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NASA NTRS2014

Physical and Dynamical Linkages Between Lightning Jumps and Storm Conceptual Models

The presence and rates of total lightning are both correlated to and physically dependent upon storm updraft strength, mixed phase precipitation volume and the size of the charging zone. The updraft modulates the ingredients necessary for electrification within a thunderstorm, while the updraft also plays a critical role in the development of severe and hazardous weather. Therefore utilizing this relationship, the monitoring of lightning rates and jumps provides an additional piece of information on the evolution of a thunderstorm, more often than not, at higher temporal resolution than current operational radar systems. This correlation is the basis for the total lightning jump algorithm that has been developed in recent years. Currently, the lightning jump algorithm is being tested in two separate but important efforts. Schultz et al. (2014; this conference) is exploring the transition of the algorithm from its research based formulation to a fully objective algorithm that includes storm tracking, Geostationary Lightning Mapper (GLM) Proxy data and the lightning jump algorithm. Chronis et al. (2014) provides context for the transition to current operational forecasting using lightning mapping array based products. However, what remains is an end-to-end physical and dynamical basis for coupling total lightning flash rates to severe storm manifestation, so the forecaster has a reason beyond simple correlation to utilize the lightning jump algorithm within their severe storm conceptual models. Therefore, the physical basis for the lightning jump algorithm in relation to severe storm dynamics and microphysics is a key component that must be further explored. Many radar studies have examined flash rates and their relationship to updraft strength, updraft volume, precipitation-sized ice mass, etc.; however, their relationship specifically to lightning jumps is fragmented within the literature. Thus the goal of this study is to use multiple Doppler and polarimetric radar techniques to resolve the physical and dynamical storm characteristics specifically around the time of the lightning jump. This information will help forecasters anticipate lightning jump occurrence, or even be of use to determine future characteristics of a given storm (e.g., development of a mesocyclone, downdraft, or hail signature on radar), providing additional lead time/confidence in the severe storm warning paradigm.

Schultz, Christopher J.↗

NASA NTRS2014

Evaluation of Model Microphysics Within Precipitation Bands of Extratropical Cyclones

It is hypothesized microphysical predictions have greater uncertainties/errors when there are complex interactions that result from mixed phased processes like riming. Use Global Precipitation Measurement (GPM) Mission ground validation studies in Ontario, Canada to verify and improve parameterizations. The WRF realistically simulated the warm frontal snowband at relatively short lead times (1014 h). The snowband structire is sensitive to the microphysical parameterization used in WRF. The Goddard and SBUYLin most realistically predicted the band structure, but overpredicted snow content. The double moment Morrison scheme best produced the slope of the snow distribution, but it underpredicted the intercept. All schemes and the radar derived (which used dry snow ZR) underpredicted the surface precipitation amount, likely because there was more cloud water than expected. The Morrison had the most cloud water and the best precipitation prediction of all schemes.

Colle, Brian A.↗

NASA NTRS2013

Bounding the Role of Black Carbon in the Climate System: a Scientific Assessment

Black carbon aerosol plays a unique and important role in Earth's climate system. Black carbon is a type of carbonaceous material with a unique combination of physical properties. This assessment provides an evaluation of black-carbon climate forcing that is comprehensive in its inclusion of all known and relevant processes and that is quantitative in providing best estimates and uncertainties of the main forcing terms: direct solar absorption; influence on liquid, mixed phase, and ice clouds; and deposition on snow and ice. These effects are calculated with climate models, but when possible, they are evaluated with both microphysical measurements and field observations. Predominant sources are combustion related, namely, fossil fuels for transportation, solid fuels for industrial and residential uses, and open burning of biomass. Total global emissions of black carbon using bottom-up inventory methods are 7500 Gg/yr in the year 2000 with an uncertainty range of 2000 to 29000. However, global atmospheric absorption attributable to black carbon is too low in many models and should be increased by a factor of almost 3. After this scaling, the best estimate for the industrial-era (1750 to 2005) direct radiative forcing of atmospheric black carbon is +0.71 W/sq m with 90% uncertainty bounds of (+0.08, +1.27)W/sq m. Total direct forcing by all black carbon sources, without subtracting the preindustrial background, is estimated as +0.88 (+0.17, +1.48) W/sq m. Direct radiative forcing alone does not capture important rapid adjustment mechanisms. A framework is described and used for quantifying climate forcings, including rapid adjustments. The best estimate of industrial-era climate forcing of black carbon through all forcing mechanisms, including clouds and cryosphere forcing, is +1.1 W/sq m with 90% uncertainty bounds of +0.17 to +2.1 W/sq m. Thus, there is a very high probability that black carbon emissions, independent of co-emitted species, have a positive forcing and warm the climate. We estimate that black carbon, with a total climate forcing of +1.1 W/sq m, is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing. Sources that emit black carbon also emit other short-lived species that may either cool or warm climate. Climate forcings from co-emitted species are estimated and used in the framework described herein. When the principal effects of short-lived co-emissions, including cooling agents such as sulfur dioxide, are included in net forcing, energy-related sources (fossil fuel and biofuel) have an industrial-era climate forcing of +0.22 (0.50 to +1.08) W/sq m during the first year after emission. For a few of these sources, such as diesel engines and possibly residential biofuels, warming is strong enough that eliminating all short-lived emissions from these sources would reduce net climate forcing (i.e., produce cooling). When open burning emissions, which emit high levels of organic matter, are included in the total, the best estimate of net industrial-era climate forcing by all short-lived species from black-carbon-rich sources becomes slightly negative (0.06 W/sq m with 90% uncertainty bounds of 1.45 to +1.29 W/sq m). The uncertainties in net climate forcing from black-carbon-rich sources are substantial, largely due to lack of knowledge about cloud interactions with both black carbon and co-emitted organic carbon. In prioritizing potential black-carbon mitigation actions, non-science factors, such as technical feasibility, costs, policy design, and implementation feasibility play important roles. The major sources of black carbon are presently in different stages with regard to the feasibility for near-term mitigation. This assessment, by evaluating the large number and complexity of the associated physical and radiative processes in black-carbon climate forcing, sets a baseline from which to improve future climate forcing estimates.

black carbon↗

NASA NTRS2013

Understanding the Relationships Between Lightning, Cloud Microphysics, and Airborne Radar-derived Storm Structure During Hurricane Karl (2010)

This study explores relationships between lightning, cloud microphysics, and tropical cyclone (TC) storm structure in Hurricane Karl (16 September 2010) using data collected by the NASA DC-8 and Global Hawk (GH) aircraft during NASA's Genesis and Rapid Intensification Processes (GRIP) experiment. The research capitalizes on the unique opportunity provided by GRIP to synthesize multiple datasets from two aircraft and analyze the microphysical and kinematic properties of an electrified TC. Five coordinated flight legs through Karl by the DC-8 and GH are investigated, focusing on the inner-core region (within 50km of the storm center) where the lightning was concentrated and the aircraft were well coordinated. GRIP datasets are used to compare properties of electrified and nonelectrified inner-core regions that are related to the noninductive charging mechanism, which is widely accepted to explain the observed electric fields within thunderstorms. Three common characteristics of Karl's electrified regions are identified: 1) strong updrafts of 10-20ms21, 2) deep mixed-phase layers indicated by reflectivities.30 dBZ extending several kilometers above the freezing level, and 3) microphysical environments consisting of graupel, very small ice particles, and the inferred presence of supercooled water. These characteristics describe an environment favorable for in situ noninductive charging and, hence, TC electrification. The electrified regions in Karl's inner core are attributable to a microphysical environment that was conducive to electrification because of occasional, strong convective updrafts in the eyewall.

Cloud mircophysics↗

NASA NTRS2012

Recent Observations of Clouds and Precipitation by the Airborne Precipitation Radar 2nd Generation in Support of the GPM and ACE Missions

In this paper we illustrate the unique dataset collected during the Global Precipitation Measurement Cold-season Precipitation Experiment (GCPEx, US/Canada Jan/Feb 2012). We will focus on the significance of these observations for the development of algorithms for GPM and ACE, with particular attention to classification and retrievals of frozen and mixed phase hydrometeors.

radar↗

NASA NTRS1959

The Effect of Rapid Liquid-Phase Reactions on Injector Design and Combustion in Rocket Motors

Data are presented indicating the rates and magnitudes of energy released by the liquid-phase reactions of various propellant combinations. The data show that this energy release can contribute significantly to the rate of vaporization of the incoming propellants and thus aid the combustion process. Nevertheless, very low performances were obtained in rocket motors with conventional impinging-jet injectors when highly reactive systems such as N104-N2H4, were employed. A possible explanation for this low performance is that the initial reactions of such systems are so rapid that liquid-phase mixing is inhibited. Evidence for such an effect is presented in a series of color photographs of open flames using various injector elements. Based on these studies, some requirements are suggested for injector elements using highly reactive propellants. Experimental results are presented of motor tests using injector elements in which some of these requirements are met through the use of a set of concentric tubes. These tests, carried out at thrust levels of 40 to 800 lb per element, demonstrated combustion efficiencies of up to 98% based on equilibrium characteristic velocity values. Results are also presented for tests made with impinging-jet and splash-plate injectors for comparison.

Elverum, Gerard W., Jr.↗

NASA NTRS2015

Recent Advances in the LEWICE Icing Model

This paper will describe two recent modifications to the Glenn ICE software. First, a capability for modeling ice crystals and mixed phase icing has been modified based on recent experimental data. Modifications have been made to the ice particle bouncing and erosion model. This capability has been added as part of a larger effort to model ice crystal ingestion in aircraft engines. Comparisons have been made to ice crystal ice accretions performed in the NRC Research Altitude Test Facility (RATFac). Second, modifications were made to the run back model based on data and observations from thermal scaling tests performed in the NRC Altitude Icing Tunnel.

fluid dynamics↗

NASA NTRS2016

Update on the NASA Glenn Propulsion Systems Lab Ice Crystal Cloud Characterization (2015)

NASA Glenn's Propulsion Systems Lab (PSL), an altitude engine test facility, was outfitted with a spray system to generate ice crystals. The first ice crystal characterization test occurred in 2012. At PSL, turbine engines and driven rigs can experience ice crystal icing at flight altitudes, temperatures and Mach numbers. To support these tests, four ice crystal characterizations have been conducted in two different facility configurations. In addition, super-cooled liquid and mixed phase clouds have also been generated. This paper will discuss the recent learning from the previous two calibrations. It will describe some of the 12-parameter calibration space, and how those parameters interact with each other, the instrumentation used to characterize the cloud and present a sample of the cloud characterization results.

Ice Clouds↗

NASA NTRS2016

Validation Process for LEWICE Coupled by Use of a Navier-Stokes Solver

A research project is underway at NASA Glenn to produce computer software that can accurately predict ice growth for many meteorological conditions for any aircraft surface. This report will present results from the latest LEWICE release, version 3.5. This program differs from previous releases in its ability to model mixed phase and ice crystal conditions such as those encountered inside an engine. It also has expanded capability to use structured grids and a new capability to use results from unstructured grid flow solvers. An extensive comparison of the results in a quantifiable manner against the database of ice shapes that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has also been performed. This paper will show the differences in ice shape between LEWICE 3.5 and experimental data. In addition, comparisons will be made between the lift and drag calculated on the ice shapes from experiment and those produced by LEWICE. This report will also provide a description of both programs. Quantitative geometric comparisons are shown for horn height, horn angle, icing limit, area and leading edge thickness. Quantitative comparisons of calculated lift and drag will also be shown. The results show that the predicted results are within the accuracy limits of the experimental data for the majority of cases.

Wright, William B.↗

NASA NTRS2016

Update on the NASA Glenn Propulsion Systems Lab Ice Crystal Cloud Characterization (2015, 2016)

NASA Glenn's Propulsion Systems Lab, an altitude engine test facility, was outfitted with a spray system to generate ice crystals in 2011. Turbine engines and driven rigs can experience ice crystal icing at flight altitudes, temperatures and Mach numbers. To support these tests, four ice crystal characterizations have been conducted in two different facility configurations. In addition, super-cooled liquid and mixed phase clouds have also been generated. This paper represents a work in progress. It will describe some of the 11-parameter calibration space, and how those parameters interact with each other, the instrumentation used to characterize the cloud and present a sample of the cloud characterization results.

Engine Icing↗

NASA NTRS2017

Validation Process for LEWICE by Use of a Navier-Stokes Solver

A research project is underway at NASA Glenn to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from the latest LEWICE release, version 3.5. This program differs from previous releases in its ability to model mixed phase and ice crystal conditions such as those encountered inside an engine. It also has expanded capability to use structured grids and a new capability to use results from unstructured grid flow solvers. A quantitative comparison of the results against a database of ice shapes that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has also been performed. This paper will extend the comparison of ice shapes between LEWICE 3.5 and experimental data from a previous paper. Comparisons of lift and drag are made between experimentally collected data from experimentally obtained ice shapes and simulated (CFD) data on simulated (LEWICE) ice shapes. Comparisons are also made between experimentally collected and simulated performance data on select experimental ice shapes to ensure the CFD solver, FUN3D, is valid within the flight regime. The results show that the predicted results are within the accuracy limits of the experimental data for the majority of cases.

large-eddy simulations↗

NASA NTRS2017

A Revised Validation Process for Ice Accretion Codes

turbulent heat flux↗

NASA NTRS2018

An Investigation of Glaciated Cloud Capabilities in the NASA Glenn Icing Research Tunnel

In 2015 the FAA added Appendix D to Part 33 engine certification requirements that included Mixed Phase and Ice Crystal Icing to aircraft engine certification. Replicating the ice crystal environment that is seen in nature has proven to be a challenge, which multiple engine ground testing facilities and icing wind tunnels have achieved to varying degrees. The Icing Research Tunnel (IRT) at NASA Glenn has always been focused on super-cooled liquid water to produce FAA Part 23 and Part 25 regulations, targeting Appendix C and lately also Appendix O. However, due to a growing interest in the field of ice crystals and the high cost of operating engine icing facilities, the IRT staff have recently completed testing using the Multi-Element Sensor (also known as the multi-wire) to measure glaciated cloud conditions. Results indicate that turning off the heat to the nozzle air and water supply can create a stable, fully glaciated cloud in the test section for a small range of conditions: drop-size distribution values below 20 microns (median volumetric diameter), air temperatures as warm as -7 deg C, and airspeeds between 100 and 250 knots. These tests also revealed how varying the total temperature, airspeed, nozzle air pressure, and nozzle water pressure affect the glaciation of the IRT cloud.

ice water content↗

NASA NTRS2018

Total Temperature Measurements Using a Rearward Facing Probe in Supercooled Liquid Droplet and Ice Crystal Clouds

Engine Icing Performance loss: rollback, surge, flameout, and even internal engine damagePartial melting and refreeze of ice inside engine core (Mason et al., 2006). Ingestion of ice crystals and aggregates, mixed-phase droplets, or supercooled liquid dropletsNeed to better understand the conditions and properties that lead to engine icing.Simulation and analysis (physical and computational, and modeling)Test facilities (PSL, NRC, ...). Thermal and computational models and analysisProbesMultiple probes (aerothermal probes and ice cloud characterization probes and techniques). Total temperatureTraditional total temperature probes (vented forward facing)Heated total temperature probes (Goodyear). Rearward facing (developmental). Total temperature relevance. Thermal interaction between the icing cloud and air flow impinging particles contribute to kinetic heating effect (Gent et al., 2000). Measurement considerations Temperature sensor accuracy. Incomplete recovery of total temperature. Thermal surfaces (sources and sinks). Flow effects (viscous losses). Debris contamination, including icing and ice ingestion.

Agui, Juan H.↗

NASA NTRS2018

NASA Observations and Modeling During ICE-POP

Recap: NASA-Specific Objectives for ICE-POP: Provide real-time observational and NWP data in support of ICE-POP, participate in significant international science effort; GPM (Global Precipitation Measurement) Ground Validation and NASA Weather Program -Direct/physical validation of active/passive satellite-based snowfall retrieval algorithms over coastline and mountains; melting layer interaction with terrain -Physics of snow, coupling to snow water equivalent rate and satellite remote sensor retrieval algorithm assumptions - -Size distributions, types/habit, water equivalent, profiles -NU-WRF (NASA-Unified Weather Research and Forecasting) Model plus Observational analyses: Movement toward “level IV products” leverage intensive and multi-faceted NWP (Numerical Weather Prediction) component -Model precipitation processes (liquid, mixed phase and frozen); Build model testing database for further active/passive remote sensing algorithm development (e.g., satellite data simulators) -"Integrated" validation of products in operational context.

Precipitation Science↗

NASA NTRS2019

Ice-Crystal Icing Accretion Studies at the NASA Propulsion Systems Laboratory

This paper describes an ice-crystal icing experiment conducted at the NASA Propulsion System Laboratory during June 2018. This test produced ice shape data on an airfoil for different test conditions similar to those inside the compressor region of a turbo-fan jet engine. Mixed-phase icing conditions were generated by partially freezing out a water spray using the relative humidity of flow as the primary parameter to control freeze-out. The paper presents the ice shape data and associated conditions which include pressure, velocity, temperature, humidity, total water content, melt ratio, and particle size distribution. The test featured a new instrument traversing system which allowed surveys of the flow and cloud. The purpose of this work was to provide experimental ice shape data and associated conditions to help develop and validate ice-crystal icing accretion models. The results support previous experimental observations of a minimum melt-ratio threshold for accretion to occur as well as the existence of a plateau region where the icing severity is high for a range of melt ratios. However, a maximum limit for melt ratio, which is suggested in the ice crystal icing literature, was not observed perhaps complicated by the potential for some supercooling of the water at these conditions.

Engine Icing↗

NASA NTRS2017

An Analysis of Coordinated Observations from NOAA's Ronald Brown Ship and G-IV Aircraft in a Landfalling Atmospheric River over the North Pacific During CalWater-2015

To gain a more complete observational understanding of atmospheric rivers (ARs) over the data-sparse open ocean, we used a diverse suite of mobile observing platforms deployed on NOAAs Ronald H. Brown (RHB) research vessel and G-IV research aircraft during the CalWater-2015 field campaign to describe the structure and evolution of a long-lived AR modulated by six frontal waves over the northeastern Pacific on 20-25 January 2015. Satellite observations and reanalysis diagnostics provided synoptic-scale context, illustrating the warm, moist southwesterly airstream within the quasi-stationary AR situated between an upper-level trough and ridge. The AR remained offshore of the U.S. West Coast but made landfall across British Columbia where heavy precipitation fell. Forty-seven rawinsondes launched from the RHB provided a comprehensive thermodynamic and kinematic depiction of the AR, including uniquely documenting an upward intrusion of strong water-vapor transport in the low-level moist southwesterly flow during the passage of frontal waves 2 through 6. A collocated 1290-MHz wind profiler showed an abrupt frontal transition from southwesterly to northerly flow below 1 km MSL coinciding with the tail-end of AR conditions. Shipborne radar and disdrometer observations in the AR uniquely captured key microphysical characteristics of shallow warm rain, convection, and deep mixed-phase precipitation. Novel observations of sea-surface fluxes in a midlatitude AR documented persistent ocean-surface evaporation and sensible-heat transfer into the ocean. The G-IV aircraft flew directly over the ship, with dropsonde and radar spatial analyses complementing the temporal depictions of the AR from the RHB. The AR characteristics varied, depending on the location of the cross section relative to the frontal waves.

atmospheric rivers↗

NASA NTRS2020

The Role of Composition and Surface Area Variability in Ice Nucleation, and How to Get Rid of It

Ice nucleation active site densities and nucleation rates are commonly determined by measuring the fraction of droplets that freeze at different temperatures. In analysing these experiments it is commonly assumed that variability in the immersed particle surface area and composition within a sample can be neglected, allowing a simple parameterization of ice nucleation efficiencies. Here it is shown that these approximations may result in large error, and translate into a bias in estimated active site densities of about six orders of magnitude. When applied in cloud models it may represent up to 5 K error in cloud glaciation temperature. A solution to this enduring problem is proposed for the first time. It is shown that by performing droplet freezing experiments varying mean particle surface area along with the temperature such a bias can be quantitatively removed. This amounts to differentiating the "freezing rate'' from the ice nucleation coefficient, or, the apparent and the actual active site density of a material. The proposed method will contribute to reduce existing uncertainties in the relative strength of the ice nucleation ability of different aerosol species, and the modeling of mixed-phase clouds.

Barahona, Donifan↗