Abstract Lightning has important effects on atmospheric constituents in primarily the middle and upper troposphere. We summarize the effects of lightning on atmospheric chemistry that have been published since the last major review in 2007. The estimates of NO x production by lightning (LNO x ) are based on five methods: theoretical/laboratory estimates applied to flash observations; aircraft measurements in storm anvils; cloud resolved modeling constrained by observations; satellite retrievals of NO 2 columns; and global and regional models constrained by aircraft or satellite data. The resulting best estimate of global LNO x production is 5 ± 2 Tg N yr −1 , which represents a small narrowing of the range from previous estimates. Model (observational) estimates are on average at the upper (lower) ends of this range. LNO x production efficiency (PE) corresponding to this range is 150–350 mol fl −1 . An inverse relationship between flash rate and LNO x PE has been ascertained from satellite and aircraft measurements. Direct O 3 and HO x production in corona discharges and HO x from subvisible flashes may be sufficiently large to warrant inclusion in models. LNO x leads to photochemical O 3 production in the upper troposphere at rates of 5–10 ppbv d −1 and contributes 1–2 ppbv to maximum 8‐hr surface O 3 (greater amounts not uncommon over higher terrain). CH 4 lifetime decreases by ∼5% per Tg N yr −1 increase of LNO x . Globally, no significant long‐term trends in lightning flash rate have been observed, but regional trends have been detected. Future flash rate trends and LNO x emissions remain uncertain.

Tropospheric ozone results from in situ chemical formation and stratosphere-troposphere exchange (STE), with the latter being more important in the middle and upper troposphere than in the lower troposphere. Ozone photochemical formation is nonlinear and results from the oxidation of methane and non-methane hydrocarbons (NMHCs) in the presence of nitrogen oxide (NOx=NO+NO2). Previous studies showed that O3 short- and long-term trends are nonlinearly controlled by near-surface anthropogenic emissions of carbon monoxide (CO), volatile organic compounds (VOCs), and nitrogen oxides, which may also be impacted by the long-range transport (LRT) of O3 and its precursors. In addition, several studies have demonstrated the important role of STE in enhancing ozone levels, especially in the midlatitudes. In this article, we investigate tropospheric ozone spatial variability and trends from 2005 to 2019 and relate those to ozone precursors on global and regional scales. We also investigate the spatiotemporal characteristics of the ozone formation regime in relation to ozone chemical sources and sinks. Our analysis is based on remote sensing products of the tropospheric column of ozone (TrC-O3) and its precursors, nitrogen dioxide (TrC-NO2), formaldehyde (TrC-HCHO), and total column CO (TC-CO), as well as ozonesonde data and model simulations. Our results indicate a complex relationship between tropospheric ozone column levels, surface ozone levels, and ozone precursors. While the increasing trends of near-surface ozone concentrations can largely be explained by variations in VOC and NOx concentration under different regimes, TrC-O3 may also be affected by other variables such as tropopause height and STE as well as LRT. Decreasing or increasing trends in TrC-NO2 have varying effects on TrC-O3, which is related to the different local chemistry in each region. We also shed light on the contribution of NOx lightning and soil NO and nitrous acid (HONO) emissions to trends of tropospheric ozone on regional and global scales.

A cloud‐resolved storm and chemistry simulation of a severe convective system in Oklahoma constrained by anvil aircraft observations of NOx was used to estimate the mean production of NOx per flash in this storm. An upward ice flux scheme was used to parameterize flash rates in the model. Model lightning was also constrained by observed lightning flash types and the altitude distribution of flash channel segments. The best estimate of mean NOx production by lightning in this storm was 80–110 mol per flash, which is smaller than many other literature estimates. This result is likely due to the storm having been a high flash rate event in which flash extents were relatively small. Over the evolution of this storm a moderate negative correlation was found between the total flash rate and flash extent and energy per flash. A longer‐term simulation at 36‐km horizontal resolution with parameterized convection was used to simulate the downwind transport and chemistry of the anvil outflow from the same storm. Convective transport of low‐ozone air from the boundary layer decreased ozone in the anvil outflow by up to 20–40 ppbv compared with the initial conditions, which contained stratospheric influence. Photochemical ozone production in the lightning‐NOx enhanced convective plume proceeded at a rate of 10–11 ppbv per day in the 9–11 km outflow layer over the 24‐hr period of downwind transport to the Southern Appalachians. Photochemical production plays a large role in the restoration of upper tropospheric ozone following deep convection.

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 (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.

Nitrogen oxides produced by lightning (LNO x ) play an important role in determining mid‐ and upper‐tropospheric concentrations of the hydroxyl radical (OH), methane (CH 4 ), and ozone (O 3 ). The moles of NO x produced per flash was examined using nitrogen dioxide (NO 2 ) columns and cloud properties from the Tropospheric Monitoring Instrument (TROPOMI) and flash counts from the Geostationary Lightning Mapper (GLM) aboard the Geostationary Operational Environmental Satellite‐16 (GOES‐16) and Earth Networks Total Lightning Network (ENTLN) for 29 convective systems over the United States that occurred during 2018 and 2019. For each of the case studies, the LNO x production efficiency (PE) was estimated using TROPOMI pixels over deep convection. First, the NO x columns associated with the TROPOMI NO 2 columns were estimated using a specially derived air mass factor (AMF). The tropospheric column due to recent lightning was then determined by subtracting from the median NO x column a background representative of the NO x column due to sources other than recent lightning. Then, the PE was calculated by multiplying the LNO x column by the storm area and dividing by the number of flashes contributing to the column. For a three‐hour chemical lifetime, the mean PE was found to be 175 ± 100 mol per flash for optical flashes from GLM and 120 ± 65 mol per flash for radio‐wave‐detected flashes from ENTLN. The uncertainty associated with these values is mostly due to uncertainties in tropospheric background, AMF, and detection efficiency. GLM PE for individual systems was found to be positively correlated with optical energy.

Lightning discharges are one of the main sources of atmospheric NOx, contributing about 10% of NOx emissions globally and playing an important role for the concentration of ozone and other chemical species in the upper troposphere. Lightning produces between 2-8 Tg N per year globally (100-400 mol NOx per flash). Reducing the uncertainty of the NOx production by lightning and understanding the factors that influence this production is still a challenge. The TROPOspheric Monitoring Instrument (TROPOMI) is orbiting the Earth from a near-polar, sun-synchronous orbit since October 2017. TROPOMI is equipped with four spectrometers that provide information about the chemical composition of the troposphere with unprecedented horizontal spatial resolutions of 3.5 x 7 km before 6 August 2019 and 3.5 x 5.5 km after that date. In this work, we combine the DLR-NO2 research product, the DLR cloud operational product and the TROPOMI v2.1_test NO2 product to estimate the production of NOx per flash (LNOx). The v2.1_test NO2 product contains more useful data pixels than the official offline v1.x data product, because of better treatment of saturation of the TROPOMI measurements (which occurs frequently over high bright clouds that are often linked with LNOx) and the use of an improved version of the FRESCO cloud algorithm. We for the first time ever use these chemical measurements from TROPOMI combined with lightning radio measurements provided by the EUropean Cooperation for LIghtning Detection (EUCLID) and the Earth Network Total Lightning Network (ENTLN), together with lightning optical measurements provided by the space-based Lightning Imaging Sensor (LIS) to estimate the Detection Effiency (DE) of EUCLID and ENTLN. In addition, we use the ECHAM5/MESSy Atmospheric Chemistry (EMAC) simulations to calculate the air mass factor employed to convert tropospheric slant column of measured NO2 to vertical column LNOx and the winds provided by reanalysis data to eliminate the influence of upwind storms in the estimation of the background NOx. Concentration. We focus our analysis on different remote regions, where the background concentration of NO is relatively low. In particular, we focus our analysis on 11 thunderstorm cases taking place near the Pyrenees, where intense thunderstorms are frequent and the DE of EUCLID and ENTLN is relatively high and homogeneous. According to our preliminary results from a single case using the DLR-NO2 research product, we get about 400 mol NOx per flash when we estimate the background using NOx from CARIBIC flights and about 200-600 mol per flash when we estimate the background using TROPOMI measurements from non-flashing pixels.

Lightning, one of the major sources of nitrogen oxides (NOx) in the atmosphere, contributes to the tropospheric concentration of ozone and to the oxidizing capacity of the atmosphere. Lightning produces between 2 and 8 Tg N yr−1 globally and on average about 250 ± 150 mol NOx per flash. In this work, we estimate the moles of NOx produced per flash (LNOx production efficiency) in the Pyrenees (Spain, France and Andorra) and in the Ebro Valley (Spain) by using nitrogen dioxide (NO2) and cloud properties from the TROPOspheric Monitoring Instrument (TROPOMI) as well as lightning data from the Earth Networks Global Lightning Network (ENGLN) and from the EUropean Co-operation for LIghtning Detection (EUCLID). The Pyrenees are one of the areas in Europe with the highest lightning frequencies, which, along with their remoteness as well as their very low NOx background, enables us to better distinguish the LNOx signal produced by recent lightning in TROPOMI NO2 measurements. We compare the LNOx production efficiency estimates for eight convective systems in 2018 using two different sets of TROPOMI research products provided by the Royal Netherlands Meteorological Institute (KNMI) and the Deutsches Zentrum für Luft- und Raumfahrt (DLR). According to our results, the mean LNOx production efficiency in the Pyrenees and in the Ebro Valley, using a 3 h chemical lifetime, ranges between 14 and 103 mol NOx per flash from the eight systems. The mean LNOx production efficiency estimates obtained using both TROPOMI products and ENGLN lightning data differ by ∼ 23 %, while they differ by ∼ 35 % when using EUCLID lightning data. The main sources of uncertainty when using ENGLN lightning data are the estimation of background NOx that is not produced by lightning and the time window before the TROPOMI overpass that is used to count the total number of lightning flashes contributing to freshly produced LNOx. The main source of uncertainty when using EUCLID lightning data is the uncertainty in the detection efficiency of EUCLID.

A primary goal of the Geostationary Operational Environmental Satellite R‐series Post Launch Test (GOES‐R PLT) Field Campaign during spring 2017 was the performance evaluation of the Geostationary Lightning Mapper (GLM) aboard the GOES‐16 satellite. The NASA Goddard Geo‐CAPE Airborne Simulator (GCAS), an ultra‐violet visible spectrometer, piggybacked on the aircraft mission to allow continuous hyper‐spectral measurements at high spectral and spatial resolutions simultaneously with optical lightning detection by the Fly’s Eye GLM Simulator while overflying convective systems. NO 2 columns retrieved from GCAS were used to estimate the moles of NO x produced per flash, referred to as lightning NO x production efficiency (LNO x PE) for convective systems over the United States and western Atlantic. The mean PE was determined to be 360 ± 180 mol per flash for optically detected GLM flashes and 230 ± 115 mol per flash for radio‐wave detected Earth Networks Total Lightning Network flashes. These values span the commonly cited range of 100–500 mol per flash for midlatitude flashes. LNO x PE was found to be positively correlated with GLM flash multiplicity and flash optical energy but negatively correlated with flash density. The positive correlations provide encouragement for PE parameterizations in terms of flash energy or multiplicity. Observations during the GOES‐R PLT field campaign provide a preview of the analysis that will be possible when continuous lightning detection is coupled with hourly NO 2 columns from a geostationary instrument such as Tropospheric Emissions: Monitoring of Pollution.

Nitric oxide (NO) is produced in lightning channels and quickly comes into equilibrium with nitrogen dioxide (NO2) in the atmosphere. The production of NOx (NO + NO2) leads to subsequent increases in the concentrations of ozone (O3) and the hydroxyl radical (OH) and decreases in the concentration of methane (CH4), thus impacting the climate system. Global production of NOx from lightning is uncertain by a factor of four. NOx production by lightning will be examined using NO2 columns from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Copernicus Sentinel-5 Precursor Satellite with an overpass time of approximately 1330 LT and flash rates from the Geostationary Lightning Mapper (GLM) on board the NOAA GOES-16 (75.2° W) and GOES-17 (137.2° W) satellites. Where there is overlap in coverage of the two GLM instruments, the greater of the two flash counts is used. Two approaches have been undertaken for this analysis: a series of case studies of storm systems over the United States, and a gridded analysis over the entire contiguous United States, Central America, northern South America, and surrounding oceans. A modified Copernicus Sentinel 5P TROPOMI NO2 data set is used here for the case-study analysis to improve data coverage over deep convective clouds. In both approaches, only TROPOMI pixels with cloud fraction > 0.95 and cloud pressure < 500 hPa are used. The stratospheric column is removed from the total slant column, and the result is divided by air mass factors appropriate for deep convective clouds containing lightning NOx (LNOx). Case studies have been selected from deep convective systems over and near the United States during the warm seasons of 2018 and 2019. For each of these systems, NOx production per flash is determined by multiplying a TROPOMI-based estimate of the mean tropospheric column of LNOx over each system by the storm area and then dividing by a GLM-based estimate of the flashes that contribute to the column. In the large temporal and spatial scale analysis, the TROPOMI data are aggregated on a 0.5 x 0.5 degree grid and converted to moles LNOx*. GLM flash counts during the one-hour period before TROPOMI overpass are similarly binned. A tropospheric background of LNOx* is estimated from grid cells without lightning and subtracted from LNOx* in cells with lightning to yield an estimate of freshly produced lightning NOx, designated LNOx. Results of the two approaches are compared and discussed with respect to previous LNOx per flash estimates.

Using the Community Multiscale Air Quality (CMAQ) model and the Benefits Mapping and Analysis Program - Community Edition (BenMAP-CE) tool, we estimate the benefits of anthropogenic emission reductions between 2002 and 2011 in the Eastern United States (US) with respect to surface ozone concentrations and ozone-related health and economic impacts, during a month of extreme heat, July 2011. Based on CMAQ simulations using emissions appropriate for 2002 and 2011, we estimate that emission reductions since 2002 likely prevented 10- 15 ozone exceedance days (using the 2011 maximum 8-hr average ozone standard of 75 ppbv) throughout the Ohio River Valley and 5- 10 ozone exceedance days throughout the Washington, DC - Baltimore, MD metropolitan area during this extremely hot month. CMAQ results were fed into the BenMAP-CE tool to determine the health and health-related economic benefits of anthropogenic emission reductions between 2002 and 2011. We estimate that the concomitant health benefits from the ozone reductions were significant for this anomalous month: 160-800 mortalities (95% confidence interval (CI): 70-1,010) were avoided in July 2011 in the Eastern U.S, saving an estimated $1.3-$6.6 billion (CI: $174 million-$15.5 billion). Additionally, we estimate that emission reductions resulted in 950 (CI: 90-2,350) less hospital admissions from respiratory symptoms, 370 (CI: 180-580) less hospital admissions for pneumonia, 570 (CI: 0-1650) less Emergency Room (ER) visits from asthma symptoms, 922,020 (CI: 469,960-1,370,050) less minor restricted activity days (MRADs), and 430,240 (CI: -280,350-963,190) less symptoms of asthma exacerbation during July 2011.Implications: We estimate the benefits of air pollution emission reductions on surface ozone concentrations and ozone-related impacts on human health and the economy between 2002 and 2011 during an extremely hot month, July 2011, in the eastern United States (US) using the CMAQ and BenMAP-CE models. Results suggest that, during July 2011, emission reductions prevented 10-15 ozone exceedance days in the Ohio River Valley and 5-10 ozone exceedance days in the Mid Atlantic; saved 160-800 lives in the Eastern US, saving $1.3 - $6.5 billion; and resulted in 950 less hospital admissions for respiratory symptoms, 370 less hospital admissions for pneumonia, 570 less Emergency Room visits for asthma symptoms, 922,020 less minor restricted activity days, and 430,240 less symptoms of asthma exacerbation.

NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011–2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea–United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori profiles) but mostly to OMI's large footprint (>312 km2).

We describe the resources used, the deployment strategy, and the outcomes of the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ) experiment, which took place in the summer of 2014 in the Front Range of Colorado. We provide a history of air quality of the region and the outcomes of previously conducted experiments, describe the atmospheric conditions encountered during the campaign, and summarize the scientific findings that the campaign produced, together with the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER‐AQ) intensive, simultaneously carried out by the National Aeronautics and Space Administration. The goal of FRAPPÉ was to measure emission tracers and photochemical tracers from the ground and by aircraft to be able to quantify the contributions of various emission sectors to the photochemical production of ozone in the Colorado Front Range. We found major contributions from the fossil fuel extraction sector as well as the transportation sector, with minor contributions from agriculture, energy generation, and industry. The meteorological conditions were also found to be critical in creating situations conducive to high ozone in the area.

Nitrogen oxide (NOx) production by lightning in the tropics is estimated using tropospheric NOx amounts (LNOx*) over deep convective grid boxes derived from Ozone Monitoring Instrument (OMI) nitrogen dioxide (NO2) slant columns and detection-efficiency-adjusted World Wide Lightning Location Network (WWLLN) flashes. The lightning NOx production efficiency (LNOx PE) in the tropics is determined for the austral and boreal summers of 2007 to 2011 by regressing regional mean daily values of LNOx* for individual seasons against daily flash totals during flash windows prior to the OMI overpass. LNOx PE is determined to be approximately two times larger over marine locations than over continental locations possibly because marine flashes are more energetic. Overall, the mean LNOx PE for the tropics is calculated to be 170 +/- 100 mol per flash with values over the tropical Pacific (low flash rate region) being largest. The main contributors to uncertainties in PE are uncertainties in WWLLN flash detection efficiency, upper tropospheric NOx lifetime in the near field of convection, and air mass factor biases.

Lightning flash rate parameterizations based on polarimetric and multi-Doppler radar inferred microphysical (e.g., graupel volume, graupel mass, 35 dBZ volume) and kinematic (e.g., updraft volume, maximum updraft velocity) parameters have important applications in atmospheric science. Although past studies have established relations between flash rate and storm parameters, their expected performance in a variety of storm and flash rate conditions is uncertain due to sample limitations. Radar network and lightning mapping array observations over Alabama of a large and diverse sample of 33 storms are input to hydrometeor identification, vertical velocity retrieval and flash rate algorithms to develop and test flash rate relations. When applied to this sample, prior flash rate linear relations result in larger errors overall, including often much larger bias (both over- and under-estimation) and root mean square errors compared to the new linear relations. At low flash rates, the new flash rate relations based on kinematic parameters have larger errors compared to those based on microphysical ones. Sensitivity of error to the functional form (e.g., zero or non-zero intercept) is also tested. When considering all factors (e.g., low errors including at low flash rate, consistency with past linear relations, and insensitivity to functional form), the flash rate parameterization based on graupel volume has the best overall performance.

Oxides of nitrogen are critical trace gases in the troposphere and are precursors for nitrate aerosol and ozone, which is an important pollutant and greenhouse gas. Lightning is the major source of NOx (NO + NO2) in the middle to upper troposphere. We estimate the production efficiency (PE) of lightning NOx (LNOx) using satellite data from the Ozone Monitoring Instrument and the ground-based World Wide Lightning Location Network in three northern midlatitudes, primarily continental regions that include much of North America, Europe, and East Asia. Data were obtained over five boreal summers, 2007-2011, and comprise the largest number of midlatitude convective events to date for estimating the LNOx PE with satellite NO2 and ground-based lightning measurements. In contrast to some previous studies, the algorithm assumes no minimum flash-rate threshold and estimates freshly produced LNOx by subtracting a background of aged NOx estimated from the Ozone Monitoring Instrument data set itself. We infer an average value of 180 +/- 100 moles LNOx produced per lightning flash. We also show evidence of a dependence of PE on lightning flash rate and find an approximate empirical power function relating moles LNOx to flashes. PE decreases by an order of magnitude for a 2 orders of magnitude increase in flash rate. This phenomenon has not been reported in previous satellite LNOx studies but is consistent with ground-based observations suggesting an inverse relationship between flash rate and size.

This study assesses the impact of the lightning nitric oxide (LNO) production schemes in the Community Multiscale Air Quality (CMAQ) model on ground-level air quality as well as aloft atmospheric chemistry through detailed evaluation of model predictions of nitrogen oxides (NOx) and ozone (O-3) with corresponding observations for the US. For ground-level evaluations, hourly O-3 and NOx values from the U.S. EPA Air Quality System (AQS) monitoring network are used to assess the impact of different LNO schemes on model prediction of these species in time and space. Vertical evaluations are performed using ozonesonde and P-3B aircraft measurements during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign conducted in the Baltimore-Washington region during July 2011. The impact on wet deposition of nitrate is assessed using measurements from the National Atmospheric Deposition Program's National Trends Network (NADP NTN). Compared with the Base model (without LNO), the impact of LNO on surface O-3 varies from region to region depending on the Base model conditions. Overall statistics suggest that for regions where surface O-3 mixing ratios are already overestimated, the incorporation of additional NO from lightning generally increased model overestimation of mean daily maximum 8 h (DM8HR) O-3 by 1-2 ppb. In regions where surface O-3 is underestimated by the Base model, LNO can significantly reduce the underestimation and bring model predictions close to observations. Analysis of vertical profiles reveals that LNO can significantly improve the vertical structure of modeled O-3 distributions by reducing underestimation aloft and to a lesser degree decreasing overestimation near the surface. Since the Base model underestimates the wet deposition of nitrate in most regions across the modeling domain with the exception of the Pacific Coast, the inclusion of LNO leads to reduction in biases and errors and an increase in correlation coefficients at almost all the NADP NTN sites. Among the three LNO schemes described in Kang et al. (2019), the hNLDN scheme, which is implemented using hourly observed lightning flash data from National Lightning Detection Network (NLDN), performs best for comparisons with ground-level values, vertical profiles, and wet deposition of nitrate; the mNLDN scheme (the monthly NLDN-based scheme) performed slightly better. However, when observed lightning flash data are not available, the linear regression-based parameterization scheme, pNLDN, provides an improved estimate for nitrate wet deposition compared to the base simulation that does not include LNO.