Bayesian Hierarchical Models for Remote Assessment of Atmospheric Dust

Dust storms emerging in the Earth's major desert regions significantly influence weather processes, the CO2-cycle and the climate on a global scale. Their effects on organisms range from providing nutrition to vegetation and microbes to direct impact on human settlements, transportation and health. The detection of dust storms, the prediction of their development, and the estimation of sources are therefore of immediate interest to a wide range of scientific disciplines. Recent spatio-temporal resolution increases of remote sensing instruments have created new opportunities to understand these phenomena. The scale of the data and their inherent stochasticity, however, pose significant challenges. This thesis develops a combination of methods from statistics, image processing, and physics that paves the way for efficient probabilistic dust assessment using satellite imagery. As a first step, we propose a BHM that maps SEVIRI measurements to a predictor of the dust density. Case studies demonstrate that, as compared to linear methods, our LSM approach mitigates effects of signal intrinsic noise on further processing steps. Furthermore, an extensive cross-validation study is employed to show that LSM successfully adapts to intra-daily changes of the infrared data and yields outstanding dust detection accuracy. Physically, the dust density and its transport process are tied together by the continuity equation. A traditional approach to determine the flow field for a given density is the variational method of Horn and Schunck (HS), which simplifies the equation to compression free motion. We characterize the equation's solution as a GMRF and introduce compressible dynamics. This link between probabilistic and variational perspectives leads to applied and theoretical advances. It enables us to employ the INLA technique for computationally efficient inference and integration over hyper-parameters. The importance of allowing for compressible motion and treating the problem in a statistical manner is emphasized by simulation and case studies showing a significant reduction in errors of the estimated flow field. In addition, we demonstrate how our methodology provides uncertainty quantification, dust storm forecasts and estimation of emission sources. The thesis is concluded by examining the analytical properties of our approach. It is shown that, under mild restrictions on an underlying Sobolev space, existence and uniqueness of the compressible flow can be guaranteed on a continuous domain and a well-posed discretization exists. Lastly, our variational calculations point to an interpretation of the density as a solution to flow-parameterized SPDE naturally extending Matern fields to non-isotropy, which provides a further step towards a joint model of dust density and flow field

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth\u27s atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle‐based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next‐generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process‐level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle‐based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods

5th Annual Jackson School Research Symposium

Geological Science

Research reports: 1991 NASA/ASEE Summer Faculty Fellowship Program

The basic objectives of the programs, which are in the 28th year of operation nationally, are: (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate an exchange of ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of the participants' institutions; and (4) to contribute to the research objectives of the NASA Centers. The faculty fellows spent 10 weeks at MSFC engaged in a research project compatible with their interests and background and worked in collaboration with a NASA/MSFC colleague. This is a compilation of their research reports for summer 1991

1992 NASA/ASEE Summer Faculty Fellowship Program

For the 28th consecutive year, a NASA/ASEE Summer Faculty Fellowship Program was conducted at the Marshall Space Flight Center (MSFC). The program was conducted by the University of Alabama and MSFC during the period June 1, 1992 through August 7, 1992. Operated under the auspices of the American Society for Engineering Education, the MSFC program, was well as those at other centers, was sponsored by the Office of Educational Affairs, NASA Headquarters, Washington, DC. The basic objectives of the programs, which are the 29th year of operation nationally, are (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate and exchange ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of the participants' institutions; and (4) to contribute to the research objectives of the NASA centers

Advances in the Modeling of Time-Resolved Laser-Induced Incandescence

Aerosolized nanoparticles represent both great potential for the development of emerging technologies and one of the biggest challenges currently facing our planet. In the former case, aerosol-based synthesis techniques represent one of the most cost-effective approaches to generating engineered nanoparticles having applications that range from medicine to energy. In the latter case, aerosolized soot is the second largest forcing factor after carbon dioxide in climate change models and contributes significantly to asthma, bronchitis, and various other respiratory illnesses. The increased predominance of engineered nanoparticles also presents significant environmental and health risks due to various toxicological effects. In any of these cases, robust characterization is critical to the function and regulation of these nanoaerosols. Time-resolved laser-induced incandescence (TiRe-LII) is well-suited to meeting this challenge. Since its inception in the 1980s, TiRe-LII has matured into a standard diagnostic for characterizing soot in combustion applications and, increasingly, engineered nanoparticles synthesized as an aerosol. The in situ nature of the technique makes it well-suited to probe in-flame soot formation and the fundamentals of nanoparticle formation. Moreover, its cost-effectiveness and real-time capabilities make TiRe-LII particularly well-suited as an avenue for online control of nanoparticle synthesis. TiRe-LII involves heating nanoparticles within a sample volume of aerosol to incandescent temperatures using a short laser-pulse. Following the laser pulse, the nanoparticles return to the ambient gas temperature via conductive and evaporative cooling. The magnitude of the peak spectral incandescence signal can be used to derive the particle volume fraction, while the temperature decay of the nanoparticles can be used to infer thermophysical properties, including the nanoparticle size, thermal accommodation coefficient (TAC), and latent heat of vaporization. Data analysis requires the use of spectroscopic models, used to convert the observed incandescence to a volume fraction or nanoparticle temperature, and heat transfer models, used to model the changes in the nanoparticle temperature over the duration of a signal. These models have evolved considerably over the past two decades, increasing the interpretive power of TiRe-LII. Nevertheless, there are several factors that impede further improvements to the reliability of TiRe-LII derived quantities. Several anomalies have been observed in measured signals collected from both engineered nanoparticle and soot, ranging from faster-than-expected temperature decays to inconsistencies in measurements between laboratories and experimental conditions. Resolving these differences is crucial to improving the robustness of TiRe-LII both as a combustion and engineered nanoparticle diagnostic. However, this first requires the development of advanced analysis tools that allow for a better understanding of nanoscale physics and the uncertainties associated with model development. This thesis presents several advances in the modeling and interpretation of TiRe-LII signals. The current state-of-the-art in TiRe-LII models is first established and the process of model inversion is discussed, with particular reference to uncertainty quantification within the Bayesian perspective. This lays the foundation for analysis of the measurement errors associated with TiRe-LII signals, providing practitioners with another source of information to characterize measurement devices and fluctuations in observed processes. Next, a novel approach to describe the relationship between the peak nanoparticle temperature and the laser fluence is derived. This allows the first comparison of fluence curves obtained using different instrumentation and under different measurement conditions. This dissertation proceeds by examining inversion of the spectroscopic model to determine both the nanoparticle temperature decay and the factor that scales emission from the nanoparticles to the observed signal. Unexpected temporal effects in the latter quantity are examined as an additional source of information that TiRe-LII practitioners can use for nanoparticle characterization and for diagnosing problems with measurement devices. Molecular dynamics simulations are employed to calculate the thermal accommodation coefficient, a parameter fundamental to the heat transfer model used in interpreting the inferred nanoparticle temperature decay, using the results are used in an analysis of TiRe-LII collected from iron, silver, and molybdenum nanoparticles. The cross-comparison of these materials highlights the utility of the developed analysis tools and provides fundamental insights into both nanoscale physics and bulk thermophysical properties. This dissertation concludes with a critical discussion of model development, emphasizing the importance of complexity and uncertainty in model selection. This is particularly important in the context of the context of the increasingly divergent set of TiRe-LII models available in the literature, indicative of model tuning. In summary, this dissertation not only presents direct improvements to the spectroscopic and heat transfer models used in traditional TiRe-LII analysis but also presents a set of new approaches by which the remaining challenges in TiRe-LII analysis can be resolved

Dynamics and clouds in planetary atmospheres from telescopic observations

This review presents an insight into our current knowledge of the atmospheres of the planets Venus, Mars, Jupiter, Saturn, Uranus and Neptune, the satellite Titan, and those of exoplanets. It deals with the thermal structure, aerosol properties (hazes and clouds, dust in the case of Mars), chemical composition, global winds, and selected dynamical phenomena in these objects. Our understanding of atmospheres is greatly benefitting from the discovery in the last 3 decades of thousands of exoplanets. The exoplanet properties span a broad range of conditions, and it is fair to expect as much variety for their atmospheres. This complexity is driving unprecedented investigations of the atmospheres, where those of the solar systems bodies are the obvious reference. We are witnessing a significant transfer of knowledge in both directions between the investigations dedicated to Solar System and exoplanet atmospheres, and there are reasons to think that this exchange will intensity in the future. We identify and select a list of research subjects that can be conducted at optical and infrared wavelengths with future and currently available ground-based and space-based telescopes, but excluding those from the space missions to solar system bodies

Research and technology, 1992

Selected research and technology activities at Ames Research Center, including the Moffett Field site and the Dryden Flight Research Facility, are summarized. These activities exemplify the Center's varied and productive research efforts for 1992