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Empathy in Frames: Assessing the Impact of Ethnic Concordance in Animated Cartoons on HIV/AIDS Stigma among South African Young Adults
No full textThis dissertation investigates whether culturally tailored animated interventions can reduce HIV- and AIDS-related stigma among young adults in South Africa.
Despite ongoing public health campaigns, HIV stigma remains a persistent barrier to prevention and treatment, particularly in populations historically marginalized by race and socio-economic status. Given the increasing reach of digital media, this project explores whether short-form animated videos can serve as cost-effective, scalable tools for stigma reduction—especially when tailored to reflect the cultural identity of target audiences. The dissertation comprises four studies.
First, a rapid review of randomized controlled trials (RCTs)targeting HIV-related stigma identifies key gaps in the literature. Second, a pre-specified research protocol outlines an experimental approach to testing culturally resonant messaging through animation. Third, a pilot study compares two animated videos—one featuring a Black South African protagonist and one with a White protagonist—to explore early signals of effectiveness and inform the full-scale RCT. Fourth, the main trial evaluates the impact of ethnic concordance between message protagonist and viewer on HIV stigma, knowledge, and engagement outcomes using a randomized controlled design with 729 participants.
Findings from the pilot and full study suggest that cultural tailoring through protagonist ethnicity mayenhance knowledge acquisition and perceptions of ethnic representation in health messages, though effects on HIV stigma were less robust. The studies also suggest that these types of HIV-literacy cartoons could have high levels of user engagement, and that deploying short animated interventions via digital platforms could be feasible and merit further research. Together, the results provide new evidence for the role of culturally specific media in public health communication and suggest promising directions for future research and intervention design
Perinatal Health Experiences and Outcomes Among Black and Hispanic Women with Disabilities
No full textBACKGROUND:
A long and continued history of systemic racism in the United States has contributed to stark racial and ethnic disparities in adverse perinatal health outcomes. Women with disabilities also experience a high burden of adverse perinatal health outcomes and continue to encounter disability-based discrimination (i.e., ableism) in healthcare. However, little is known about the perinatal health of Black and Hispanic women with disabilities. This is a significant gap in knowledge, as women who experience the compounded influence of racism and ableism may have an increased risk of adverse perinatal health outcomes. Therefore, the overall purpose of this dissertation was to study the pregnancy and postpartum experiences and outcomes of Black and Hispanic women with disabilities. The aims were to: (1) synthesize studies describing the perinatal healthcare experiences of people with physical, sensory, and/or intellectual and developmental disabilities to identify shared and unique care needs; (2) examine the associations between maternal disability status and adverse pregnancy outcomes among Black and Hispanic women; and (3) examine the associations between maternal disability status and attendance at a four-to-six-week postpartum health visit among Black and Hispanic women.
METHODS:
We conducted three studies in this dissertation: (1) a meta-synthesis of the qualitative literature following Sandelowski and Barroso’s methods to synthesize the perinatal healthcare experiences of people with disabilities in the United States and Canada; (2) a secondary analysis of Pregnancy Risk Assessment Monitoring System (PRAMS) surveys and multivariable logistic regression to estimate the odds of preterm birth, low birthweight, and small for gestational age by overall disability, reported level of difficulty, and disability type; (3) a secondary analysis of PRAMS surveys and multivariable logistic regression to estimate the odds of attendance at a four-to-six-week postpartum health visit also by overall disability, reported level of difficulty, and disability type. In the quantitative Aims 2 and 3, disability was measured with the Washington Group-Short Set of Questions on Functioning (WG-SS), a self-report survey which asks respondents to rate the level of difficulty they experience in six domains of functioning (i.e., vision, hearing, mobility, cognition, self-care, and communication).
RESULTS:
In Aim 1, we identified 21 studies and synthesized three overarching themes: (1) Pervasive Ableism, (2) An Uninformed and Unaccommodating Experience, and (3) Resilience in the Face of Ableism. We also identified subthemes describing unique experiences by disability type, such as the nature of perinatal healthcare inaccessibility. In addition, we found that minoritized people with disabilities often reported stigmatizing experiences with clinicians. In Aim 2 (N=8,747), we found no statistically significant differences in the odds of preterm birth or low birthweight by overall disability, reported level of difficulty, or type of disability, including multiple disabilities. Women with any disability were 44% less likely to have a small for gestational age infant compared to women without disabilities. The odds of having a small for gestational age infant were significantly higher among women who reported ‘some difficulty’ to any WG-SS item compared to women who reported ‘no difficulty’ to all items. However, we did not observe this association among women who reported ‘a lot of difficulty’ on the WG-SS. In addition, women who reported a communication disability were 70% less likely to have a small for gestational age infant compared to women without disabilities. Further, Black women with any disability were 50% less likely to have a small for gestational age infant compared to Black women without disabilities. There were no significant differences in small for gestational age among Hispanic women with and without disabilities. In Aim 3 (N=9,034), we found that women with any disability were 62% less likely to attend a four-to-six-week postpartum health visit compared to women without disabilities. We also observed a significant decrease in the odds of attending the visit as women’s reported level of difficulty increased. Specifically, women who reported ‘some difficulty’ to any WG-SS item were 28% less likely to attend, while women who reported ‘a lot of difficulty’ were 67% less likely to attend the visit compared to women who reported ‘no difficulty’ to all items. In analyses by disability type, women who reported blindness/low vision, cognition disability, communication disability, or multiple disabilities were significantly less likely to attend the visit relative to women without disabilities. In within-group analyses, Black women with any disability were 52% less likely to attend compared to Black women without disabilities. Hispanic women with any disability were 72% less likely to attend compared to Hispanic women without disabilities.
CONCLUSIONS:
Our findings suggest that Black and Hispanic women with disabilities experience stigmatizing encounters with clinicians and this intersectional oppression may contribute to perinatal health inequities. Although we found inconsistent evidence supporting the associations between maternal disability and adverse pregnancy outcomes, there were stark inequities in attending a four-to-six-week postpartum health visit by disability status in all analyses. Therefore, there is an urgent need to understand the barriers to postpartum healthcare for Black and Hispanic women with disabilities to prevent maternal morbidity and mortality. This dissertation contributes to the sparse published literature on the perinatal health of Black and Hispanic women with disabilities and provides preliminary evidence to inform clinical practice, policy, and future research to advance perinatal health equity
A New Ruling Class and Its Empires: The Case of Nineteenth-Century Egypt
No full textEgypt in the nineteenth century saw a rapid shift towards state modernization, the formation of a modern army, some degree of transition to capitalism, and a new ruling class. The state and its new ruling class consistently sought autonomy but not independence from the Ottoman Empire while being invested in their own colonial venture, controlling a sizeable territory in Central and East Africa. Yet, in 1882, parts of the same ruling class called for British military intervention in Egypt. Under British occupation, Egypt remained an Ottoman province for decades and retained some of its imperial interests in Sudan.
This dissertation offers a new holistic account of why Egypt was concurrently a province in the Ottoman Empire, a colonial force expanding its territories in Sudan, and, in 1882, occupied by the British. By focusing on Egypt’s economic elites, it shows how their internal conflicts and developing relationships with the state are vital in understanding Egypt’s peculiar position in relation to the Ottoman and British Empire as well as the occupation of Sudan. This is part of a broader argument that power structures in the periphery are integral to understanding imperialism. This story does not easily fit our conventional understandings of empires, modernization, and nation-state formation. Historians have written extensively on different sides of this story, yet a convincing account of how these overlapping and, seemingly contradictory manifestations of imperialism exist simultaneously is missing.
Based on extensive archival research using Arabic, Ottoman, English, and French sources, the dissertation explores the emergence and significance of this new class. The rise of this class of large landholders and financiers is often understood as an outcome of the failure of Mehmed Ali’s state centralization and market control efforts in the first half of the century. The dissertation shows that it was the same centralization and market control that drove the rapid process of land expropriation and consolidation, creating a new class of large landholders by the mid-century.
This class, in turn, contributed to dismantling the very system that created it. The interests of the landed elite are thus central to understanding the economic and social transitions of the mid-nineteenth century. It follows these elites, arguing that conflicts of interest within these groups and the state’s attempts to manage them contributed to the shaping and development of Egyptian state institutions. The dissertation shows how networks of economic interests, together with the balance of power between different groups of elites, depended on Egypt continuing to be a province of the Ottoman Empire. The dissertation then argues that Egyptian territorial expansions in Sudan were driven by interests in expanding cotton plantations and exerting more control over trade in the region. Finally, I argue that the key to understanding the British occupation in Egypt lies in the decision among parts of the Egyptian ruling class to call for British military intervention. This decision was taken in reaction to a middle-class revolution that coincided with a deep crisis within the ruling class.
My dissertation is part of a broader research agenda that focuses on local class actors and revisits the political economies of late development and imperialism. The project engages extensively with existing debates on imperialism, particularly with regard to the British Empire. The British occupation of Egypt in 1882 has long played a central part in the historiography of the British Empire and the development of theories of imperialism. Expanding our explanatory scope to the multiple forms of imperialism in the case of Egypt in the second half of the nineteenth century provides a unique potential to test the limits of our understanding of these questions
Dynamical Climate Drivers of Forest Fire in Western North America and Beyond
No full textBurned forest area has increased significantly in Western North America in recent decades, driven in part by climate conditions becoming more conducive to fire. This dissertation advances our understanding of the large-scale climate dynamics that drive drought and forest fire in Western North America and similar regions around the world. We also investigate the causes and implications of climate model biases in simulating natural climate variability, particularly for modes and phases of variability with large impacts on drought and fire in Western North America.
In the first chapter, we identify regional and global climate patterns in preceding seasons that typically influence the year-to-year variability of burned summer forest area in California. High vapor pressure deficit (VPD), high temperatures, low precipitation, high subsidence, high geopotential height, low soil moisture, and low snowpack and snowmelt anomalies all correlate significantly with July California burned area as far back as the January before the fire season. These climate anomalies occur as part of a hemispheric scale pattern with weak connections to the tropical Pacific Ocean. We explain how climate and weather anomalies, particularly extreme heat, drove the record-breaking burned-area year of 2018.
VPD, a function of temperature and humidity, is a skillful seasonal predictor of burned area in the southwestern United States (the ”Southwest”). Unexpectedly, despite the increased capacity of a warmer atmosphere to hold water vapor, near-surface specific humidity decreased from 1970 to 2019 in much of the Southwest, particularly in spring, summer, and fall. In Chapter 2, we identify declining near-surface humidity from 1970 to 2019 in the Southwest with reanalysis and in situ station data. Focusing on the interior Southwest in the months preceding the summer forest fire season, we find that an early spring decline in precipitation in the interior region induced a decline in soil moisture and evapotranspiration, drying the lower troposphere in summer. This prior season precipitation decline is in turn related to a trend toward a Northern Hemisphere stationary wave pattern that places a high pressure ridge over the interior Southwest. Using fixed humidity and temperature scenarios and the observed exponential relationship between VPD and burned forest area, we estimate that with no increase in temperature at all, the humidity decline alone would still lead to nearly one-quarter of the observed VPD-induced increase in burned area over 1984–2019.
Sea-surface temperature variability in the Pacific plays a powerful role in evolving global hydroclimate on decadal timescales, particularly in Western North America. Chapter 3 evaluates the ability of the current generation of climate models (CMIP6) to simulate realistic decadal sea-surface temperature variability in the Pacific and its teleconnections to circulation, precipitation, and aridity around the world. Using CMIP6 model large ensembles, we evaluate model fidelity in reproducing spatial and temporal characteristics of the Pacific Decadal Oscillation (PDO) and the Interdecadal Pacific Oscillation (IPO), and their hydroclimate teleconnections compared to observations. We find that models’ underestimation of decadal-scale Pacific SST variability is associated with their inability to produce large-amplitude decadal swings in precipitation in Southwestern North America that drive decadal variability in VPD. Finally, in Chapter 4, we investigate and contrast the possible climate drivers of observed increases in fire in the southwestern U.S. versus Eastern Australia, two of the most fire-prone regions of the world with significant, opposite-signed hydroclimate teleconnections to modes of Pacific decadal variability. We show that in both regions, VPD has increased with a large contribution from anthropogenic climate change. In the southwestern U.S., the recent trend in the tropical Pacific west--east sea surface temperature (SST) gradient contributed positively to the VPD-induced increase in burned forest area since 1984. However, in Eastern Australia, the tropical Pacific SST gradient trend has likely offset the anthropogenic climate change-induced increase in burned forest area
Statistical Methods for Complex, Biased, and Sparse Health Record Data
No full textBiomedical research increasingly relies on statistical and machine learning methods to extract meaningful insights from complex, high-dimensional data. Standard approaches often fail to capture the full scope of dependencies, biases, and heterogeneity inherent in biomedical datasets. Three major challenges hinder our ability to draw accurate conclusions from such data: (1) the limitations of conventional statistical methods in detecting complex relationships, (2) datasets affected by nonrandom sample selection, which distorts what we are able to learn, and (3) capturing complex patterns given limited data size and sparsity. This dissertation develops novel methodological solutions to address these challenges, with applications in structure learning, causal mediation analysis, and longitudinal disease modeling.
A fundamental goal in biomedical research is to accurately learn dependencies between biomarkers in physiological systems. Graphical models may be used for this purpose, however, standard approaches rely on independence assumptions that often miss associations occurring at the tails of distributions. This is important in many biological settings where extreme values signal disease or dysfunction. We introduce Quantile Association via Conditional Concordance (QuACC), a novel measure of conditional association designed to capture quantile-specific dependencies in multivariate data. We use this statistic to construct quantile-specific graphical models that reveal dependencies overlooked by traditional methods. When applied to biobank data, we reveal tail-dependent interactions between biomarkers in individuals with mitochondrial disease.
Beyond understanding biomarker associations, causal inference is necessary for evaluating the impact of social and medical factors on health outcomes. In clinical decision-making, sample selection bias can distort causal effects estimates. For example, in liver transplantation, only a subset of referred patients complete the evaluation process, with dropout often influenced by social determinants of health (SDOH), including race and neighborhood deprivation factors. Using causal graphical models, we develop a method to correct for selection bias in causal mediation analysis, and recover unbiased direct, indirect, and path-specific effects from socioeconomic position to transplant listing status. This approach enables the study of causal questions that are affected by sample selection bias.
Finally, improving health outcomes requires not only an understanding of causal mechanisms, but also the ability to accurately model complex covariate behavior, particularly in the presence of small sample sizes and data sparsity. The long-term effects of severe illnesses, such as COVID-19 acute lung injury (ALI)/ARDS, remain poorly understood, especially regarding persistent biomarker abnormalities and physical function impairments. Using longitudinal modeling and time series clustering, we investigate persistent elevations in inflammatory and endothelial biomarkers among COVID-19 ALI/ARDS survivors over a three-year period. These findings show the lasting physiological and physical function impacts of severe COVID-19 and emphasize the need for targeted post-recovery interventions.
Together, these contributions advance the statistical foundations of biomedical data analysis by developing new methodologies for dependency modeling of biomarkers, drawing causal inference under selection bias, and characterizing diseases in small, sparse datasets. These methods aim to inform both scientific discovery and clinical decision-making
Preserving Saudi’s Modern Heritage: The Case of SOM, Yamasaki, and Transnational Modernism
No full textThe Kingdom of Saudi Arabia, as we know it today, has a long and culturally rich history. That history has been safeguarded by the Saudi Ministry of Culture since its establishment, starting with the humble beginning of the Antiquity and Museums Agency of 1964. Over the past few years, not only has the Ministry of Culture expanded, but it has also generated new cultural disciplines to include under its governance. What started as a simple agency developed into eleven diverse cultural commissions that one ministry governs. As a result, preservation efforts expanded discipline-wise to render a more holistic image of Saudi Arabia’s cultural heritage.
During the era of the Antiquity and Museum Act of 1972, the focus was primarily on preserving vernacular architecture and archeological sites of importance. However, now that the focus of the Ministry has broadened, preliminary efforts have been extended to preserve the plethora of cultural disciplines that exist in the entirety of the country. This thesis will analyze how current preservation policies and frameworks influence the Modern Heritage of a certain era in Saudi Arabia’s development. The era in reference is often referred to as the Leap, a period of architectural and developmental significance in the history of the country that began in the 1960s and reached its peak in the 70s.
The Leap, which was rendered a leap due to the surge in development following the commercialization of petroleum, birthed monumental Modernism in Saudi Arabia. The significance of that architecture has been historically neglected in books that historicize the Modernist era, despite the unique circumstances that brought it about. This research highlights the significance of transnational Modernism in Saudi Arabia by relaying its petroleum-embedded history. Using the work of SOM and Yamasaki as a basis, this thesis aims to analyze how current preservation policies and initiatives are successful or lacking in their interaction with Modern Heritage, and consequently, the potential benefits and challenges of preserving transnational Modernism
Cryogenic Ultrafast Nanoscopy of Complex Materials
No full textIn this dissertation, we address the longstanding challenge of directly probing electronic and structural dynamics in complex quantum materials at length scales far below the diffraction limit. To do so, we have developed a versatile tabletop beamline capable of generating and detecting light from the visible through the mid-infrared (MIR) and into the terahertz (THz) range which we then couple into our home built cryogenic scattering-type scanning near-field optical microscope (Cryo-SNOM). Our custom beamline employs a high-power, ultrafast Yb-doped laser and nonlinear optical phenomena – most notably tilted-pulse-front pumping of LiNbO₃ for broadband THz generation and electro-optic sampling in ZnTe for sensitive time domain detection. This beamline delivers more than 10 mW of THz radiation spanning 0.1–3 THz with >80 dB dynamic range and a temporal resolution of 20 fs.
This THz light is coupled into the near field via an atomic force microscope tip, thus providing ~100 nm spatial resolution.Using a room temperature microscope coupled to our ultrafast source, we first investigate nanoscale femtosecond dynamics of the Mott insulator Ca₂RuO₄ in the MIR. Temperature-cycling experiments reveal surface-confined stripe domains of coexisting insulating and metallic phases, whose depth and volume fraction evolve predictably across the insulator-metal transition. Ultrafast pump-probe SNOM then shows that above-gap photoexcitation injects free carriers that rapidly become trapped, likely as polarons, producing a transient mid-gap absorption and phonon renormalization on a sub-picosecond timescale.
Next, we turn to van der Waals (vdW) heterostructures. We employ our custom built Cryo-SNOM coupled to our newly developed THz beamline to investigate propagating plasmon polaritons – a coupled light-matter mode encoded with the electronic properties of the host medium. First, we visualize charge-transfer plasmons propagating in bespoke graphene/α-RuCl₃ lateral cavities. These measurements represent a new paradigm for quantitative characterization of long-wavelength polaritons in any vdW heterostructure while also providing insight into the nature of plasmons in graphene/α-RuCl₃ heterostructures. Second, using space-time mapping metrology we study propagating plasmon polaritons in graphene/hBN/Bi₂Sr₂CaCu₂O₈₊δ cavities.
In these preliminary measurements, we demonstrate long lived, gate tunable plasmons in graphene separated by a ~20 nm hBN spacer from optimally doped Bi₂Sr₂CaCu₂O₈₊δ. This proximity can lead to coupling between the graphene plasmons and the hyperbolic polaritonic modes in the high-temperature superconductor. Then, using magnetic-force microscopy, we measure the local Meissner effect in the Bi₂Sr₂CaCu₂O₈₊δ embedded in these vdW cavity heterostructures. From these measurements, we extract the local the superfluid density in the Bi₂Sr₂CaCu₂O₈₊δ flake and any potential modification related to plasmonic coupling with the proximal graphene layer.
Finally, we demonstrate space-time duality in plasmon polariton propagation in graphene. By tailoring ultrafast complex-frequency excitations, we sustain polaritonic fields over unprecedented distances, revealing new pathways for spatio-temporal control of light–matter interactions at the nanoscale.
Together, these studies establish Cryo-SNOM as a multi-messenger probe that unifies ultrafast spectroscopy, near-field imaging, and local scanning probes, and opens routes to manipulating and understanding emergent phenomena in correlated and low-dimensional materials
Unlocking Storage Performance: A Systems Approach to Kernel Bypass, Replication, and Caching
No full textModern storage technologies, such as NVMe SSDs and RDMA-enabled network fabrics, offer unprecedented performance, significantly raising the bar for software infrastructure efficiency. However, traditional storage software stacks, particularly within the Linux kernel, have emerged as critical performance bottlenecks, limiting the full utilization of these hardware capabilities. This thesis addresses this challenge through a systematic exploration of kernel bypass, replication efficiency, and caching strategies, each aimed at significantly improving storage system performance.
The first component of this thesis introduces BPF-KV, a key-value store designed around XRP, an innovative in-kernel execution framework utilizing eBPF (extended Berkeley Packet Filter). BPF-KV leverages XRP to safely bypass the kernel storage stack, executing critical storage functions directly within the NVMe interrupt handler. By embedding simple, user-defined functions such as index traversals and aggregations in kernel space, BPF-KV minimizes kernel-user space crossings, significantly reducing latency and improving throughput. This approach maintains compatibility with existing kernels and preserves essential system properties such as isolation and security, unlike traditional kernel bypass techniques like SPDK, which sacrifice safety and CPU efficiency. Experimental results demonstrate that BPF-KV achieves up to 2.5× higher throughput and substantially lower tail latency compared to traditional system calls.
The second contribution, RubbleDB, addresses inefficiencies in replicated log-structured merge (LSM) tree-based key value stores, prevalent in modern databases. Traditional replication mechanisms redundantly execute compaction operations across replicas, consuming excessive CPU resources. RubbleDB eliminates this redundancy by using NVMe-over-Fabrics (NVMe-oF), an efficient, CPU-friendly networked storage protocol, to share compacted SSTable files directly between replicas. By pre-allocating storage space and employing direct I/O via NVMe-oF, RubbleDB ensures strong consistency and efficient data replication without redundant CPU work. Evaluations demonstrate that RubbleDB significantly reduces CPU usage and network overhead, thereby enhancing the scalability and performance of distributed LSM-tree-based databases under write-intensive workloads.
Finally, the thesis presents DFUSE, a distributed file system that delivers strongly consistent kernel-level write-back caching, overcoming limitations inherent in existing FUSE-based distributed systems. Traditionally, FUSE systems face a trade-off between strong consistency (write-through caching) and high performance (write-back caching with weak consistency). DFUSE resolves this trade-off by embedding distributed coordination logic directly into the kernel’s FUSE driver. By offloading consistency control to the kernel, DFUSE effectively synchronizes the page cache across nodes, ensuring strong consistency while leveraging the performance advantages of write-back caching. Experimental evaluations show DFUSE achieves up to 68% higher throughput and 40% lower latency compared to traditional FUSE designs.
Together, BPF-KV, RubbleDB, and DFUSE represent a holistic systems approach to unlocking the performance potential of modern storage hardware. By systematically addressing kernel overhead, replication inefficiencies, and caching consistency, this thesis offers concrete, widely applicable solutions that significantly enhance storage system performance in diverse deployment scenarios
Automated uterocervical feature extraction from transvaginal ultrasound images to inform preterm birth prediction and digital twin models
No full textPreterm birth (PTB) is the leading cause of perinatal death, affecting approximately 10% of pregnancies, both in the US and abroad. Despite global health campaigns to address PTB, rates have remained stagnant and even on the rise in some countries over the past decade. Currently, transvaginal ultrasound (TVUS) measurement of cervical length (CL) is the soleclinically-accepted quantitative imaging metric for PTB risk, but offers limited predictive value. Many hospital systems incorporate serial CL screening (multiple time points) to identify risk of sPTB, but others have not adopted this practice because there is a lack of scientific consensus on whether this metric is predictive enough to justify the costs. While cervical length is believed to be an important predictor of PTB, it likely does not capture the entire picture of cervicabiomechanical health and remodeling.
Incorporation of additional uterocervical features, describing the shape and size of maternal anatomy, could help improve prediction models of preterm birth, as well as guide computational models of pregnancy. While computational models of cervical biomechanics show promise as risk predictors of PTB, they require precise, time-intensive clinician-provided measurements. Automatic extraction of anatomical features, following AI-enabled ultrasound segmentation, offers a solution to this labeling bottleneck.
This research aims to 1) train AI-based segmentation models to label cervical anatomy from cervical ultrasound images, 2) extract uterocervical geometry measurements from these labeled anatomy masks, 3) examine preliminary links between newly proposed uterocervical geometry features and PTB outcomes, 4) explore how these geometries can be used to automatically create three dimensional geometries for simulations of pregnancy, and 5) create a large clinical dataset of cervical ultrasound images linked to patient health record data and birth outcomes (gestational age at delivery). Because pregnancy is a protected population, databases of this nature are extremely limited in number and access. Ultimately, the newly curated clinical database can be used to verify the results of this research and support future studies of pregnancy.
This research explores a new paradigm to measure cervical structural features in-vivo, which can be used to power 3D digital twin models of pregnancy, quantitative ultrasound-based stiffness measurements of the cervix, and machine-learning based prediction models of PTB. Additionally, this work can be adapted as a teaching-tool for novice sonographers, and used to increase access to cervical length screening for PTB in low-resource settings. Ultimately, this technology may be deployed in the clinic to guide sonographers taking cervical ultrasound images, and provide human-in-the-loop automation of cervical feature measurements, which may better describe cervical structural health in pregnancy, and therefore elucidate the pathways of preterm birth prevention
Interactions between soil moisture and precipitation in a changing world
No full textThis dissertation explores the direct (irrigation) and indirect (climate change) impacts of anthropogenic activities on soil moisture and precipitation, including the two-way coupled interactions between the atmosphere and land surface. Together, these chapters provide an integrated view of the water cycle, complicated by the context of a warming climate. For the water cycle, climate change is not just a story of precipitation changes, but also a story about altered atmospheric evaporative demand—with links to drought onset and termination, soil moisture dynamics, and human water management.
Here we ask: how will soil moisture and precipitation respond to climate change? And how will changes in soil moisture from anthropogenic activities affect the earth system? Chapter 1 outlines the interactions between soil moisture, precipitation, and irrigation within the changing water cycle. Chapter 2 demonstrates that warming-driven increases in evaporative demand require greater rainfall to terminate droughts in many regions. Chapter 3 reveals how moisture supply and demand mechanisms drive surface drydown dynamics. Chapter 4 shows that irrigation can influence precipitation patterns across continental scales, demonstrating the far-reaching consequences of artificially altering the water cycle.
Anthropogenic climate change has already affected drought severity and risk across many regions and climate models project additional increases in drought risk with future warming. Historically, droughts are typically caused by periods of below-normal precipitation and terminated by average or above-normal precipitation. In many regions, however, soil moisture is projected to decrease primarily through warming-driven increases in evaporative demand, potentially affecting the ability of negative precipitation anomalies to cause drought and positive precipitation anomalies to terminate drought.
In Chapter 2, we use climate model simulations from Phase Six of the Coupled Model Intercomparison Project (CMIP6) to investigate how different levels of warming (1, 2, and 3°C) affect the influence of precipitation on soil moisture drought in the Mediterranean and Western North America regions. We demonstrate that the same monthly precipitation deficits (25th percentile relative to a preindustrial baseline) at a global warming level of 2°C increase the probability of both surface and rootzone soil moisture drought by 29 % in the Mediterranean and 32 % and 6 % in Western North America compared to the preindustrial baseline. Furthermore, the probability of a dry (25th percentile relative to a preindustrial baseline) surface soil moisture month given a high (75th percentile relative to a preindustrial baseline) precipitation month is 6 (Mediterranean) and 3 (Western North America) times more likely in a 2°C world compared to the preindustrial baseline. For these regions, warming will likely increase the risk of soil moisture drought during low precipitation periods while simultaneously reducing the efficacy of high precipitation periods to terminate droughts.
Soil moisture drydown is an important characteristic of surface hydrology, with strong relevance for how drought may change in a warming world. However, traditional methods of calculating soil drydown generally assume moisture is lost exponentially following a precipitation event but fail to account for continued moisture infusions from subsequent precipitation.
In Chapter 3, we introduce a new approach for assessing surface soil moisture drydown that allows us to determine the time it takes for an infusion of precipitation to leave the soil without a priori filtering of precipitation events. Our simple model provides a more flexible framework for analyzing the sensitivity of soil moisture dynamics to climate across different seasons and timeframes. Applying our approach to western North America, we characterize soil moisture drydown across several observation-derived datasets (MERRA-2, NLDAS-2 MOSAIC, NLDAS-2 NOAH), testing the sensitivity of drydown times to seasonality, precipitation, and the land surface model used.
We find that this simple model can provide coherent drydown estimates for both MERRA-2 and NLDAS-2 MOSAIC. In NLDAS-2 NOAH, however, drydown time is more poorly defined due to increased surface soil moisture and lower evapotranspiration. We use this model to estimate the observational uncertainty in drydown times and set new benchmarks against which climate models can be evaluated. The approach can enhance our understanding of drought initiation and termination, including how characteristics of soil moisture drought may change in a warming climate. Irrigation has long been both an essential tool in global agriculture and a significant anthropogenic land-use forcing of climate. However, while the effects of irrigation on surface energy partitioning and temperature are well established, the effects of this land use forcing on precipitation are more uncertain.
In Chapter 4, we use GISS ModelE, a state-of-the-art general circulation model, with irrigated and non-irrigated scenarios to explore how irrigation affects precipitation across monsoon and non-monsoon regions of North Africa, West Africa, Southwest Asia, and Southeast Asia. We find that irrigation increases precipitation across most non-monsoonal areas of tropical and subtropical Asia and North Africa and within monsoon regions outside the summer monsoon season. These increases in precipitation occur both locally, in irrigated grid cells, and also far outside the main geographic centers of irrigation.
However, monsoon season precipitation responses to irrigation are mixed, with large increases in non-irrigated West Africa; increases over the intensely irrigated area of Northwest India; declines over peninsular India; and modest declines in Southeast Asia. Precipitation responses outside of monsoon regions, or outside the main monsoon season, are largely explained through the effect of irrigation on moist static instability: readily available surface moisture in heavily irrigated regions increases surface moist static energy and that forcing is large enough to reduce free tropospheric temperatures, decreasing moist static energy aloft across the entire domain. By contrast, monsoon precipitation responses are driven by the effects of irrigation on large scale circulation and moisture flux convergence. Chapter 4 highlights, for the most intensively irrigated region of the world, the complexity of mechanisms involved in the seasonally and geographically diverse precipitation responses.
The evidence presented here demonstrates that human interventions through irrigation and greenhouse gas emissions create cascading effects throughout the global water cycle, requiring both mitigation of warming and adaptive management strategies that account for these hydrological dynamics