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All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Explicitly Resolving Lightning and Electrification Processes from the 10-12 April 2019 Thundersnow Outbreak

The 10-12 April 2019 thundersnow (i.e., lightning within snowfall) outbreak was examined via ground- and space-based lightning observations and was simulated using a numerical weather prediction model with an explicit electrification parameterization. When compared to observations, the simulation propagated the synoptic snowband two to six hours faster while also exaggerating the 3-D reflectivity structure. Throughout the event, the simulation produced 1,733 thundersnow flashes which was less than what was observed by ground- and space-based lightning sensors. In general, simulated thundersnow flashes were spatially offset from the largest reflectivities within the synoptic snowband and tended to occur within elevated convection that traversed isentropically along the top of mid-level frontogenesis. These simulated thundersnow flashes were associated with a tripole charge structure with ice/snow hydrometeors contributing most to the main negative charge region. Both simulated and observed thundersnow flashes initiated in conditionally unstable environments. Lastly, a conceptual model was developed to explain the spatial separation between the largest reflectivities in the snowband and the occurrence of thundersnow. It is hypothesized that the spatial offset of thundersnow initiation from the reflectivity cores within the synoptic snowband arose from a thermal circulation – induced by mid-level frontogenesis – that advects positively charged ice/snow hydrometeors towards the surface and creates a nearly homogeneous vertical charge structure.

lightning↗
NASA NTRS2014

A WRF-Chem Flash Rate Parameterization Scheme and LNOx Analysis of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). Based on the measurements taken of the 29-30 May 2012 Oklahoma thunderstorm, an analysis against a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the same event at 3-km horizontal resolution was performed. One of the main objectives was to include various flash rate parameterization schemes (FRPSs) in the model and identify which scheme(s) best captured the flash rates observed by the National Lightning Detection Network (NLDN) and Oklahoma Lightning Mapping Array (LMA). The comparison indicates how well the schemes predicted the timing, location, and number of lightning flashes. The FRPSs implemented in the model were based on the simulated thunderstorms physical features, such as maximum vertical velocity, cloud top height, and updraft volume. Adjustment factors were applied to each FRPS to best capture the observed flash trend and a sensitivity study was performed to compare the range in model-simulated lightning-generated nitrogen oxides (LNOx) generated by each FRPS over the storms lifetime. Based on the best FRPS, model-simulated LNOx was compared against aircraft measured NOx. The trace gas analysis, along with the increased detail in the model specification of the vertical distribution of lightning flashes as suggested by the LMA data, provide guidance in determining the scenario of NO production per intracloud and cloud-to-ground flash that best matches the NOx mixing ratios observed by the aircraft.

Atmospheric chemistry↗
NASA NTRS2014

A Wrf-Chem Flash Rate Parameterization Scheme and LNO(x) Analysis of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). Based on the measurements taken of the 29-30 May 2012 Oklahoma thunderstorm, an analysis against a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the same event at 3-km horizontal resolution was performed. One of the main objectives was to include various flash rate parameterization schemes (FRPSs) in the model and identify which scheme(s) best captured the flash rates observed by the National Lightning Detection Network (NLDN) and Oklahoma Lightning Mapping Array (LMA). The comparison indicates how well the schemes predicted the timing, location, and number of lightning flashes. The FRPSs implemented in the model were based on the simulated thunderstorms physical features, such as maximum vertical velocity, cloud top height, and updraft volume. Adjustment factors were added to each FRPS to best capture the observed flash trend and a sensitivity study was performed to compare the range in model-simulated lightning-generated nitrogen oxides (LNOx) generated by each FRPS over the storms lifetime. Based on the best FRPS, model-simulated LNOx was compared against aircraft measured NOx. The trace gas analysis, along with the increased detail in the model specification of the vertical distribution of lightning flashes as suggested by the LMA data, provide guidance in determining the scenario of NO production per intracloud and cloud-to-ground flash that best matches the NOx mixing ratios observed by the aircraft.

Cloud physics↗
NASA NTRS2008

Forecasting Lightning Threat using Cloud-Resolving Model Simulations

Two new approaches are proposed and developed for making time and space dependent, quantitative short-term forecasts of lightning threat, and a blend of these approaches is devised that capitalizes on the strengths of each. The new methods are distinctive in that they are based entirely on the ice-phase hydrometeor fields generated by regional cloud-resolving numerical simulations, such as those produced by the WRF model. These methods are justified by established observational evidence linking aspects of the precipitating ice hydrometeor fields to total flash rates. The methods are straightforward and easy to implement, and offer an effective near-term alternative to the incorporation of complex and costly cloud electrification schemes into numerical models. One method is based on upward fluxes of precipitating ice hydrometeors in the mixed phase region at the-15 C level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domain-wide statistics of the peak values of simulated flash rate proxy fields against domain-wide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. Our blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Exploratory tests for selected North Alabama cases show that, because WRF can distinguish the general character of most convective events, our methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because the models tend to have more difficulty in predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models,the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of forecasts become available.

McCaul, Eugene W., Jr.↗
NASA NTRS2009

Forecasting Lightning Threat using Cloud-resolving Model Simulations

As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\dgc\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because models tend to have more difficulty in correctly predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models, the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of cloud-allowing forecasts become available.

McCaul, E. W., Jr.↗
NASA NTRS1993

Propagation of electromagnetic waves parallel to the magnetic field in the nightside Venus ionosphere

The propagation of electromagnetic waves parallel to the magnetic field in the nightside Venus ionosphere is presented in a theoretical and numerical analysis. The model assumes a source of electromagnetic radiation in the Venus atmosphere, such as that produced by lightning. Specifically addressed is wave propagation in the altitude range z = 130-160 km at the four frequencies detectable by the Pioneer Venus Orbiter Electric Field Detector: 100 Hz, 730 Hz, 5.4 kHz, and 30 kHz. Parameterizations of the wave intensities, peak electron density, and Poynting flux as a function of magnetic field are presented. The waves are found to propagate most easily in conditions of low electron density and high magnetic field. The results of the model are consistent with observational data.

Huba, J. D.↗
NASA NTRS2006

Overview of the Field Phase of the NASA Tropical Cloud Systems and Processes (TCSP)Experiment

The Tropical Cloud Systems and Processes experiment is sponsored by the National Aeronautics and Space Administration (NASA) to investigate characteristics of tropical cyclone genesis, rapid intensification and rainfall using a three-pronged approach that emphasizes satellite information, suborbital observations and numerical model simulations. Research goals include demonstration and assessment of new technology, improvements to numerical model parameterizations, and advancements in data assimilation techniques. The field phase of the experiment was based in Costa Rica during July 2005. A fully instrumented NASA ER-2 high altitude airplane was deployed with Doppler radar, passive microwave instrumentation, lightning and electric field sensors and an airborne simulator of visible and infrared satellite sensors. Other assets brought to TCSP were a low flying uninhabited aerial vehicle, and a surface-based radiosonde network. In partnership with the Intensity Forecasting Experiment of the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division, two NOAA P-3 aircraft instrumented with radar, passive microwave, microphysical, and dropsonde instrumentation were also deployed to Costa Rica. The field phase of TCSP was conducted in Costa Rica to take advantage of the geographically compact tropical cyclone genesis region of the Eastern Pacific Ocean near Central America. However, the unusual 2005 hurricane season provided numerous opportunities to sample tropical cyclone development and intensification in the Caribbean Sea and Gulf of Mexico as well. Development of Hurricane Dennis and Tropical Storm Gert were each investigated over several days in addition to Hurricane Emily as it was close to Saffir-Simpson Category 5 intensity. An overview of the characteristics of these storms along with the pregenesis environment of Tropical Storm Eugene in the Eastern Pacific will be presented.

Hood, Robbie E.↗
NASA NTRS2003

Regional-Scale Modeling at NASA Goddard Space Flight Center

Over the past decade, the Goddard Mesoscale Modeling and Dynamics Group has used a popular regional scale model, MM5, to study precipitation processes. Our group is making contributions to the MM5 by incorporating the following physical and numerical packages: improved Goddard cloud processes, a land processes model (Parameterization for Land-Atmosphere-Cloud Exchange - PLACE), efficient but sophisticated radiative processes, conservation of hydrometeor mass (water budget), four-dimensional data assimilation for rainfall, and better computational methods for trace gas transport. At NASA Goddard, the MM5 has been used to study: (1) the impact of initial conditions, assimilation of satellite-derived rainfall, and cumulus parameterizations on rapidly intensifying oceanic cyclones, hurricanes and typhoons, (2) the dynamic and thermodynamic processes associated with the development of narrow cold frontal rainbands, (3) regional climate and water cycles, (4) the impact of vertical transport by clouds and lightning on trace gas distributiodproduction associated with South and North American mesoscale convective systems, (5) the development of a westerly wind burst (WWB) that occurred during the TOGA COARE and the diurnal variation of precipitation in the tropics, (6) a Florida sea breeze convective event and a Mid-US flood event using a sophisticated land surface model, (7) the influence of soil heterogeneity on land surface energy balance in the southwest GCIP region, (8) explicit simulations (with 1.33 to 4 km horizontal resolution) of hurricanes Bob (1991) and Bonnie (1998), (9) a heavy precipitation event over Taiwan, and (10) to make real time forecasts for a major NASA field program. In this paper, the modifications and simulated cases will be described and discussed.

Tao, W.-K.↗
NASA NTRS2013

Lightning NOx Statistics Derived by NASA Lightning Nitrogen Oxides Model (LNOM) Data Analyses

What is the LNOM? The NASA Marshall Space Flight Center (MSFC) Lightning Nitrogen Oxides Model (LNOM) [Koshak et al., 2009, 2010, 2011; Koshak and Peterson 2011, 2013] analyzes VHF Lightning Mapping Array (LMA) and National Lightning Detection Network(TradeMark) (NLDN) data to estimate the lightning nitrogen oxides (LNOx) produced by individual flashes. Figure 1 provides an overview of LNOM functionality. Benefits of LNOM: (1) Does away with unrealistic "vertical stick" lightning channel models for estimating LNOx; (2) Uses ground-based VHF data that maps out the true channel in space and time to < 100 m accuracy; (3) Therefore, true channel segment height (ambient air density) is used to compute LNOx; (4) True channel length is used! (typically tens of kilometers since channel has many branches and "wiggles"); (5) Distinction between ground and cloud flashes are made; (6) For ground flashes, actual peak current from NLDN used to compute NOx from lightning return stroke; (7) NOx computed for several other lightning discharge processes (based on Cooray et al., 2009 theory): (a) Hot core of stepped leaders and dart leaders, (b) Corona sheath of stepped leader, (c) K-change, (d) Continuing Currents, and (e) M-components; and (8) LNOM statistics (see later) can be used to parameterize LNOx production for regional air quality models (like CMAQ), and for global chemical transport models (like GEOS-Chem).

Koshak, William↗
NASA NTRS2017

Ozone Production by Corona Discharges During a Convective Event in DISCOVER-AQ Houston

An ozonesonde launched near electrically active convection in Houston, TX on 5 September 2013 during the NASA DISCOVER-AQ project measured a large enhancement of ozone throughout the troposphere. A separate ozonesonde was launched from Smith Point, TX (approx. 58 km southeast of the Houston site) at approximately the same time as the launch from Houston and did not measure that enhancement. Furthermore, ozone profiles for the descent of both sondes agreed well with the ascending Smith Point profile, suggesting a highly localized event in both space and time in which an anomalously large enhancement of 70 - 100 ppbv appeared in the ascending Houston ozonesonde data. Compared to literature values, such an enhancement appears to be the largest observed to date. Potential sources of the localized ozone enhancement such as entrainment of urban or biomass burning emissions, downward transport from the stratosphere, photochemical production from lightning NO(sub x), and direct ozone production from corona discharges were investigated using model simulations. We conclude that the most likely explanation for the large ozone enhancement is direct ozone production by corona discharges. Integrating the enhancement seen in the Houston ozone profile and using the number of electrical discharges detected by the NLDN (or HLMA), we estimate a production of 2.48 x 10(exp. 28) molecules of ozone per flash which falls within the range of previously recorded values (9.89 x 10(exp. 26) - 9.82 x 10)exp. 28) molecules of ozone per flash). Since there is currently no parameterization for the direct production of ozone from corona discharges we propose the implementation of an equation into a chemical transport model. Ultimately, additional work is needed to further understand the occurrence and impact of corona discharges on tropospheric chemistry on short and long timescales.

ozone↗
NASA NTRS2014

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U.S. Deep South Summer Convection

Convection-allowing numerical weather simula- tions have often been shown to produce convective storms that have significant sensitivity to choices of model physical parameterizations. Among the most important of these sensitivities are those related to cloud microphysics, but planetary boundary layer parameterizations also have a significant impact on the evolution of the convection. Aspects of the simulated convection that display sensitivity to these physics schemes include updraft size and intensity, simulated radar reflectivity, timing and placement of storm initi- ation and decay, total storm rainfall, and other storm features derived from storm structure and hydrometeor fields, such as predicted lightning flash rates. In addition to the basic parameters listed above, the simulated storms may also exhibit sensitivity to im- posed initial conditions, such as the fields of soil temper- ature and moisture, vegetation cover and health, and sea and lake water surface temperatures. Some of these sensitivities may rival those of the basic physics sensi- tivities mentioned earlier. These sensitivities have the potential to disrupt the accuracy of short-term forecast simulations of convective storms, and thereby pose sig- nificant difficulties for weather forecasters. To make a systematic study of the quantitative impacts of each of these sensitivities, a matrix of simulations has been performed using all combinations of eight separate microphysics schemes, three boundary layer schemes, and two sets of initial conditions. The first version of initial conditions consists of the default data from large-scale operational model fields, while the second features specialized higher- resolution soil conditions, vegetation conditions and water surface temperatures derived from datasets created at NASA's Short-term Prediction and Operational Research Tran- sition (SPoRT) Center at the National Space Science and Technology Center (NSSTC) in Huntsville, AL. Simulations as outlined above, each 48 in number, were conducted for five midsummer weakly sheared coastal convective events each at two sites, Mobile, AL (MOB) and Houston, TX (HGX). Of special interest to operational forecasters at MOB and HGX were accuracy of timing and placement of convective storm initiation, reflectivity magnitudes and coverage, rainfall and inferred lightning threat.

McCaul, Eugene W., Jr.↗
NASA NTRS2014

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U. S. Deep South Summer Convection

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics parameterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRT Center to select NOAA/NWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boundary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage of lightning activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

McCaul, E. W., Jr.↗
DOE OSTI2021

Hybridizing Machine Learning and Physically-based Earth System Models to Improve Prediction of Multivariate Extreme Events (AI Exploration of Wildland Fire Prediction)

Focal Areas: This project responds to two focal areas identified in the DOE Call for AI4ESP White Papers: 1) Predictive modeling through the use of artificial intelligence (AI) techniques, and 2) insights gleaned from complex data using explainable AI and big data analytics. Science Challenge: Large wildland fires (hereafter wildfires) appearing as high-impact compound climate extreme events are closely related to hydroclimate and water cycle extremes that modulate surface fuel supply and combustibility. These compound events have multivariate climatic features (e.g., temperature, precipitation, relative humidity, wind, lightning) and societal drivers (e.g., forest management, land use change, human caused ignitions). Meanwhile, they induce strong feedbacks to the coupled atmosphere, biosphere, and hydrosphere by perturbing regional and global radiation budget as well as ecological, biogeochemical, and water cycles across multiple spatiotemporal scales. The nonlinear interactions between these natural and anthropogenic components of the Earth system are too complex to be completely and adequately represented in today’s Earth system models (ESMs). The inherent stochastic nature of fire activity at all scales further increases the difficulty of its prediction using ESMs that are usually developed from deterministic equations and parameterizations. Besides, concurrence of long-term (decadal to interdecadal) global climate change and fire regime shifts overlapping with short-term (intraseasonal to interannual) variations of regional fire weather and burning activity confound predictability of these compound extreme events. We propose to address the above scientific challenges by using machine learning (ML)-based data-driven modeling techniques to integrate observations and physically-based ESMs’ simulations in a computationally efficient hybrid prediction system. This prediction system is supposed to characterize the wildfire’s sensitivity to climate and exogenous drivers at high resolution (~ 0.25°) on subseasonal to seasonal (S2S) timescales providing improved predictability and explainability. We will use the system to help identify: (1) What are the computational elements of a hybrid system needed to predict compound climate extreme events such as global wildfires? (2) What are the key drivers (either natural or anthropogenic) that modulate short-term variations of multivariate fire weather and burning activity over different regions? How can one take advantage of those driver-response relationships to improve the predictability of large wildfires on S2S time scales? (3) What are the underlying physical mechanisms and sources of improved predictability? Which ML techniques are optimal in revealing and adapting these mechanisms?

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

TRMM Observations of Convective Regimes in the Amazon

This study utilizes TRMM satellite precipitation radar, lightning imaging sensor, and passive microwave imager data together with ground-based lightning data to investigate the vertical structure, lightning, and rainfall characteristics of Amazonian and central South American convection for three separate wet-seasons. These characteristics are partitioned as a function of 850 mb zonal wind direction, motivated by observations collected during the six-week TRMM-LBA field campaign. The TRMM-LBA field campaign observations suggest that systematic variations in Amazonian convective vertical structure, lightning, and rainfall are all linked to bimodal variations in the low-level zonal wind (e.g., easterly and westerly regimes). The more spatially and temporally comprehensive TRMM dataset used in this study extends the TRMM-LBA observations by examining regime variability in Amazonian and South American convective structure over a continental scale domain. On a continental-scale, patterns of east and west regime 850 mb winds combined with LIS lightning flash densities suggest the presence of synoptic-scale controls (e.g., intrusion of extratropical frontal systems and interaction with the SACZ) on regional-scale variability in convective vertical structure. TRMM PR, TMI and ground-based lightning data suggest that regional variability in wet-season convective structure is most evident over the southern Amazon, Mato Grosso, Altiplano, southern Brazil, and eastern coastal regions of central and southern South America. Convective vertical structure, rain fall rates, and lightning activity are all more pronounced during easterly (westerly) regimes over the southern Amazon and Mato Grosso (Altiplano, and southern Brazil). Importantly, when considered with case-study results from TRMM-LBA, the systematic differences in convective structure that occur as a function of regime suggest that associated regime-differences may exist in the vertical distribution of diabatic heating. Hence the discrimination of convective vertical structure "regimes" over parts of the Amazon and vicinity based on a resolved variable such as the 850 mb zonal wind direction, while far from being perfect, may have important applications to the problems of cumulus parameterization, rainfall estimation and retrievals of latent heating over the Amazon.

Petersen, W. A.↗