tail rainbands sustain convective organization even after they separated from the pre-existing TCs, but despite the enhanced convective activity, the persistent VWS that produced the rainbands was an overriding negative factor that inhibits genesis. This dissertation provides a detailed look at the complex interactions between VWS and the incipient TC depending on spatial scales, the vertical depth of shear, environmental moisture, and the structure of the TC vortex. The findings herein improve our process-based understanding of why moderate VWS, especially in combination with environmental dry air, produces unstable and uncertain conditions for TC genesis.Item Open Access Retrieval techniques and information content analysis to improve remote sensing of atmospheric water vapor, liquid water and temperature from ground-based microwave radiometer measurements(Colorado State University. Libraries, 2015) Sahoo, Swaroop, author; Reising, Steven C., advisor; Notaros, Branislav M., committee member; Vivekanandan, Jothiram, committee member; Rutledge, Steven A., committee memberTo view the abstract, please see the full text of the document.Item Open Access Simulating southwestern U.S. desert dust influences on severe, tornadic storms(Colorado State University. Libraries, 2012) Lerach, David Gregory, author; Cotton, William R., advisor; Rutledge, Steven A., committee member; Kreidenweis, Sonia M., committee member; Roesner, Larry A., committee memberIn this study, three-dimensional numerical simulations were performed using the Regional Atmospheric Modeling System (RAMS) model to investigate possible southwestern U.S. desert dust impacts on severe, tornadic storms. Initially, two sets of simulations were conducted for an idealized supercell thunderstorm. In the first set, two numerical simulations were performed to assess the impacts of increased aerosol concentrations acting as cloud condensation nuclei (CCN) and giant CCN (GCCN). Initial profiles of CCN and GCCN concentrations were set to represent "clean" continental and aerosol-polluted environments, respectively. With a reduction in warm- and cold-rain processes, the polluted environment produced a longer-lived supercell with a well-defined rear flank downdraft (RFD) and relatively weak forward flank downdraft (FFD) that produced weak evaporative cooling, a weak cold-pool, and an EF-1 tornado. The clean environment produced no tornado and was less favorable for tornadogenesis. In the second ensemble, aerosol microphysical effects were put into context with those of convective available potential energy (CAPE) and low-level moisture. Simulations initialized with greater low-level moisture and higher CAPE produced significantly stronger precipitation, which resulted in greater evaporation and associated cooling, thus producing stronger cold-pools at the surface associated with both the forward- and rear-flank downdrafts. Simulations initialized with higher CCN concentrations resulted in reduced warm rain and more supercooled water aloft, creating larger anvils with less ice mass available for precipitation. These simulated supercells underwent less evaporative cooling within downdrafts and produced weaker cold-pools compared to the lower CCN simulations. Tornadogenesis was related to the size, strength, and location of the FFD- and RFD-based cold-pools. The combined influence of low-level moisture and CAPE played a considerably larger role on tornadogenesis compared to aerosol impacts. However, the aerosol effect was still evident. In both idealized model ensembles, the strongest, longest-lived tornado-like vortices were associated with warmer and weaker cold-pools, higher CAPE, and less negative buoyancy in the near-vortex environment compared to those storms that produced shorter-lived, weaker vortices. A final set of nested grid simulations were performed to evaluate dust indirect microphysical and direct radiative impacts on a severe storms outbreak that occurred during 15-16 April 2003 in Texas and Oklahoma. In one simulation, neither dust microphysical nor radiative effects were included (CTL). In a second simulation, only dust radiative effects were considered (RAD). In a third simulation, both dust radiative and indirect microphysical effects were simulated (DST), where dust was allowed to serve as CCN, GCCN, and ice nuclei (IN). Fine mode dust serving as CCN reduced warm rain formation in the DST simulation. Thus, cloud droplets were transported into the mixed phase region, enhancing freezing, aggregation, and graupel and hail production. However, graupel and hail were of smaller sizes in the DST simulation due to reduced riming efficiencies. Dust particles serving as GCCN and IN played secondary roles, as these impacts were offset by other processes. The DST simulation yielded the lowest rainfall rates and accumulated precipitation, as much of the total water mass within the convective cells were in the form of aggregates and small graupel particles that were transported into the anvil region rather than falling as precipitation. The combined effects of warm rain efficiency, ice production, and hydrometeor size controlled the evolution of cold-pools and storm structure. The RAD and CTL simulations produced widespread cold-pools, which hindered the formation of long-lived supercells relative to the DST simulation. The DST convective line was associated with reduced rainfall and multiple long-lived supercells. Comparisons between the RAD and CTL simulations revealed that dust radiative influences played an important role in convective initiation. The increased absorption of solar radiation within the dust plume in the RAD simulation warmed the dust layer over time, which reduced the amount of radiation that reached the surface, resulting in slight cooling at the surface and increased atmospheric stability within the lowest 2 km. Dew points at low levels were slightly lower in the RAD simulation, due to reduced surface water vapor fluxes (latent heat fluxes) below the dust plume. With the presence of a stronger capping inversion but more available low-level moisture, the CTL simulation initially produced more widespread convection and precipitation, while the RAD simulation produced the strongest convective cores, including a long-lived supercell. The results from all three sets of simulations suggest that dust indirect microphysical and direct radiative impacts on severe convection may at times greatly influence the development of severe storms. In this study, dust often increased the potential for tornadogenesis. Additional modeling studies at horizontal grid spacing ≤100 m are needed in order to address the robustness of these results and better isolate potential dust influences on severe storms and tornadogenesis.