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The Lake Michigan Ozone Study 2017 (LMOS 2017) was a collaborative multiagency field study targeting ozone chemistry, meteorology, and air quality observations in the southern Lake Michigan area. The primary objective of LMOS 2017 was to provide measurements to improve air quality modeling of the complex meteorological and chemical environment in the region. LMOS 2017 science questions included spatiotemporal assessment of nitrogen oxides (NOx = NO + NO2) and volatile organic compounds (VOC) emission sources and their influence on ozone episodes; the role of lake breezes; contribution of new remote sensing tools such as GeoTASO, Pandora, and TEMPO to air quality management; and evaluation of photochemical grid models. The observing strategy included GeoTASO on board the NASA UC-12 aircraft capturing NO2 and formaldehyde columns, an in situ profiling aircraft, two ground-based coastal enhanced monitoring locations, continuous NO2 columns from coastal Pandora instruments, and an instrumented research vessel. Local photochemical ozone production was observed on 2 June, 9–12 June, and 14–16 June, providing insights on the processes relevant to state and federal air quality management. The LMOS 2017 aircraft mapped significant spatial and temporal variation of NO2 emissions as well as polluted layers with rapid ozone formation occurring in a shallow layer near the Lake Michigan surface. Meteorological characteristics of the lake breeze were observed in detail and measurements of ozone, NOx, nitric acid, hydrogen peroxide, VOC, oxygenated VOC (OVOC), and fine particulate matter (PM2.5) composition were conducted. This article summarizes the study design, directs readers to the campaign data repository, and presents a summary of findings.

Nitrogen oxides (NOx = NO + NO2) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations in NO2 are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO2 concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements and surface EPA Air Quality System (AQS) observations as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; GOME-2A: Global Ozone Monitoring Experiment – 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument in July 2011 during the DISCOVER-AQ campaign over the Baltimore–Washington region. The model simulations at 36 and 4 km resolutions are in reasonably good agreement with the regional mean temporospatial NO2 observations in the daytime. However, we find significant overestimations (underestimations) of model-simulated NO2 (O3) surface concentrations during nighttime, which can be mitigated by enhancing nocturnal vertical mixing in the model. Another discrepancy is that Pandora-measured NO2 TVCDs show much less variation in the late afternoon than simulated in the model. The higher-resolution 4 km simulations tend to show larger biases compared to the observations due largely to the larger spatial variations in NOx emissions in the model when the model spatial resolution is increased from 36 to 4 km. OMI, GOME-2A, and the high-resolution aircraft ACAM observations show a more dispersed distribution of NO2 vertical column densities (VCDs) and lower VCDs in urban regions than corresponding 36 and 4 km model simulations, likely reflecting the spatial distribution bias of NOx emissions in the National Emissions Inventory (NEI) 2011.

Nitrogen oxides (NO(x)=NO+NO(2)) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations in NO(2) are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO(2) concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements and surface EPA Air Quality System (AQS) observations as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; GOME-2A: Global Ozone Monitoring Experiment – 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument in July 2011 during the DISCOVER-AQ campaign over the Baltimore–Washington region. The model simulations at 36 and 4 km resolutions are in reasonably good agreement with the regional mean temporospatial NO(2) observations in the daytime. However, we find significant overestimations (underestimations) of model-simulated NO(2) (O(3)) surface concentrations during night-time, which can be mitigated by enhancing nocturnal vertical mixing in the model. Another discrepancy is that Pandora-measured NO(2) TVCDs show much less variation in the late afternoon than simulated in the model. The higher-resolution 4 km simulations tend to show larger biases compared to the observations due largely to the larger spatial variations in NO(x) emissions in the model when the model spatial resolution is increased from 36 to 4 km. OMI, GOME-2A, and the high-resolution aircraft ACAM observations show a more dispersed distribution of NO(2) vertical column densities (VCDs) and lower VCDs in urban regions than corresponding 36 and 4 km model simulations, likely reflecting the spatial distribution bias of NO(x) emissions in the National Emissions Inventory (NEI) 2011.

Airborne and ground-based Pandora spectrometer NOspan classCombining double low line"inline-formula"2/span column measurements were collected during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region, which coincided with early observations from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOMI NOspan classCombining double low line"inline-formula"2/span Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NOspan classCombining double low line"inline-formula"2/span. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (span classCombining double low line"inline-formula"ir/i2Combining double low line/spanthinsp;0.92 and slope of 1.03), with the largest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representativity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representativity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250thinsp;mthinsp;span classCombining double low line"inline-formula"×/spanthinsp;250thinsp;m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (span classCombining double low line"inline-formula"ir/i2Combining double low line0.96/span) than Pandora measurements are with TROPOMI (span classCombining double low line"inline-formula"ir/i2Combining double low line0.84/span). The largest outliers between TROPOMI and the reference measurements appear to stem from too spatially coarse a priori surface reflectivity (0.5span classCombining double low line"inline-formula"g /span) over bright urban scenes. In this work, this results during cloud-free scenes that, at times, are affected by errors in the TROPOMI cloud pressure retrieval impacting the calculation of tropospheric air mass factors. This factor causes a high bias in TROPOMI TrVCs of 4thinsp;%-11thinsp;%. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19thinsp;%-33thinsp;% during the LISTOS timeframe of June-September 2018. Part of this low bias is caused by coarse a priori profile input from the TM5-MP model; replacing thesespan idCombining double low line"page6114"/ profiles with those from a 12thinsp;km North American Model-Community Multiscale Air Quality (NAMCMAQ) analysis results in a 12thinsp;%-14thinsp;% increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7thinsp;%-19thinsp;% low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets./.

Satellite data from the Ozone Measuring Instrument (OMI) and Earth Polychromatic Imaging Camera (EPIC) are used to study long-term changes and global distribution of UV erythemal irradiance E(ζ,φ,z,t) (mW m−2) and the dimensionless UV index E ∕ (25 m Wm−2) over major cities as a function of latitude ζ, longitude φ, altitude z, and time t. Extremely high amounts of erythemal irradiance (12 < UV index ) are found for many low-latitude and high-altitude sites (e.g., San Pedro, Chile, 2.45 km; La Paz, Bolivia, 3.78 km). Lower UV indices at some equatorial or high-altitude sites (e.g., Quito, Ecuador) occur because of persistent cloud effects. High UVI levels (UVI > 6) are also found at most mid-latitude sites during the summer months for clear-sky days. OMI time-series data starting in January 2005 to December 2018 are used to estimate 14-year changes in erythemal irradiance ΔE, total column ozone ΔTCO3, cloud and haze transmission ΔCT derived from scene reflectivity LER, and reduced transmission from absorbing aerosols ΔCA derived from absorbing aerosol optical depth τA for 191 specific cities in the Northern Hemisphere and Southern Hemisphere from 60∘ S to 60∘ N using publicly available OMI data. A list of the sites showing changes at the 1 standard deviation level 1σ is provided. For many specific sites there has been little or no change in E(ζ,φ,z,t) for the period 2005–2018. When the sites are averaged over 15∘ of latitude, there are strong correlation effects of both short- and long-term cloud and absorbing aerosol change as well as anticorrelation with total column ozone change ΔTCO3. Estimates of changes in atmospheric transmission ΔCT (ζ, φ, z, t) derived from OMI-measured cloud and haze reflectivity LER and averaged over 15∘ of latitude show an increase of 1.1±1.2 % per decade between 60 and 45∘ S, almost no average 14-year change of 0.03±0.5 % per decade from 55∘ S to 30∘ N, local increases and decreases from 20 to 30∘ N, and an increase of 1±0.9 % per decade from 35 to 60∘ N. The largest changes in E(ζ,φ,z,t) are driven by changes in cloud transmission CT. Synoptic EPIC radiance data from the sunlit Earth are used to derive ozone and reflectivity needed for global images of the distribution of E(ζ,φ,z,t) from sunrise to sunset centered on the Americas, Europe–Africa, and Asia. EPIC data are used to show the latitudinal distribution of E(ζ,φ,z,t) from the Equator to 75∘ for specific longitudes. EPIC UV erythemal images show the dominating effect of solar zenith angle (SZA), the strong increase in E with altitude, and the decreases caused by cloud cover. The nearly cloud-free images of E(ζ,φ,z,t) over Australia during the summer (December) show regions of extremely high UVI (14–16) covering large parts of the continent. Zonal averages show a maximum of UVI = 14 in the equatorial region seasonally following latitudes where SZA = 0∘. Dangerously high amounts of erythemal irradiance (12 < UV index < 18) are found for many low-latitude and high-altitude sites. High levels of UVI are known to lead to health problems (skin cancer and eye cataracts) with extended unprotected exposure, as shown in the extensive health statistics maintained by the Australian Institute of Health and Welfare and the United States National Institute of Health National Cancer Institute.

Adverse air quality impacts human health and climate and has implications for environmental equity. The Compact Hyperspectral Air Pollution Sensor (CHAPS) is a newly designed small imaging spectrometer for remote sensing of nitrogen dioxide (NO2) and other air pollutants from space. It incorporates two emerging technologies, to achieve the miniaturization necessary to fit within a 6U CubeSat. The first is freeform optics, which can be used to reduce the size of an imaging spectrometer without compromising optical performance. We report the science requirements; preliminary, fully freeform and fully reflective optical design of the CHAPS demonstrator, CHAPS-D; and model its performance. The second technology is additive manufacturing, coupled with topology optimization, which has a number of potential advantages over traditional subtractive manufacturing. The instrument mechanical structure, including optical mounts and integral light baffles, and two of the optical elements will be additively manufactured using a high-strength nextgeneration aluminum alloy. We show preliminary results of additive manufacturing tests. CHAPS-D is currently being developed for ground-based and airborne testing.

EPIC (Earth Polychromatic Imaging Camera) raw level-0 (L0) data in one channel is a 12-bit 2048x2048 pixels image array plus auxiliary data such as telemetry, temperature readings, cloud, aerosol, ocean surface and vegetation properties, sulfur dioxide, etc. The EPIC L1a processor applies a series of correction steps on the L0 data to convert them into corrected count rates (level-1a or L1a data): Dark correction, Enhanced pixel detection, Read wave correction, Latency correction, Non-linearity correction, Temperature correction, Conversion to count rates, Flat fielding, and Stray light correction. L1a images should have all instrumental effects removed and only need to be multiplied by one single number for each wavelength to obtain radiances, which are the basis for all higher-level EPIC products, such as ozone and sulfur dioxide total column amounts, vegetation index, cloud, aerosol, ocean surface and vegetation properties, etc. This paper gives an overview of the mathematics and the pre-launch and on-orbit calibration behind each correction step.

Airborne and ground-based Pandora spectrometer NO2 column measurements were collected during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region, which coincided with early observations from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOMI NO2 Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO2. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r2 =0.92 and slope of 1.03), with the largest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representativity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representativity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250m×250m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r2 = 0.96) than Pandora measurements are with TROPOMI (r2 = 0.84). The largest outliers between TROPOMI and the reference measurements appear to stem from too spatially coarse a priori surface reflectivity (0.5°) over bright urban scenes. In this work, this results during cloud-free scenes that, at times, are affected by errors in the TROPOMI cloud pressure retrieval impacting the calculation of tropospheric air mass factors. This factor causes a high bias in TROPOMI TrVCs of 4%–11%. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19%–33% during the LISTOS timeframe of June–September 2018. Part of this low bias is caused by coarse a priori profile input from the TM5-MP model; replacing these profiles with those from a 12 km North American Model–Community Multiscale Air Quality (NAMCMAQ) analysis results in a 12%–14% increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7%–19% low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets.

NASA deployed the GeoTASO airborne UV–visible spectrometer in May–June 2017 to produce high-resolution (approximately 250 m×250 m) gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. The results collected show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r2=0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and spatial heterogeneity that may be observed differently by the sunward-viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO (Tropospheric Emissions: Monitoring Pollution), TROPOMI (TROPOspheric Monitoring Instrument), and OMI (Ozone Monitoring Instrument), the agreement with Pandora measurements degraded, particularly for the most polluted columns as localized large pollution enhancements observed by Pandora and GeoTASO are spatially averaged with nearby less-polluted locations within the larger area representative of the satellite spatial resolutions (aircraft-to-Pandora slope: TEMPO scale =0.88; TROPOMI scale =0.77; OMI scale =0.57). In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well at least up to pollution scales of 30×1015 molecules cm−2. Two publicly available OMI tropospheric NO2 retrievals are found to be biased low with respect to these Pandora observations. However, the agreement improves when higher-resolution a priori inputs are used for the tropospheric air mass factor calculation (NASA V3 standard product slope =0.18 and Berkeley High Resolution product slope =0.30). Overall, this work explores best practices for satellite validation strategies with Pandora direct-sun observations by showing the sensitivity to product spatial resolution and demonstrating how the high-spatial-resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high-temporal-resolution ground-based column observations to evaluate the influence of spatial heterogeneity on validation results.

Nitrogen oxides (NOx = NO + NO2) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations of NO2 are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO2 concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements, surface EPA Air Quality System (AQS) observations, as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; and GOME-2A: Global Ozone Monitoring Experiment – 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument, in July 2011 during the DISCOVER-AQ campaign over the Baltimore-Washington region. The model simulations at 36- and 4-km resolutions are in reasonably good agreement with the temporospatial NO2 observations in the daytime. However, nighttime mixing in the model needs to be enhanced to reproduce the observed NO2 diurnal cycle in the model. Another discrepancy is that Pandora measured NO2 TVCDs show much less variation in the late afternoon than simulated in the model. Relative to the 36-km model simulations, the 4-km model results show larger biases compared to the observations due largely to the larger spatial variations of NO2 in the model when the spatial resolution is increased from 36 to 4 km, although the biases are often comparable to the ranges of the observations. The high-resolution aircraft ACAM observations show a more dispersed distribution of NO2 vertical column densities (VCDs) and lower VCDs in urban regions than 4-km model simulations, reflecting likely the spatial distribution bias of NOx emissions in the National Emissions Inventory (NEI) 2011 at high resolution.

Nonmethane volatile organic compounds (NMVOCs) result in ozone and aerosol production that adversely affects the environment and human health. For modeling purposes, anthropogenic NMVOC emissions have been typically compiled using the “bottom-up” approach. To minimize uncertainties of the bottom-up emission inventory, “top-down” NMVOC emissions can be estimated using formaldehyde (HCHO) observations. In this study, HCHO vertical column densities (VCDs) obtained from the Geostationary Trace gas and Aerosol Sensor Optimization spectrometer during the Korea–United States Air Quality campaign were used to constrain anthropogenic volatile organic compound (AVOC) emissions in South Korea. Estimated top-down AVOC emissions differed from those of the up-to-date bottom-up inventory over major anthropogenic source regions by factors of 1.0 ± 0.4 to 6.9 ± 3.9. Our evaluation using a 3D chemical transport model indicates that simulated HCHO mixing ratios using the top-down estimates were in better agreement with observations onboard the DC-8 aircraft during the campaign relative to those with the bottom-up emission, showing a decrease in model bias from –25% to –13%. The top-down analysis used in this study, however, has some limitations related to the use of HCHO yields, background HCHO columns, and AVOC speciation in the bottom-up inventory, resulting in uncertainties in the AVOC emission estimates. Our attempt to constrain diurnal variations of the AVOC emissions using the aircraft HCHO VCDs was compromised by infrequent aircraft observations over the same source regions. These limitations can be overcome with geostationary satellite observations by providing hourly HCHO VCDs.

Abundant NO2 column measurements from airborne and ground-based Pandora spectrometers were collected as part of the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region and coincided with early measurements from the Sentinel-5P TROPOMI instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOspheric Monitoring Instrument (TROPOMI) NO2 Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO2. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r2=0.92 and slope of 1.03) with the biggest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representivity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representivity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250 m × 250 m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r2=0.96) than Pandora measurements are with TROPOMI (r2=0.84). The largest outliers between TROPOMI and the reference measurements are caused by errors in the TROPOMI retrieval of cloud pressure impacting the calculation of tropospheric air mass factors in cloud-free scenes. This factor causes a high bias in TROPOMI TrVCs of 4–11 %. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19–33% during the LISTOS timeframe of June–September 2018. Part of this low bias is caused by coarse a priori profile input from TM5-MP model; replacing these profiles with those from a 12 km NAMCMAQ analysis results in a 12–14 % increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7–19 % low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets.

Next generation air quality sensors are currently planned to launch within the next couple of years. The Tropospheric Emissions: Monitory of Pollution (TEMPO-United States) and Geostationary Environment Monitoring Sensor (GEMS-South Korea) are two such missions that will probe the boundary layer/lower troposphere at unprecedented spatial and temporal scales. These missions are designed to provide constraints on chemical forecast models and specifically to answer the question: "What are the temporal and spatial variations of emissions of gases and aerosols important for air quality and climate?" In preparation for these missions a number of airborne air quality field missions have been performed to collect data at similar spatial and temporal scales, and during relevant seasonal air quality episodes including fires. This data is being used to improve the trace gas retrieval algorithms and explore the unique spatial scales and diurnal patterns that will be encountered when the geostationary experiments are operational. This overview will present details of two of the instruments used during these campaigns, the GeoCAPE Airborne Simulator (GCAS) and the Geostationary Trace Gas and Aerosol Sensor Optimization (GeoTASO) instruments. Maintained at the Goddard Space Flight Center's Radiometric Calibration and Development Facility (RCDF), these instruments are similar in design and sensitivty to what will be measured on-orbit by the TEMPO and GEMS sensors. Results of the retrieval of high spatial resolution nitrogen dioxide and formaldehyde will presented. Examples of vertical column retrievals will be presented under various source/weather conditions as well as the uncertainties that result from both instrument and radiative transfer assumptions.

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 %.

Ten wavelength channels of calibrated radiance image data from the sunlit Earth are obtained every 65 min during Northern Hemisphere summer from the EPIC (Earth Polychromatic Imaging Camera) instrument on the DSCOVR (Deep Space Climate Observatory) satellite located near the Earth–Sun Lagrange 1 point (L1), about 1.5 million km from the Earth. The L1 location permitted seven observations of the Moon's shadow on the Earth for about 3 h during the 21 August 2017 eclipse. Two of the observations were timed to coincide with totality over Casper, Wyoming, and Columbia, Missouri. Since the solar irradiances within five channels (λi = 388, 443, 551, 680, and 780 nm) are not strongly absorbed in the atmosphere, they can be used for characterizing the eclipse reduction in reflected radiances for the Earth's sunlit face containing the eclipse shadow. Five channels (λi = 317.5, 325, 340, 688, and 764 nm) that are partially absorbed in the atmosphere give consistent reductions compared to the non-absorbed channels. This indicates that cloud reflectivities dominate the 317.5–780 nm radiances reflected back to space from the sunlit Earth's disk with a significant contribution from Rayleigh scattering for the shorter wavelengths. An estimated reduction of 10 % was obtained for spectrally integrated radiance (387 to 781 nm) reflected from the sunlit Earth towards L1 for two sets of observations on 21 August 2017, while the shadow was in the vicinity of Casper, Wyoming (42.8666° N, 106.3131° W; centered on 17:44:50 UTC), and Columbia, Missouri (38.9517° N, 92.3341° W; centered on 18:14:50 UTC). In contrast, when non-eclipse days (20 and 23 August) are compared for each wavelength channel, the change in reflected light is much smaller (less than 1 % for 443 nm compared to 9 % (Casper) and 8 % (Columbia) during the eclipse). Also measured was the ratio REN(λi) of reflected radiance on adjacent non-eclipse days divided by radiances centered in the eclipse totality region with the same geometry for all 10 wavelength channels. The measured REN(443 nm) was smaller for Columbia (169) than for Casper (935), because Columbia had more cloud cover than Casper. REN(λi) forms a useful test of a 3-D radiative transfer models for an eclipse in the presence of optically thin clouds. Specific values measured at Casper with thin clouds are REN(340 nm) = 475, REN(388 nm) = 3500, REN(443 nm) = 935, REN(551 nm) = 5455, REN(680 nm) = 220, and REN(780 nm) = 395. Some of the variability is caused by changing cloud amounts within the moving region of totality during the 2.7 min needed to measure all 10 wavelength channels.

Using hyperspectral data collected by the Airborne Compact Atmospheric Mapper (ACAM) and a shipborne radiometer in Chesapeake Bay in July–August 2011, this study investigates diurnal changes of surface remote sensing reflectance (Rrs). Atmospheric correction of ACAM data is performed using the traditional “black pixel” approach through radiative transfer based look-up-tables (LUTs) with non-zero Rrs in the near-infrared (NIR) accounted for by iterations. The ACAM-derived Rrs was firstly evaluated through comparison with Rrs derived from the Moderate Resolution Imaging Spectroradiometer satellite measurements, and then validated against in situ Rrs using a time window of ±1 h or ±3 h. Results suggest that the uncertainties in ACAM-derived Rrs are generally comparable to those from MODIS satellite measurements over coastal waters, and therefore may be used to assess whether Rrs diurnal changes observed by ACAM are realistic (i.e., with changes > 2 × uncertainties). Diurnal changes observed by repeated ACAM measurements reaches up to 66.8% depending on wavelength and location and are consistent with those from the repeated in situ Rrs measurements. These findings suggest that once airborne data are processed using proper algorithms and validated using in situ data, they are suitable for assessing diurnal changes in moderately turbid estuaries such as Chesapeake Bay. The findings also support future geostationary satellite missions that are particularly useful to assess short-term changes.

The Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) instrument has been used as a precursor for a hyperspectral instrument on the future geostationary satellite, yet its ability to “measure” ocean reflectance needs to be evaluated. Here, we demonstrate its capacity through vicarious calibration and atmospheric correction of data collected during flight campaigns over the Louisiana shelf in September 2013 and over the North Atlantic Ocean in November 2015. GCAS-measured at-sensor radiance was first vicariously calibrated using concurrent measurements by the Moderate Resolution Imaging Spectrometer (MODIS) and radiative transfer simulations with the MODerate resolution atmospheric TRANsmission (MODTRAN). Then, atmospheric correction has been implemented using MODTRAN-developed lookup tables and the traditional Gordon and Wang “black pixel” approach but with nonzero water-leaving radiance in the near-infrared accounted for through iteration. The atmospheric correction algorithm was applied to the vicariously calibrated GCAS imagery, with resulting $R_{\mathrm{ rs}}$ compared with concurrent MODIS $R_{\mathrm{ rs}}$ and in situ $R_{\mathrm{ rs}}$ . The comparison shows a mean relative difference of about 25% ( $N = 11$ ) between GCAS and in situ $R_{\mathrm{ rs}}$ in the blue–green bands for clear to moderately turbid waters.

Nitrogen dioxide (NO2) is a short-lived atmospheric pollutant that serves as an air quality indicator, and is itself a health concern. The Airborne Compact Atmospheric Mapper (ACAM) was flown on board the NASA UC-12 aircraft during the DISCOVER-AQ Maryland field campaign in July 2011. The instrument collected hyperspectral remote sensing measurements in the 304-910 nm range, allowing day-time observations of several tropospheric pollutants, including nitrogen dioxide (NO2), at an unprecedented spatial resolution of 1.5 × 1.1 km2. Retrievals of slant column abundance are based on the Differential Optical Absorption Spectroscopy (DOAS) method. For the Air Mass Factor (AMF) computations needed to convert these retrievals to vertical column abundance, we include high resolution information for the surface reflectivity by using bidirectional reflectance distribution function (BRDF) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). We use high-resolution simulated vertical distributions of NO2 from the Community Multiscale Air Quality (CMAQ) and Global Modeling Initiative (GMI) models to account for the temporal variation in atmospheric NO2 to retrieve middle- and lower-tropospheric NO2 columns (NO2 below the aircraft). We compare NO2 derived from ACAM measurements with in-situ observations from NASA's P-3B research aircraft, total column observations from the ground-based Pandora spectrometers, and tropospheric column observations from the space-based OMI instrument. The high-resolution ACAM measurements not only give new insights into our understanding of atmospheric composition and chemistry through observation of sub-sampling variability in typical satellite and model resolutions, but they also provide opportunities for testing algorithm improvements for forthcoming geostationary air quality missions.

As an image-driven method to correct for atmospheric effects, the cloud shadow CS approach does not require accurate radiometric calibration of the sensor, making it feasible to process remotely sensed data when radiometric calibration may contain non-negligible uncertainties. Using measurements from the Geostationary Coastal and Air Pollution Events Airborne Simulator and from the Moderate Resolution Imaging Spectroradiometer over the Louisiana Shelf, we evaluate the CS approach to airplane measurements in turbid-water environments. The original CS approach somehow produced remote-sensing reflectance Rrs, sr−1 with an abnormal spectral shape, likely a result of the assumption of identical path radiance for the pair of pixels in and out of the shadow, which is not exactly valid for measurements made from a low-altitude airplane. To overcome this limitation, an empirical scheme using an effective wavelength-dependent radiance reflectance for the cloud γ, sr−1 was developed and reasonable GCAS Rrs retrievals are then generated, which were further validated against in situ Rrs. Issues and challenges in applying CS to measurements of low-altitude airplanes are discussed.

The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) was developed at NASA’s Goddard Space Flight Center (GSFC) and has flown in multiple field campaigns to perform mapping of the regional-scale EPA criteria pollutants nitrogen dioxide, ozone, and formaldehyde. GCAS will also participate in validation campaigns for NASA’s Tropospheric Emissions: Monitoring POllution (TEMPO) mission and the Korean Geostationary Environment Monitoring Spectrometer (GEMS) mission, both scheduled to launch in the early 2020s. GCAS houses two commercial Offner-type grating spectrometers that measure backscattered solar spectral radiance from the near-ultraviolet to near-infrared at high spatial resolution (typically 250 meters at 8.5 kilometer altitude). These radiances are used to retrieve spatial and temporal distributions of trace gases relevant to the boundary layer and free tropospheric atmospheric chemistry cycles. In this paper, we describe the field calibration techniques employed to characterize the spectral and temporal radiometric stability of the system during its most recent deployment in the 2018 Long Island Sound Trace Ozone Study (LISTOS) field campaign. Overall measurement uncertainty, retrieval impacts, and lessons learned for future deployments will also be described.

NASA deployed an airborne UV/Visible spectrometer, GeoTASO, in May–June 2017 to produce high resolution (approximately 250 × 250 m), gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. Results show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r2 = 0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and also spatial heterogeneity that may be observed differently by the sunward viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO, TROPOMI, and OMI, the agreement with Pandora measurements is degraded as localized polluted plumes observed by Pandora are spatially averaged over larger areas (aircraft-to-Pandora slope: TEMPO scale = 0.88; TROPOMI scale = 0.77; OMI scale = 0.57). This behavior suggests that satellite products are representative of individual Pandora observations up to a certain pollution scale that depends on satellite spatial resolution. In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well up to pollution scales of 30 x 1015 molecules cm−2. Two publicly available OMI tropospheric NO2 retrievals are both found to be biased low with respect to Pandora observations (NASA V3 Standard Product slope = 0.18 and Berkeley High Resolution Product slope = 0.30). However, the agreement improves when higher resolution a priori inputs are used for the tropospheric air mass factor calculation. Overall, this work explores best practices for satellite validation strategies by showing the sensitivity to product spatial resolution and demonstrates how the high spatial resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high temporal resolution surface observations to evaluate the influence of spatial heterogeneity on validation results.

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 Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) instrument is an airborne hyperspectral spectrometer measuring backscattered solar radiation in the ultraviolet (290–400 nm) and visible (415–695 nm) wavelength regions. This paper presents high-resolution sulfur dioxide (SO2) maps over the Korean Peninsula, produced by SO2 retrievals from GeoTASO measurements during the Korea–United States Air Quality Field Study (KORUS-AQ) from May to June 2016. The highly sensitive GeoTASO instrument with a spatial resolution of ~250 m × 250 m can detect point emission sources of SO2 within its fields of view, even without merging multiple overlapping observations. To retrieve SO2 vertical columns from the GeoTASO measurements, we apply an algorithm based on principal component analysis (PCA), which is effective in suppressing noise and biases in SO2 retrievals. The retrievals successfully capture SO2 plumes and various point sources such as power plants, a petrochemical complex, and a steel mill, located in South Chungcheong Province, some of which are not detected by a ground-based in situ measurement network. Spatial distributions of SO2 from GeoTASO observations in source areas are consistent with those from the Stack Tele-Monitoring System reports and airborne in situ SO2 measurements. Comparisons of SO2 retrievals from GeoTASO and existing satellite sensors demonstrate the significance of high-resolution SO2 observations, by indicating that GeoTASO detects small SO2 emission sources that are not precisely resolved by single overpasses of satellites. To assess future geostationary SO2 observations having a higher spatial resolution, we upscale the GeoTASO SO2 retrievals to a spatial resolution of the Geostationary Environment Monitoring Spectrometer (GEMS). Since the upscaled GeoTASO retrievals also detect SO2 plumes clearly, we expect from GEMS to identify even small SO2 emission sources over Asia.

The National Oceanic and Atmospheric Administration (NOAA) Deep Space Climate Observatory (DSCOVR) spacecraft was launched on 11 February 2015 and in June 2015 achieved its orbit at the first Lagrange point (L1), 1.5 million km from Earth toward the sun. There are two National Aeronautics and Space Administration (NASA) Earth-observing instruments on board: the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR). The purpose of this paper is to describe various capabilities of the DSCOVR EPIC instrument. EPIC views the entire sunlit Earth from sunrise to sunset at the backscattering direction (scattering angles between 168.5° and 175.5°) with 10 narrowband filters: 317, 325, 340, 388, 443, 552, 680, 688, 764, and 779 nm. We discuss a number of preprocessing steps necessary for EPIC calibration including the geolocation algorithm and the radiometric calibration for each wavelength channel in terms of EPIC counts per second for conversion to reflectance units. The principal EPIC products are total ozone (O3) amount, scene reflectivity, erythemal irradiance, ultraviolet (UV) aerosol properties, sulfur dioxide (SO2) for volcanic eruptions, surface spectral reflectance, vegetation properties, and cloud products including cloud height. Finally, we describe the observation of horizontally oriented ice crystals in clouds and the unexpected use of the O2 B-band absorption for vegetation properties.

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 pushbroom 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) 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 %.

The contribution of atmospheric aerosols to the Earth's energy budget is an important and relatively uncertain component of the Earth system, with correspondingly large uncertainties implied for climate models. Comprehensive observations of the vertical profile of aerosol extinction are needed to accurately characterize these particles (e.g. composition, size, spatial and temporal distribution) to properly account for their climate impacts and constrain models. Satellite limb scattering measurements provide superior results for observations of stratospheric aerosols compared to occultation measurements. We are developing a compact instrument called Multi-Angle Stratospheric Aerosol Radiometer (MASTAR) that simplifies the current OMPS Limb Profiler design to fit into a 3U Cubesat configuration, and also provides important supplemental information through the use of multiple simultaneous viewing directions.

Ten wavelength channels of calibrated radiance image data from the Sunlit Earth are obtained every 65 minutes during Northern Hemisphere summer from the DSCOVR/EPIC instrument located near the Earth-Sun Lagrange-1 point (L 1 ), 1.5 million km from the Earth. The L 1 location permitted seven observations of the Moon’s shadow on the Earth for about 3 hours during the 21 August 2017 eclipse. Two of the observations were timed to be over Casper, Wyoming and Columbia, Missouri. Since, the solar irradiances within 5 channels (λ i = 388, 443, 551, 680, and 780 nm) are not strongly absorbed in the atmosphere, they can be used for characterizing eclipse reduction in reflected radiances for the sunlit face of the Earth containing the eclipse shadow. Five channels (λ i = 317.5, 325, 340, 688, and 764 nm) that are partially absorbed in the atmosphere give consistent reductions compared to the non-absorbed channels. This indicates that cloud reflectivities dominate the 317.5 to 780 nm radiances reflected back to space from the sunlit Earth’s disk with a strong contribution from Rayleigh scattering for the shorter wavelengths. A reduction of 9.7 ± 1.7 % in the radiance (387 to 781 nm) reflected from the Earth towards L 1 was obtained for the set of observations on 21 August 2017, while the shadow was in the vicinity of Casper, Wyoming (42.8666° N, 106.3131° W, centered on 17:44:50 UTC). In contrast, when successive non-eclipse days are compared for each wavelength channel, the change in reflected light is much smaller (less than 1 % for 443 nm compared to 9 % during the eclipse). Also measured was the spatially averaged ratio R EN (λ i ) > of reflected radiance within the eclipse totality region to radiances for the same geometry on adjacent non-eclipse days for all 10 wavelength channels. The measured R EN (443 nm) > was smaller for Columbia (35) than for Casper (122), because Columbia had more cloud cover than Casper. R EN (λ i ) forms a useful test of 3-D radiative transfer models for an eclipse in the presence of optically thin clouds. A previously published clear-sky model (Emde and Mayer, 2007) shows results for a nearly overhead eclipse had R EN (340 nm)=1.7 x 10 4 compared to the maximum measured non-averaged R EN (340) at Casper of 515 ± 27 with optically thin clouds under similar geometrical conditions.

A number of satellite‐based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high‐quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO_2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NO_x emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO_2 profiles from a high‐resolution regional model (1 × 1 km^2) constrained by P‐3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO_2 absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO_2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 10^(15) molecules cm^(−2). On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2–50% reduction in polluted areas, partly counterbalancing the well‐documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions.

The Ozone Mapping Profiler Suite (OMPS) was launched aboard the Suomi National Polar-orbiting Partnership spacecraft on October 28, 2011. A successful thorough Early Orbit Checkout (EOC) enabled the current Intensive Calibration and Validation stage. We present our analyses and results of OMPS Nadir early-orbit sensor performance and calibration. We collected and analyzed data from both nominal and diagnostic activities via orbital measurements of detector dark current, sensor linearity, and solar irradiance. Our results demonstrate that the OMPS Nadir sensors smoothly transitioned from ground to orbit by meeting or exceeding sensor level requirements. The orbital measurements agree with the predicted values determined during the prelaunch calibration and characterization of OMPS. Our results also suggest that the effects of charge coupled device (CCD) lattice damage due to energetic particle hits onto the CCD must be accounted for in the dark current calibration.

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.

The Ozone Monitoring Instrument (OMI) was launched on July 15, 2004 on the National Aeronautics and Space Administration's Earth Observing System Aura satellite. The OMI instrument is an ultraviolet-visible imaging spectrograph that uses two-dimensional charge-coupled device detectors to register both the spectrum and the swath perpendicular to the flight direction with a 115/spl deg/ wide swath, which enables global daily ground coverage with high spatial resolution. This paper presents the OMI design and discusses the main performance and calibration features and results.

The Airborne Compact Atmospheric Mapper (ACAM), an ultraviolet/visible/near-infrared spectrometer, has been flown on board the NASA UC-12 aircraft during the DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) campaigns to provide remote sensing observations of tropospheric and boundary layer pollutants from its radiance measurements. To improve 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.

The NASA ESTO-funded Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) development project demonstrates a reconfigurable multi-order airborne spectrometer and tests the performance of spectra separation and filtering on the sensor spectral measurements and subsequent trace gas and aerosol retrievals. The activities support mission risk reduction for the UV-Visible air quality measurements from geostationary orbit for the TEMPO and GEMS missions1 . The project helps advance the retrieval algorithm readiness through retrieval performance tests using scene data taken with varying sensor parameters. We report initial results of the project.

The Ozone Mapping Profiler Suite (OMPS) was launched aboard the Suomi National Polar-orbiting Partnership (Suomi NPP) spacecraft on October 28, 2011. OMPS is meant to continue NOAA/NASA's long-term ozone data record and bridge the gap to the Joint Polar Satellite System (JPSS) missions later this decade. We present results from the OMPS Nadir and Limb sensors' early orbit checkout (EOC) operations with comparisons to pre-launch thermal vacuum tests. Characterization measurements of detector performance show that offset, gain, and read noise trends remain within 0.2% of the pre-launch values with significant margin below sensor requirements. Nadir Total Column detector dark generation rate trends show a slow growth in both halves of the focal plane as compared to initial on-orbit measurements. Nadir solar calibration measurements remain within 2% of the initial in-flight observation and indicate no spatially dependent change to within 1%. Limb Profiler solar calibration trending indicate a potential goniometry correction error as high as 5%. Spectral registration changes based on solar observations are determined to be less than one pixel for the Nadir Total Column and Limb sensors but approximately one pixel for Nadir Profiler. Preliminary comparisons to Thullier reference solar spectral irradiances show wavelength dependent differences greater than 5%.

Assessment of the effect of Vacuum Ultra Violet (VUV) irradiation on the Bidirectional Reflectance Distribution Function (BRDF) of Spectralon is presented in this paper. The sample was a 99% white Spectralon calibration standard irradiated with VUV source positioned at 60° off the irradiation direction for a total of 20 hours. The BRDF before and after VUV irradiation was measured and compared at number of wavelengths in the UV, VIS and IR. Non-isotropic directional degradation of Spectralon diffuser under ionizing radiation was detected at different BRDF measurement geometries primarily at UV spectral range. The 8° directional/hemispherical reflectance of the same sample was also measured and compared from 200nm to 2500nm.

The dark signal on an Ozone Mapper Profiler Suite (OMPS) charge-coupled device (CCD) results when electrons are thermally emitted into the conduction band of pixels in the active and storage regions. It effectively adds offsets to the photon-generated pixel counts and therefore impacts the Sensor Data Record (SDR) performance. This paper presents OMPS on-orbit results from dark current and electrical bias characterization and calibration on the system level. In particular, data from nominal and diagnostic activities has been collected and analyzed to extract general trends and features about the in-flight detector behaviors. The in-flight dark and bias signals are then compared with the prelaunch on-ground performance for each channel. The South Atlantic Anomaly (SAA) impact and temperature dependency are also addressed. The analysis results have demonstrated that the OMPS CCD performance successfully transferred from ground to orbit; the in-flight timing pattern of the nominal dark measurements are well suited to determine general dark currents of the individual pixels, and data collected during the early orbit calibration are sufficient to perform internal consistency checks of sensor dark and bias parameters and instrument behavior. Results also suggest that to minimize the influence of hot pixels and other effects of CCD lattice damage due to energetic particle hits, the dark current shall be updated on a daily basis rather than the weekly basis as planned.

Backscattered ultraviolet (BUV) instruments designed for measuring stratospheric ozone profiles have proven to be robust tools for observing polar mesospheric clouds (PMCs). These measurements are available for more than 30 years, and have been used to demonstrate the existence of long-term variations in PMC occurrence frequency and brightness. The Ozone Monitoring Instrument (OMI) on the EOS Aura satellite provides new and improved capabilities for PMC characterization. OMI uses smaller pixels than previous BUV instruments, which increases its ability to identify PMCs and discern more spatial structure, and its wide cross-track viewing swath provides full polar coverage up to 90 latitude every day in both hemispheres. This cross-track coverage allows the evolution of PMC regions to be followed over several consecutive orbits. Localized PMC variations determined from OMI measurements are consistent with coincident SBUV/2 measurements. Nine seasons of PMC observations from OMI are now available, and clearly demonstrate the advantages of these measurements for PMC analysis.

Optical spectroradiometers used to measure and monitor the radiance output of uniform sources must be thoroughly characterized. The viability of the use of an instrument for such purposes is based upon the establishment of knowledge of its radiometric responsivity characteristics. The NASA Goddard Space Flight Center Radiometric Calibration Laboratory (RCL) has commissioned a new spectroradiometer for use in measurements of irradiance and radiance sources. The spectroradiometer is comprised of a commercial scanning grating, Czerny-Turner double monochromator. This spectroradiometer has been used to make measurements on a number of irradiance and radiance sources over the wavelength range of 300 to 2400 nm. Instrument characterization included determination of stability, functional wavelength calibration and scattered light performance. Comparison measurements were also made with other radiometers. The data gathered from these measurements is presented, analyzed, and discussed.

The Airborne Compact Atmospheric Mapper (ACAM) was designed and built at the NASA Goddard Space Flight Center (GSFC) as part of an effort to provide cost-effective remote sensing observations of tropospheric and boundary layer pollutants and visible imagery for cloud and surface information. ACAM has participated in three campaigns to date aboard NASA's Earth Science Project Office (ESPO) WB-57 aircraft. This paper provides an overview of the instrument design and summarizes its ability to determine the minimal measurable slant-column concentration of nitrogen dioxide (NO2) as well as exploring the calibration stability of commercially available miniature spectrometers.

The NASA Goddard Space Flight Center (GSFC) Radiation Calibration Facility (RCF) maintains several large integrating sphere sources covering the visible and near infrared wavelength range. Two critical requirements of an integrating sphere source are short and long-term operational stability and repeatability. Monitoring the source is essential in determining the origin of systemic errors, thus increasing confidence in source performance, and quantifying repeatability. If monitor data falls outside the established parameters, this is an indication that the source requires maintenance or re-calibration against the National Institute of Science and Technology (NIST) irradiance standard. The GSFC RCF has developed a Filter Radiometer Monitoring System (FRMS) to continuously monitor the performance of its integrating sphere calibration sources in the 400-2400nm region. Sphere output change mechanisms include lamp aging, coating (BaSO 4 ) deterioration, and ambient water vapor level. The FRMS wavelength bands are selected to quantify changes caused by these mechanisms. The FRMS design and operation is presented, as well as data from monitoring three of the RCF's integrating sphere sources.

A variety of instruments have been developed over the past 50 years to measure spectral radiance in absolute units at UV and visible wavelengths with high spectral resolution. While there is considerable experience in the measurement of spectral irradiance, less emphasis has been given to the reliable measurement of spectral radiance from ground observations. We discuss the methodology and calibration procedures for five instruments capable of making such measurements. Four of these instruments are based on double monochromators that scan each wavelength in turn, and one is based on a single monochromator with a charged coupled device (CCD) allowing the recording of all wavelengths simultaneously. The measured spectral radiance deviates between 3% and about 35% depending on the instruments. The results are compared with radiative transfer calculations when the aerosol characteristics of the atmosphere are known.