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At least 145 records · Page 8

Pressure Transient Analyses and Poroelastic Modeling of Hydraulic Fracture Dilation for Multiple Injections at the Devine Fracture Pilot Site

Our team has conducted electromagnetic (EM) surveys for the past six years to monitor hydraulic-fracture behavior at the Devine Fracture Pilot Site (DFPS). The sub-horizontal orientation of a shallow hydraulic fracture at the DFPS provides uniform access to the fracture area for interrogation and data collection. Ahmadian et al. (2023) suggested a possible correlation between spatiotemporal changes in the flow rate, bottomhole pressure (BHP), and the observed surface recorded electric field at the DFPS. In this paper, we present the development of poroelastic forward models and pressure transient analyses (PTAs) to support the development of a multiphysics inverse model for these EM surveys. First, we conducted PTAs of the shut-in periods after six injections out of 10 to determine the fracture closure pressure (FCP) or the overburden pressure used in a poroelastic fracture reopening model. Second, we developed a finite-element poroelastic model throughout five injection cycles to include the effect of the cumulative injected volumes due to the previous injections on current fracture dilation in the presence of highly permeable unpropped and propped zones adjacent to the cohesive layer that models fracture reopening. Fracture reopening in this poroelastic model is based on a calibrated traction-separation response using the bottomhole pressure collected in two injection campaigns in 2020 and 2022. We used the outcomes of a previous simulation study of the primary hydraulic-fracturing stimulation to define the dimension of an unpropped fracture zone ahead of the propped fracture area. The PTAs led to FCPs consistent with those obtained using the injection data collected at the DFPS in 2020. Further, these analyses showed that at later injections, the fracture closure occurred at a later time with respect to the shut-in time, inferring the effect of cumulative injected volumes in previous injections. The simulation results show that considering the propped and unpropped fracture zones improves our poroelastic model in predicting the injection-well BHP. The numerical simulation results demonstrate a significant excess pore pressure near the fracture because of the preceding formation loadings by the previous injections. The obtained fracture dilation area and fluid pressure distribution provide a basis to improve the development of a multiphysics inverse model. Furthermore, in an iteratively coupled scheme, this pressure distribution can be introduced into EM models to render a holistic view of the causative mechanisms for the surface signal anomalies.

02 PETROLEUM↗

Atmospheric teleconnection processes linking winter air stagnation and haze extremes in China with regional Arctic sea ice decline

Abstract. Recent studies suggested significant impacts of boreal cryosphere changes on wintertime air stagnation and haze pollution extremes in China. However, the underlying mechanisms of such a teleconnection relationship remains unclear. Here we use the Whole Atmosphere Community Climate Model (WACCM) to investigate dynamic processes leading to atmospheric circulation and air stagnation responses to Arctic sea ice changes. We conduct four climate sensitivity experiments by perturbing sea ice concentrations (SIC) and corresponding sea surface temperature (SST) in autumn and early winter over the whole Arctic and three subregions in the climate model. The results indicate distinct responses in circulation patterns and regional ventilation to the region-specific Arctic changes, with the largest increase of both the probability (by 132 %) and the intensity (by 30 %) of monthly air stagnation extremes being found in the experiment driven by SIC and SST changes over the Pacific sector of the Arctic (the East Siberian and Chukchi seas). The increased air stagnation extremes are mainly driven by an amplified planetary-scale atmospheric teleconnection pattern that resembles the negative phase of the Eurasian (EU) pattern. Dynamical diagnostics suggest that convergence of transient eddy forcing in the vicinity of Scandinavia in winter is largely responsible for the amplification of the teleconnection pattern. Transient eddy vorticity fluxes dominate the transient eddy forcing and produce a barotropic anticyclonic anomaly near Scandinavia and wave train propagation across Eurasia to the downstream regions in East Asia. The piecewise potential vorticity inversion analysis reveals that this long-range atmospheric teleconnection of Arctic origin takes place primarily via the middle and upper troposphere. The anomalous ridge over East Asia in the middle and upper troposphere worsens regional ventilation conditions by weakening monsoon northwesterlies and enhancing temperature inversions near the surface, leading to more and stronger air stagnation and pollution extremes over eastern China in winter. Ensemble projections based on state-of-the-art climate models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) corroborate this teleconnection relationship between high-latitude environmental changes and midlatitude weather extremes, though the tendency and magnitude vary considerably among each participating model.

54 ENVIRONMENTAL SCIENCES↗

Diagnostic analysis and spectral energetics of a blocking event in the GLAS climate model simulation

A synoptic and spectral analysis of a blocking event is presented, with attention given to the temporal evolution, maintenance, and decay of the block. The GLAS numerical climate model was used to generate a blocking event by the introduction of SST anomalies. Wavenumbers 2 and 3 became stationary around their climatological locations, and their constructive interference produced persistent blocking ridges over the west coast of North America and the other over western Europe. Time variations of the kinetic and potential energies and energy conversions during the blocking were performed. Spectrally filtered Hovmoller diagrams were developed for the winter of 1976-77, and showed that long waves were stationary over most of the interval, which featured severe weather conditions.

Chen, T.-C.↗

Concept for Inclusion of Analytical and Computational Capability in Optical Plume Anomaly Detection (OPAD) for Measurement of Neutron Flux

Researchers are working on many fronts to make possible high-speed, automated classification and quantification of constituent materials in numerous environments. NASA's Marshall Space Flight Center has implemented a system for rocket engine flowfields/plumes. The Optical Plume Anomaly Detector (OPAD) system was designed to utilize emission and absorption spectroscopy for monitoring molecular and atomic particulates in gas plasma. An accompanying suite of tools and analytical package designed to utilize information collected by OPAD is known as the Engine Diagnostic Filtering System (EDiFiS). The current combination of these systems identifies atomic and molecular species and quantifies mass loss rates in H2/O2 rocket plumes. Capabilities for real-time processing are being advanced on several fronts, including an effort to hardware encode components of the EDiFiS for health monitoring and management. This paper addresses the OPAD with its tool suites, and discusses what is considered a natural progression: a concept for taking OPAD to the next logical level of high energy physics, incorporating fermion and boson particle analyses in measurement of neutron flux.

Patrick, Marshall Clint↗

Concept for Inclusion of Analytical and Computational Capability in Optical Plume Anomaly Detection (OPAD) for Measurement of Neutron Flux

Researchers are working on many konts to make possible high speed, automated classification and quantification of constituent materials in numerous environments. NASA's Marshall Space Flight Center has implemented a system for rocket engine flow fields/plumes; the Optical Plume Anomaly Detection (OPAD) system was designed to utilize emission and absorption spectroscopy for monitoring molecular and atomic particulates in gas plasma. An accompanying suite of tools and analytical package designed to utilize information collected by OPAD is known as the Engine Diagnostic Filtering System (EDIFIS). The current combination of these systems identifies atomic and molecular species and quantifies mass loss rates in H2/O2 rocket plumes. Additionally, efforts are being advanced to hardware encode components of the EDIFIS in order to address real-time operational requirements for health monitoring and management. This paper addresses the OPAD with its tool suite, and discusses what is considered a natural progression: a concept for migrating OPAD towards detection of high energy particles, including neutrons and gamma rays. The integration of these tools and capabilities will provide NASA with a systematic approach to monitor space vehicle internal and external environment.

Patrick, M. Clinton↗

Investigation of Spiral Bevel Gear Condition Indicator Validation via AC-29-2C Using Fielded Rotorcraft HUMS Data

This report presents the analysis of gear condition indicator data collected on a helicopter when damage occurred in spiral bevel gears. The purpose of the data analysis was to use existing in-service helicopter HUMS flight data from faulted spiral bevel gears as a Case Study, to better understand the differences between HUMS data response in a helicopter and a component test rig, the NASA Glenn Spiral Bevel Gear Fatigue Rig. The reason spiral bevel gear sets were chosen to demonstrate differences in response between both systems was the availability of the helicopter data and the availability of a test rig that was capable of testing spiral bevel gear sets to failure. The objective of the analysis presented in this paper was to re-process helicopter HUMS data with the same analysis techniques applied to the spiral bevel rig test data. The damage modes experienced in the field were mapped to the failure modes created in the test rig. A total of forty helicopters were evaluated. Twenty helicopters, or tails, experienced damage to the spiral bevel gears in the nose gearbox. Vibration based gear condition indicators data was available before and after replacement. The other twenty tails had no known anomalies in the nose gearbox within the time frame of the datasets. These twenty tails were considered the baseline dataset. The HUMS gear condition indicators evaluated included gear condition indicators (CI) Figure of Merit 4 (FM4), Root Mean Square (RMS) or Diagnostic Algorithm 1 (DA1) and +/- 3 Sideband Index (SI3). Three additional condition indicators, not currently calculated on-board, were calculated from the archived data. These three indicators were +/- 1 Sideband Index (SI1), the DA1 of the difference signal (DiffDA1) and the peak-to-peak of the difference signal (DP2P). Results found the CI DP2P, not currently available in the on-board HUMS, performed the best, responding to varying levels of damage on thirteen of the fourteen helicopters evaluated. Two additional CIs also not in the on-board system, DiffDA1and SI1, also performed well responding to twelve and ten of the fourteen helicopters evaluated respectively. Of the three CIs currently available in the MSPU, DA1, FM4 and SI3, SI3, responded to eight, DA1 responded to six and FM4 responded to four of the fourteen helicopters evaluated. FM4, the poorest performing CI, was not as responsive to damage as the other five CIs. Conversely, when compared to the other two, it was the only CI that responded to damage on two helicopters. CI response could not be correlated to specific failure modes due to limited pictures and subjective descriptions found within the TDA. Flight regime did affect CI response to some gear faults. Due to the range of operating conditions for each regime, more studies are required to determine their sensitivity to regimes.

rotorcraft↗

ENSO-Induced Teleconnection: Process-Oriented Diagnostics to Assess Rossby Wave Sources and Ambient Flow Properties in Climate Models

Climate model fidelity in representing ENSO-induced teleconnection is assessed with process-oriented diagnostics that examine a chain of processes, from equatorial Pacific precipitation to the midlatitude circulation pattern over the Pacific–North American regions. Such processes are rarely addressed during model development. Using an upper-tropospheric divergent level, local vorticity gradient of the ambient zonal flow (∂ 2 U¯/∂y 2 ) and a restoring force for Rossby waves (β * ) are estimated, the equivalent barotropic vorticity equation is solved, and an anomalous Rossby wave source (RWS') quantified. The analysis is applied to AMIP5 and AMIP6 simulations. For a realistic circulation response representation, the hypothesis that models accurately represent the strength and location of RWS', and spatial variations in β * is tested. Compared to AMIP5, in AMIP6 there are clear improvements in representing RWS' and β * . To validate the hypothesis, the analysis identifies two metrics: spatially coherent RWS' in the subtropical North Pacific, and longitudes of negative β * over the western-central North Pacific. By projecting these metrics in two and three-dimensional views, improvements or degradations in model versions are apparent. If a model’s fidelity in representing ∂ 2 U¯/∂y 2 and RWS' are compromised, then radiated Rossby waves are reflected more equatorward, resulting in zonally elongated circulation anomalies over the central North Pacific. Thus, during climate model development, applying this analysis frequently will keep a regular check on the fidelity of the modeled response to anomalous El Niño convection in conjunction with changing model ambient flow dependencies. As a result, this analysis is intended to form a process-oriented diagnostics package, a community contribution to the NOAA Model Diagnostics Task Force.

54 ENVIRONMENTAL SCIENCES↗

A process-based evaluation of biases in extratropical stratosphere–troposphere coupling in subseasonal forecast systems

Abstract. Two-way coupling between the stratosphere and troposphere is recognized as an important source of subseasonal-to-seasonal (S2S) predictability and can open windows of opportunity for improved forecasts. Model biases can, however, lead to a poor representation of such coupling processes; drifts in a model's circulation related to model biases, resolution, and parameterizations have the potential to feed back on the circulation and affect stratosphere–troposphere coupling. We introduce a set of diagnostics using readily available data that can be used to reveal these biases and then apply these diagnostics to 22 S2S forecast systems. In the Northern Hemisphere, nearly all S2S forecast systems underestimate the strength of the observed upward coupling from the troposphere to the stratosphere, downward coupling within the stratosphere, and the persistence of lower-stratospheric temperature anomalies. While downward coupling from the lower stratosphere to the near surface is well represented in the multi-model ensemble mean, there is substantial intermodel spread likely related to how well each model represents tropospheric stationary waves. In the Southern Hemisphere, the stratospheric vortex is oversensitive to upward-propagating wave flux in the forecast systems. Forecast systems generally overestimate the strength of downward coupling from the lower stratosphere to the troposphere, even as most underestimate the radiative persistence in the lower stratosphere. In both hemispheres, models with higher lids and a better representation of tropospheric quasi-stationary waves generally perform better at simulating these coupling processes.

Garfinkel, Chaim I. (ORCID:000000017258666X)↗

Consistency Between Tropical Divergent Circulations from Reanalysis Data Sets and Satellite-Derived Precipitation, Radiation, and Surface Fluxes

Large-scale divergent circulations are part of the atmospheric dynamic response to diabatic heating from condensation, radiative processes, and surface heat fluxes. Vertical motion and the associated divergent wind is thus intimately tied to the hydrologic cycle and the global heat balance. Vertical motions are recovered diagnostically from reanalyses and, as such, are subject to shortcommings in model physics, numerics, and data availability. We use several Global Energy and Water Cycle Experiment (GEWEX) Earth Observation System (EOS) data sets derived from satellite data to assess interannual divergent flow anomalies in the National Centers for Environmental Prediction (NCEP), Goddard Space Flight Center (GSFC), and GSFC Data Assimilation Office (DAO) analyses. Among the data sets are monthly, 2.5 degree gridded precipitation (Microwave Sounding Unit (MSU) and Special Sensor Microwave Imager (SSM/I-based)), Top or the atmosphere (TOA) radiative fluxes from ERBS, surface radiative fluxes from the SRB project, and surface latent and sensible flux estimates from SSM/I. These data sets can be considered as independent of the reanalysis fields. We focus largely on the period 1987-1989 encompassing a strong El Nino / la Nina couplet. Consequently we emphasize interannual changes as well as climatological aspects of the reanalyses. In the processes of this study we use simple integral constraints enforced through the satellite-derived data sets to derive corrections to the divergent circulation produced from the reanalyses. We examine the implications of these corrections in describing how perturbations to the tropical heat balance evolve during a warm / cool couplet. In particular the perturbations to the planetary scale water vapor transport, and the resulting changes in TOA and surface radiative fluxes are considered.

Robertson, Franklin R.↗

A bi-level data-driven framework for fault-detection and diagnosis of HVAC systems

Long-term operation of heating, ventilation, and air conditioning (HVAC) systems will eventually lead to a range of HVAC system failures, resulting in excessive energy consumption and maintenance costs. Here, to avoid HVAC malfunctioning, fault detection diagnostic (FDD) is utilized as a common practice. Machine learning methods have lately received considerable interest for FDD analysis of HVAC systems due to their high detection accuracy. Meanwhile, HVAC malfunctions are regarded as rare occurrences, hence normal operating data samples are much more accessible than data samples in faulty and malfunctioning conditions. The dominating frequency of normal operation in HVAC datasets has also led to heavily biased classification algorithms within the literature. Moreover, the focus of previous literature has been on increasing the accuracy of the models which leads to a high number of false positives (misleading alarms) in the system. In order to enhance the performance of diagnostic procedures and fill the mentioned gaps, this study proposes a novel data-driven framework. A bi-level machine learning framework is developed for diagnosing faults in air handling units (AHUs) and rooftop units (RTUs) based on principal component analysis (PCA), time series anomaly detection, and random forest (RF). It is shown that PCA can reduce the dataset dimension with one principal component accounting for 95% of data variance. Also, the random forest could classify the faults with 89% precision for single-zone AHU, 85% precision for RTU, and 79% for multi-zone AHU. By proposing this framework, three persistent challenges are addressed: (I) minimizing false positives; (II) accounting for data imbalance; and (III) normal condition monitoring of equipment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Demonstration of a Retrofit Architecture for Intelligent Control and Diagnostics of a Turbofan Engine

A retrofit architecture for intelligent turbofan engine control and diagnostics that changes the fan speed command to maintain thrust is proposed and its demonstration in a piloted flight simulator is described. The objective of the implementation is to increase the level of autonomy of the propulsion system, thereby reducing pilot workload in the presence of anomalies and engine degradation due to wear. The main functions of the architecture are to diagnose the cause of changes in the engine s operation, warning the pilot if necessary, and to adjust the outer loop control reference signal in response to the changes. This requires that the retrofit control architecture contain the capability to determine the changed relationship between fan speed and thrust, and the intelligence to recognize the cause of the change in order to correct it or warn the pilot. The proposed retrofit architecture is able to determine the fan speed setting through recognition of the degradation level of the engine, and it is able to identify specific faults and warn the pilot. In the flight simulator it was demonstrated that when degradation is introduced into an engine with standard fan speed control, the pilot needs to take corrective action to maintain heading. Utilizing the intelligent retrofit control architecture, the engine thrust is automatically adjusted to its expected value, eliminating yaw without pilot intervention.

Litt, Jonathan S.↗

Mineral resources, geological structure, and landform surveys

Diagnostic ERTS imagery has been used to pinpoint surface conditions associated with known mining districts. These include enhancements which depict hitherto unrecognized surface alteration and allow analysis of ore-controlling fractures distribution in a regional context. ERTS has likewise provided observational data containing previously unrecognized surface anomalies in large oil-producing basins which correlate closely with known oil fields. These observational data offer promise of providing new and powerful techniques for oil exploration, especially if further work using more sophisticated enhancement-processing proves capable of emphasizing the anomalies. ERTS is showing a better-than-anticipated potential for producing accurate small-scale (large-area) geologic maps, often containing details that were previously not recorded on similar regional maps. The maps produced from ERTS imagery can be prepared more effectively than previously possible, mainly because of the synoptic, multispectral, and repetitive character of ERTS data. ERTS has also provided extensive information on possible geologic hazards. Many new fractures have been identified in several regions of the Pacific Coast seismic belt that have histories of recent earthquakes. This has obvious implications for engineering projects such as dams, aqueducts, and transportation routes. In the mid-continent area, ERTS data have been used to predict zones of rooffall danger in a working coal mine from newly discovered lineations (probably fractures) used as indicators of hazards.

Short, N. M.↗

Entanglement, trace anomaly, and confinement in QCD

We formulate confinement in quantum chromodynamics (QCD) as an entropic surface phenomenon. Quark and gluon quantum information is localized on a transverse, entangling two-sphere of radius 𝑅 𝐸⁢𝐸 ; at this radius the QCD vacuum—partitioned by a hadron into interior and exterior regions—reaches its maximal entanglement entropy. Lattice-QCD determinations of the scalar (trace) gravitational form factors fix both 𝑅 𝐸⁢𝐸 and the transverse trace-anomaly density 𝜌 ℎ ⁡(𝑅 𝐸⁢𝐸 ), yielding a parameter-free slope 𝑐 ℎ = 8⁢𝜋 2 ⁢𝑅𝑆$^2_{𝐸⁢𝐸}$𝜌 ℎ ⁡(𝑅 𝐸⁢𝐸 ) and a mechanical entropy 𝑆 𝐸⁢𝐸 ⁡(𝑦) = 𝑐 ℎ ⁢𝑦 that grows linearly with rapidity 𝑦. The entropy gradient ∂ 𝑅 𝑆 𝐸⁢𝐸 changes sign at 𝑅 𝐸⁢𝐸 : it pushes colored degrees of freedom outward for 𝑟 <𝑅 𝐸⁢𝐸 and pulls them inward for 𝑟 >𝑅 𝐸⁢𝐸 , thereby localizing them on the codimension-2 entangling two-sphere Σ ⊥ = 𝑆$^2_{𝑅_{𝐸⁢𝐸}}$ (which, in the infinite-momentum frame (IMF), projects onto the transverse plane)—the “information wall.” This provides a high-energy (large-𝑦) entropic confinement diagnostic that complements—rather than replaces—Wilson’s area-law criterion, which probes long-distance dynamics near the rest frame (𝑦 → 0). Imposing unitarity on an entropic ansatz for the amplitude yields 𝜎⁡(𝑠) ∝ 𝑦 𝛿 . World data favor 𝛿 = 2 for elastic 𝑝⁡𝑝⁡($𝑝\bar{⁡𝑝}$) scattering and heavy-quark photoproduction, whereas 𝜙 photoproduction favors a softer 𝛿 = 0.387. All extracted cross sections remain well below the Froissart-Martin bound. These results provide a confinement criterion quantified directly from nonperturbative QCD inputs, unifying the trace anomaly, entanglement entropy, and high-energy scattering within a single quantitative framework.

Color confinement↗

Cooperating Expert Systems For Automated Monitoring And Diagnostics

Human operators freer to perform nonrepetitive tasks. Expert software system for monitoring multiple streams of sensory data from interacting equipment subsystems undergoing development. Organized hierarchically to monitor multiple equipment subsystems simultaneously. Each expert software subsystem responsible for one of equipment subsystems. Intended to assist human analysts in interpretation of telemetry data indicating operating statuses of subsystems of spacecraft, enables analysts to maintain desired mode(s) of operation, and helps to correct anomalies in subsystems or in overall spacecraft system. Other versions devised for industrial monitoring and analysis tasks similarly complicated.

Schwuttke, Ursula M.↗

Basin-Scale Assessment of the Land Surface Water Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

The purpose of this study is to evaluate the components of the land surface water budget in the four land surface models (Noah, SAC-Sacramento Soil Moisture Accounting Model, (VIC) Variable Infiltration Capacity Model, and Mosaic) applied in the newly implemented National Centers for Environmental Prediction (NCEP) operational and research versions of the North American Land Data Assimilation System version 2 (NLDAS-2). This work focuses on monthly and annual components of the water budget over 12 National Weather Service (NWS) River Forecast Centers (RFCs). Monthly gridded FLUX Network (FLUXNET) evapotranspiration (ET) from the Max-Planck Institute (MPI) of Germany, U.S. Geological Survey (USGS) total runoff (Q), changes in total water storage (dS/dt, derived as a residual by utilizing MPI ET and USGS Q in the water balance equation), and Gravity Recovery and Climate Experiment (GRACE) observed total water storage anomaly (TWSA) and change (TWSC) are used as reference data sets. Compared to these ET and Q benchmarks, Mosaic and SAC (Noah and VIC) in the operational NLDAS-2 overestimate (underestimate) mean annual reference ET and underestimate (overestimate) mean annual reference Q. The multimodel ensemble mean (MME) is closer to the mean annual reference ET and Q. An anomaly correlation (AC) analysis shows good AC values for simulated monthly mean Q and dS/dt but significantly smaller AC values for simulated ET. Upgraded versions of the models utilized in the research side of NLDAS-2 yield largely improved performance in the simulation of these mean annual and monthly water component diagnostics. These results demonstrate that the three intertwined efforts of improving (1) the scientific understanding of parameterization of land surface processes, (2) the spatial and temporal extent of systematic validation of land surface processes, and (3) the engineering-oriented aspects such as parameter calibration and optimization are key to substantially improving product quality in various land data assimilation systems.

NLDAS-2↗

Infrared line diagnostics of active galactic nuclei

The CLOUDY photoionization code of Ferland (1991) is employed to predict intensities and ratios of the near-, mid-, and far-IR ionic fine-structure lines from AGN of the LINER and Seyfert types, and starbursts. The depths of varying the important model parameters, including ionization parameter, density, and optical depth, are investigated. The way in which detailed IR spectroscopy can reveal the presence of density inhomogeneities and abundance anomalies is shown, and the slope of the ionizing continuum and the amount of reddening and the reddening law are determined. The predictions of the present model and others are compared to the observed line ratios of the starburst galaxy M82 and of the Galactic center. No single-zone model adequately predicted all of the observed lines, but a simple combination of a starburst plus photodissociation region of higher density have a good fit for M82. The present model predictions are used to estimate the detectability of IR fine-structure lines in various active galaxies.

Spinoglio, Luigi↗

Development of Langmuir and Spatially Resolved OES Diagnostics for Arc Jet Shock and Boundary Layer Measurements Relevant to Atmospheric Re-Entry Environments

The second-generation miniature Arc Jet Research Chamber (mARC) ground testing facility at NASA Ames requires physical characterization of its supersonic plasma flow to verify numerical models and material sample testing. Two types of plasma diagnostics will be utilized: Langmuir probes and optical emission spectroscopy (OES). Several single and triple Langmuir probes have been constructed and will be inserted parallel to the flow via a sweep arm to measure post-shock electron temperature and number density along radial profiles at different axial distances. Due to the high heat flux (200-3000 W/cm2) sweep durations are necessarily short (< 0.1 s). Measuring these properties near the probe surface provide characterization of the post-shock environment. This is an important metric for validating coupled CFD-material codes, and will provide insight into longstanding thermocouple anomalies attributed to charging of heatshield surfaces. An OES system has also been assembled to obtain spatially resolved density and temperature for various flow species. The system consists of a convex lens that forms an image of the plasma onto a 16-channel linear fiber array, which will simultaneously capture the spectra from sixteen different locations. The light emission from the plasma is then focused by a spherical mirror into a spectrometer and recorded with a camera. These measurements non-intrusively provide a new spatially resolved flow characterization capability. This will initially be used to resolve issues with shock radiation interference in pyrometer measurements of material surface temperature. The design of each diagnostic and any initial results will be discussed.

Ethan Main-Loam Leong↗

Differential credibility assessment for statistical downscaling

Climate science is increasingly using (i) ensembles of climate projections from multiple models derived using different assumptions and/or scenarios and (ii) process-oriented diagnostics of model fidelity. Efforts to assign differential credibility to projections and/or models are also rapidly advancing. A framework to quantify and depict the credibility of statistically downscaled model output is presented and demonstrated. Here, the approach employs transfer functions in the form of robust and resilient generalized linear models applied to downscale daily minimum and maximum temperature anomalies at 10 locations using predictors drawn from ERA-Interim reanalysis and two global climate models (GCM; GFDL-ESM2M and MPI-ESM-LR). The downscaled time series are used to derive several impact relevant CLIMDEX temperature indices that are assigned credibility based on (1) the reproduction of relevant large-scale predictors by the GCMs (i.e. fraction of regression beta-weights derived from predictors that are well-reproduced) and (2) the degree of variance in the observations reproduced in the downscaled series following application of a new variance inflation technique. Credibility of the downscaled predictands varies across locations, between the two GCM and is generally higher for minimum temperature than maximum temperature. The differential credibility assessment framework demonstrated here is easy to use and flexible. It can be applied as is to inform decision makers regarding projection confidence, and/or extended to include other components of the transfer functions, and/or used to weight members of a statistically downscaled ensemble.

54 ENVIRONMENTAL SCIENCES↗