Theses and Dissertations

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Open Access
Investigation of enhanced-reflectivity features embedded within a wintertime orographic cloud on 28-29 November 1984
(Colorado State University. Libraries, 1994) Baker, Ian T., author; Grant, Lewis O., advisor; Mielke, Paul W., committee member; Cotton, William R., committee member
A combination of aircraft, sounding, surface, vertically-pointing ku-Band radar and dual-channel radiometer data was used to investigate the microphysical characteristics of enhanced-reflectivity areas embedded within an orographic cloud in northwestern Colorado on 28-29 November 1984. The orographic cloud was associated with the passage of an open wave and upper-level front over the region, and embedded within the cloud were regularly-spaced areas of increased reflectivity as seen by the vertically-pointing radar. The radiometer observed a cyclical component on both the liquid and vapor channels when oriented in the vertical. Aircraft data reveal that there was supercooled liquid water in the cloud at levels as high as 41 kPa and as far as 55 km upwind of the barrier. 2D-C and 2D-P probe data indicated two crystal regimes, one where concentrations in individual size bins were larger and spectra were broader, indicating crystal growth. In the other, concentrations were smaller and size spectra were narrower. Radar data indicate that the enhanced-reflectivity regions were between 10-20 km apart, with a length dimension on the order of 5 km wide. It is believed that the presence of the enhanced-reflectivity areas is closely linked to the presence of a decoupled layer on the windward side of the barrier, and preliminary evidence points to a gravity-wave mechanism as a physical cause.
Open Access
Air quality impacts from unconventional oil and gas development
(Colorado State University. Libraries, 2024) Ku, I-Ting, author; Collett, Jeffrey L., Jr., advisor; Fischer, Emily V., committee member; Carlson, Kenneth H., committee member; Kreidenweis, Sonia, committee member
Unconventional oil and natural gas development (UOGD) has expanded rapidly across the United States raising concerns about associated air quality impacts. While significant effort has been made to quantify and limit methane emissions, relatively few observations have been made of emitted Volatile Organic Compounds (VOCs). Extensive air monitoring during development of several large, multi-well pads in Broomfield, Colorado, in the Denver-Julesburg Basin, provides a novel opportunity to examine changes in local concentrations of air toxics and other VOCs during drilling and completions of new wells. With simultaneous measurements of methane and 50 VOCs from October 2018 to December 2022 at as many as 19 sites near well pads, in adjacent neighborhoods, and at a more distant reference location, we identify impacts from each phase of well development and production. In Part 1, we report how emissions from Broomfield pre-production and production operations influence air toxics and other VOC concentrations at nearby locations. Use of weekly, time-integrated canisters, a Proton Transfer Reaction Mass Spectrometer (PTR-MS), continuous photoionization detectors (PID) to trigger canister collection upon detection of VOC-rich plumes, and an instrumented vehicle, provided a powerful suite of measurements to characterize both transient plumes and longer-term changes in air quality. Prior to the start of well development, VOC gradients were small across Broomfield. Once drilling commenced, concentrations of oil and gas (O&G) related VOCs, including alkanes and aromatics, increased around active well pads. Concentration increases were clearly apparent during certain operations, including drilling, coil tubing/millout operations, and production tubing installation. Emissions of C8-C10 n-alkanes during drilling operations highlighted the importance of VOC emissions from a synthetic drilling mud chosen to reduce odor impacts. More than 90 transient plumes were sampled and connected with specific UOGD operations. The chemical signatures of these plumes differed by operation type. Concentrations of individual, O&G-related VOCs in these plumes were often several orders of magnitude higher than in background air, with maximum ethane and benzene concentrations of 79,600 and 819 ppbv, respectively. Study measurements highlight future emission mitigation opportunities during UOGD operations, including better control of emissions from shakers that separate drill cuttings from drilling mud, production separator maintenance operations, and periodic emptying of sand cans during flowback operations. In Part 2 OH reactivities (OHR) were calculated to examine the potential of emitted VOCs to contribute to regional ozone formation. NO2 was the largest contributor to OHR during winter when OHR values peaked, while VOCs dominated OH sinks during summer. Oxygenated VOCs and C3-C7 n-alkanes, closely associated with O&G activities, were primary contributors to OHR levels during the summer ozone season. In Part 3 we leverage observations from Broomfield and other Colorado O&G air quality studies to examine relationships between O&G emissions of methane and VOCs. A key goal is to determine whether more commonly measured methane emissions can serve as a surrogate to estimate emissions of less frequently measured compounds such as benzene, a key air toxic. While strong correlations are observed between benzene and methane emissions in some situations, considerable variability is observed in this relationship across locations and operations suggesting caution in assuming that reductions in methane emissions will yield proportionate reductions in releases of air toxics.
Open Access
Emissions, evolution, and transport of ammonia (NH₃) from large animal feeding operations: a summertime study in northeastern Colorado
(Colorado State University. Libraries, 2024) Juncosa Calahorrano, Julieta Fernanda, author; Fischer, Emily V., advisor; Collett, Jeffrey L., Jr., committee member; Pierce, Jeffrey R., committee member; Jathar, Shantanu H., committee member
The Transport and Transformation of Ammonia (TRANS2Am) airborne field campaign occurred over northeastern Colorado during the summers of 2021 and 2022. TRANS2Am measured ammonia NH3 emissions from cattle feedlots and dairies with the goal of describing the near-field evolution of the NH3 emitted from animal feeding operations. Most of the animal husbandry facilities in Colorado are co-located with oil and gas development within the Denver-Julesburg basin, an important source of methane (CH4) and ethane (C2H6) in the region. Leveraging TRANS2Am observations, this dissertation presents estimates of NH3 emissions ratios with respect to CH4 (NH3 EmR), with and without correction of CH4 from oil and gas, for 29 feedlots and dairies in the region. The data show larger emissions ratios than previously reported in the literature with a large range of values (i.e., 0.1 - 2.6 ppbv ppbv-1). Facilities housing cattle and dairy had a mean (std) of 1.20 (0.63) and 0.29 (0.08) ppbv ppbv-1, respectively. NH3 emissions have a strong dependency with time of day, with peak emissions around noon and lower emissions earlier in the morning and during the evening. Only 15% of the total ammonia (NHx) is in the particle phase (i.e., NH4+) near major sources during the warm summer months. Finally, estimates of NH3 emission rates from 4 optimally sampled facilities range from 4 - 29 g NH3 · h-1 · hd-1. This work also investigates the nearfield evolution of NH3 in five plumes from large animal husbandry facilities observed during TRANS2Am using a mass balance approach with CH4 as a conservative tracer in the timescales of plume transport. Since the plumes in TRANS2Am were not sampled in a pseudo-lagrangian manner, an empirical model is needed to correct for variations in summertime NH3 emissions as a function of local time (LT) (CF = 1.87ln(LT) - 3.95). Results from the mass balance approach show that the average summertime NH3 decay time below 80% and 60% against deposition in plumes from large animal feeding operations is ~1 and ~2 hours, respectively. Additionally, we present estimates of deposition/emission fluxes every 5 km downwind of the plume. We found that deposition almost always happens in the first 10 km from the emission source. Beyond that, the complex environmental exchange of NH3 between the atmosphere and the surface suggests that fresh NH3 emissions from small nearby sources, water bodies, and crops/soil could contribute to sufficient NH3 to switch the direction of the flux (to emission). Large uncertainties still remain in emission and deposition fluxes, shining light on the need for more measurements in the region. To our knowledge, this is the first study presenting NH3 evolution in the atmosphere using a conservative tracer and airborne measurements. The second goal of TRANS2Am was to investigate easterly wind conditions capable of moving agricultural emissions of ammonia (NH3) through urban areas and into the Rocky Mountains. TRANS2Am captured 6 of these events, unveiling important commonalities. 1) NH3 enhancements are present over the mountains on summer afternoons when easterly winds are present in the foothills region. 2) The abundance of summertime gas-phase NH3 is 1 and 2 orders of magnitude higher than particle-phase NH4+ over the mountains and major agricultural sources, respectively. 3) During thermally driven circulation periods, emissions from animal husbandry sources closer to the mountains likely contribute more to the NH3 observed over the mountains than sources located further east. 4) Transport of summertime plumes from major animal husbandry sources in northeastern Colorado westward across the foothills requires ~5 hours. 5) Winds drive variability in the transport of NH3 into nearby mountain ecosystems, producing both direct plume transport and recirculation. A similar campaign in other seasons, including spring and autumn, when synoptic scale events can produce sustained upslope transport, would place these results in context.
Open Access
Application of an interpretable prototypical-part network to subseasonal-to-seasonal climate prediction over North America
(Colorado State University. Libraries, 2024) Gordillo, Nicolas J., author; Barnes, Elizabeth, advisor; Schumacher, Russ, committee member; Anderson, Chuck, committee member
In recent years, the use of neural networks for weather and climate prediction has greatly increased. In order to explain the decision-making process of machine learning "black-box" models, most research has focused on the use of machine learning explainability methods (XAI). These methods attempt to explain the decision-making process of the black box networks after they have been trained. An alternative approach is to build neural network architectures that are inherently interpretable. That is, construct networks that can be understood by a human throughout the entire decision-making process, rather than explained post-hoc. Here, we apply such a neural network architecture, named ProtoLNet, in a subseasonal-to-seasonal climate prediction setting. ProtoLNet identifies predictive patterns in the training data that can be used as prototypes to classify the input, while also accounting for the absolute location of the prototype in the input field. In our application, we use data from the Community Earth System Model version 2 (CESM2) pre-industrial long control simulation and train ProtoLNet to identify prototypes in precipitation anomalies over the Indian and North Pacific Oceans to forecast 2-meter temperature anomalies across the western coast of North America on subseasonal-to-seasonal timescales. These identified CESM2 prototypes are then projected onto fifth-generation ECMWF Reanalysis (ERA5) data to predict temperature anomalies in the observations several weeks ahead. We compare the performance of ProtoLNet between using CESM2 and ERA5 data. We then demonstrate a novel approach for performing transfer learning between CESM2 and ERA5 data which allows us to identify skillful prototypes in the observations. We show that the predictions by ProtoLNet using both datasets have skill while also being interpretable, sensible, and useful for drawing conclusions about what the model has learned.
Open Access
Topographic and diurnal influences on storms associated with heavy rainfall in northern Colorado
(Colorado State University. Libraries, 2024) Douglas, Zoe A., author; Rasmussen, Kristen L., advisor; Bell, Michael M., committee member; Kampf, Stephanie K., committee member
Despite its profound impacts on agricultural and socioeconomical conditions globally, heavy rainfall is a high-impact weather phenomenon of which we have limited quantitative understanding and forecast skill. The Prediction of Rainfall Extremes Campaign in the Pacific (PRECIP) planned to observe the spectrum of heavy rainfall events in the moisture-rich environment of Taiwan and Japan during 2020, but was delayed until 2022 due to the global COVID-19 pandemic. As a result of this unanticipated delay, the PRECIP science team conducted the Preparatory Rockies Experiment for the Campaign in the Pacific ("PRE"-CIP), which observed precipitation over northern Colorado from May to August 2021 using Colorado State University's ground-based research radars and radiosondes. Extreme precipitation features are identified in the radar data and organized into storm modes based on prior research on the Tropical Rainfall Measuring Mission satellite's Precipitation Radar. An "ingredients-based" approach provides a theoretical framework to separate the storm modes into a spectrum of storm intensity and duration during the entire "PRE"-CIP field project, allowing us to connect storm modes to the topography, diurnal cycle, and overall rainfall characteristics in northern Colorado. While precipitation occurred from the mountains to the plains, the highest concentration of storm tracks calculated from all ground-based radar observations occurred over the Rocky Mountains, regardless of storm duration. The majority of storm tracks are of low intensity and short duration, with over 80% of tracked storms having lifetimes of 1 h or less, suggesting that the general population of warm-season precipitation in northern Colorado is short-lived and of weak intensity. When considering heavy rainfall-producing storms, deep convection is the most dominant storm mode in northern Colorado by up to three orders of magnitude over broader convective and stratiform systems. Deep convection most frequently occurred over the Rocky Mountains in the afternoon, while broader convective and stratiform systems most frequently occurred over the foothills and plains in the evening to nighttime hours. Therefore, diurnal forcing and orographic lift play important roles in the morphology of warm-season precipitation in northern Colorado, as has been seen in mountainous regions across the world. The frequent occurrence of deep convective storms directly over the Rocky Mountains, however, differs from the deep convective hotspots seen in the lowlands downstream of similarly large mountain barriers like the Andes and Himalayas. Ultimately, these radar-based analyses are important for the eventual comparison of heavy rainfall in a semi-arid midlatitude region (Colorado) and a moisture-rich tropical environment (Taiwan and Japan), thus providing an enhanced global understanding of the commonalities of heavy rainfall processes.
Open Access
The effects of land surface-atmosphere interactions within two convective storm regimes
(Colorado State University. Libraries, 2024) Ascher, Benjamin D., author; van den Heever, Susan C., advisor; Schumacher, Russ, committee member; McGrath, Daniel, committee member
Convective storms, which are driven in part by atmospheric thermodynamic instability, come in a range of shapes and sizes and bring a variety of impacts both at the surface and throughout the atmosphere. Often these storms initiate as a result of lifting within the Planetary Boundary Layer (PBL), the behavior of which is strongly affected by the characteristics of the land surface below them. To examine the effects of land surface properties on convective storm behavior and impacts, I have conducted two high-resolution mesoscale modeling studies. The first study examined the impact of Lake Huron on convective lake-effect snow over Lake Erie, while the second analyzed the effects of heterogeneous vegetation cover on deep convection in an idealized coastal environment. Our findings in the first study revealed that Lake Huron initiates lake-effect snow bands which persist over land between Lake Huron and Lake Erie and then reintensify after moving over Lake Erie. The persistent band "kickstarts" convection over Lake Erie and increases snowfall over and downwind of Lake Erie compared to when Lake Huron is not present. I also found that areas of snow-free land can act as a "brown lake" and initiate lake effect-like convection on their own. An area of snow-free land upwind of Lake Erie fulfilled a similar role to Lake Huron in enhancing convection and snowfall downwind of Lake Erie. Such findings may have important implications for improved short-term forecasting of the location and intensity of heavy snowfall. The results in our second study indicated that heterogeneous land surfaces enhance convective storm activity over certain vegetation types and suppress it over others. In particular, I found an increase in precipitation over forests surrounded by pasture lands and suburban regions, while the precipitation over the pasture and suburban regions is suppressed. I also discovered that circulations induced by these heterogeneous land surfaces appear to be more important to the location and timing of convection initiation than a sea breeze which forms in the simulations. Finally, I concluded that cold pools produced by convective storms reinforce the land surface-induced circulations, thereby allowing these circulations to collide in the center of the forested region, where they initiate intense convection which subsequently produces heavy rainfall.
Embargo
The abundance and sources of ice nucleating particles (INPs) within Alaskan ice fog
(Colorado State University. Libraries, 2024) Lill, Emily, author; Fischer, Emily V., advisor; Creamean, Jessie, advisor; Kreidenweis, Sonia, committee member; Wall, Diana, committee member
Fairbanks, Alaska often experiences low visibility due to air pollution. Low wind speeds and strong temperature inversions paired with local emissions from burning of wood, oil, gasoline, and coal lead to wintertime pollution events where concentrations of fine particulate matter (PM2.5) often reach 50 μg m-3, exceeding the Environmental Protection Agency (EPA) 24-hour National Ambient Air Quality Standard (NAAQS) of 35 μg m-3. When temperatures fall below -15°C and sufficient moisture is present, these pollution events can facilitate the formation of ice fog, further worsening air quality and visibility issues for aviation and transportation. The formation of ice crystals from supercooled droplets is aided by a small, but critical, number of aerosol particles that potentially act as ice nucleating particles (INPs). However, studies evaluating the quantities and sources of INPs during ice fog are limited. The Alaskan Layered Pollution and Chemical Analysis (ALPACA) field campaign included the deployment of a suite of atmospheric measurements in January - February 2022 with the goal of better understanding atmospheric processes and pollution under cold and dark conditions. We report on measurements of particle composition, particle size, INP composition, and INP size during an ice fog period (29 January - 3 February). There was a 153% increase in coarse particulate matter (PM10) during the ice fog period, associated with a decrease in air temperature. Results also show a 58% decrease in INPs active at -15°C during the ice fog period, indicating that particles were scavenged by ice fog ice crystals, likely via nucleation. Peroxide and heat treatments were performed on INPs in order to determine the fraction of INPs that were biological, organic, or inorganic. One hypothesis consistent with the results of the peroxide treatments is that more efficient INPs derived from biological materials or organics that typically activate at warmer freezing temperatures may have been depleted during the ice fog event. The reduction in heat-labile INPs during the ice fog event was unexpected for Fairbanks in the winter due to the very low temperatures and limited biological aerosol sources. Aerosol compositional measurements corroborate the presence of INPs from biomass burning and road dust.
Open Access
Assimilation of geostationary, infrared satellite data to improve forecasting of mid-level, mixed-phase clouds
(Colorado State University. Libraries, 2009) Seaman, Curtis J., author; Vonder Haar, Thomas H., advisor
Mid-level, mixed-phase clouds (altocumulus and altostratus) are difficult to forecast due to the fact that they are generally thin and form in areas of weak vertical velocity where operational models typically have poor vertical resolution and poor moisture initialization. This study presents experiments designed to test the utility of assimilating infrared window and water vapor channels from the Geostationary Operational Environmental Satellite (GOES) instruments, Imager and Sounder, into a mesoscale cloud-resolving model to improve model forecasts of mid-level clouds. The Regional Atmospheric Modeling Data Assimilation System (RAMDAS) is a four-dimensional variational (4-DVAR) assimilation system used to test the viability of assimilating cloudy scene radiances into a cloud-free initial model state for one case of a long-lived, isolated altocumulus cloud over the Great Plains of the United States. Observations from one observation time are assimilated and significant innovations are achieved. Three experiments are performed: (1) assimilation of the 6.7 μm (water vapor) and 10.7 μm (window) channels from GOES Imager, (2) assimilation of the 7.02μm (water vapor) and 12.02 μm (window) channels from GOES Sounder, and (3) assimilation of the 6.7 μm channel from GOES Imager and the 7.02 μm channel from GOES Sounder. It is shown that the GOES Sounder channels provide more useful information than the GOES Imager channels due to increased sensitivity to the mid-troposphere. The decorrelation lengths and variance used in the background error covariance are varied and the impact on the results of the experiments is discussed. The effect of constraining the surface temperatures during assimilation of the window channels is also discussed. It is found that, in a cloud-free initial model state, the adjoint sensitivities are calculated on the assumption that there is no cloud, even with cloud in the satellite observations. This has a significant impact on the success of other 4-DVAR satellite data assimilation experiments.
Open Access
Quasi-stationary, extreme-rain-producing convective systems associated with midlevel cyclonic circulations
(Colorado State University. Libraries, 2008) Schumacher, Russ Stanley, author; Johnson, Richard H., advisor
Observations and numerical simulations are used to investigate the atmospheric processes responsible for initiating, organizing, and maintaining quasi-stationary mesoscale convective systems (MCSs) that form in association with midlevel mesoscale convective vortices or cutoff lows. Six events were identified in which an MCS remained nearly stationary for 6-12 hours and produced excessive rainfall that led to significant flash flooding. Examination of individual events and composite analyses reveals that the MCSs formed in thermodynamic environments characterized by very high relative humidity at low levels, moderate convective available potential energy, and very little convective inhibition. In each case, the presence of a strong low-level jet (LLJ) led to a pronounced reversal of the wind shear vector with height. Convection was initiated by lifting associated with the interaction between the LLJ and the midlevel circulation. One of these events was examined in detail using numerical simulations. This MCS, which occurred on 6-7 May 2000 in eastern Missouri, produced in excess of 300 mm of rain in 9 hours and led to destructive flash flooding. Simulations indicate that the MCS was long-lived despite the lack of a cold pool at the surface. Instead, a nearly stationary low-level gravity wave helped to organize the convection into a quasi-linear system that was conducive to extreme local rainfall amounts. Additionally, the convective system acted to reintensify the midlevel MCV and also caused a distinct surface low pressure center to develop in both the observed and simulated system. To further understand the important processes in these MCSs, idealized simulations using a low-level lifting mechanism and a composite thermodynamic profile are employed. These simulations successfully replicate many of the features of the observed systems. The low-level environment is nearly saturated, which is not conducive to the production of a strong surface cold pool; yet the convection quickly organizes into a quasi-linear system that produces very heavy local rainfall. As in the May 2000 case, a low-level gravity wave was responsible for this organization. The upstream development of new convective cells is shown to result from the interaction of the reverse-shear flow with these waves.
Open Access
Properties of the tropical hydrologic cycle as analyzed through 3-dimensional k-means cluster analysis
(Colorado State University. Libraries, 2008) Rogers, Matthew Alan, author; Stephens, Graeme, advisor
As the primary locations of deep convective activity and unrestrained tropical wave dynamics, the tropical West Pacific and East Indian oceans are among the most important regions in the tropics. Given that most of the region consists of unpopulated expanses of ocean, observations of tropical atmospheric properties in this important region is exceptionally difficult. Only with the help of satellite observations are we capable of gleaning valuable data from this region, and our utilization of advanced analysis techniques allows us to gain more from these observations then would otherwise be possible. In that vein, this dissertation reports on the use of a unique statistical technique, long known to other fields of research, as applied to a combined-instrument satellite observation dataset over the warm pool region of the tropical West Pacific ocean. The statistical technique, known as k-means cluster analysis, is used to delineate self-similar populations of cloud type, hereafter referred to as cloud regimes, from frequency-distribution histograms of cloud-top height, cloud optical thickness, and rainfall amount. We will show that four primary cloud regimes exist in the tropical region discussed, that the four regimes vary primarily through differences in convective activity, and that these four cloud regimes exist in a coherent temporal structure that explains the long-observed variability in convective activity seen in the tropics. Combining this regime information with satellite observations, along with reanalysis data, we then examine the individual properties of each cloud regime. These observations give us the means to understand the forcings behind cloud regime change in the region. We confirm the structural properties of these regimes using analysis from a cloud-resolving model, and apply our new understanding of the mechanism behind this large-scale forcing to the governance of the tropical hydrologic cycle as a whole. The insights gained from this analysis have benefits to both the fields of atmospheric remote sensing, and of cloud- and climate modeling of the tropical atmosphere. Applications of this technique are of particular interest to researchers developing retrieval algorithms for latent heat profiles using active sensors such as the cloud-profiling radar aboard CloudSat.
Open Access
Making real time measurements of ice nuclei concentrations at upper tropospheric temperatures: extending the capabilities of the continuous flow diffusion chamber
(Colorado State University. Libraries, 2009) Richardson, Mathews, author; Kreidenweis, Sonia, advisor
Due to their ubiquity, cirrus clouds are important drivers of climate. Researchers have developed a parameterization that predicts the onset of homogeneous freezing for particles of varying chemical composition. This parameterization is widely used to model cold cloud formation, but the applicability of this parameterization to real atmospheric aerosol has yet to be determined. The field-ready version of Colorado State University's continuous-flow diffusion chamber (CFDC-1H) is one of the few instruments capable of measuring atmospheric ice nuclei concentrations in real time. In this study, we examined the operational limits of the CFDC-1H at low temperature through a series of controlled laboratory studies using (NH 4)2SO4 particles at different operating conditions. We found that residence time played a dominant role in the CFDC-1H's ability to detect the onset of freezing at conditions closer to those predicted. Numerical studies confirmed this and indicated that at warmer temperatures the inability of the CFDC-1H to observe freezing onset conditions as predicted was attributable to the inability of particles to dilute rapidly enough while at colder temperatures the limited availability of water vapor in conjunction with limited residence times inhibited cloud particle growth. The final portion of this study focused on measurements of the freezing onset conditions of an ambient aerosol. Using water uptake measurements, we found that the hygroscopicity (κ) of the ambient aerosol (0.1 to 0.2) was significantly lower than that of ammonium sulfate (0.6). However, as predicted by theory, there was no observably significant difference between the onset conditions of size-selected (NH4)2SO4 and size-selected ambient aerosol. Freezing activation curves for the total ambient aerosol indicated that size plays an important role in the fraction freezing and should be considered when making conclusions regarding chemical composition as a function of fraction freezing. The chemical composition of ice crystal residuals was dominated by mineral type elements and carbon containing particles, contrary to expectations. Further work is necessary for any conclusive statement regarding the chemical composition of the freezing nuclei.
Open Access
On the role of warm rain clouds in the tropics
(Colorado State University. Libraries, 2008) Rapp, Anita Denise, author; Kummerow, Christian D., advisor
A combined optimal estimation retrieval algorithm has been developed for warm rain clouds using Tropical Rainfall Measuring Mission (TRMM) satellite measurements. The algorithm uses TRMM Microwave Imager (TMI) brightness temperatures that have been deconvolved to the 19-GHz field-of-view (FOV) to retrieve cloud liquid water path (LWP), total precipitable water, and wind speed. Resampling the TMI measurements to a common FOV is found to decrease retrieved LWP by 30%. These deconvolved brightness temperatures are combined with cloud fraction from the Visible Infrared Scanner (VIRS) to overcome the beam-filling effects and with rainwater estimates from the TRMM Precipitation Radar (PR). This algorithm is novel in that it takes into account the water in the rain and retrieves the LWP due to only the cloud water in a raining cloud, thus allowing the investigation of the effects of precipitation on cloud properties. The uncertainties due to forward model parameters and assumptions are computed and range from 1.7 K at 10 GHz to about 6K at the 37 and 85 GHz TMI channels. Examination of the sensitivities in the LWP retrieval shows that the cloud fraction information increases the retrieved LWP with decreasing cloud fraction and that the PR rainwater reduces retrieved LWP. Retrieval algorithm results from December 2005 to January 2006 show that warm rain cloud LWP and the ratio of warm rain cloud LWP to rainwater both decrease by 50% over sea surface temperatures (SST) ranging from 292 to 302 K in the tropical western Pacific due to increased precipitation efficiency depleting more of the cloud water at higher SSTs. The LWP retrieval developed in this study is also applied to study the influence of warm rain clouds on atmospheric preconditioning for deep convection associated with tropical depression-type disturbances (TDs). Results show that positive warm rain cloud LWP anomalies occur with positive low-level moistening and heating anomalies prior to TD events, but that there is little variation in the properties of non-raining clouds. The moistening by these clouds is also shown to influence the generation of convective available potential energy (CAPE) prior to deep convection.
Open Access
The optical, chemical, and physical properties of aerosols and gases emitted by the laboratory combustion of wildland fuels
(Colorado State University. Libraries, 2008) McMeeking, Gavin R., author; Kreidenweis, Sonia M., advisor
Biomass burning is a major source of trace gases and particles that have a profound impact on the atmosphere. Trace gases emitted by fires include the greenhouse gases CO2 and CH4, as well as CO and volatile organic compounds that affect air quality. Particle emissions affect climate, visibility, the hydrologic cycle, and human health. This work presents measurements of trace gas and aerosol emissions from a series of controlled laboratory burns for various plant species common to North America. Over 30 fuels were tested through ~250 individual burns during the Fire Laboratory at Missoula Experiment. Emission factors are presented as a function of modified combustion efficiency (MCE), a measure of the fire combustion conditions. The emissions of many trace gas and aerosol species depended strongly on MCE: smoldering-phase combustion dominated fires (low MCE) emitted roughly four times as much gas-phase hydrocarbon species and organic aerosols than flaming-phase dominated fires (high MCE). Inorganic aerosol emissions depended more strongly on plant species and components than on MCE. Flaming-phase dominated fires tended to produce aerosol with high mass fractions of strongly light-absorbing elemental carbon. Smoldering-phase fires produced aerosol with large mass fractions of more weakly light absorbing organic carbon, but this material was found to have a strong wavelength dependence of absorption, greater than the inverse wavelength relationship typically assumed for light absorbing aerosol. A two component model-featuring elemental carbon with a weak wavelength dependence but high mass-normalized absorption efficiency and organic carbon with a strong wavelength dependence but low mass-normalized absorption efficiency-is shown to represent the bulk absorption spectra of biomass burning aerosol. The results show that at wavelengths below ~450 nm, organic carbon light absorption could rival that of elemental carbon for aerosol dominated by organic carbon. If ignored, the light absorption by organic carbon can cause errors in predicted surface ultraviolet and visible radiation fluxes and photochemical photolysis rates in regions affected by biomass burning emissions. The dependence of spectral aerosol optical properties on combustion conditions means that fire behavior must be accurately assessed and predicted to ensure accurate emissions inventories and estimates of biomass burning atmospheric impacts.
Open Access
A study of the relationship between thunderstorm processes and cloud-top ice crystal size
(Colorado State University. Libraries, 2008) Lindsey, Daniel T., author; Johnson, Richard H., advisor
Satellite observations and numerical models are used to understand the physical mechanisms responsible for thunderstorms with varying cloud-top ice crystal sizes. Geostationary Operational Environmental Satellite (GOES) data are used to create a three-year climatology of cloud-top 3.9 µm reflectivity, a quantity which is closely correlated with particle size. Maximum mean values are found over the High Plains and Rocky Mountain regions of the U.S., suggesting that convection over that region tends to generate smaller anvil ice crystals than areas throughout much of the eastern U.S. To correct for preferred forward scattering by the cloud-top ice crystals, an effective radius retrieval using GOES is developed. Forward radiative transfer simulations are run for a wide range of cloud-top ice crystal sizes and sun-cloud-satellite scattering angles. The output is used to generate a lookup table, so that GOES-measured radiances may be used along with sun-satellite geometry to obtain an estimate for particle size. Validation of the retrieval shows that the assumed scattering properties perform quite well. To help explain the geographical variation in cloud-top ice crystal size, a composite analysis is performed in the High Plains region by averaging environmental conditions for days which produced both small and large ice crystal storms. Small ice is found to occur with relatively high based storms and steep mid-level lapse rates. Additionally, observational evidence from a pyrocumulonimbus event is presented to show the effect of low-level cloud condensation nuclei (CCN) on cloud-top ice crystal size. Model simulations using the Colorado State University Regional Atmospheric Modeling System (RAMS) are performed to help understand the physical mechanisms responsible for cloud-top ice crystal size. Through a series of sensitivity tests, it is found that larger low-level CCN concentrations lead to smaller anvil ice. In addition, as cloud-base temperature decreases (and cloud-base height increases), storm-top ice crystals get smaller. A weaker updraft strength is found to have very little effect on ice crystal size.
Open Access
Improving numerical weather prediction: error growth at the convective scale and speed
(Colorado State University. Libraries, 2009) Leoncini, Giovanni, author; Pielke, Roger A., Sr., advisor
Despite the continuous growth of the available computational power, it is undoubtedly beneficial, for both the research and operational communities, to increase the efficiency of Numerical Weather Prediction. Because parameterizations often occupy a significant portion of the total execution time the first focus of this work is to provide a methodology to transform parameterizations into algorithms that provide the same output at a fraction of the computational cost (i.e., transfer schemes). Several transfer schemes are developed for the Harrington radiation parameterization, in the clear sky case and implemented in the Regional Atmospheric Modeling System. The best one requires roughly 5% of the computational expense of the parent scheme. Accuracy is generally preserved and an analysis of the main meteorological fields after two days of simulations does not show significant differences. The differences for the 2 m temperature are larger than for the other fields, but still smaller than the differences introduced by a second common parameterization. A second area where NWP is in need of improvements is convective-scale forecasting. The advantages of more accurate forecasting derive from the high societal impact of convective events, which can be severe and lead to loss of life and property. Ensemble forecasting is an ideal tool to handle uncertainties in forecasts and the second aim of this study is to identify the processes that lead to error growth at the convective scale, for a case study over the United Kingdom using the Met Office Unified Model. The perturbation was applied to the potential temperature at a specific model level within the boundary layer, either sequentially (every 30 minutes) or at specific times. It was determined that acoustic waves are generated and can affect the background state. Vertical stability is also altered and occasionally lids can be set or removed. The unique boundary-layer scheme also contributes to error growth, by triggering different parameterizations as a response to the perturbation. Finally there are qualitative differences between high amplitude perturbations (1 K) and the smaller ones (0.01 and 0.1 K), but the root mean square error reaches similar values at saturation.
Open Access
The impact of natural dust aerosol on warm and cold cloud formation
(Colorado State University. Libraries, 2008) Koehler, Kirsten, author; Kreidenweis, Sonia M., advisor
Dust particles' ability to scatter and absorb radiation and their potential to interact with water vapor may lead to important direct and indirect radiative impacts on the climate. Due to differences in solubility, hygroscopicity, chemical and surface properties, dust particles from different regions may interact with cloud development in a variety of ways that are not fully understood. In this work four types of dust from the Southwestern U.S. and Northern Africa were studied. The characteristics of the samples used cover a range of soluble contents, geographic locations of origin, and collection methods. Hygroscopic growth of the particles was determined using a humidified tandem differential mobility analyzer (HTDMA) at relative humidities (RH) from 5-95% and cloud condensation nuclei (CCN) activity was measured using a continuous flow CCN counter at supersaturations up to 2%. At cold temperatures (-60
Open Access
Tropical cyclone evolution via internal asymmetric dynamics
(Colorado State University. Libraries, 2008) Hendricks, Eric A., author; Schubert, Wayne, advisor
This dissertation advances our understanding by which tropical cyclones (TCs) evolve solely due to internal dynamics, in the absence of large-scale environmental factors and surface fluxes, using a hierarchy of numerical model simulations, diagnostics and observations. In the first part, the role of inner-core (eye and eyewall) transport and mixing processes in TC structure and evolution is examined, and in the second part, some asymmetric dynamics of tropical cyclone evolution are studied: spontaneous inertia-gravity wave radiation from active TC cores and an observational case study of the role of vortical hot towers in tropical transition. The role of two-dimensional transport and mixing in TC structure and intensity change is quantified. First, the mixing properties of idealized hurricane-like vortices are assessed using the effective diffusivity diagnostic. Both monotonic and dynamically unstable vortices are considered. For generic deformations to monotonic vortices, axisymmetrization induces potential vorticity (PV) wave breaking outside the radius of maximum wind, forming a finite radial length surf zone characterized by chaotic mixing. Although on a much smaller scale, this surf zone is analogous to the surf zone outside the wintertime stratospheric polar vortex. For unstable rings, during barotropic instability both the inner and outer breaking PV waves create horizontal mixing regions. For thin ring breakdowns, the entire inner-core becomes a strong mixing region and passive tracers can be transported quickly over large horizontal distances. For thick ring breakdowns, an asymmetric partial barrier region may remain intact at the hurricane tangential jet, with mixing regions on each side where the waves break. The inner, breaking PV wave is quite effective at mixing passive tracers between the eye and eyewall; with a monotonic low-level equivalent potential temperature radial profile, these results support the hurricane super-intensity mechanism. Next, a systematic study of inner-core PV mixing resulting from unstable vortex breakdowns is conducted. After verifying linear theory, the instabilities are followed into their nonlinear regime and the resultant end states are assessed for 170 different PV rings, covering a wide spectrum of real hurricanes.
Open Access
The near-global distribution of light precipitation from CloudSat
(Colorado State University. Libraries, 2008) Haynes, John M., author; Stephens, Graeme L., advisor
The W-band (94 GHz) Cloud Profiling Radar (CPR) on CloudSat is sensitive to both clouds and precipitation. A precipitation retrieval applicable to space-borne, millimeter wavelength radars is introduced. Measurements of the attenuated backscatter of the surface are used to derive the path integrated attenuation (PIA) through precipitating columns, which follows from the clear-sky scattering characteristics of the surface. Over ocean, this can be estimated as a function of near-surface wind speed and sea surface temperature. Assuming an exponential rain drop size distribution, the relationship between PIA and rain rate is derived from Mie theory for homogeneous columns of warm rain. Multiple scattering is found to be significant for rainfall rates exceeding 3 to 5 mm h-1. To correct for this effect, Monte Carlo modeling is used to simulate the relationship between rainfall and PIA for various vertical precipitation profiles. Multiple scattering is found to increase return power to the radar, acting opposite attenuation. A model of the melting layer is also incorporated to better represent attenuating characteristics near the bright band, where snow aggregates melt into rain. It is found that failure to account for extra attenuation caused by melting particles results in overestimation of precipitation rate. The retrieval algorithm is applied to near-global CloudSat observations. Precipitation in the tropics is found to prefer clouds with lowest-layer cloud tops near 2 and 15 km. A third mode, likely associated with congestus, is found to be common in the tropical western Pacific, Indian, and Atlantic basins. There are vast regions of the globe where nearly all precipitation falls from cloud with lowest-layer tops below 4.75 km. Over the tropical oceans as a whole, precipitation falls twice as often from these clouds as any other cloud type. Furthermore, multiple layered cloud systems are found to be ubiquitous globally. In the tropics, it is estimated that half the accumulated precipitation comes from multiple layered systems rather than the classic "deep convective" model. Outside the tropics, the CPR observes precipitation more often than the passive microwave AMSR-E, with greater resulting seasonal accumulations.
Open Access
Characteristics of precipitation: CloudSat observations and model predictions of the current and future climate
(Colorado State University. Libraries, 2008) Ellis, Todd Douglas, author; Stephens, Graeme L., advisor
The overall purpose of this study is to examine the characteristics of precipitation as they are predicted to change in a typical climate change scenario and as they exist now and how well model reproduces those observations. The first part of this study examines the controls on global precipitation evident in a transient carbon dioxide doubling experiment conducted using coupled climate models collected for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4). As noted in other studies, the ensemble mean changes in water vapor occur at a rate more than three times that of precipitation. A simple ratio of these changes is introduced as a type of measure of the efficiency of the atmospheric hydrologic cycle in responding to changes in moisture, and varies between about 0.09 and 0.25 for the models studied. It is shown that the change in precipitation sensitivity is primarily governed by how emission of radiation from the clear-sky atmosphere increases as water vapor increases. This relationship closely matches one derived from simple energy balance arguments involving changes to water vapor emission alone. The study also presents the precipitation incidence over the global oceans as calculated from the CloudSat satellite, showing precipitation into the high latitudes and calculating that precipitation occurs 11% of the time over the oceans. These data are verified using ship-based (ICOADS) and island-based (GSOD) data. This study then extends the use of these data to an analysis of the observed cloud structures that are associated with rainfall over the oceans and then comparing them to special runs of the ECMWF weather forecast and HadGAM1 climate prediction models. These comparisons show that the models don't predict shallow precipitation nor layered precipitation structures as often as they are observed, and predict incorrect global precipitation incidences.
Open Access
Analysis and application of the CASA IP1 X-band polarimetric radar network
(Colorado State University. Libraries, 2009) Dolan, Brenda, author; Rutledge, Steven A., advisor
The Collaborative Adaptive Sensing of the Atmosphere's Integrated Project 1 (CASA IP1) network of four X-band, polarimetric, Doppler, adaptively scanning radars is investigated for studying storm microphysics and kinematics. The complications of non-Rayleigh scattering and attenuation at X-band are explored for impact on microphysical interpretation. The rapid and adaptive scanning strategy is evaluated for application of dual-Doppler techniques to retrieve the 3-D wind field, and general understanding of storm interactions. Several rain rate algorithms are invoked to estimate surface rainfall. A case study from 10 June 2007 illustrates the capabilities and limitations of using the IP1 network for studies of storm interactions, and lightning data are analyzed to relate these interactions to storm electrification. The nearby S-band, polarimetric KOUN radar is studied for comparison. Scattering simulations using the T-matrix model are performed on seven hydrometeor types (excluding hail) to understand the non-Rayleigh effects at X-band compared with S-band. The simulations show the greatest non-linearities in Zdr and Kadp of rain and graupel. Results of the simulations are used to develop a specific X-band fuzzy logic hydrometeor identification algorithm (HID) for diagnosing bulk regions of hydrometeors. Attenuation and non-Rayleigh scattering are present in the IP1 data, but with mitigation techniques these have minimal impact on the analysis. The high temporal resolution is integral in resolving up- and downdrafts, as well as hydrometeor evolution, but the inconsistent and lack of upper-level coverage are significant limitations for quantitative analysis of kinematic and microphysical relationships. Observations using IP1 data of a storm on 10 June 2007 show the development of the updraft, subsequent graupel echo volume evolution, and onset of lightning. Development of the downdraft is preceded by large volumes of graupel in the mid-levels. A second peak in intra-cloud lightning is observed to be associated with an increase in height of the upper positive charge, resulting from a kinematic intensification. Many of these trends are corroborated by KOUN. Rain rate estimation comparisons show that the X-band blended algorithm performs better compared with ground-based sensors than the simple Z-R relationship and employs polarimetric estimators more often than S-band blended methods.