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Development and application of linear and nonlinear methods for interpretation of lightning strikes to in-flight aircraft

Since 1980, NASA has been collecting direct strike lightning data by flying an instrumented F-106B aircraft into thunderstorms. The continuing effort to interpret the measured data is reported here. Both linear and nonlinear finite difference modeling techniques are applied to the problem of lightning triggered by an aircraft in a thunderstorm. Five different aircraft are analyzed to determine the effect of aircraft size and shape on lightning triggering. The effect of lightning channel impedance on aircraft response is investigated. The particle environment in thunderstorms and electric field enhancements by typical ice particles is also investigated.

Rudolph, Terence↗

Particle Trajectory and Icing Analysis of the E(sup 3) Turbofan Engine Using LEWICE3D Version 3

Particle trajectory and ice shape calculations were made for the Energy Efficient Engine (E(sup 3)) using the LEWICE3D Version 3 software. The particle trajectory and icing computations were performed using the new "block-to-block" collection efficiency method which has been incorporated into the LEWICE3D Version 3 software. The E(sup 3) was developed by NASA and GE in the early 1980 s as a technology demonstrator and is representative of a modern high bypass turbofan engine. The E(sup 3) flow field was calculated using the NASA Glenn ADPAC turbomachinery flow solver. Computations were performed for the low pressure compressor of the E(sup 3) for a Mach 0.8 cruise condition at 11,887 m assuming a standard warm day for three drop sizes and two drop distributions typically used in aircraft design and certification. Particle trajectory computations were made for water drop sizes of 5, 20, and 100 microns. Particle trajectory and ice shape predictions were made for a 20 micron Langmuir-D distribution and for a 92 mm Super-cooled Large Droplet (SLD) distribution with and without splashing effects for a Liquid Water Content (LWC) of 0.3 g/cu m and an icing time of 30 min. The E3 fan and spinner combination proved to be an effective ice removal mechanism as they removed greater than 36 percent of the mass entering the inlet for the icing cases. The maximum free stream catch fraction for the fan and spinner combination was 0.60 while that on the elements downstream of the fan was 0.03. The non-splashing trajectory and collection efficiency results showed that as drop size increased impingement rates increased on the spinner and fan leaving less mass to impinge on downstream components. The SLD splashing case yielded more mass downstream of the fan than the SLD non-splashing case due to mass being splashed from the upstream inlet lip, spinner and fan components. The ice shapes generated downstream of the fan were either small or nonexistent due to the small available mass and evaporation except for the 92 m SLD splashing case. Relatively large ice shapes were predicted for internal guide vane #1 and rotor #1 for the 92 m SLD splashing case due to re-impingement of splashed mass.

Bidwell, Colin S.↗

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distribution parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), groupel and frozen drops/hall] Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bim model explicitly calculates and allows for the examination of both the mass and number concentration of cpecies in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fever droplets, larger size develop due to greater condencational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.

Tao, Wei-Kuo↗

The Role of Aerosols on Precipitation Processes: Cloud Resolving Model Simulations

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, the sub-tropics (Florida) and midlatitudes using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CeN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for these cases. It is shown that since the low (CN case produces fewer droplets, larger sizes develop due to greater condensational and collection growth, leading to a broader size spectrum in comparison to the high CCN case. Sensitivity tests were performed to identify the impact of ice processes, radiation and large-scale influence on cloud-aerosol interactive processes, especially regarding surface rainfall amounts and characteristics (i.e., heavy or convective versus light or stratiform types). In addition, an inert tracer was included to follow the vertical redistribution of aerosols by cloud processes. We will also give a brief review from observational evidence on the role of aerosol on precipitation processes.

Tao, Wei-Kuo↗

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e.,pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size categor, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fewer droplets, larger sized develop due to the greater condensational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.

Tao, Wei-Kuo↗

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

Tao, Wei-Kuo↗

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles (i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail). Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, in the sub-tropics (Florida) and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration.

Tao, Wei-Kuo↗

The Role of Aerosols on Precipitation Processes

Cloud physics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distribution below the clouds. Therefore, the size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral--bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Tao, Wei-Kuo↗

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Tao, Wei-Kuo↗

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-resolving Model Simulations

Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, r d a U production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembe1 (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and platelike), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

Tao, Wei-Kuo↗

On charging of snow particles in blizzard

The causes of the charge polarity on the blizzard, which consisted of fractured snow crystals and ice particles, were investigated. As a result, the charging phenomena showed that the characteristics of the blizzard are as follows: (1) In the case of the blizzard with snowfall, the fractured snow particles drifting near the surface of snow field (lower area: height 0.3 m) had positive charge, while those drifting at higher area (height 2 m) from the surface of snow field had negative charge. However, during the series of blizzards two kinds of particles positively and negatively charged were collected in equal amounts in a Faraday Cage. It may be considered that snow crystals with electrically neutral properties were separated into two kinds of snow flakes (charged positively and negatively) by destruction of the snow crystals. (2) In the case of the blizzard which consisted of irregularly formed ice drops (generated by peeling off the hardened snow field), the charge polarity of these ice drops salting over the snow field was particularly controlled by the crystallographic characteristics of the surface of the snow field hardened by the powerful wind pressure.

Shio, Hisashi↗

Ice rule breakdown and frustrated antiferrotoroidicity in an artificial colloidal Cairo ice

Abstract We combine experiments and numerical simulations to investigate the low energy states and the emergence of topological defects in an artificial colloidal ice in the Cairo geometry. This type of geometry is characterized by a mixed coordination ( z ), with coexistence of both z = 3 and z = 4 vertices. We realize this particle ice by confining field tunable paramagnetic colloidal particles within a lattice of topographic double wells at a one to one filling using optical tweezers. By raising the interaction strength via an applied magnetic field, we find that the ice rule breaks down, and positive monopoles with charge q = + 2 accumulate in the z = 4 vertices and are screened by negative ones ( q = − 1 ) in the z = 3. The resulting, strongly coupled state remains disordered. Further, via analysis of the mean chirality associated to each pentagonal plaquette, we find that the disordered ensemble for this geometry is massively degenerate and it corresponds to a frustrated antiferrotoroid.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Impact of a New Cloud Microphysics Parameterization on the Simulations of Mesoscale Convective Systems in E3SM

Abstract Mesoscale convective systems (MCSs) are one of the most climatically significant forms of convection because of their large role in water and energy cycles. The mesoscale features associated with MCS are difficult to represent in climate models because the relevant dynamics and physics are absent or poorly represented with coarse model resolution (∼100 km). Using a regionally refined model (RRM) with 0.25° grid spacing embedded in the Energy Exascale Earth System Model (E3SM), we explore the impact of cloud microphysics parameterizations on the simulation of precipitation, particularly MCS precipitation over the contiguous United States. The Predicted Particle Properties (P3) cloud microphysics scheme has been modified and implemented into E3SM to overcome the limitations of the default Morrison and Gettelman (MG2) scheme in which rimed precipitating ice particles (graupel/hail) are absent and frozen particles are artificially partitioned into cloud ice and snow. We show that P3 improves the simulation of precipitation statistics including frequency distribution compared with MG2 with a limited effect on the diurnal cycle. P3 predicts higher hourly rain rates, resulting in 20% more MCSs and a higher total MCS precipitation (4.4%) compared to MG2, agreeing better with observations. The improvements with P3 mainly result from improved representations of ice microphysics, which not only produces higher rain rates through melting but also leads to a stronger large‐scale ascending motion by releasing more latent heating. This study suggests that improving microphysics parameterization is important for simulating MCS precipitation as future climate model resolutions continue to increase.

54 ENVIRONMENTAL SCIENCES↗

Cirrus microphysics observations made during FIRE 2: Small particles, high concentrations, and probe comparisons

Aircraft observations of cirrus cloud microphysics were made near Coffeyville, Kansas during Nov. and Dec. 1991. Cloud microphysics measurements were made using both a PMS 2DC probe and an ice particle replicator, both were mounted on the UND Citation aircraft. Intercomparison is made of the size, area, and ice mass spectra determined from these probes. The PMS 2DC undercounts particles for D less than 70 microns and the replicator oversizes particles for D greater than 150 microns, at least when column rosettes are encountered. High concentrations of particles with D less than 50 microns are noted in selected portions of the 22 Nov. 91 replicator data set. Relations between the maximum dimension of a crystal and its shadow area (known as area dimensional relationships) are computed from the PMS data. Area and mass dimensional relationships are used to give a simple analytical expression for computing the wavelength dependent absorption coefficient averaged over a size bin. Calculations based upon the replicator data show that crystals with D less than 50 microns contribute significantly to the solar extinction and infrared absorption coefficients during some time intervals.

Arnott, W. P.↗

Relating Lightning Flash Size and Energy to Tropical Cyclone Structure and Intensity Change

The number and location of lightning flashes within tropical cyclones (TCs) has proven to be a useful predictor of TC intensity change. Generally, a large number of lightning flashes located within the radius of maximum wind indicates a convective structure favorable for intensification. However, weakening TCs can also exhibit numerous lightning flashes, and rapid intensification can occur in the absence of inner-core lightning. It is thus difficult to interpret what the presence or absence of inner-core lightning might mean for a TC’s future evolution. The Geostationary Lightning Mapper (GLM) offers a new capability to observe not only the number and location of lightning flashes, but also the size and optical energy of those flashes. This presentation describes the application of these new metrics to further understand the relationship between lightning and TC structural and intensity evolution. Evidence is presented that flash size and optical energy reveal more about the convective and kinematic structures relevant to intensity change than an analysis of lightning flash count and location alone. We hypothesize that large, energetic lightning flashes are generated when the TC secondary circulation is strongest, an environment which favors increased generation of ice particles in the eyewall updraft and larger charge separation through outward advection of ice in the upper-level outflow. Conversely, smaller, lower-energy lightning flashes tend to occur in more localized turbulent updrafts, which can be forced by a variety of processes – some of which act to weaken the storm. These hypotheses are supported by numerical simulations of TC convection.

Patrick Duran↗

An Overview of Mesoscale Convective Systems: Global Climatology, Satellite Observations, and Modeling Strategies

Deep convection is responsible for redistributing water as well as energy and providing vital water resources for many regions of the world. Cumulonimbus clouds aggregation into a single storm system develop mesoscale convective systems (MCS). MCSs have precipitation covering a horizontal region on the scale of 100?km or more. After more than the last seven decades, MCS has been gradually received wide attention in the scientific community as an important component of the Earth's hydrologic cycle and energy balance. MCSs differ from ordinary deep convection because of the mesoscale circulations consisting of a layer of air overturning on a scale much larger than those created by individual convective updrafts or downdrafts. Moreover, a key feature that separates MCS from ordinary deep convection is the significant portion of stratiform precipitation that results in the production and detrainment of a large number of ice particles from their organized convective cores and continues the mesoscale ascent that supports ice growth and aggregation as the crystals fall. This significant stratiform precipitation gives rise to top-heavy latent heating profiles that have substantial impacts on the upper-level global circulations, especially for those MCS that have a larger portion of stratiform rainfall. Top-heavy latent heating profiles are more frequent over the ocean than over the land. These unique features of MCS suggest that they are important for the hydrologic cycle, general circulation, and radiative balance of the climate system. In this chapter, we focus on the recent advances in the climatological perspective of MCS as well as the research tools used to better understand MCS after the advent of the satellite era. We will discuss both tropical and midlatitude MCS, the influence of modes of tropical climate variability on MCS, and the new insight from satellite observations on MCS interaction with the land surface.

Chakraborty, Sudip↗

Convective Melting of Particles in Flow Under Microgravity Conditions

Study of melting of dispersed or packed solid particles in a fluid under gravity and microgravity conditions provides benchmark information for many engineering applications such as material processing, environmental assessment and protection and space fire protection. During such processes, packed or dispersed solid particles are interacting with fluid flow at above-melting temperatures. By unmasking the buoyancy effects in coupled flow, phase change and heat transport phenomena, a better understanding of melting rate in non-thermal equilibrium, convective conditions can be studied. A series of flight experiments were conducted onboard the NASA KC-135 Microgravity Research Airplane. The Particle Melting in Plow (PMF) module was designed to allow flow through the initially packed ice particles at controlled temperature and velocity. To achieve this, a close-loop flow system was designed. Video images were taken to record the visualization of the melting process, from which a time variation of packed particle thickness distribution at different times can be obtained by the image analysis method. The fluid temperature distribution within the melting zone is measured by thermocouples. An infrared camera was mounted from the top of the test section to record the ice-water thermal images at a given location. The results from thermal images yield local temperature variation between melting solid and liquid and local Stephan number. Typical results for a number of cases are presented. The mathematical model, describing mass, energy, and momentum balance equations for the liquid and solid phases, is presented. It is found that melting rate is influenced mainly by the ratio of Reynolds number (based on the initial particle diameter) to the Froud number, and Stephan number. At the absence of gravity, Froud number approaches zero, Reynolds number and Stephan number become dominant factors governing the melting rate. The numerically determined results are compared with the experimental ones. It is found that the discrepancy between the predicted and measured melting rate is largely due to the inaccuracy in the constitutive equations for effective thermal physical properties, such as effective thermal conductivity and diffusivity, and transport properties, such as particle interaction coefficient, and local heat transfer coefficient of particles.

Stewart, C.↗

A Model to Assess the Risk of Ice Accretion Due to Ice Crystal Ingestion in a Turbofan Engine and its Effects on Performance

The occurrence of ice accretion within commercial high bypass aircraft turbine engines has been reported under certain atmospheric conditions. Engine anomalies have taken place at high altitudes that were attributed to ice crystal ingestion, partially melting, and ice accretion on the compression system components. The result was one or more of the following anomalies: degraded engine performance, engine roll back, compressor surge and stall, and flameout of the combustor. The main focus of this research is the development of a computational tool that can estimate whether there is a risk of ice accretion by tracking key parameters through the compression system blade rows at all engine operating points within the flight trajectory. The tool has an engine system thermodynamic cycle code, coupled with a compressor flow analysis code, and an ice particle melt code that has the capability of determining the rate of sublimation, melting, and evaporation through the compressor blade rows. Assumptions are made to predict the complex physics involved in engine icing. Specifically, the code does not directly estimate ice accretion and does not have models for particle breakup or erosion. Two key parameters have been suggested as conditions that must be met at the same location for ice accretion to occur: the local wet-bulb temperature to be near freezing or below and the local melt ratio must be above 10%. These parameters were deduced from analyzing laboratory icing test data and are the criteria used to predict the possibility of ice accretion within an engine including the specific blade row where it could occur. Once the possibility of accretion is determined from these parameters, the degree of blockage due to ice accretion on the local stator vane can be estimated from an empirical model of ice growth rate and time spent at that operating point in the flight trajectory. The computational tool can be used to assess specific turbine engines to their susceptibility to ice accretion in an ice crystal environment.

Jorgenson, Philip C. E.↗