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At least 109 records · Page 6

Cirrus Susceptibility to Changes in Ice Nuclei: Physical Processes, Model Uncertainties, and Measurement Needs

One of the proposed concepts for mitigating the warming effect of increasing greenhouse gases is seeding cirrus cloud with ice nuclei (IN) in order to reduce the lifetime and coverage of cold cirrus that have a net warming impact on the earth's surface. Global model simulations of the net impact of changing upper tropospheric IN have given widely disparate results, partly as a result of poor understanding of ice nucleation processes in the current atmosphere, and partly as a result of poor representation of these processes in global models. Here, we present detailed process-model simulations of tropical tropopause layer (TTL) transport and cirrus formation with ice nuclei properties based on recent laboratory nucleation experiments and field measurements of aerosol composition. The model is used to assess the sensitivity of TTL cirrus occurrence frequency and microphysical properties to the abundance and efficacy of ice nuclei. The simulated cloud properties compared with recent high-altitude aircraft measurements of TTL cirrus and ice supersaturation. We find that abundant effective IN (either from glassy organic aerosols or crystalline ammonium sulfate with concentrations greater than about 100/L) prevent the occurrences of large ice concentration and large ice supersaturations, both of which are clearly indicated by the in situ observations. We find that concentrations of effective ice nuclei larger than about 50/L can drive significant changes in cirrus microphysical properties and occurrence frequency. However, the cloud occurrence frequency can either increase or decrease, depending on the efficacy and abundance of IN added to the TTL. We suggest that our lack of information about ice nuclei properties in the current atmosphere, as well as uncertainties in ice nucleation processes and their representations in global models, preclude meaningful estimates of climate impacts associated with addition of ice nuclei in the upper troposphere. We will briefly discuss the key field measurements needed to constrain ice nucleation processes.

Jensen, Eric↗

Constraining Upper Troposphere/Lower Stratosphere Aerosol Physical Processes with High-Altitude Aircraft Measurements

Interest in a more complete understanding of the sources, composition and microphysics of stratospheric aerosol particles has intensified during recent years for several reasons: (1) small volcanic eruptions have been recognized as a driver of short-term changes in climate forcing; (2) emissions of sulfur dioxide (SO2) and other aerosol precursors have shifted to south Asia and other low latitude regions with intense vertical transport; (3) organic material has been recognized as a key contributor to lower stratospheric aerosol mass; and (4) interest in possible solar radiation management (geoengineering) through significant enhancements in stratospheric aerosols has intensified. To address stratospheric aerosol science issues, we are proposing a NASA Earth Ventures mission to NASA to provide extensive high-altitude aircraft measurements of critical gas-phase and aerosol properties at multiple locations across the planet. In this presentation, we will discuss the objectives of the proposed campaign, the measurements provided, the sampling strategy, and the modeling and analysis approaches that would be used to address specific science questions.

Jensen, Eric↗

Physical Processes Controlling the Distribution of Relative Humidity in the Tropical Tropopause Layer over the Pacific

The distribution of relative humidity with respect to ice (RHI) in the Boreal wintertime Tropical Tropopause Layer (TTL - about 14-19 km) over the Pacific is examined with the extensive dataset of measurements from the NASA Airborne Tropical TRopopause EXperiment (ATTREX). Multiple deployments of the Global Hawk during ATTREX provided hundreds of vertical profiles spanning the Pacific with accurate measurements of temperature, pressure, water vapor concentration, ozone concentration, and cloud properties. We also compare the measured RHI distributions with results from a transport and microphysical model driven by meteorological analysis fields. Notable features in the distribution of RHI versus temperature and longitude include (1) the common occurrence of RHI values near ice saturation over the western Pacific in the lower TTL (temperatures greater than 200 K) and in airmasses with low ozone concentrations indicating recent detrainment from deep convection; (2) low RHI values in the lower TTL over the eastern Pacific where deep convection is infrequent; (3) RHI values following a constant H2O mixing ratio in the upper TTL (temperatures below about 195 degrees Kelvin), particularly for samples with ozone mixing ratios greater than about 50-100 parts-per-billion-volume indicating mixtures of tropospheric and stratospheric air, and (4) RHI values typically near ice saturation in the coldest airmasses sampled (temperatures less than about 190 degrees Kelvin). We find that the typically saturated air in the lower TTL over the western Pacific is largely driven by the frequent occurrence of deep convection in this region. The nearly-constant water vapor mixing ratios in the upper TTL result from the combination of slow ascent (resulting in long residence times) and wave-driven temperature variability on a range of time scales (resulting in most air parcels having experienced low temperature and dehydration).

ozone↗

Computational framework for modeling of physical process

Techniques, systems, and devices are described for providing a computational frame for estimating high-dimensional stochastic behaviors. In one exemplary aspect, a method for performing numerical estimation includes receiving a set of measurements of a stochastic behavior. The set of correlated measurements follows a non-standard probability distribution and is non-linearly correlated. Also, a non-linear relationship exists between a set of system variables that describes the stochastic behavior and a corresponding set of measurements. The method includes determining, based on the set of measurements, a numerical model of the stochastic behavior. The numerical model comprises a feature space comprising non-correlated features corresponding to the stochastic behavior. The non-correlated features have a dimensionality of M and the set of measurements has a dimensionality of N, M being smaller than N. The method includes generating a set of approximated system variables corresponding to the set of measurements based on the numerical model.

Chen, Xiao↗

Computational framework for modeling of physical process

Techniques, systems, and devices are described for providing a computational frame for estimating high-dimensional stochastic behaviors. In one exemplary aspect, a method for performing numerical estimation includes receiving a set of measurements of a stochastic behavior. The set of correlated measurements follows a non-standard probability distribution and is non-linearly correlated. Also, a non-linear relationship exists between a set of system variables that describes the stochastic behavior and a corresponding set of measurements. The method includes determining, based on the set of measurements, a numerical model of the stochastic behavior. The numerical model comprises a feature space comprising non-correlated features corresponding to the stochastic behavior. The non-correlated features have a dimensionality of M and the set of measurements has a dimensionality of N, M being smaller than N. The method includes generating a set of approximated system variables corresponding to the set of measurements based on the numerical model.

Chen, Xiao↗

Use of stratospheric aerosol properties as diagnostics of Antarctic vortex processes

Physical properties of the stratospheric aerosol population are inferred from cloud-free SAGE II multiwavelength extinction measurements in the Antarctic during late summer (February/March) and spring (September/October, November). Seasonal changes in these properties are used to infer physical processes occurring in the Antarctic stratosphere over the course of the winter. The analysis suggests that the apparent springtime cleansing of the Antarctic stratosphere is the result of aerosol redistribution through subsidence of the polar vortex air mass and sedimentation of large polar stratospheric cloud particles. The analysis also suggests that vortex processes are responsible for a significant downward transport of aerosol through the tropopause.

Thomason, Larry W.↗

Universal Heliophysical Processes

The physical processes in the heliospace are a direct consequence of the Sun s mass and electromagnetic emissions. There has been enormous progress in studying these processes since the dawn of the space age half a century ago. The heliospace serves as a great laboratory to study numerous physical processes, using the vast array of ground and spacebased measurements of various physical quantities. The observational capabilities collectively form the Great Observatory to make scientific investigations not envisioned by individual instrument teams. The International Heliophysical Year (IHY) program has been promoting scientific investigations on the universality of physical processes such as shocks, particle acceleration, dynamo, magnetic reconnection, magnetic flux ropes, plasma-neutral matter interactions, turbulence, and several other topics. This chapter highlights scientific deliberations on these and related topics that took place during the IAGA session on "Universal Heliophysical Processes" in Sopron, Hungary. The session featured several invited and contributed papers that focused on observations, theory and modeling of the universal heliophysical processes.

Gopalswamy, Natchimuthuk↗

Comprehensive Analysis of the Relative Dispersion of Droplet-Size Distributions and Their Relationships to Key Physical Fog Processes Under Different Aerosol Conditions and Evolutionary Stages

The relative dispersion of cloud and fog droplets has significant impacts on aerosol indirect effects, radiative transfer, and microphysical processes. However, previous studies have been mostly concerned with clouds, with limited studies on fog, particularly those that examine the combined influences of all key physical processes and their roles during fog evolution. As such, this study aims to conduct a comprehensive investigation by examining the relationships between relative dispersion and other microphysical variables, as well as the underlying microphysical and dynamic processes, based on field fog campaigns in polluted and clean conditions. In polluted fog, droplet concentrations are higher, leading to smaller droplets and increased dispersion. The correlation between dispersion and droplet volume-mean radius is positive in the polluted fog, but shifts to negative in clean fog. Here, we attribute the difference to various microphysical processes like aerosol activation, condensation, collision-coalescence, and entrainment-mixing. In polluted fog, high aerosol concentrations, low supersaturations, and strong turbulence (entrainment-mixing) provide suitable conditions for the simultaneous occurrence of droplet condensation and aerosol activation, resulting in a positive correlation between dispersion and volume-mean radius, especially during the fog formation stage. In contrast, during the mature stage in clean fog, condensation is dominant with weak aerosol activation leading to a negative correlation between relative dispersion and volume-mean radius. The collision-coalescence process is more active in the mature stage, increasing radii and leading to the negative correlation between dispersion and volume-mean radius. This result sheds new light on understanding the relative dispersion and mechanisms in fog under different aerosol backgrounds.

54 ENVIRONMENTAL SCIENCES↗

The expansion of a plasma into a vacuum - Basic phenomena and processes and applications to space plasma physics

In this review attention is called to basic phenomena and physical processes involved in the expansion of a plasma into a vacuum, or the expansion of a plasma into a more tenuous plasma, in particular the fact that upon the expansion, ions are accelerated and reach energies well above their thermal energy. Also, in the process of the expansion a rarefaction wave propagates into the ambient plasma, an ion front moves into the expansion volume, and discontinuities in plasma parameters occur. The physical processes which cause the above phenomena are discussed, and their possible application is suggested for the case of the distribution of ions and electrons (hence plasma potential and electric fields) in the wake region behind artificial and natural obstacles moving supersonically in a rarefied space plasma. To illustrate this, some in situ results are reexamined. Directions for future work in this area via the utilization of the Space Shuttle and laboratory work are also mentioned.

Wright, K. H., Jr.↗

Methods and devices for preventing computationally explosive calculations in a computer for model parameters distributed on a hierarchy of geometric simplices

A computer-implemented method of preventing computationally explosive calculations. The method includes obtaining, by a processor of the computer, measured data of one of a physical process or a physical object; performing hierarchical numerical modeling of a physical process inclusive of an Earth model containing at least one of (a) infrastructure in the ground and (b) a formation feature in the ground, wherein predicted data is generated; comparing the measured data to the predicted data to calculate an estimated error; analyzing the estimated error via an inversion process to update the at least one of the Earth model and infrastructure model so as to reduce the estimated error and to determine a final composite Earth model of at least one of the infrastructure and the feature; and using the final composite Earth model to characterize at least one of the process and the physical object.

Source record↗

Machine learning based algorithms for uncertainty quantification in numerical weather prediction models

Complex numerical weather prediction models incorporate a variety of physical processes, each described by multiple alternative physical schemes with specific parameters. The selection of the physical schemes and the choice of the corresponding physical parameters during model configuration can significantly impact the accuracy of model forecasts. There is no combination of physical schemes that works best for all times, at all locations, and under all conditions. It is therefore of considerable interest to understand the interplay between the choice of physics and the accuracy of the resulting forecasts under different conditions. This paper demonstrates the use of machine learning techniques to study the uncertainty in numerical weather prediction models due to the interaction of multiple physical processes. The first problem addressed herein is the estimation of systematic model errors in output quantities of interest at future times, and the use of this information to improve the model forecasts. The second problem considered is the identification of those specific physical processes that contribute most to the forecast uncertainty in the quantity of interest under specified meteorological conditions. In order to address these questions we employ two machine learning approaches, random forests and artificial neural networks. The discrepancies between model results and observations at past times are used to learn the relationships between the choice of physical processes and the resulting forecast errors. Numerical experiments are carried out with the Weather Research and Forecasting (WRF) model. The output quantity of interest is the model precipitation, a variable that is both extremely important and very challenging to forecast. The physical processes under consideration include various micro-physics schemes, cumulus parameterizations, short wave, and long wave radiation schemes. The experiments demonstrate the strong potential of machine learning approaches to aid the study of model errors.

97 MATHEMATICS AND COMPUTING↗

Towards 5G-Enabled Operational Technology for Process Monitoring and Network Slicing

Cyber-Physical Systems (CPS) are deployed to monitor physical processes in critical cyber-enabled services like power generation. However, CPS ecosystems are typically designed without robust security. While it is important to ensure optimal performance of the Operational Technology (OT) environments, security cannot be overlooked. To modernize traditional OT services, 5G technology is being integrated. 5G technology offers low latency and high availability, making it a suitable infrastructure for managing and monitoring physical processes. How-ever, integrating 5G mechanisms into large-scale OT networks introduces new implementation and performance challenges. Therefore, this paper presents a 5G-enabled CPS architecture (5G-CPS) that describes the necessary components, services, and communication protocols and conducts feasibility study to integrate 5G technology in industrial control system networks to understand the performance merits. The 5G-CPS architecture aims to minimize implementation and operational challenges associated with integrating 5G technology into constrained OT.

Aguayo, Jared M.↗

Space plasma physics: I - Stationary processes

The physics of stationary processes in space plasmas is examined theoretically in an introduction intended for graduate students. The approach involves the extensive use of numerical simulations. Chapters are devoted to fundamental principles, small-amplitude waves, and the stationary solar plasma system; typical measurement data and simulation results are presented graphically.

Hasegawa, Akira↗

Physical-chemical processes in a protoplanetary cloud

Physical-chemical processes in a protoplanetary cloud are discussed. The following subject areas are covered: (1) characteristics of the chemical composition of molecular interstellar clouds; (2) properties and physico-chemical process in the genesis of interstellar dust grains; and (3) the isotope composition of volatiles in bodies of the Solar System.

Lavrukhina, Avgusta K.↗