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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.

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).

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 (O3) with corresponding observations for the US. For ground-level evaluations, hourly O3 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 O3 varies from region to region depending on the Base model conditions. Overall statistics suggest that for regions where surface O3 mixing ratios are already overestimated, the incorporation of additional NO from lightning generally increased model overestimation of mean daily maximum 8 h (DM8HR) O3 by 1–2 ppb. In regions where surface O3 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 O3 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.

This work describes the lightning nitric oxide (LNO) production schemes in the Community Multiscale Air Quality (CMAQ) model. We first document the existing LNO production scheme and vertical distribution algorithm. We then describe updates that were made to the scheme originally based on monthly National Lightning Detection Network (mNLDN) observations. The updated scheme uses hourly NLDN (hNLDN) observations. These NLDN-based schemes are good for retrospective model applications when historical lightning data are available. For applications when observed data are not available (i.e., air quality forecasts and climate studies that assume similar climate conditions), we have developed a scheme that is based on linear and log-linear parameters derived from regression of multiyear historical NLDN (pNLDN) observations and meteorological model simulations. Preliminary assessment for total column LNO production reveals that the mNLDN scheme overestimates LNO by over 40 % during summer months compared with the updated hNLDN scheme that reflects the observed lightning activity more faithfully in time and space. The pNLDN performance varies with year, but it generally produced LNO columns that are comparable to hNLDN and mNLDN, and in most cases it outperformed mNLDN. Thus, when no observed lightning data are available, pNLDN can provide reasonable estimates of LNO emissions over time and space for this important natural NO source that influences air quality regulations.

The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) was developed in support of NASA's decadal survey GEO-CAPE geostationary satellite mission. GCAS is an airborne push-broom remote-sensing instrument, consisting of two channels which make hyperspectral measurements in the ultraviolet/visible (optimized for air quality observations) and the visible–near infrared (optimized for ocean color observations). The GCAS instrument participated in its first intensive field campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign in Texas in September 2013. During this campaign, the instrument flew on a King Air B-200 aircraft during 21 flights on 11 days to make air quality observations over Houston, Texas. We present GCAS trace gas retrievals of nitrogen dioxide (NO2) and formaldehyde (CH2O), and compare these results with trace gas columns derived from coincident in situ profile measurements of NO2 and CH2O made by instruments on a P-3B aircraft, and with NO2 observations from ground-based Pandora spectrometers operating in direct-sun and scattered light modes. GCAS tropospheric column measurements correlate well spatially and temporally with columns estimated from the P-3B measurements for both NO2 (r2 = 0.89) and CH2O (r2 = 0.54) and with Pandora direct-sun (r2 = 0.85) and scattered light (r2 = 0.94) observed NO2 columns. Coincident GCAS columns agree in magnitude with NO2 and CH2O P-3B-observed columns to within 10 % but are larger than scattered light Pandora tropospheric NO2 columns by 33 % and direct-sun Pandora NO2 columns by 50 %.

Over the past 24 years, the AErosol RObotic NETwork (AERONET) program has provided highly accurate remote-sensing characterization of aerosol optical and physical properties for an increasingly extensive geographic distribution including all continents and many oceanic island and coastal sites. The measurements and retrievals from the AERONET global network have addressed satellite and model validation needs very well, but there have been challenges in making comparisons to similar parameters from in situ surface and airborne measurements. Additionally, with improved spatial and temporal satellite remote sensing of aerosols, there is a need for higher spatial-resolution ground-based remote-sensing networks. An effort to address these needs resulted in a number of field campaign networks called Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) that were designed to provide a database for in situ and remote-sensing comparison and analysis of local to mesoscale variability in aerosol properties. This paper describes the DRAGON deployments that will continue to contribute to the growing body of research related to meso- and microscale aerosol features and processes. The research presented in this special issue illustrates the diversity of topics that has resulted from the application of data from these networks.

An observation-constrained box model based on the Carbon Bond mechanism, version 5 (CB05), was used to study photochemical processes along the NASA P-3B flight track and spirals over eight surface sites during the September 2013 Houston, Texas deployment of the NASA Deriving Information on Surface Conditions from COlumn and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign. Data from this campaign provided an opportunity to examine and improve our understanding of atmospheric photochemical oxidation processes related to the formation of secondary air pollutants such as ozone (O3). O3 production and its sensitivity to NOx and volatile organic compounds (VOCs) were calculated at different locations and times of day. Ozone production efficiency (OPE), defined as the ratio of the ozone production rate to the NOx oxidation rate, was calculated using the observations and the simulation results of the box and Community Multiscale Air Quality (CMAQ) models. Correlations of these results with other parameters, such as radical sources and NOx mixing ratio, were also evaluated. It was generally found that O3 production tends to be more VOC-sensitive in the morning along with high ozone production rates, suggesting that control of VOCs may be an effective way to control O3 in Houston. In the afternoon, O3 production was found to be mainly NOx-sensitive with some exceptions. O3 production near major emissions sources such as Deer Park was mostly VOC-sensitive for the entire day, other urban areas near Moody Tower and Channelview were VOC-sensitive or in the transition regime, and areas farther from downtown Houston such as Smith Point and Conroe were mostly NOx-sensitive for the entire day. It was also found that the control of NOx emissions has reduced O3 concentrations over Houston but has led to larger OPE values. The results from this work strengthen our understanding of O3 production; they indicate that controlling NOx emissions will provide air quality benefits over the greater Houston metropolitan area in the long run, but in selected areas controlling VOC emissions will also be beneficial.

The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 moleculescm−2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

The Airborne Compact Atmospheric Mapper (ACAM), an ultraviolet/visible/near-infrared spectrometer, has been flown on board the NASA UC-12 aircraft during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaigns to provide remote sensing observations of tropospheric and boundary-layer pollutants from its radiance measurements. To assure the trace-gas retrieval from ACAM measurements we perform detailed characterization and verification of ACAM slit functions. The wavelengths and slit functions of ACAM measurements are characterized for the air-quality channel (~304–500 nm) through cross-correlation with a high-resolution solar irradiance reference spectrum after necessarily accounting for atmospheric gas absorption and the ring effect in the calibration process. The derived slit functions, assuming a hybrid combination of asymmetric Gaussian and top-hat slit functions, agree very well with the laboratory-measured slit functions. Comparisons of trace-gas retrievals between using derived and measured slit functions demonstrate that the cross-correlation technique can be reliably used to characterize slit functions for trace-gas retrievals.

During the July 2011 Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field experiment in Maryland, significant enhancements in Aerosol Robotic Network (AERONET) sun–sky radiometer measured aerosol optical depth (AOD) were observed in the immediate vicinity of non-precipitating cumulus clouds on some days. Both measured Ångström exponents and aerosol size distribution retrievals made before, during and after cumulus development often suggest little change in fine mode particle size; therefore, implying possible new particle formation in addition to cloud processing and humidification of existing particles. In addition to sun–sky radiometer measurements of large enhancements of fine mode AOD, lidar measurements made from both ground-based and aircraft-based instruments during the experiment also measured large increases in aerosol signal at altitudes associated with the presence of fair weather cumulus clouds. These data show modifications of the aerosol vertical profile as a result of the aerosol enhancements at and below cloud altitudes. The airborne lidar data were utilized to estimate the spatial extent of these aerosol enhancements, finding increased AOD, backscatter and extinction out to 2.5 km distance from the cloud edge. Furthermore, in situ measurements made from aircraft vertical profiles over an AERONET site during the experiment also showed large increases in aerosol scattering and aerosol volume after cloud formation as compared to before. The 15-year AERONET database of AOD measurements at the Goddard Space Flight Center (GSFC), Maryland site, was investigated in order to obtain a climatological perspective of this phenomenon of AOD enhancement. Analysis of the diurnal cycle of AOD in summer showed significant increases in AOD from morning to late afternoon, corresponding to the diurnal cycle of cumulus development.

We assess the standard operational nitrogen dioxide (NO2) data product (OMNO2, version 2.1) retrieved from the Ozone Monitoring Instrument (OMI) onboard NASA's Aura satellite using a combination of aircraft and surface in~situ measurements as well as ground-based column measurements at several locations and a bottom-up NOx emission inventory over the continental US. Despite considerable sampling differences, NO2 vertical column densities from OMI are modestly correlated (r = 0.3–0.8) with in situ measurements of tropospheric NO2 from aircraft, ground-based observations of NO2 columns from MAX-DOAS and Pandora instruments, in situ surface NO2 measurements from photolytic converter instruments, and a bottom-up NOx emission inventory. Overall, OMI retrievals tend to be lower in urban regions and higher in remote areas, but generally agree with other measurements to within ± 20%. No consistent seasonal bias is evident. Contrasting results between different data sets reveal complexities behind NO2 validation. Since validation data sets are scarce and are limited in space and time, validation of the global product is still limited in scope by spatial and temporal coverage and retrieval conditions. Monthly mean vertical NO2 profile shapes from the Global Modeling Initiative (GMI) chemistry-transport model (CTM) used in the OMI retrievals are highly consistent with in situ aircraft measurements, but these measured profiles exhibit considerable day-to-day variation, affecting the retrieved daily NO2 columns by up to 40%. This assessment of OMI tropospheric NO2 columns, together with the comparison of OMI-retrieved and model-simulated NO2 columns, could offer diagnostic evaluation of the model.

We describe a new algorithm for the retrieval of nitrogen dioxide (NO2) vertical columns from nadir-viewing satellite instruments. This algorithm (SP2) is the basis for the Version 2.1 OMI This algorithm (SP2) is the basis for the Version 2.1 Ozone Monitoring Instrument (OMI) NO2 Standard Product and features a novel method for separating the stratospheric and tropospheric columns. NO2 Standard Product and features a novel method for separating the stratospheric and tropospheric columns. The approach estimates the stratospheric NO2 directly from satellite data without using stratospheric chemical transport models or assuming any global zonal wave pattern. Tropospheric NO2 columns are retrieved using air mass factors derived from high-resolution radiative transfer calculations and a monthly climatology of NO2 profile shapes. We also present details of how uncertainties in the retrieved columns are estimated. The sensitivity of the retrieval to assumptions made in the stratosphere–troposphere separation is discussed and shown to be small, in an absolute sense, for most regions. We compare daily and monthly mean global OMI NO2 retrievals using the SP2 algorithm with those of the original Version 1 Standard Product (SP1) and the Dutch DOMINO product. The SP2 retrievals yield significantly smaller summertime tropospheric columns than SP1, particularly in polluted regions, and are more consistent with validation studies. SP2 retrievals are also relatively free of modeling artifacts and negative tropospheric NO2 values. In a reanalysis of an INTEX-B validation study, we show that SP2 largely eliminates an ~20% discrepancy that existed between OMI and independent in situ springtime NO2 SP1 measurements.

Cloud chemistry simulations were performed for a Hector thunderstorm observed on 16 November 2005 during the SCOUT-O3/ACTIVE campaigns based in Darwin, Australia, with the primary objective of estimating the average NO production per lightning flash in this unique storm type which occurred in a tropical island environment. The 3-D WRF-Aqueous Chemistry (WRF-AqChem) model is used for these calculations and contains the WRF nonhydrostatic cloud-resolving model with online gas- and aqueous-phase chemistry and a lightning-NOx (LNOx) production algorithm. The model was initialized by inducing convection with an idealized morning sounding and sensible heat source, and initial condition chemical profiles from merged aircraft observations in undisturbed air. Many features of the idealized model storm, such as storm size and peak radar reflectivity, were similar to the observed storm. Tracer species, such as CO, used to evaluate convective transport in the simulated storm found vertical motion from the boundary layer to the anvil region was well represented in the model, with a small overestimate of enhanced CO at anvil altitudes. The lightning detection network (LINET) provided lightning flash data for the model and a lightning placement scheme injected the resulting NO into the simulated cloud. A lightning NO production scenario of 500 moles flash−1 for both CG and IC flashes yielded anvil NOx mixing ratios that compared well with aircraft observations and were also similar to those deduced for several convective modeling analyses in the midlatitudes and subtropics. However, these NO production values were larger than most estimates for tropical thunderstorms and given several uncertainties, LNOx production may have been as large as 600 moles flash−1. Approximately 85% of the simulated LNOx mass was located above 7 km in the later stages of the storm, which was greater than amounts found for subtropical and midlatitude convection. Modeled upper tropospheric NO2 partial columns were also considerably greater than most satellite observations of tropical marine convective events, as tropical island convection, such as Hector, is more vigorous and more productive of LNOx. Additional research is needed to investigate whether LNOx production per flash increases in storms with greater wind shear, such as this Hector storm, which showed significant variation in wind direction with altitude.

A lightning-nitrogen oxide (NO) algorithm is implemented in the Community Multiscale Air Quality Model (CMAQ) and used to evaluate the impact of lightning-NO emissions (LNOx) on tropospheric photochemistry over the United States during the summer of 2006. For a 500 mole per flash lightning-NO source, the mean summertime tropospheric NO2 column agrees with satellite-retrieved columns to within −5 to +13%. Temporal fluctuations in the column are moderately well simulated; however, the addition of LNOx does not lead to a better simulation of day-to-day variability. The contribution of lightning-NO to the model column ranges from ∼10% in the northern US to >45% in the south-central and southeastern US. Lightning-NO adds up to 20 ppbv to upper tropospheric model ozone and 1.5–4.5 ppbv to 8-h maximum surface layer ozone, although, on average, the contribution of LNOx to model surface ozone is 1–2 ppbv less on poor air quality days. LNOx increases wet deposition of oxidized nitrogen by 43% and total deposition of nitrogen by 10%. This additional deposition reduces the mean magnitude of the CMAQ low-bias in nitrate wet deposition with respect to National Atmospheric Deposition monitors to near zero. Differences in urban/rural biases between model and satellite-retrieved NO2 columns were examined to identify possible problems in model chemistry and/or transport. CMAQ columns were too large over urban areas. Biases at other locations were minor after accounting for the impacts of lightning-NO emissions and the averaging kernel on model columns. In order to obtain an upper bound on the contribution of uncertainties in NOy chemistry to upper tropospheric NOx low biases, sensitivity calculations with updated chemistry were run for the time period of the Intercontinental Chemical Transport Experiment (INTEX-A) field campaign (summer 2004). After adjusting for possible interferences in NO2 measurements and averaging over the entire campaign, these updates reduced 7–9 km biases from 32 to 17% and 9–12 km biases from 57 to 46%. While these changes lead to better agreement, a considerable unexplained NO2 low-bias remains in the uppermost troposphere.

From 13 July–9 August 2007, 25 ozonesondes were launched from Las Tablas, Panama as part of the Tropical Composition, Cloud, and Climate Coupling (TC4) mission. On 5 August, a strong convective cell formed in the Gulf of Panama. World Wide Lightning Location Network (WWLLN) data indicated 563 flashes (09:00–17:00 UTC) in the Gulf. NO2 data from the Ozone Monitoring Instrument (OMI) show enhancements, suggesting lightning production of NOx. At 15:05 UTC, an ozonesonde ascended into the southern edge of the now dissipating convective cell as it moved west across the Azuero Peninsula. The balloon oscillated from 2.5–5.1 km five times (15:12–17:00 UTC), providing a unique examination of ozone (O3) photochemistry on the edge of a convective cell. Ozone increased at a rate of ~1.6–4.6 ppbv/hr between the first and last ascent, resulting cell wide in an increase of ~(2.1–2.5) × 106 moles of O3. This estimate agrees to within a factor of two of our estimates of photochemical lightning O3 production from the WWLLN flashes, from the radar-inferred lightning flash data, and from the OMI NO2 data (~1.2, ~1.0, and ~1.7 × 106 moles, respectively), though all estimates have large uncertainties. Examination of DC-8 in situ and lidar O3 data gathered around the Gulf that day suggests 70–97% of the O3 change occurred in 2.5–5.1 km layer. A photochemical box model initialized with nearby TC4 aircraft trace gas data suggests these O3 production rates are possible with our present understanding of photochemistry.

Improved estimates of NOx from lightning sources are required to understand tropospheric NOx and ozone distributions, the oxidising capacity of the troposphere and corresponding feedbacks between chemistry and climate change. In this paper, we report new satellite ozone observations from the Tropospheric Emission Spectrometer (TES) instrument that can be used to test and constrain the parameterization of the lightning source of NOx in global models. Using the National Lightning Detection (NLDN) and the Long Range Lightning Detection Network (LRLDN) data as well as the HYPSLIT transport and dispersion model, we show that TES provides direct observations of ozone enhanced layers downwind of convective events over the USA in July 2006. We find that the GEOS-Chem global chemistry-transport model with a parameterization based on cloud top height, scaled regionally and monthly to OTD/LIS (Optical Transient Detector/Lightning Imaging Sensor) climatology, captures the ozone enhancements seen by TES. We show that the model's ability to reproduce the location of the enhancements is due to the fact that this model reproduces the pattern of the convective events occurrence on a daily basis during the summer of 2006 over the USA, even though it does not well represent the relative distribution of lightning intensities. However, this model with a value of 6 Tg N/yr for the lightning source (i.e.: with a mean production of 260 moles NO/Flash over the USA in summer) underestimates the intensities of the ozone enhancements seen by TES. By imposing a production of 520 moles NO/Flash for lightning occurring in midlatitudes, which better agrees with the values proposed by the most recent studies, we decrease the bias between TES and GEOS-Chem ozone over the USA in July 2006 by 40%. However, our conclusion on the strength of the lightning source of NOx is limited by the fact that the contribution from the stratosphere is underestimated in the GEOS-Chem simulations.

Understanding the mechanisms that transport pollutants from the surface to the free atmosphere is important for determining the atmosphere's chemical composition. This study quantifies the vertical transport of tropospheric carbon monoxide (CO) by deep mesoscale convective systems and assesses the ability of the satellite-borne Tropospheric Emission Spectrometer (TES) to detect the resulting enhanced CO in the upper atmosphere. A squall line that is similar to one occurring during NASA's INTEX-B mission is simulated using a typical environmental wind shear profile and the 2-D Goddard Cumulus Ensemble model. The simulation provides post-convection CO profiles. The structure of the simulated squall line is examined, and its vertical transport of CO is quantified. Then, TES' ability to resolve the convectively modified CO distribution is documented using a "clear-sky" retrieval scheme. Results show that the simulated squall line transports the greatest mass of CO in the upper levels, with a value of 96 t upward and 67 t downward at 300 hPa. Results indicate that TES has sufficient sensitivity to resolve convectively lofted CO, as long as the retrieval scene is cloud-free. TES swaths located immediately downwind of squall lines have the greatest chance of sensing convective transport because the impact of clouds on retrieval quality becomes less. A note of caution is to always analyze TES-derived CO data (or data from any satellite sensor) together with the retrieval averaging kernels that describe the information content of the retrieval.

Transport and scavenging of chemical constituents in deep convection is important to understanding the composition of the troposphere and therefore chemistry-climate and air quality issues. High resolution cloud chemistry models have been shown to represent convective processing of trace gases quite well. To improve the representation of sub-grid convective transport and wet deposition in large-scale models, general characteristics, such as species mass flux, from the high resolution cloud chemistry models can be used. However, it is important to understand how these models behave when simulating the same storm. The intercomparison described here examines transport of six species. CO and O3, which are primarily transported, show good agreement among models and compare well with observations. Models that included lightning production of NOx reasonably predict NOx mixing ratios in the anvil compared with observations, but the NOx variability is much larger than that seen for CO and O3. Predicted anvil mixing ratios of the soluble species, HNO3, H2O2, and CH2O, exhibit significant differences among models, attributed to different schemes in these models of cloud processing including the role of the ice phase, the impact of cloud-modified photolysis rates on the chemistry, and the representation of the species chemical reactivity. The lack of measurements of these species in the convective outflow region does not allow us to evaluate the model results with observations.

To improve the trace gas retrieval from Airborne Compact Atmospheric Mapper (ACAM) during the DSICOVER-AQ campaigns, we characterize the signal to noise ratio (SNR) of the ACAM measurement. From the standard deviations of the fitting residuals, the SNRs of ACAM nadir measurements are estimated to vary from ~300 at 310 nm to ~1000 in the blue spectral region; the zenith data are noisier due to reduced levels of illumination and lower system throughput and also show many more pixels with abrupt anomalous values; therefore, a new method is developed to derive a solar irradiance reference at the top of the atmosphere (TOA) from average nadir measurements, at instrument spectral resolution and including instrument calibration characteristics. Using this reference can significantly reduce fitting residuals and improve the retrievals. This approach derives an absolute reference for direct fitting algorithms involving radiative transfer calculations and thus can be applied to both aircraft and ground-based measurements. The comparison of ACAM radiance with simulations using coincident ozonesonde and OMI data shows large wavelength-dependent biases in ACAM data, varying from ~−19% at 310 nm to 5% at 360 nm. Correcting ACAM radiance in direct-fitting based ozone profile algorithm significantly improves the consistency with OMI total ozone.