Browsing by Author "Chiu, Christine, committee member"
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Item Open Access Analyzing the detection efficiency of the Geostationary Lightning Mapper in isolated convection(Colorado State University. Libraries, 2021) Clayton, Adam Wayne, author; Rutledge, Steven, advisor; Miller, Steven, advisor; Chiu, Christine, committee member; Eykholt, Richard, committee memberThe Geostationary Lightning Mapper (GLM) flying on GOES-16 and GOES-17 has provided near-hemispheric lightning detection for nearly two years. Since operation began, several attempts have been made to compare flash rate observations from GLM against ground-based lightning detection systems. While GLM captures a high percentage of flashes in the field-of-view of GOES-16 and GOES-17, some studies have shown reduced detection efficiency at storm-scale. The problem of analyzing lightning from space is a complex one. Several factors such as: flash area, flash length, cloud water and ice contents, flash height, flash brightness and position relative to satellite nadir affect the detection efficiency of GLM. This study analyzes numerous convective cells in the Alabama, Colorado, and W. Texas regions to further analyze the detection efficiency of GLM. Lightning data from VHF-based lightning mapping arrays (LMAs) in each region were compared directly to measurements from GLM. The GLM/LMA ratio for each cell was computed during the lifetime of the thunderstorm. Additionally, graupel echo volumes, precipitation ice water paths, and cloud ice and cloud water paths were calculated to access the microphysics of each cell. This study features an in-depth analysis of thunderstorms that vary in size and severity from each region. Further, a statistical analysis of all of the variables was performed to determine the major factors that affect GLM detection efficiency. This study found that flash rate, flash brightness and near cloud-top water and ice water paths significantly affect GLM detection efficiency. Specifically, thunderstorms with increased flash rates, cloud-top water paths, and decreased flash size/brightness are often characterized by low (< 20%) GLM detection efficiencies. These characteristics are common in so-called "anomalous" charge structure thunderstorms that frequent the northern Colorado region. Additionally, this study confirmed results from previous studies which found that the GLM DE decreases as the distance from nadir increases. These results will be helpful for meteorologists utilizing GLM observations to assist with decisions regarding severe weather.Item Open Access Assessing the state-dependency of infrared satellite precipitation errors(Colorado State University. Libraries, 2022) Goldenstern, Eric, author; Kummerow, Christian, advisor; Chiu, Christine, committee member; Ebert-Uphoff, Imme, committee memberThe sensing and prediction of precipitation remains at the forefront of weather forecasting, building upon centuries of measurement and study. While in-situ and ground-based methodologies such as rain gauges and weather radars provide the best assessments of precipitation, they are prone to sampling issues and coverage gaps both over challenging terrain and in developing areas of the world. As a result, the use of remote sensing methodologies, namely satellites, have allowed for the expansion of precipitation measurement to encompass nearly the entire Earth. However, unlike rain gauges, satellites are incapable of directly sensing precipitation; rather, they must infer it from the spectral information that can be captured from space through a mathematical framework known as a retrieval. While satellite precipitation retrievals are a boon to the meteorological community due to their ability to fill in these coverage gaps, their indirect nature inevitably gives rise to errors in the measurements themselves. Furthermore, these errors have historically been specific to their training area and are not directly comparable to the errors in other areas. Therefore, this thesis aims to begin disentangling these errors into more generalizable metrics through known information about the measurements themselves and the environmental state being observed. To do this, a neural-network style retrieval algorithm was developed using infrared and lightning data from the Geostationary Operational Environmental Satellite – 16 (GOES-16) to create a validation statistics study. The error from this retrieval, selected to be its bias statistic, was then analyzed both in the context of the satellite data and ancillary meteorological data. From these analyses, it was shown that an understanding of the satellite data allows for limited reproducibility of the retrieval bias tendencies across multiple areas of study, and that ancillary environmental information can shed additional light on how these errors are influenced by the underlying meteorological state. Though this thesis does not create an exact, quantitative methodology for such an assessment, it does provide a direction in which a framework can be established to predict precipitation uncertainties for a more global perspective.Item Embargo Changes in shortwave solar radiation under local and transported wildfire smoke plumes: implications for agriculture, solar energy, and air quality applications(Colorado State University. Libraries, 2024) Corwin, Kimberley A., author; Fischer, Emily, advisor; Pierce, Jeffrey, committee member; Chiu, Christine, committee member; Corr-Limoges, Chelsea, committee member; Burkhardt, Jesse, committee memberThe emission and transport of pollutants from wildfires is well-documented, particularly at the surface. However, smoke throughout the atmospheric column affects incoming shortwave solar radiation with potentially wide-ranging consequences. By absorbing and scattering light, smoke changes the amount and characteristics of shortwave radiation–a resource that controls plant photosynthesis, solar energy generation, and atmospheric photochemical reactions. In turn, these influence ecological systems as well as air quality and human health. This dissertation examines how wildfire smoke alters boundary layer and surface-level shortwave radiation in ways that are relevant for agricultural, energy, and air quality applications. First, I present an analysis of smoke frequency and smoke-driven changes in the total and diffuse fraction (DF) of photosynthetically active radiation (PAR; 400-700 nm) at the surface. I compare PAR and PAR DF on smoke-impacted and smoke-free days during the agricultural growing season from 2006 to 2020 using data from 10 ground-based radiation monitors and satellite-derived smoke plume locations. I show that, on average, 20% of growing season days are smoke-impacted and that smoke prevalence has increased over time (r = 0.60, p < 0.05). Smoke frequency peaks in the mid to late growing season (i.e., July, August), particularly over the northern Rocky Mountains, Great Plains, and Midwest. I find an increase in the distribution of PAR DF on smoke-impacted days, with larger increases at lower cloud fractions. On clear-sky days, daily average PAR DF increases by 10 percentage points when smoke is present. Spectral analysis of clear-sky days shows smoke increases DF (average: +45%) and decreases total irradiance (average: −6%) across six wavelengths measured from 368 to 870 nm. Optical depth measurements from ground and satellite observations both indicate that spectral DF increases and total spectral irradiance decreases with increasing smoke plume optical depth. My analysis provides a foundation for understanding smoke's impact on PAR, which carries implications for agricultural crop productivity under a changing climate. Second, I examine smoke's impact on two key measures used to assess a location's baseline solar resource availability for solar energy production: direct normal (DNI) and global horizontal (GHI) irradiance. I quantify smoke-driven changes in DNI and GHI at different spatial and temporal scales across the contiguous U.S. (CONUS) using radiative transfer model output and satellite-based smoke, aerosol, and cloud observations. Importantly, I expand the scale of previous studies on smoke and solar energy by including areas primarily affected by dilute, aged, transported smoke plumes in addition to areas with dense, fresh, local smoke plumes. I show that DNI and GHI decrease as smoke frequency increases at the state, regional, and national scale. DNI is more sensitive to smoke with sizable losses persisting downwind of fires. Although large reductions in GHI are possible close to fires, mean GHI declines minimally (< 5%) due to transported smoke. Overall, GHI–the main resource used for photovoltaic energy production–remains a relatively stable resource across most of CONUS even in extreme fire seasons, which is promising given U.S. solar energy goals. Third, I investigate smoke-driven changes in surface-level and boundary layer downwelling actinic flux (F↓)–a crucial component of determining the rate of photooxidation in the atmosphere. I present a case study of changes in F↓ at 550 nm (process validation) and 380 nm (NO2 photolysis) along a research flight through the California Central Valley during the 2018 Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN) aircraft campaign. F↓ was measured onboard via the HIAPER Airborne Radiation Package (HARP), and I use the National Center for Atmospheric Research (NCAR) Tropospheric Ultraviolet and Visible (TUV) Radiation Model to compute F↓ under smoke-free and smoke-impacted conditions. Modeling F↓ with TUV facilitates calculating the change in F↓ and provides a means of assessing F↓ at altitudes not sampled by the aircraft, such as the ground. I find that the smoke-impacted F↓ from TUV aligns closely with HARP observations: all modeled fluxes are within 20% of measurements at 550 nm and 85% are within 20% of measurements at 380 nm. The average modeled-to-measured ratios (F ↓550=0.96; F ↓380=0.89) indicate that TUV minorly underestimates the observed F↓. On average, observed F↓380 decreased 26%, 17%, and 9% at 0-0.5 km, 0.5-1 km, and 1-1.5 km, respectively, while TUV estimates larger reductions of 41%, 26%, and 19% at the same altitudes. At the ground-level, I calculate a 47% decrease in F↓380 using TUV, which is likely an upper bound given the model slightly underestimates observations. As wildfire smoke increases with climate change, understanding how smoke aloft changes photochemistry is increasingly important for constraining future air quality.Item Open Access Consistency in the AMSR-E snow products: groundwork for a coupled snowfall and SWE algorithm(Colorado State University. Libraries, 2019) Gonzalez, Ryan L., author; Kummerow, Christian, advisor; Liston, Glen, committee member; Chiu, Christine, committee member; Notaros, Branislav, committee memberSnow is an important wintertime property because it is a source of freshwater, regulates land-atmosphere exchanges, and increases the surface albedo of snow-covered regions. Unfortunately, in-situ observations of both snowfall and snow water equivalent (SWE) are globally sparse and point measurements are not representative of the surrounding area, especially in mountainous regions. The total amount of land covered by snow, which is climatologically important, is fairly straightforward to measure using satellite remote sensing. The total SWE is hydrologically more useful, but significantly more difficult to measure. Accurately measuring snowfall and SWE is an important first step toward a better understanding of the impacts snow has for hydrological and climatological purposes. Satellite passive microwave retrievals of snow offer potential due to consistent overpasses and the capability to make measurements during the day, night, and cloudy conditions. However, passive microwave snow retrievals are less mature than precipitation retrievals and have been an ongoing area of research. Exacerbating the problem, communities that remotely sense snowfall and SWE from passive microwave sensors have historically operated independently while the accuracy of the products has suffered because of the physical and radiometric dependency between the two. In this study, we assessed the relationship between the Northern Hemisphere snowfall and SWE products from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). This assessment provides insight into regimes that can be used as a starting point for future improvements using coupled snowfall and SWE algorithm. SnowModel, a physically-based snow evolution modeling system driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis, was employed to consistently compare snowfall and SWE by accounting for snow evolution. SnowModel has the ability to assimilate observed SWE values to scale the amount of snow that must have fallen to match the observed SWE. Assimilation was performed using AMSR-E, Canadian Meteorological Centre (CMC) Snow Analysis, and Snow Data Assimilation System (SNODAS) SWE to infer the required snowfall for each dataset. Observed AMSR-E snowfall and SWE were then compared to the MERRA-2 snowfall and SnowModel-produced SWE as well as SNODAS and CMC inferred snowfall and observed SWE. Results from the study showed significantly different snowfall and SWE bias patterns observed by AMSR-E. Specifically, snowfall was underestimated nearly globally and SWE had pronounced regions of over and underestimation. Snowfall and SWE biases were found to differ as a function of surface temperature, snow class, and elevation.Item Open Access Development, fabrication and testing of the scanning and calibration subsystems for the Tropospheric Water and Cloud ICE instrument for 6U CubeSats(Colorado State University. Libraries, 2019) Kilmer, Braxton, author; Reising, Steven C., advisor; Chandrasekar, V., committee member; Chiu, Christine, committee memberGlobal observations of ice cloud particle size and ice water content are needed to improve weather forecasting and climate prediction. The interaction between ice particles and upwelling radiation at sub-millimeter-wavelengths strongly depends on ice particle size and observation frequency. Sub-millimeter-wavelength radiometry provides the capability to fill an observational gap by allowing the detection and sizing of ice particles with diameters between 50 μm and 1 mm. Atmospheric temperature and water vapor profiles can also be yielded at sub-millimeter-wavelengths. The Tropospheric Water and Cloud ICE (TWICE) millimeter- and sub-millimeter-wave radiometer instrument is currently under development for 6U CubeSats in a joint effort among Colorado State University (lead), NASA/Caltech Jet Propulsion Laboratory, and Northrop Grumman Corporation. The TWICE radiometer instrument is designed to provide global measurements of cloud ice, as well as temperature and water vapor profiles in the upper troposphere/lower stratosphere. The TWICE radiometer instrument has 16 frequency channels near 118 GHz for temperature profiling, near 183 and 380 GHz for water vapor profiling, and centered on 240, 310, 670, and 850 GHz quasi-window channels for ice particle sizing. The TWICE radiometer instrument uses a conical scanning strategy to observe the Earth's atmosphere and surface. The complete TWICE scan is designed to sweep out a 200° arc once per second, and the scan direction reverses every second interval. The TWICE scanning system is designed to fit inside a 6U CubeSat in terms of volume and mass, while meeting the torque and acceleration requirements of the scanning radiometer instrument. A stepper motor and gearbox mechanism were selected for the TWICE scanning system. Precisely placed position sensors, in combination with stepper motor step calculation, provide sufficient angular position data, in place of a traditional encoder. The TWICE scanning system has been tested, and angular position analysis has been performed. The TWICE instrument performs end-to-end, two-point radiometric calibration by observing an ambient temperature calibration target and cosmic microwave background reflector during each conical scan. The ambient calibration target is designed to enable simultaneous blackbody measurements at all TWICE millimeter- and sub-millimeter-wave channels. Calibration target design parameters, including size, geometry, thermal and electromagnetic properties, have been chosen to meet the performance requirements of the ambient target and to minimize temperature gradients. Reflection coefficient measurements have been performed in the millimeter to sub-millimeter wavelength range of the TWICE channels. Thermal analysis of the ambient calibration target has been performed using ANSYS software. The resulting ambient calibration target design meets functional requirements as well as size and weight constraints to fit into a 6U CubeSat. The TWICE radiometer instrument employs several subsystems that need to communicate during nominal operation. An interface board was designed to meet the communication needs of and provide power regulation for the various interfacing subsystems of the instrument. The interface board is responsible for controlling the scanning subsystem of the radiometer instrument, performing temperature data acquisition for the radiometer instrument front end and the ambient calibration target, routing signals to and from the control and data handling subsystem of the radiometer instrument, and regulating power to the on-board computer. The interface board has been manufactured and its performance has been tested.Item Open Access Exploring precipitation processes in stratocumulus clouds from satellite-derived cloud properties(Colorado State University. Libraries, 2021) Murakami, Yasutaka, author; Kummerow, Christian D., advisor; van den Heever, Susan C., advisor; Chiu, Christine, committee member; Venkatachalam, Chandrasekaran, committee memberMarine stratocumulus clouds are low-level convective clouds that develop within the marine atmospheric boundary layer and have a large impact on the global radiation budget and hydrological cycle. Drizzle plays an important but complicated role in their longevity and microphysical properties. Many studies have examined the response of cloud base rain rate to varying cloud droplet number concentrations and cloud thickness, as well as liquid water path (LWP), and found that cloud base rain rates are enhanced with lower cloud droplet number concentrations and greater cloud thickness or LWP. In warm stratocumulus clouds, cloud base rain rate is a combination of raindrop embryo production through collision coalescence (i.e. autoconversion) and raindrop embryo growth by collecting cloud droplets (i.e. accretion). Previous studies have shown that cloud base rain rate depends on LWP or cloud thickness and the geographical location of stratocumulus clouds, but the dependence of the autoconversion process on these variables is not well known because cloud base rain rate represents the effects of both autoconversion and accretion. This two-part dissertation explores the dependence of stratocumulus cloud precipitation processes on cloud thickness and geographical location by examining the cloud properties retrieved by A-Train satellite observations from CloudSat's Cloud Profiling Radar (CPR), CALIPSO's Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Aqua's Moderate Resolution Imaging Spectroradiometer (MODIS). In the first part, the relations between cloud top properties (radar reflectivity, LWC and cloud droplet number concentration) and cloud geometrical thickness are investigated for subtropical stratocumulus clouds. Satellite-observations show that cloud top LWC and effective radius increase as clouds become thicker. The data also suggest that autoconversion may be more efficient in thicker clouds. These findings are consistent with previous studies that have shown that thicker clouds have larger cloud droplets and thus produce more rain embryos. However, it is also found that clouds separate into two sub-groups as they transition from thick (i.e. geometrical thickness of 384-480m) to very thick clouds (i.e. geometrical thickness of 624-720m). Drizzling clouds have higher LWC and their drops have larger effective radii, whereas non-drizzling clouds have lower cloud top LWC and smaller effective radii. In the second part, the climatology of satellite-derived cloud top properties (radar reflectivity, LWC and cloud droplet number concentration) for 8 stratocumulus cloud regions are presented. While LWP tends to be larger for midlatitude clouds, cloud top LWC tends to be larger at subtropical stratocumulus clouds. Since midlatit0ude stratocumulus clouds are thicker, these results suggests that effective condensation rates are larger for subtropical stratocumulus clouds. Both cloud top and cloud base radar reflectivity also tend to be larger for subtropical stratocumulus clouds. Based on these findings, the sensitivity of cloud top radar reflectivity on LWC and cloud droplet number concentration are examined. Cloud top radar reflectivity is more (less) sensitive to changes in LWC and cloud droplet number concentration for clouds with stronger (weaker) cloud top radar reflectivity. This is consistent with previous findings that collision-coalescence efficiency between liquid water droplets (i.e. approximately 20 μm in diameter) increases non-linearly with droplet size. The overall results presented in this dissertation indicate that the autoconversion process can be represented with a globally applicable function of cloud top LWC and cloud droplet number concentration for all stratocumulus clouds regardless of their geolocation and geometrical thickness. It is also demonstrated that cloud top raindrop embryo generation rate is an important factor for determining the precipitation generation rate for stratocumulus clouds as a whole. In general, accretional growth is controlled by both the total cross-sectional area of rain drops and LWP. By comparing spatial patterns of cloud top radar reflectivity (i.e. total cross-sectional area of rain drops) and radar reflectivity increase from cloud top to bottom (i.e. accretional growth), it is found that accretional growth depends more on total cross-sectional area of rain drops and less on LWP in stratocumulus clouds. These conclusions can explain the findings of previous studies that cloud base rain rate depends on LWP (or cloud thickness) and geographical location of stratocumulus clouds. Cloud base rain rate is dependent on geometrical thickness because cloud top LWC increases as cloud become thicker. Subtropical stratocumulus clouds tend to have stronger precipitation at a given LWP compared to midlatitude stratocumulus clouds because the effective condensation rate of subtropical stratocumulus clouds is greater and so is the cloud top LWC. In this study, the effect of Cloud Condensation Nuclei on warm rain processes is represented by varying cloud droplet number concentration. The results presented in this dissertation represent more than one hundred thousand independent pixels and provide a statistically robust benchmark that numerical models should reproduce.Item Open Access Mineral dust lofting and interactions with cold pools(Colorado State University. Libraries, 2021) Bukowski, Jennifer, author; van den Heever, Susan, advisor; Chiu, Christine, committee member; Rasmussen, Kristen, committee member; Jathar, Shantanu, committee member; Barth, Mary, committee member; Miller, Steven, committee memberConvective dust storms, or haboobs, form when strong surface winds loft loose soils in convective storm outflow boundaries. Haboobs are a public safety hazard and can cause a near instantaneous loss of visibility, inimical air quality, and contribute significantly to regional dust and radiation budgets. Nevertheless, reliable predictions of convective dust events are inhibited by a lack of understanding regarding the complex and non-linear interactions between cold pools, dust radiative effects, and land surface processes, and their associated uncertainties in numerical models. In this dissertation, model simulations of real and idealized haboobs are used to address limitations in regional dust modeling, the direct radiative effect of mineral dust on cold pool properties and dynamics, and feedbacks between haboobs and the land surface. In the first study, we assess the influence of horizontal resolution, specifically parameterized versus convection-allowing resolution, on dust lofting, vertical transport, and aerosol heating rates in the WRF-Chem regional model. On average, convection-permitting simulations exhibit higher surface wind speeds, enhanced convective activity, and drier soil, which leads to more dust emissions to the atmosphere. More frequent and stronger vertical velocities also transport dust further aloft and increase the atmospheric lifetime of these particles. We conclude that tuning dust emissions in coarse-resolution regional simulations can only improve the results to first-order and cannot fully rectify discrepancies in the representation of convective dust transport in terms of aerosol distributions or the net aerosol radiative effect. The second study, WRF-Chem is utilized to simulate the effect dust radiation interactions have on a long-lived haboob case study that spans three distinct radiative regimes: day (high shortwave), evening (low shortwave), and night (longwave only). A sophisticated algorithm, known as TOBAC, is used to track and identify the numerous cold pool boundaries and assemble statistics that represent the impact of including dust radiative effects. To first order, dust scattering of shortwave radiation in the day leads to a colder, dustier, and faster moving cold pool. In the transition period of early evening, the shortwave effects diminish while longwave absorption by dust leads to warmer and slower cold pools that loft less dust as they propagate onward. At night, the haboob is again warmer due to dust absorption, but gustier in the more stable nocturnal surface layer. Lastly, the third study focuses on feedbacks between parameters that affect both dust mobilization and cold pool dynamics. The Elementary Effects statistical method is applied to an ensemble of 120 idealized RAMS simulations of daytime and nighttime haboobs. This sensitivity analysis identifies and ranks the importance of different input factors in predicting haboob properties as: initial cold pool temperature, surface type, soil type, and finally soil moisture. Most of these parameters modify the cold pool via their impacts on surface fluxes, although the effect of surface type is dominated by the change in roughness length. A semi-linear connection between haboob dust and cold pool temperature is detected in the statistics, and a relationship between dust flux and cold pool temperature is proposed which relates haboob strength to the thermodynamic environment.Item Open Access On intensity change and the effects of shortwave radiation on tropical cyclone rainbands(Colorado State University. Libraries, 2020) Trabing, Benjamin, author; Bell, Michael, advisor; Chiu, Christine, committee member; Knaff, John, committee member; Windom, Bret, committee member; van den Heever, Sue, committee memberIn this dissertation, the effects of shortwave radiation and the diurnal cycle of radiation on tropical cyclone rainbands are explored. In order to improve short term forecasts of tropical cyclone intensity and size, a better understanding of the processes that affect the inner rainbands of tropical cyclones is warranted. In Chapter 2, the distribution of intensity forecast errors from the National Hurricane Center (NHC) are characterized in the Atlantic and East Pacific basins. Analysis of the forecast error distributions and the relationship between the thermodynamic environments in which those errors occur leads to the conclusion that improvements need to be made to our understanding and prediction of inner-core processes, particularly to predict rapid changes in intensification and weakening. The effect of shortwave radiation on tropical cyclone rainbands during an eyewall replacement cycle (ERC) is examined in Chapter 3. In the idealized experiments we vary the amount of incoming solar radiation to change the magnitude of the response and assess the sensitivity of the timing of the ERC. Shortwave radiation has a delaying effect on the ERC primarily through its modifications of the distribution of convective and stratiform heating profiles in the rainbands. Shortwave radiation reduces the amount and strength of convective heating profiles by stabilizing the thermodynamic profiles and reducing convective available potential energy. The idealized modeling study shows that the coupled interactions between the shortwave radiation and the cloud microphysics is at the crux of the experiment and requires further verification by observations. Chapter 4 explores the diurnal cycle of convection in the rainbands of Typhoon Kong-rey (2018) using a suite of novel observations from the Propagation of Intraseasonal Tropical Oscillations (PISTON) field campaign. Convection in the rainbands of Typhoon Kong-rey had a more pronounced diurnal cycle compared to the rest of PISTON where shortwave heating in the upper-levels increased the static stability during the day. Pronounced diurnal oscillations in the brightness temperatures, which are out of phase with those documented in Dunion et al. (2014), are found to be coupled with outflow jets below the tropopause and radially outward propagating convective rainbands approximately ∼6 hours later. In Chapter 5 an attempt is made to simulate the diurnal variations in the rainbands of Typhoon Kong-rey that were observed during PISTON. Four experiments are conducted using commonly used shortwave radiation and cloud microphysics schemes to determine the extent to which previous and future studies can reproduce diurnal variability. Of the four experiments, only one realistically simulated Typhoon Kong-rey's rapid intensification and none of the experiments reproduce the diurnal oscillations in the infrared brightness temperatures. The interactions between the shortwave radiation and cloud microphysics schemes cause variations in the distribution of convective and stratiform pre- cipitation in the inner-rainbands and the extent of upper-level clouds that can largely explain the differences in the intensity. Sensitivity tests suggest that more work on documenting radiation-microphysics interactions is needed to improve model forecasts of inner-rainband structure.Item Open Access On the certainty framework for causal network discovery with application to tropical cyclone rapid intensification(Colorado State University. Libraries, 2022) DeCaria, Michael, author; van Leeuwen, Peter Jan, advisor; Chiu, Christine, committee member; Barnes, Elizabeth, committee member; Ebert-Uphoff, Imme, committee memberCausal network discovery using information theoretic measures is a powerful tool for studying new physics in the earth sciences. To make this tool even more powerful, the certainty framework introduced by van Leeuwen et al. (2021) adds two features to the existing information theoretic literature. The first feature is a novel measure of relative strength of driving processes created specifically for continuous variables. The second feature consists of three decompositions of mutual information between a process and its drivers. These decompositions are 1) coupled influences from combinations of drivers, 2) information coming from a single driver coupled with a specific number of other drivers (mlinks), and 3) total influence of each driver. To represent all the coupled influences, directed acyclic hypergraphs replace the standard directed acyclic graphs (DAGs). The present work furthers the interpretation of the certainty framework. Measuring relative strength is described thermodynamically. Two-driver coupled influence is interpreted using DAGs, introducing the concept of separability of drivers' effects. Coupled influences are proved to be a type of interaction information. Also, total influence is proved to be nonnegative, meaning the total influences constitute a nonnegative decomposition of mutual information. Furthermore, a new reference distribution for calculating self-certainty is introduced. Finally, the framework is generalized for variables that are continuous with one discrete mode, for which partial Shannon entropy is introduced. The framework was then applied to the rapid intensification of Hurricane Patricia (2015). The hourly change in maximum tangential windspeed was used as the target. The four drivers were outflow layer (OL) maximum radial windspeed (uu), boundary layer (BL) radial windspeed at radius of maximum wind (RMW) (ul), equivalent potential temperature at BL RMW (θe), and the temperature difference between the OL and BL (ΔT). All variables were azimuthally averaged. The drivers explained 45.5% of the certainty. The certainty gain was 35.8% from θe, 24.5% from ΔT, 24.0% from uu, and 15.7% from ul. The total influence of θe came mostly from inseparable effects, while the total influence of uu came mostly from separable effects. Physical mechanisms, both accepted in current literature and suggested from this application, are discussed.Item Open Access System design and development of Front-X: an X-band dual-polarization phased array weather radar(Colorado State University. Libraries, 2019) Morin, Alexander, author; Chandrasekar, V., advisor; Cheney, Margaret, committee member; Chiu, Christine, committee memberThe electronic beam steering capability of phased array weather radars has the potential to improve the temporal resolution of meteorological data and enable the development of multifunction radars, yet questions about their dual-polarimetric performance remain an ongoing topic of research. This thesis presents the system design and development of Front-X, an X-band dual-polarization phased array weather radar capable of both electronic and mechanical beam steering, whose purpose is to serve as a test-bed for implementing adaptive scan strategies, developing phased array radar calibration techniques, and exploring the efficacy of electronic scanning for weather applications. The design, development, calibration, and configuration of a system controller, antenna positioner, and signal processor are discussed. Furthermore, the system is demonstrated through a comparison of polarimetric electronic and mechanical scan weather data, including various electronic scan correction methods, and visually verified through a comparison to data collected with the proven CHILL X-band radar.Item Open Access The impact of upper tropospheric temperatures and radiation on idealized tropical cyclones(Colorado State University. Libraries, 2018) Trabing, Benjamin, author; Bell, Michael, advisor; Chiu, Christine, committee member; Suryanarayanan, Siddharth, committee memberPotential intensity (PI) theory predicts that the tropopause temperature acts as a powerful constraint on tropical cyclone (TC) intensity and structure. The physical mechanisms by which the upper tropospheric thermal structure and radiative forcing impact TC intensity and structure have not been fully explored however, due in part to limited observations and the complex interactions between clouds, radiation, and storm dynamics. Idealized Weather Research and Forecasting (WRF) ensembles were conducted using a combination of three different tropopause temperatures (196, 199, and 202 K) with different radiation schemes (full diurnal radiation, longwave only, and no radiation) on weather timescales. The simulated TC intensity and structure were strongly sensitive to colder tropopause temperatures using only longwave radiation, but were less sensitive using full-radiation and no radiation. The maximum intensity of the longwave only simulations were more sensitive to small boundary layer moisture perturbations in the initial conditions. Colder tropopause temperatures resulted in deeper convection, increased ice mass aloft, and when radiation was included more intense storms on average. Deeper convection led to increased local longwave cooling rates but reduced top of atmosphere outgoing longwave radiation, such that from a Carnot engine perspective, the radiative heat sink is reduced in the stronger storms. It is hypothesized that a balanced response in the secondary circulation described by the Eliassen equation arises from upper troposphere radiative cooling/heating anomalies that leads to stronger tangential winds. The results of this study further suggest that cloud-radiative feedbacks have a non-negligible impact on weather timescales.Item Open Access Trends in regional atmospheric water cycles across ocean basins diagnosed using multiple products(Colorado State University. Libraries, 2021) Koeritzer, Drew W., author; Kummerow, Christian, advisor; Chiu, Christine, committee member; Niemann, Jeffrey, committee memberThe importance of water within the earth system, especially its direct impacts on weather and climate through its presence and transport in the atmosphere, cannot be overstated. Accordingly, it is critical to obtain an accurate baseline understanding of the current state of the atmospheric branch of the water cycle if we are to infer future changes to the water cycle and associated influences on weather and climate. Technological advances in both remote and in-situ observing systems have made it possible to characterize water and energy budgets on global scales. However, relatively little work has been done to study the degree of closure, and thus the accuracy of these methods, at regional scales – especially over the oceans. This is a task complicated by the lack of long-term continuous data records of the variables of interest, including ocean surface evaporation, atmospheric water vapor flux divergence, and precipitation. This work aims to fill these gaps and contribute to the establishment of a baseline understanding of the water cycle within the current TRMM and GPM era. The evolution of water cycle closure within five independent regions in the equatorial Pacific, Atlantic, and Indian Oceans has been established previously using atmospheric reanalysis and gridded observational and pseudo-observational data products. That research found that while the water budgets closed extremely well in most basins, the water cycle within the West Pacific was found to trend out of closure within the first decade of the 21st century. The current study aims to extend this analysis temporally, in addition to including a wider variety of independent data sources to confirm the presence of this emerging lack of closure and hypothesize the reason for its existence. Differences between independent products are used within the context of each region to infer whether the emerging lack of closure is a data artifact or is a result of a more fundamental shift in the physical mechanisms and characteristics of the evaporation, precipitation, or water vapor flux divergence within a specific region. Results confirm an initial hypothesis that the emerging lack of water cycle closure in the West Pacific is not due to satellite or instrument drift. Rather, it appears to be related to changes in the prevalence of deep isolated versus deep organized convection in the West Pacific region and its associated impact on passive microwave precipitation retrieval algorithms.Item Open Access Using GOES-16 ABI data to detect convection, estimate latent heating, and initiate convection in a high resolution model(Colorado State University. Libraries, 2021) Lee, Yoonjin, author; Kummerow, Christian D., advisor; Zupanski, Milija, advisor; Bell, Michael B., committee member; Chandrasekar, V., committee member; Chiu, Christine, committee memberConvective-scale data assimilation has received more attention in recent years as spatial resolution of forecast models has become finer and more observation data are available at such fine scale. Significant amounts of observation data are available over the globe, but only a limited number of observations are assimilated in operational forecast models in the most effective way. One of the most important observation data for predicting precipitation is radar reflectivity from ground-based radars as it provides three-dimensional structure of precipitation. Many operational models use these data to create cloud analysis and initiate convection. In High-Resolution Rapid Refresh (HRRR), the cloud permitting operational model at National Oceanic and Atmospheric Administration (NOAA) that is responsible for short term forecasts over the Contiguous United States (CONUS), latent heating is derived from ground-based radars and added in the observed convective regions to initiate convection. Even though adding heating is shown to improve forecasts of convection, this cannot be done over ocean or mountainous regions where radar data is not available. Geostationary data are available regardless of radar coverage and its data are provided in similar spatial and temporal resolution as ground-based radar. Currently, geostationary data are only used as a source of cloud top information or atmospheric motion vectors due to lack of vertical information. However, Geostationary Operational Environmental Satellites (GOES)-16 and -17 have high temporal resolution data that can compensate the lack of vertical information. From loops of one-minute visible images, convective clouds can be detected by finding a region with a constant bubbling. Therefore, this dissertation seeks a way to use these high temporal resolution GOES-16 data to mimic what radars do over land. In the first two papers presented in the dissertation, two methods are proposed to detect convection using one-minute GOES-16 Advanced Baseline Imager (ABI) data. The first method explicitly calculates Tb decrease or lumpiness of reflectance data and finds convective regions. The second paper tries to automate this process using machine learning method. Results from both methods are comparable to radar product, but the machine learning model seems to detect more convective regions than the conventional method. In the third paper, latent heating profiles for convective clouds are estimated from GOES-16. Once a convective cloud is detected, latent heating profiles corresponding to cloud top temperature of the convective cloud is searched from the lookup table created using model simulations. This technique is similar to spaceborne radar inferred latent heating developed for National Aeronautics and Space Administration (NASA)'s Global Precipitation Measurement Mission (GPM). Latent heating assigned from GOES-16 is shown to be similar to latent heating derived from Next-Generation Radar (NEXRAD) once they are summed up over each cloud. Finally in the last paper, latent heating estimated by using the method from the third paper are assimilated into the Weather Research and Forecasting (WRF) model to examine impacts of using GOES-16 derived latent heating in initiating convection in the forecast model. Two case studies are presented to compare results using GOES-16 derived heating and NEXRAD derived heating. Results show that using GOES-16 derived heating sometimes produce deeper convection than it should, but it improves overall precipitation forecasts. This appears related to the much deeper column of heating assigned by GOES than the empirical relation used by the HRRR operational scheme. In addition, in a case when storms developed over Gulf of Mexico where radar data are not available, forecasts are improved using GOES-16 latent heating.Item Open Access Utilization of convolutional neural networks in the classification of snowflakes based on images by a multi-angle snowflake camera(Colorado State University. Libraries, 2019) Hicks, Adam, author; Notaros, Branislav, advisor; Chiu, Christine, committee member; Pezeshki, Ali, committee memberRecent developments in machine learning are applied to in-situ data collected by a Multi-Angle Snowflake Camera (MASC), incorporating convolutional and residual networks in big data environments. These networks provide the following benefits: require little initial preparation and automatic feature extraction, high accuracy and through transfer learning techniques, and relatively small training sets. The networks have large supporting communities and are popular for image processing and classification tasks specifically. In this paper, a convolutional neural network (CNN) is adapted and tasked with classifying images captured from two storm events in December 2014 and February 2015 in Greeley, Colorado. A training data set containing 1400 MASC images was developed by visual inspection of recognizable snowflake geometries and sorted into six distinct classes. The network trained on this data set achieved a mean accuracy of 93.4% and displayed excellent generality. A separate training data set was developed sorting flakes into three classes showcasing distinct degrees of riming. The network was then tasked with classifying images and estimating where flakes fell within this riming scale. The riming degree estimator yields promising initial results but would benefit from larger training sets. Future applications are discussed.