Engineering topics

Pickering, Kenneth

Publications and source records attributed to Pickering, Kenneth.

16 records

DOE OSTI2023

Machine-learning-based investigation of the variables affecting summertime lightning occurrence over the Southern Great Plains

Lightning is affected by many factors, many of which are not routinely measured, well understood, or accounted for in physical models. Several commonly used machine learning (ML) models have been applied to analyze the relationship between Atmospheric Radiation Measurement (ARM) data and lightning data from the Earth Networks Total Lightning Network (ENTLN) in order to identify important variables affecting lightning occurrence in the vicinity of the Southern Great Plains (SGP) ARM site during the summer months (June, July, August and September) of 2012 to 2020. Testing various ML models, we found that the random forest model is the best predictor among common classifiers. When convective clouds were detected, it predicts lightning occurrence with an accuracy of 76.9 % and an area under the curve (AUC) of 0.850. Using this model, we further ranked the variables in terms of their effectiveness in nowcasting lightning and identified geometric cloud thickness, rain rate and convective available potential energy (CAPE) as the most effective predictors. The contrast in meteorological variables between no-lightning and frequent-lightning periods was examined for hours with CAPE values conducive to thunderstorm formation. Besides the variables considered for the ML models, surface variables and mid-altitude variables (e.g., equivalent potential temperature and minimum equivalent potential temperature, respectively) have statistically significant contrasts between no-lightning and frequent-lightning hours. For example, the minimum equivalent potential temperature from 700 to 500 hPa is significantly lower during frequent-lightning hours compared with no-lightning hours. Finally, a notable positive relationship between the intracloud (IC) flash fraction and the square root of CAPE ($\sqrt{CAPE}$) was found, suggesting that stronger updrafts increase the height of the electrification zone, resulting in fewer flashes reaching the surface and consequently a greater IC flash fraction.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2019

A TROPOMI- and GLM-Based Estimate of NOx Production by Lightning over the U.S.

Lightning produces NO because the extreme temperatures (>20000 K) in lightning channels dissociate molecular O2 and molecular N2, which then combine to form NOx which quickly reacts with O3 to form NO2. Lightning is responsible for 10-15% of NOx emissions globally. This is 2 – 8 Tg N a-1 [Schumann and Huntrieser, 2007] or 100 to 400 mol per flash. Much of the uncertainty stems from limited knowledge of lightning NOx production per flash (LNOx PE) or per unit flash length. Most LNOx is injected into mid- and upper-troposphere where away from deep convection its lifetime is longer relative to lower troposphere NOx. NOx in this region enhances the concentrations of upper tropospheric NOy, OH, and O3 and contributes to positive radiative forcing by O3 and negative forcing by CH4. We have previously used OMI NO2 to obtain estimates of LNOx production per flash over the Gulf of Mexico (Pickering et al., 2016, JGR), in convective events during NASA’s TC4 field program (Bucsela et al., 2010, JGR), and over broad regions of the tropics (Allen et al., 2019, JGR) and midlatitudes (Bucsela et al., 2019, JGR). In the latter studies, we obtained PE values of 170 ± 100 mol flash and 180 ± 100 mol flash, respectively.

Allen, Dale↗

NASA NTRS2015

A WRF-Chem Analysis of Flash Rates, Lightning-NOx Production and Subsequent Trace Gas Chemistry 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). This is a continuation of previous work, which compared lightning observations (Oklahoma Lightning Mapping Array and National Lightning Detection Network) with flashes generated by various flash rate parameterization schemes (FRPSs) from the literature in a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the 29-30 May 2012 Oklahoma thunderstorm. Based on the Oklahoma radar observations and Lightning Mapping Array data, new FRPSs are being generated and incorporated into the model. The focus of this analysis is on estimating the amount of lightning-generated nitrogen oxides (LNOx) produced per flash in this storm through a series of model simulations using different production per flash assumptions and comparisons with DC3 aircraft anvil observations. The result of this analysis will be compared with previously studied mid-latitude storms. Additional model simulations are conducted to investigate the upper troposphere transport, distribution, and chemistry of the LNOx plume during the 24 hours following the convective event to investigate ozone production. These model-simulated mixing ratios are compared against the aircraft observations made on 30 May over the southern Appalachians.

Cummings, Kristin A.↗

NASA NTRS2014

Satellite Data of Atmospheric Pollution for U.S. Air Quality Applications: Examples of Applications, Summary of Data End-User Resources, Answers to FAQs, and Common Mistakes to Avoid

Satellite data of atmospheric pollutants are becoming more widely used in the decision-making and environmental management activities of public, private sector and non-profit organizations. They are employed for estimating emissions, tracking pollutant plumes, supporting air quality forecasting activities, providing evidence for "exceptional event" declarations, monitoring regional long-term trends, and evaluating air quality model output. However, many air quality managers are not taking full advantage of the data for these applications nor has the full potential of satellite data for air quality applications been realized. A key barrier is the inherent difficulties associated with accessing, processing, and properly interpreting observational data. A degree of technical skill is required on the part of the data end-user, which is often problematic for air quality agencies with limited resources. Therefore, we 1) review the primary uses of satellite data for air quality applications, 2) provide some background information on satellite capabilities for measuring pollutants, 3) discuss the many resources available to the end-user for accessing, processing, and visualizing the data, and 4) provide answers to common questions in plain language.

Duncan, Bryan↗

NASA NTRS2011

DISCOVER-AQ: An Overview and Initial Comparisons of NO2 with OMI Observations

The first deployment of the Earth Venture -1 DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) project was conducted during July 2011 in the Baltimore-Washington region. Two aircraft (a P-3B for in-situ sampling and a King Air for remote sensing) were used along with an extensive array of surface-based in-situ and remote sensing instrumentation. Fourteen flight days were accomplished by both aircraft and over 250 profiles of trace gases and aerosols were performed by the P-3B over surface air quality monitoring stations, which were specially outfitted with sunphotometers and Pandora UV/Vis spectrometers. The King Air flew with the High Spectral Resolution Lidar for aerosols and the ACAM UV/Vis spectrometer for trace gases. This suite of observations allows linkage of surface air quality with the vertical distributions of gases and aerosols, with remotely-sensed column amounts observed from the surface and from the King Air, and with satellite observations from Aura (OMI and TES), GOME-2, MODIS and GOES. The DISCOVER-AQ data will allow determination of under what conditions satellite retrievals are indicative of surface air quality, and they will be useful in planning new satellites. In addition to an overview of the project, a preliminary comparison of tropospheric column NO2 densities from the integration of in-situ P-3B observations, from the Pandoras and ACAM, and from the new Goddard OMI NO2 algorithm will be presented.

Pickering, Kenneth↗

NASA NTRS2011

Tropospheric Ozone Profiling Using Simulated GEO-CAPE Measurement

Multi-spectral retrievals (UV+VIS, UV+TIR, UV+VIS+TIR) improve sensitivity to the variability in near-surface O3 by a factor of 2 - 2.7 over those from UV or TIR alone. Multi-spectral retrievals provide the largest benefit when there is enhanced O3 near the surface. Combining all 3 wavelengths (UV+VIS+TIR) provides the greatest sensitivity below 850 hPa, with a 36% improvement over UV+VIS and a 17% improvement over UV+TIR. The impacts of clouds and aerosols are being assessed.

human versus natural sources↗

NASA NTRS2011

Impact of Lightning-NO Emissions on Summertime U.S. Photochemistry as Determined Using the CMAQ Model with NLDN-Constrained Flash Rates

Lightning-NO emissions are responsible for 15-30 ppbv enhancements in upper tropospheric ozone over the eastern United States during the summer time. Enhancements vary from year to year but were particularly large during the summer of 2006, a period during which meteorological conditions were particularly conducive to ozone formation. A lightning-NO parameterization has been developed that can be used with the CMAQ model. Lightning-NO emissions in this scheme are assumed to be proportional to convective precipitation rate and scaled so that monthly average flash rates in each grid box match National Lightning Detection Network (NLDN) observed flash rates after adjusting for climatological intracloud to cloud-to-ground (IC/CG) ratios. The contribution of lightning-NO emissions to eastern United States NOx and ozone distributions during the summer of 2006 will be evaluated by comparing results of 12- km CMAQ simulations with and without lightning-NO emissions to measurements from the IONS field campaign and to satellite retrievals from the Tropospheric Emission Spectrometer (TES) and the Ozone Monitoring Instrument (OMI) aboard the Aura satellite. Special attention will be paid to the impact of the assumed vertical distribution of emissions on upper tropospheric NOx and ozone amounts.

Allen, Dale↗

NASA NTRS2010

Applications of OMI Tropospheric NO(Sub 2) Data: Air Quality Trends in the US and Lightning NO(x) Source Strength

This talk will be presented in two parts: 1) an analysis of tropospheric column NO2 trends in the eastern half of the United States over the period 2005 to 2009 and 2) estimation of lightning NO(x) production rates based on OMI observations and lightning flash rate data. The air quality trends in the eastern US will be determined for specific subregions using tropospheric column NO2 data from OMI for 2005 through 2008 and from GOME-2 for 2007 through 2009. This period is characterized by significant NO(x) emission reductions at power plants within most of this region. The air quality trends will be compared with those estimated from continuous emission monitoring data from the power plants compiled by the US Environmental Protection Agency. OMI NO2 data have also been used to estimate lightning NOx production per flash in selected storms near Costa Rica and Panama during the 2007 NASA TC4 field campaign and over the continental US, Gulf of Mexico, and western Atlantic during the summers of 2005 and 2006. The lightning signal is extracted from the OMI data through a custom retrieval in which an NO2 profile representative of convective outflow is used in the airmass factor calculation and the background NO2 column is subtracted from the tropospheric column. When combined with NO(x)/NO2 ratios from the NASA GMT model and observed flash rates, the resulting estimates of NO(x) production per flash are comparable to those estimated obtained from analyses of aircraft data and cloud-resolving modeling.

Pickering, Kenneth↗

NASA NTRS2009

Satellite Observations for Detecting and Tracking Changes in Atmospheric Composition

The satellite observations provide constraints on detailed atmospheric modeling, including emissions inventories, indications of transport, harmonized data over vast areas suitable for trends analysis, and a link between spatial scales ranging from local to global, and temporal scales from diurnal to interannual. 1 The National Oceanic and Atmospheric Administration's (NOAA) long-term commitments help provide these observations in cooperation with international meteorological organizations. NASA s long-term commitments will advance scientifically important observations as part of its Earth Science Program, and will assist the transition of the science measurements to applied analyses through the Applied Science Program. Both NASA and NOAA have begun to provide near realtime data and tools to visualize and analyze satellite data,2 while maintaining data quality, validation, and standards. Consequently, decision-makers can expect satellite data services to support air quality decision making now and in the future. The international scientific community's Integrated Global Atmosphere Chemistry Observation System Report3 outlined a plan for ground-based, airborne and satellite measurements and models to integrate the observations into a four-dimensional representation of the atmosphere (space and time) to support assessment and policy information needs. This plan is being carried out under the Global Earth Observation System of Systems (GEOSS). Demonstrations of such an integrated capability4 provide new understanding of the changing atmosphere and link policy decisions to benefits for society. In this article, we highlight the use of satellite data to constrain biomass burning emissions, to assess oxides of nitrogen (NO(x)) emission reductions, and to contribute to state implementation plans, as examples of the use of satellite observations for detecting and tracking changes in atmospheric composition.

Neil, Doreen O.↗

NASA NTRS2009

Production of Lightning NO(x) and its Vertical Distribution Calculated from 3-D Cloud-scale Chemical Transport Model Simulations

A 3-D cloud scale chemical transport model that includes a parameterized source of lightning NO(x), based on observed flash rates has been used to simulate six midlatitude and subtropical thunderstorms observed during four field projects. Production per intracloud (P(sub IC) and cloud-to-ground (P(sub CG)) flash is estimated by assuming various values of P(sub IC) and P(sub CG) for each storm and determining which production scenario yields NO(x) mixing ratios that compare most favorably with in-cloud aircraft observations. We obtain a mean P(sub CG) value of 500 moles NO (7 kg N) per flash. The results of this analysis also suggest that on average, P(sub IC) may be nearly equal to P(sub CG), which is contrary to the common assumption that intracloud flashes are significantly less productive of NO than are cloud-to-ground flashes. This study also presents vertical profiles of the mass of lightning NO(x), after convection based on 3-D cloud-scale model simulations. The results suggest that following convection, a large percentage of lightning NO(x), remains in the middle and upper troposphere where it originated, while only a small percentage is found near the surface. The results of this work differ from profiles calculated from 2-D cloud-scale model simulations with a simpler lightning parameterization that were peaked near the surface and in the upper troposphere (referred to as a "C-shaped" profile). The new model results (a backward C-shaped profile) suggest that chemical transport models that assume a C-shaped vertical profile of lightning NO(x) mass may place too much mass neat the surface and too little in the middle troposphere.

Ott, Lesley↗

NASA NTRS2008

Cloud-Resolved Simulations of Lightning NOx in an Observed Hector Thunderstorm

Cloud chemistry simulations are being performed for a "Hector" storm observed on 16 November 2005 during the SCOUT-03lACTIVE campaigns based in Darwin, Australia. The primary objective of these simulations is to estimate the average production of NO per lightning flash during the storm. The 3-D WRF-AqChem model is being used for these calculations. This modeling package contains the WRF nonhydrostatic cloud-resolving model, online gas- and aqueous-phase chemistry, and a lightning algorithm (Barth et al., 2007). Early morning soundings of temperature, water vapor and winds are used to initialize the model. Surface heating of the Tiwi Islands is simulated in the model to induce convection. Observations from the Egrett, Falcon, Geophysica, and Dornier aircraft in air undisturbed by the storm are used to construct composite initial condition chemical profiles. Convective transport in the model is tested using tracer species such as CO and O3. Lightning flashes observed by the LINET network are input to the model and a lightning placement scheme is used to inject the resulting NO into the simulated cloud. Various scenarios of NO production per flash are used for cloud-to-ground and intracloud flashes in a series of simulations for the storm. Resulting NO, mixing ratios from each simulation are compared with upper tropospheric anvil observations (from the Geophysica and Egrett aircraft) to determine the best fit with the mean NOx at anvil altitudes, the profile shape, and the frequency distribution of NOx values. We will compare the results for lightning NO production from this tropical thunderstorm with similar analyses conducted for several midlatitude and subtropical convective events.

Pickering, Kenneth↗

NASA NTRS2007

OMI Tropospheric NO2 from Lightning in Observed Convective Events

Lightning is responsible for an estimated 15 percent of total NO emissions, and is one of the most prominent sources in the upper troposphere. In this study, we present evidence of lightning-generated NO2 (LNO2) using data from the Ozone Monitoring Instrument (OMI), which has observed tropospheric NO2 since its launch in 2004. Although LNO2 has been also reported in previous satellite studies from the Global Ozone Monitoring Experiment (GOME) and SCIAMACHY, OMI is better suited for such measurements by virtue of its higher spatial resolution and daily global coverage. We will present data clearly showing the LNO2 signal in the OMI tropospheric NO2 product on two days over and downwind of specific convective systems in the US Midwest. Gridded monthly mean tropospheric NO 2 data are subtracted from the daily gridded data to obtain the presumed LNO2 signal. Observed cloud-to-ground (CG) lightning flashes from the National Lightning Detection Network (NLDN) were counted along middle and upper tropospheric back trajectories that were run from the regions containing the LNO2 signal. A vertically-weighted average number of upwind CG flashes was obtained using a profile of LNO(x) mass obtained from a series of midlatitude cloud-resolved storm chemistry simulations. The number of CG flashes was scaled up to total flashes (intracloud (IC) flashes plus CG) using a climatological IC/CG ratio. The number of moles of LNO(x) in the region considered was estimated by assuming that LNO2 is 30 percent of LNO(x). This value was divided by the number of upwind flashes to obtain an average estimate of the number of moles produced per flash. Results yield values in the range obtained through other estimation techniques (e.g., aircraft measurements, models). We will also present a similar analysis over northern Australia during the SCOUT-O3/ACTIVE field campaigns in November and December 2005, in which we will compare the OMI LNOx signals with aircraft observations from the storm anvils.

Pickering, Kenneth↗

NASA NTRS2007

OMI Tropospheric NO2 from Lightning in Observed Convective Events

Lightning is responsible for an estimated 10-20% of NO(x) emissions in the troposphere. In this study, we present evidence of lightning-generated NO2 (LNO2) using data from the Ozone Monitoring Instrument (OMI), which has observed tropospheric NO2 since its launch in 2004. Although LNO2 has been also reported in previous satellite studies from the Global Ozone Monitoring Experiment (GOME) and SCIAMACHY, OMI is better suited for such measurements by virtue of its higher resolution and daily global coverage. The LNO2 signal is clearly seen in OMI data on two days over and downwind of convective systems in the US Midwest in 2006. We also present an analysis of OMI data over northern Australia during the SCOUT-O3/ACTIVE field campaigns in November and December 2005. Both single- and multi-day averages are presented to examine possible LNO2 signals from individual diurnally recurrent convective events. In these events we compare the OMI signals with aircraft observations from the storm anvils.

Pickering, Kenneth↗

NASA NTRS2007

The Role of Convection in Redistributing Formaldehyde to the Upper Troposphere Over North America and the North Atlantic during the Summer 2004 INTEX Campaign

Measurements of CH2O from a tunable diode laser absorption spectrometer (TDLAS) were acquired onboard the NASA DC-8 during the summer 2004 INTEX-NA (Intercontinental Chemical Transport Experiment - North America) campaign to test our understanding of convection and production mechanisms in the upper troposphere (UT, 6-12-km) over continental North America and the North Atlantic Ocean. Point-by-point comparisons with box model calculations, when MHP (CH3OOH) measurements were available for model constraint, resulted in a median CH2O measurement/model ratio of 0.91 in the UT. Multiple tracers were used to arrive at a set of UT CH2O background and perturbed air mass periods, and 46% of the TDLAS measurements fell within the latter category. At least 66% to 73% of these elevated UT observations were caused by enhanced production from CH2O precursors rather than direct transport of CH2O from the boundary layer. This distinction is important, since the effects from the former can last for over a week or more compared to one day or less in the case of convective transport of CH2O itself. In general, production of CH2O from CH4 was found to be the dominant source term, even in perturbed air masses. This was followed by production from MHP, methanol, PAN type compounds, and ketones, in descending order of their contribution. In the presence of elevated NO from lightning and potentially from the stratosphere, there was a definite trend in the CH2O discrepancy, which for the highest NO mixing ratios produced a median CH2O measurement/model ratio of 3.9 in the 10-12-km range. Discrepancies in CH2O and HO2 in the UT with NO were highly correlated and this provided further information as to the possible mechanism(s) responsible. These discrepancies with NO are consistent with additional production sources of both gases involving CH3O2 + NO reactions, most likely caused by unmeasured hydrocarbons.

Fried, Alan↗

NASA NTRS1999

A Three-Dimensional Total Odd Nitrogen (NO(y)) Simulation During SONEX using a Stretched-Grid Chemical Transport Model

The relative importance of various odd nitrogen (NOy) sources including lightning, aircraft, and surface emissions on upper tropospheric total odd nitrogen is illustrated as a first application of the three-dimensional Stretched-Grid University of Maryland/Goddard Chemical-Transport Model (SG-GCTM). The SG-GCTM has been developed to look at the effect of localized sources and/or small scale mixing processes on the large-scale or global chemical balance. For this simulation, the stretched-arid was chosen so that its maximum resolution is located over eastern North America and the North Atlantic; a region that includes most of the SONEX (the SASS (Subsonic Assessment) Ozone and Nitrogen Oxides Experiment) flight paths. The SONEX period (October-November 1997) is simulated by driving the SG-GCTM with assimilated data from the GEOS-STRAT DAS (Goddard Earth Observing System-STRAT Data Assimilation System). A new algorithm is used to parameterize the lightning, flash rates that are needed to calculate emissions of NOy by lightning. Model-calculated upper tropospheric NOy and NOy measurements from the NASA DC-8 aircraft are compared. Spatial variations in NOy were well captured especially with the stretched-grid run; however, model-calculated concentrations were often too high in the upper troposphere, particularly during the first several flights. The lightning algorithm does a reasonably good job; however, the use of emissions from observed lightning, flashes significantly improves the simulation on a few occasions, especially November 3, 1997, indicating that significant uncertainty remains in parameterizing lightning in CTMS. Aircraft emissions play a relatively minor role (about 12%) in the upper tropospheric NOY budget averaged along SONEX flight paths; however, the contribution of such emmissions is as large as about 30% during portions of some flights.

Allen, Dale↗

NASA NTRS1993

Chemistry on the mesoscale: Modeling and measurement issues

The topics covered include the following: Regional Acid Deposition Model (RADM) -- a coupled chemistry/mesoscale model; convection in RADM; unresolved issues for mesoscale modeling with chemistry -- nonprecipitating clouds; unresolved issues for mesoscale modeling with chemistry -- aerosols; tracer studies with Goddard Cumulus Ensemble Model (GCEM); field observations of trace gas transport in convection; and photochemical consequences of convection.

Thompson, Anne↗