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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Inertial oscillation of a vertical rotating draft with application to a supercell storm

An analytic model (vertical rotating draft) which includes the gross features of a supercell storm on an f-plane, undergoes an inertial oscillation that appears to have been overlooked in previous analytic and numerical models. The oscillation is nonlinear and consists of a long quiescent phase and a short intense phase. During the intense phase, the rotating draft has the following features of a supercell: the diameter of the core contracts as it spins up and expands as it spins down; if vertical wind shear is included, the track of the rotating draft turns to the right (an anticyclonic rotating draft turns to the left); this turning point is followed by a predominantly upward flow; and the horizontal pressure gradient is very small (a property of most tornadoless supercells). The rapid spin-up during the intense phase and the high Rossby numbers obtainable establish the ability of the Coriolis force to spin up single cyclonic or anticyclonic supercells by means of this inertial oscillation. This surprising result has implications for numerical supercell simulations, which generally do not rely on the Coriolis force as a source of rotation. The physics and mathematics of the inertial oscillation are given, and the solution is applied to a documented supercell.

Supercell thunderstorm↗
NASA NTRS2005

Stalled Pulsing Inertial Oscillation Model for a Tornadic Cyclone

A supercell storm is a tall, rotating thunderstorm that can generate hail and tornadoes. Two models exist for the development of the storm's rotation or mesocyclone - the conventional splitting-storm model, and the more recent pulsing inertial oscillation (PIO) model, in which a nonlinear pulse represents the supercell. Although data support both models and both could operate in the same supercell, neither model has satisfactorily explained the tornadic cyclone. A tornadic cyclone is an elevated vorticity concentration of Rossby number approximately 1000 that develops within the contracting mesocyclone shortly before a major tornado appears at the surface. We now show that if the internal temperature excess due to latent energy release is limited to the realistic range of -12 K to +12 K, the PIO model can stall part way through the pulse in a state of contraction and spin-up. Should this happen, the stalled-PIO model can evolve into a tornadic cyclone with a central pressure deficit that exceeds 40 mb, which is greater than the largest measured value. This simulation uses data from a major tornadic supercell that occurred over Oklahoma City, Oklahoma, USA, on May 3, 1999. The stalled-PIO mechanism also provides a strategy for human intervention to retard or reverse the development of a tornadic cyclone and its pendant tornado.

Costen, Robert C.↗
NASA NTRS1988

A diagnostic study of vertical fluxes in cumulus clouds using model output data

Midlatitude supercell, Florida sea-breeze convection, and tropical squall line simulations were performed using the Colorado State University Regional Atmospheric Modeling System which employed the non-hydrostatic, fully compressible, equations with parameterized microphysics. The time evolution of the vertical velocity variance (VVV) is especially interesting since it is a measure of the strength of convection. This variance exhibits striking similarities when analyzed for the aforementioned cases which may indicate that all convection is fundamentally similar. Vertical mass and moisture covariances appear strongly linked to VVV, so it may be the appropriate variable on which to base a hybrid cumulus parameterization scheme.

Weissbluth, M. J.↗
NASA NTRS1998

Pulsing Inertial Oscillation, Supercell Storms, and Surface Mesonetwork Data

The pulsing inertial oscillation (PIO) model is a nonlinear, time-dependent, translating vortex solution of the inviscid, compressible fluid dynamic equations in the middle troposphere. The translation of this vortex during a pulse is strikingly similar to that of a supercell storm -- a rotating thunderstorm that can generate tornadoes and hail. Two studies were performed to test the hypothesis that some supercell storms are manifestations of a PIO pulse. The first study applied the model to an intense interior draft whose buoyancy was bounded by a temperature excess of +/- 12 K. The peak updraft speed achieved was 41.5 m/ s and the peak Rossby number was 92.9. The study also pointed to an advanced concept for attaining higher values. The second study applied the PIO model to a supercell storm as a whole and succeeded in replicating its bulk properties, such as mesocyclonic circulation, net mass and moisture influxes, and time track. This study also identified a critical feature of the PIO model that could be tested against storm data: The average vertical draft is downward before the turn in the storm track and upward afterwards. In the conventional theory, the average vertical draft is upward from storm inception until dissipation. These differing draft predictions were compared with the best available data, which are surface mesonetwork data. These data were found to support the PIO model. However, surface data alone are not conclusive, and further measurements are warranted.

Costen, R. C.↗
NASA NTRS2012

Numerical Simulation of a Tornado Generating Supercell

The development of tornadoes from a tornado generating supercell is investigated with a large eddy simulation weather model. Numerical simulations are initialized with a sounding representing the environment of a tornado producing supercell that affected North Carolina and Virginia during the Spring of 2011. The structure of the simulated storm was very similar to that of a classic supercell, and compared favorably to the storm that affected the vicinity of Raleigh, North Carolina. The presence of mid-level moisture was found to be important in determining whether a supercell would generate tornadoes. The simulations generated multiple tornadoes, including cyclonic-anticyclonic pairs. The structure and the evolution of these tornadoes are examined during their lifecycle.

Proctor, Fred H.↗
NASA NTRS1992

Inertial Oscillation of a Vertical Rotating Draft with Application to a Supercell Storm: Video Supplement to NASA-TP-3230

In this video (8 min., color, sound, VHS), animation depicts the inertial oscillation of a new mathematical model ('vertical rotating draft') for spinning up a single supercell storm. The oscillation consists of a long quiescent phase when the draft is large in diameter and rotates anticyclonically and a short intense phase when the draft is small and cyclonic. During the intense phase, the rotating draft resembles a supercell. The physical basis for the oscillation is depicted by tracking air parcels in the draft as they move along inertial circles (projected on a horizontal plane), where the horizontal pressure gradient is zero and the Coriolis force balances the centrifugal force. A side view of the oscillation shows that contraction and expansion are linked, respectively, to buoyantly driven compressible downdraft and updraft. An aerial view tracks the draft as it moves above the surface of the Earth and turns to the right during the intense phase. Radar echoes from a supercell storm are superimposed for comparison. The data appear to support only the intense phase. A critical experiment would measure the predominantly downward flow that theoretically occurs before the right turn in a supercell track and causes contraction and spin-up.

Supercell thunderstorm↗
NASA NTRS1987

The terminal area simulation system. Volume 2: Verification cases

The numerical simulation of five case studies are presented and are compared with available data in order to verify the three-dimensional version of the Terminal Area Simulation System (TASS). A spectrum of convective storm types are selected for the case studies. Included are: a High-Plains supercell hailstorm, a small and relatively short-lived High-Plains cumulonimbus, a convective storm which produced the 2 August 1985 DFW microburst, a South Florida convective complex, and a tornadic Oklahoma thunderstorm. For each of the cases the model results compared reasonably well with observed data. In the simulations of the supercell storms many of their characteristic features were modeled, such as the hook echo, BWER, mesocyclone, gust fronts, giant persistent updraft, wall cloud, flanking-line towers, anvil and radar reflectivity overhang, and rightward veering in the storm propagation. In the simulation of the tornadic storm a horseshoe-shaped updraft configuration and cyclic changes in storm intensity and structure were noted. The simulation of the DFW microburst agreed remarkably well with sparse observed data. The simulated outflow rapidly expanded in a nearly symmetrical pattern and was associated with a ringvortex. A South Florida convective complex was simulated and contained updrafts and downdrafts in the form of discrete bubbles. The numerical simulations, in all cases, always remained stable and bounded with no anomalous trends.

Proctor, F. H.↗
NASA NTRS2014

Terminal Area Simulation System User's Guide - Version 10.0

The Terminal Area Simulation System (TASS) is a three-dimensional, time-dependent, large eddy simulation model that has been developed for studies of wake vortex and weather hazards to aviation, along with other atmospheric turbulence, and cloud-scale weather phenomenology. This document describes the source code for TASS version 10.0 and provides users with needed documentation to run the model. The source code is programed in Fortran language and is formulated to take advantage of vector and efficient multi-processor scaling for execution on massively-parallel supercomputer clusters. The code contains different initialization modules allowing the study of aircraft wake vortex interaction with the atmosphere and ground, atmospheric turbulence, atmospheric boundary layers, precipitating convective clouds, hail storms, gust fronts, microburst windshear, supercell and mesoscale convective systems, tornadic storms, and ring vortices. The model is able to operate in either two- or three-dimensions with equations numerically formulated on a Cartesian grid. The primary output from the TASS is time-dependent domain fields generated by the prognostic equations and diagnosed variables. This document will enable a user to understand the general logic of TASS, and will show how to configure and initialize the model domain. Also described are the formats of the input and output files, as well as the parameters that control the input and output.

Switzer, George F.↗
NASA NTRS2008

Extreme Helicity and Intense Convective Towers in Hurricane Bonnie

Helicity was calculated in Hurricane Bonnie (1998) using tropospheric-deep dropsonde soundings from the NASA Convection and Moisture Experiment. Large helicity existed downshear of the storm center with respect to the ambient vertical wind shear. It was associated with veering, semicircular hodographs created by strong, vortex-scale, radial-vertical flow induced by the shear. The most extreme values of helicity, among the largest ever reported in the literature, occurred in the vicinity of deep convective cells in the downshear-left quadrant. These cells reached as high as 17.5 km and displayed the temporal and spatial scales of supercells. Convective available potential energy (CAPE) averaged 861 J/kg downshear, but only about one-third as large upshear. The soundings nearest the deep cells were evaluated using two empirical supercell parameters that make use of CAPE, helicity, and/or shear. These parameters supported the possible existence of supercells as a consequence of the exceptional helicity combined with moderate but sufficient CAPE. Ambient vertical wind shear exceeded 12 m/s for 30 h, yet the hurricane maintained 50 m/s maximum winds. It is hypothesized that the long-lived convective cells enabled the storm to resist the negative impact of the shear. Supercells in large-helicity, curved-hodograph environments appear to provide a useful conceptual model for intense convection in the hurricane core. Helicity calculations might also give some insight into the behavior of vortical hot towers, which share some characteristics with supercells.

Molinari, John↗
NASA NTRS2016

WRF-Chem Simulations of Lightning-NOx Production and Transport in Oklahoma and Colorado Thunderstorms Observed During DC3

The focus of this analysis is on lightning-generated nitrogen oxides (LNOx) and their distribution for two thunderstorms observed during the Deep Convective Clouds and Chemistry (DC3) field campaign in May-June 2012. The Weather Research and Forecasting Chemistry (WRF-Chem) model is used to perform cloud-resolved simulations for the May 29-30 Oklahoma severe convection, which contained one supercell, and the June 6-7 Colorado squall line. Aircraft and ground-based observations (e.g., trace gases, lightning and radar) collected during DC3 are used in comparisons against the model-simulated lightning flashes generated by the flash rate parameterization schemes (FRPSs) incorporated into the model, as well as the model-simulated LNOx predicted in the anvil outflow. Newly generated FRPSs based on DC3 radar observations and Lightning Mapping Array data are implemented in the model, along with previously developed schemes from the literature. The results of these analyses will also be compared between storms to investigate which FRPSs were most appropriate for the two types of convection and to examine the variation in the LNOx production. The simulated LNOx results from WRF-Chem will also be compared against other previously studied mid-latitude thunderstorms.

Lightning↗
NASA NTRS2006

The Effects of Lightning NO(x) Production during the July 21 EULINOX Storm studied with a 3-D Cloud-scale Chemical Transport Model

The July 21,1998 thunderstonn observed during the European Lightning Nitrogen Oxides Project (EULINOX) project was simulated using the three-dimensional Goddard Cumulus Ensemble (GCE) model. The simulation successfully reproduced a number of observed storm features including the splitting of the original cell into a southern cell which developed supercell characteristics, and a northern cell which became multicellular. Output from the GCE simulation was used to drive an offline cloud-scale chemical transport model which calculates tracer transport and includes a parameterization of lightning NO(x) production which uses observed flash rates as input. Estimates of lightning NO(x) production were deduced by assuming various values of production per intracloud and production per cloud-to-ground flash and comparing the results with in-cloud aircraft observations. The assumption that both types of flashes produce 360 moles of NO per flash on average compared most favorably with column mass and probability distribution functions calculated from observations. This assumed production per flash corresponds to a global annual lightning NOx source of 7 Tg N per yr. Chemical reactions were included in the model to evaluate the impact of lightning NO(x), on ozone. During the storm, the inclusion of lightning NOx in the model results in a small loss of ozone (on average less than 4 ppbv) at all model levels. Simulations of the chemical environment in the 24 hours following the storm show on average a small increase in the net production of ozone at most levels resulting from lightning NO(x), maximizing at approximately 5 ppbv per day at 5.5 km. Between 8 and 10.5 km, lightning NO(x) causes decreased net ozone production.

Ott, Lesley E.↗
NASA NTRS1989

Simulated appearance of an evolving supercell hail storm at SSM/I microwave frequencies

The contribution of distinct classes of hydrometeors generated from a cloud model to top-of-atmosphere microwave brightness temperatures is studied at the four separate frequencies of the Special Sensor Microwave Imager (SSM/I). The relative radiative role of individual modes of hydrometeors during the evolution of a severe thunderstorm is examined using a microwave radiative transfer model coupled with a three-dimensional cloud model capable of simulating the essential dynamical and microphysical features of an intense hail store. Consideration is given to plans to use the simulation results with actual multichannel measurements from SSM/I to provide a framework for multispectral precipitation retrieval algorithms.

Smith, Eric A.↗
NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗
NASA NTRS2017

High Ice Water Concentrations in the 19 August 2015 Coastal Mesoconvective System

During August 2015, NASA's DC-8 research aircraft was flown into High Ice Water Content (HIWC) events as part of a three-week campaign to collect airborne radar data and to obtain measurements from microphysical probes. Goals for this flight campaign included improved characterization of HIWC events, especially from an airborne radar perspective. This paper focuses on one of the flight days, in which a coastal mesoscale convective system (MCS) was investigated for HIWC conditions. The system appears to have been maintained by bands of convection flowing in from the Gulf of Mexico. These convective bands were capped by a large cloud canopy, which masks the underlying structure if viewed from an infrared sensing satellite. The DC-8 was equipped with an IsoKinetic Probe that measured ice concentrations of up to 2.3 g m(exp -3) within the cloud canopy of this system. Sustained measurements of ice crystals with concentrations exceeding 1 g m(exp -3) were encountered for up to ten minutes of flight time. Airborne Radar reflectivity factors were found to be weak within these regions of high ice water concentrations, suggesting that Radar detection of HIWC would be a challenging endeavor. This case is then investigated using a three-dimensional numerical cloud model. Profiles of ice water concentrations and radar reflectivity factor demonstrate similar magnitudes and scales between the flight measurements and model simulation. Also discussed are recent modifications to the numerical model's ice-microphysics that are based on measurements during the flight campaign. The numerical model and its updated ice-microphysics are further validated with a simulation of a well-known case of a supercell hailstorm measured during the Cooperative Convective Precipitation Experiment. Differences in HIWC between the continental supercell and the coastal MCS are discussed.

Proctor, Fred H.↗
NASA NTRS2006

High-Resolution Analysis Products to Support Severe Weather and Cloud-to-Ground Lightning Threat Assessments over Florida

The Applied Meteorology Unit (AMU) located at the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) implemented an operational configuration of the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS), as well as the ARPS numerical weather prediction (NWP) model. Operational, high-resolution ADAS analyses have been produced from this configuration at the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) over the past several years. Since that time, ADAS fields have become an integral part of forecast operations at both NWS MLB and SMG. To continue providing additional utility, the AMU has been tasked to implement visualization products to assess the potential for supercell thunderstorms and significant tornadoes, and to improve assessments of short-term cloud-to-ground (CG) lightning potential. This paper and presentation focuses on the visualization products developed by the AMU for the operational high-resolution ADAS and AR.PS at the NWS MLB and SMG. The two severe weather threat graphics implemented within ADAS/ARPS are the Supercell Composite Parameter (SCP) and Significant Tornado Parameter (SIP). The SCP was designed to identify areas with supercell thunderstorm potential through a combination of several instability and shear parameters. The SIP was designed to identify areas that favor supercells producing significant tornadoes (F2 or greater intensity) versus non-tornadic supercells. Both indices were developed by the NOAAINWS Storm Prediction Center (SPC) and were normalized by key threshold values based on previous studies. The indices apply only to discrete storms, not other convective modes. In a post-analysis mode, the AMU calculated SCP and SIP for graphical output using an ADAS configuration similar to the operational set-ups at NWS MLB and SMG. Graphical images from ADAS were generated every 15 minutes for 13 August 2004, the day that Hurricane Charley approached and made landfall on the Florida peninsula. Several tornadoes struck the interior of the Florida peninsula in advance of Hurricane Charley's landfall during the daylight hours of 13 August. Since SPC had previously examined this case using SCP and SIP graphics generated from output of the Rapid Update Cycle (RUC) model, this day served as a good benchmark to compare and validate the high-resolution ADAS graphics against the smoother RUC analyses, which serves as background fields to the ADAS analyses. The ADAS-generated SCP and STP graphics have been integrated into the suite of products examined operationally by NWS MLB forecasters and are used to provide additional guidance for assessment of the near-storm environment during convective situations.

Case, Jonathan↗
NASA NTRS1990

Tornadogenesis via squall line and supercell interaction revisited - The 15 November 1989 Huntsville tornado

A case study analyzing the environmental setting and storm system morphology that provides observational evidence of a mechanism involving the interaction of a gust front with a preexisting mesocyclone is presented. This case serves to reemphasize the existence of a high conditional probability of tornado occurrence, given the merger of a gust front (or storm outflow) with a moderate to strong thunderstorm ahead of it. The resultant data serve to illustrate some important unresolved issues relevant to the severe weather warning system that involve the present and planned local warning and network radars, and future algorithms that might intelligently integrate other data sources and models with the radar data.

Goodman, Steven J.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-35370-DND

The above anvil cirrus plume (AACP) is a weather phenomenon that signifies an intense tropopause penetrating updraft which can inject cirrus clouds several kilometers into the stratosphere. Storms that have such intense updrafts are often supercells which generate severe weather such as tornadoes, high winds, and hail. In addition, AACPs moisten the stratosphere and influence the Earth's radiative balance. Though an AACP can be identified by the human eye, no automated AACP detection methods currently exist. Lack of detection inhibits understanding of where and how often AACPs occur, and how these storms influence stratospheric air composition. Previous work involved synthesis of multiple remote sensing and severe weather report/warning data sources to identify AACPs in Geostationary Operational Environmental Satellite system (GOES) satellite imagery and better understand their weather impacts (Bedka et al. (Wea. Forecasting, 2018)). This current study demonstrates an automated AACP identification method based on the application of a deep learning segmentation model known as a U-net. This study documents the development of a U-net model capable of identifying emergent AACPs using only satellite infrared (IR) and visible reflected sunlight imagery. The performance of a U-net is quantitatively benchmarked with human AACP identifications and qualitatively assessed through animations of detections generated from GOES-16 1-minute temporal resolution imagery.

Charles Liles↗