The Earth Polychromatic Imaging Camera (EPIC), onboard the Deep Space Climate Observatory (DSCOVR) spacecraft, located at the Earth-Sun Lagrange 1 point, has captured a unique optical effect during lunar occultation named “Gaia’s Crown.” In EPIC images, the phenomenon appears as a small “flange” at the Earth–Moon contact when the Moon is roughly half below Earth’s limb; it is present in the visible and near-infrared channels but absent in the ultraviolet. Using atmospheric data and 3D, voxel-based ray tracing models, this effect was identified as a combination of atmospheric distortion and a complex mirage caused by variations in the Earth’s atmosphere. Additionally, it is shown that while satellites closer to the Earth can see a similar phenomenon, Gaia’s Crown presents unique distortion effects that demonstrate how EPIC’s vantage point at 1.5 million kilometers from Earth provides a different perspective on atmospheric optics.

Multispectral images of Jupiter were obtained by the Earth polychromatic imaging camera (EPIC) orbiting at the Earth–Sun Lagrange point 1 (L1) on 15 March 2016 and again on 5 June 2019 using a 30-cm Cassegrain telescope imaging on a 2,048 × 2,048 pixel detector with a 0.62° field of view. The images of Jupiter were obtained using 10 narrow bandpass filters (in the range of 317.5–779.5 nm) that were radiometrically calibrated and designed to have very little out-of-band transmissions. The EPIC instrument was carefully corrected for geometric stray-light effects, pixel non-uniformity (flat fielding), and etaloning (680–780 nm). The Jupiter images were contained in a small disk of diameter 43 pixels near the center of the detector. The resulting images had a spatial resolution of 4,900 km as well as showed clear evidence of limb darkening, the east-west bands, and the red spot of Jupiter. These results were compared with previous measurements from Jupiter filter images obtained by the Hubble space telescope from a ground-based filter instrument at the Tortugas Mountain Observatory operated by New Mexico State University and the portable filter device PlanetCam at Calar Alto Observatory in Spain. The EPIC estimates of the whole-disk albedo are in good agreement with previous high-spectral-resolution spectrometer results (from the European Southern Observatory in La Silla, Chile) in the visible and near-infrared wavelengths but are lower in five ultraviolet (UV) narrow bandpass filter channels (318–388 nm). A possible reason for this disagreement with the spectrometer-estimated UV albedo could be out-of-band stray light from the spectrometer grating. The EPIC observations from L1 have better spatial resolution than ground-based filter measurements and are expected to provide improved estimates of Jupiter’s limb darkening. Absorption by methane was considered during the measurements, and the current mixing ratio 2 × 10−3 is estimated to be insufficient to explain the decrease in albedo between 764 and 779.5 nm unless the reflecting cloud layer is at a pressure of two atmospheres.

The Earth polychromatic imaging camera (EPIC) onboard the deep space climate observatory (DSCOVR) began obtaining fully illuminated Earth images across 10 wavelength bands on 6 July 2015. The ultraviolet bands 317, 325, 340, and 388 nm are used to retrieve the total column ozone (TCO) values at different local times during the day. On 28 June 2019, the spacecraft experienced a gyroscope failure; after recovery, the EPIC TCO values retrieved from 2021 to 2024 still agree well with those obtained from the ground-based Pandora spectrometer instruments in terms of both the hourly and weekly average basis. The hourly EPIC TCO values show more variability than the matched Pandora TCO values but generally deviate within 2% while tracking the shape of the Pandora daily variations in most cases. At 13:30 hours, the TCO data from the ozone and mapping profiler suite (OMPS) and ozone monitoring instrument (OMI) are also observed to frequently agree with the time-matched Pandora and EPIC TCO values. In addition, comparisons were made with the version-3 (V03) hourly TCO retrievals from the US tropospheric monitoring of pollution (TEMPO) geostationary satellite over two North American sites, namely, Toronto (Canada) and Dearborn (Michigan, United States). The long-term weekly lowess average EPIC and Pandora TCO values agree with deviations of less than 2%, as does the 3-week lowess average of the OMPS TCO value. An analysis of the TCO values from Pandora and 1 year of TEMPO V03 suggests that the noon TCO values are 2%–5% higher than the morning and afternoon values.

Observations of trace gases, such as O3, HCHO, and NO2, and their seasonal dependence can be made using satellite and ground-based data from the Ozone Monitoring Instrument (OMI) satellite and Pandora ground-based instruments. Both operate with spectrometers that have similar characteristics in wavelength range and spectral resolution that enable them to retrieve total column amounts of formaldehyde (TCHCHO) and nitrogen dioxide (TCNO2) and total column ozone (TCO). The polar orbiting OMI observes at 13:30 +/- 0:25 LST (local solar time) plus an occasional second side-scan point 90 min later at mid-latitudes. The ground-based Pandora spectrometer system observes the direct sun all day, with a temporal resolution of 2 min. At most sites, the Pandora data show a strong seasonal dependence for TCO and TCHCHO and less seasonal dependence for TCNO2. Use of a low-pass filter LOWESS(3-month) can reveal the seasonal dependence of TCNO2 for both OMI and Pandora at mid-latitude sites usually correlated with seasonal heating using natural gas or oil. Compared to Pandora, OMI underestimates the amount of NO2 air pollution that occurs during most days, as the OMI TCNO2 retrieval occurs around 13:30 +/- 0:25 LST, which tends to be near the frequent minimum of the daily TCNO2 time series. Even when the Pandora data are restricted to between 13:00 and 14:00 LST, OMI retrieves less TCNO2 than Pandora over urban sites because of OMI's large field of view. The seasonal behavior of TCHCHO is mostly caused by the release of HCHO precursors from plant growth and emissions from lakes that peak in the summer, as observed by Pandora and OMI. Long-term averages show that OMI TCHCHO usually has the same seasonal dependence but differs in magnitude from the amount measured by Pandora and is frequently larger. Comparisons of OMI total column NO2 and HCHO with Pandora daily time series show both agreement and disagreement at various sites and for different days, with the Pandora results frequently being larger. For ozone, daily time-dependent comparisons of OMI TCO with those retrieved by Pandora show good agreement in most cases. Additional diurnal comparisons are shown of Pandora TCO with hourly retrievals during a day from the EPIC (Earth Polychromatic Imaging Camera) spacecraft instrument orbiting the Earth-Sun Lagrange point L1.

A technique to determine the radiometric stability of the Earth Polychromatic Imaging Camera (EPIC) and the National Institute of Standards and Technology Advanced Radiometer (NISTAR), the two Earth-viewing instruments operating aboard the Deep Space Climate Observatory (DSCOVR) satellite, which is orbiting the Sun at the Lagrange-1 point, L-1, approximately 1.5 million kilometers away from Earth, has been developed and applied. Apart from the satellite's own measurements, it only uses output from the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate data center (ERA5). This method can be applied to all channels (and not just a subset) and can be repeated periodically to track the instruments' stability. The method includes the removal of climatological diurnal and seasonal cycles, a multivariate regression fitting with selected ERA5 model output parameters, and referencing the data to the EPIC 551-nm channel, which has been determined to show no drift over the entire mission lifetime together with the NISTAR photodiode channel (200-1,100 nm). The obtained sensitivity changes were very small, ranging from a maximum total degradation of 3% over 10 years in the short UV (<340 nm) to no detectable changes for some channels. For the EPIC UV channels, the derived results were confirmed through a comparison of the EPIC data with radiances from the Ozone Mapping and Profiler Suite (OMPS). We attribute this excellent instrument performance mostly to the L-1 orbit, which is not only an ideal location for Earth observation, but is also extremely beneficial (quiet) with respect to instrument performance. At L-1, there are only minor temperature variations and much smaller exposure to charged particles from the Sun compared to satellites orbiting the Earth, which are fully or partly inside the Earth's radiation belts. In this sense, L-1 can be considered "observational and instrumental heaven." The technique described here could only be applied because DSCOVR has two different instruments (EPIC and NISTAR) observing the same Earth flux input. This suggests that it is extremely useful (maybe even essential) to combine imaging instruments (like EPIC) with integrating instruments (like NISTAR) in remote sensing applications.

Abstract. Both The OMI (Ozone Monitoring Instrument) satellite and the Pandora ground-based instruments operate with spectrometers that have similar characteristics in wavelength range and spectral resolution that enable them to retrieve total column amounts of formaldehyde TCHCHO, and nitrogen dioxide TCNO2, and ozone TCO at 13:30 ± 0:45 local time. At most sites, Pandora shows a strong seasonal dependence for TCO and TCHCHO and little seasonal dependence for TCNO2, while OMI sees little seasonal dependence for TCHCHO and TCNO2 but does see seasonal dependence for TCO. The seasonal behavior of TCHCHO is caused by plant growth and emissions from lakes that peak in the summer suggesting that OMI is not correctly retrieving TCHCHO all the way to the Earth’s boundary layer. Since the OMI retrieval is around 13:30 local equator crossing time ± 0:45 and tends to occur near the frequent minimum of the daily TCNO2 time series, OMI underestimates the amount of air pollution that occurs during each year. Better TCNO2 agreement occurs when the Pandora data is averaged between 13:00 and 14:00 hours local time. Comparisons of OMI total column NO2 and HCHO with Pandora daily time series show both agreement and disagreement at various sites and days. Similar comparisons of OMI TCO with those retrieved by Pandora show good agreement in most cases. Additional comparisons are shown of Pandora TCO with hourly retrievals during a day from EPIC (Earth Polychromatic Imaging Camera) spacecraft instrument orbiting the Earth-Sun Lagrange point L1.

Vertical column density (VCD) of nitrogen dioxide (NO2) was measured using Pandora spectrometers at six sites on the Korean Peninsula during the Megacity Air Pollution Studies-Seoul (MAPS-Seoul) campaign from May to June 2015. To estimate the tropospheric NO2 VCD, the stratospheric NO2 VCD from the Ozone Monitoring Instrument (OMI) was subtracted from the total NO2 VCD from Pandora. European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis wind data was used to analyze variations in tropospheric NO2 VCD caused by wind patterns at each site. The Yonsei/SEO site was found to have the largest tropospheric NO2 VCD (1.49 DU on average) from a statistical analysis of hourly tropospheric NO2 VCD measurements. At rural sites, remarkably low NO2 VCDs were observed. However, a wind field analysis showed that trans-boundary transport and emissions from domestic sources lead to an increase in tropospheric NO2 VCD at NIER/BYI and KMA/AMY, respectively. At urban sites, high NO2 VCD values were observed under conditions of low wind speed, which were influenced by local urban emissions. Tropospheric NO2 VCD at HUFS/Yongin increases under conditions of significant transport from urban area of Seoul according to a correlation analysis that considers the transport time lag. Significant diurnal variations were found at urban sites during the MAPS-Seoul campaign, but not at rural sites, indicating that it is associated with diurnal patterns of NO2 emissions from dense traffic.

In this study, the WRF-Chem v4.4 model was utilized to evaluate the sensitivity of O3 simulations with three bottom-up emission inventories (EDGAR-HTAP v2 and v3 and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O3 and its main precursor NO2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8 h average (MDA8) O3 in the model do not completely align with the observations. The model MDA8 O3 had a negative (positive) bias north (south) of 30° N over China. All simulations underestimated the observed CO by 50 %–60 % over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2 and v3 and KORUS v5 simulated the vertical shapes and diurnal patterns of O3 and other precursors effectively, but the model underestimated the observed O3, CO, and HCHO concentrations. Notably, the model aromatic volatile organic compounds (VOCs) were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O3 biases and the effects of the long-range transport on the O3 over South Korea. The doubled CO and VOC emission simulations improved the model O3 simulations for the local-emission-dominant case but led to the model O3 overestimations for the transport-dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea.

Abstract. Monthly averaged total column ozone data ΩMOD from the Merged Ozone Data set (MOD) were examined to show that the latitude-dependent ozone depletion turnaround dates TA(θ) range from 1994 to 1998. ΩMOD used in this study was created by combining data from Solar Backscattered Ultraviolet instruments (SBUV/SBUV-2) and the Ozone Mapping and Profiler Suite (OMPS-NP) from 1979 to 2021. TA(θ) is defined as the date when the zonally average ozone ceased decreasing. The new calculated systematic latitude-dependent TA(θ) shape should appear in atmospheric models that combine the effects of photochemistry and dynamics in their estimate of ozone recovery. Trends of zonally averaged total column ozone in percent per decade were computed before and after TA(θ) using two different trend estimate methods that closely agree, Fourier Series Multivariate Linear Regression and linear regression on annual averages. During the period 1979 to TA(θ) the most dramatic rates of SH ozone loss were PD = −10.9 ± 3 % per decade at 77.5° S and −8.5 ± 0.9 % per decade at 65° S, which is about double the NH rate of loss of PD = −5.6 ± 4 %/decade at 77.5° N and 4.4 ± 1 %/decade at 65° N for the period 1979 toTA(θ). After TA(θ), there has been an increase at 65° S of PD = 1.6 ± 1.4% per decade with smaller increases from 55° S to 25° S and a small decrease at 35° N of −0.4 ± 0.3 %/decade. Except for the Antarctic region, there only has been a small recovery in the Southern Hemisphere toward 1979 ozone values and almost none in the Northern Hemisphere.

Abstract. We describe a new method for estimating the total reflected shortwave energy from the Earth Polychromatic Imaging Camera (EPIC) and compare it with direct measurements from the NIST Advanced Radiometer (NISTAR) instrument (Electrical substitution radiometer) – both are onboard the Lagrange-1 orbiting Deep Space Climate Observatory (DSCOVR). The 6 narrow-band wavelength channels (340 to 780 nm) available from EPIC provide a framework for estimating the integrated spectral energy for each EPIC pixel. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the SCIAMACHY instrument provide spectral information away from the EPIC wavelengths, particularly for wavelengths longer than 780 nm. The total area-weighted reflected shortwave energy from an entire EPIC image is compared with co-temporal Band B Shortwave reflected energy observed by NISTAR. Our analysis from March to December 2017 shows the two are highly correlated with differences ranging from -10 to 10 Watts m-2. The offset bias over the entire period is less than 0.2 Watts m-2. We also compare our EPIC energy maps with the Clouds and the Earth’s Radiant Energy System (CERES) Single Scanner Footprint (SSF) Shortwave (SW) reflected energy observed within 3 hours of an EPIC image. Our EPIC-AVIRIS SW estimate is 5–20 % higher near the EPIC image center and 5–20 % lower near the image edges compared with the CERES SSF.

WRF-Chem and WPS v4.4 source codes and their configurations with namelist files. Emission inventory data sets (EDGAR-HTAP v2 and v3) for 'anthro_emis' input are included. The KORUS v5 emission data are provided with 'wrfchemi' format. The 'namelist.input' contains physics and chemistry options that are used for WRF-Chem model. The model grid information is available in 'namelist.wps'. Kim, K.-M., Kim, S.-W., Seo, S., Blake, D. R., Cho, S., Crawford, J. H., Emmons, L., Fried, A., Herman, J. R., Hong, J., Jung, J., Pfister, G., Weinheimer, A. J., Woo, J.-H., and Zhang, Q.: Sensitivity of the WRF-Chem v4.4 ozone, formaldehyde, and precursor simulations to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2023-132, in review, 2023.

Monthly averaged total column ozone data (ΩMOD(t,θ)) from the NASA Merged Ozone Data Set (MOD) were examined to show that the latitude-dependent (θ) ozone depletion turnaround dates (TA(θ)) range from 1994 to 1998. TA(θ) is defined as the approximate date when the zonally averaged ozone ceased decreasing. ΩMOD data used in this study were created by combining data from Solar Backscattered Ultraviolet instruments (SBUV/SBUV-2) and the Ozone Mapping and Profiler Suite (OMPS-NP) from 1979 to 2021. The newly calculated systematic latitude-dependent hemispherically asymmetric TA(θ) shape currently does not appear in the suite of chemistry–climate models that are part of the Chemistry–Climate Model Validation Activity (CCMVal), which combines the effects of photochemistry, volcanic eruptions, and dynamics in their estimate of ozone recovery. Trends of zonally averaged total column ozone in percent per decade were computed before and after TA(θ) using two different trend estimate methods that closely agree, Fourier series multivariate linear regression and linear regression on annual averages. During the period 1979 to TA(θ), the most dramatic rates of Southern Hemisphere (SH) ozone loss were PD=-10.9±3 % per decade at 77.5∘ S and -8.0±1.1 % per decade at 65∘ S, which is about double the Northern Hemisphere (NH) rate of loss of PD=-5.6±4 % per decade at 77.5∘ N and 4.4±1 % per decade at 65∘ N for the period 1979 to TA(θ). After TA(θ), there was an increase at 65∘ S of PD=1.6±1.4 % per decade with smaller increases from 55 to 25∘ S and a small decrease at 35∘ N of -0.4±0.3 % per decade. Except for the Antarctic region, there only has been a small recovery in the SH toward 1979 ozone values and almost none in the NH.

Abstract. Measured backscattered UV radiances at 388±1.5 nm are converted to Lambert Equivalent Reflectivity (LER) are from EPIC (Earth Polychromatic Imaging Camera) onboard the DSCOVR spacecraft (Deep Space Climate Observatory) orbiting about the Sun-Earth Lagrange-1 (L1) gravitational balance point. The average percent of reflected solar energy in the 388±1.5 nm band is 29.2 % of the global incident solar energy in that band. Maximum reflected 388 nm solar energy RSE, mostly from clouds, occurs during the summer solstice in each hemisphere, December in the Southern Hemisphere SH and June in the Northern Hemisphere NH. The global average RSE (90° S to 90° N) has a maximum in December and a minimum in June showing that the SH cloud reflected energy is greater than that in the NH. Backscattering from land and oceans at 388 nm is small since the average clear-sky reflectivity of the Earth’s surface free of snow and ice is about 0.05. Calculations of RSE based on the 388 nm LER show a 7 % increase during December 2020 in RSE at 40° S to 50° S when the backscattering angle BA was 178.05°, and 6 % at 30° S to 40° S in November 2021 when BA = 177.5° compared to previous years, 2015–2019, with a smaller BA. Comparison of 380 nm RSE at 40° S to 50° S during December 2020 from the low Earth polar-orbiting nadir mapper in the Ozone Mapping and Profiler Suite (OMPS-NM) near 13:30 local solar time suggests that there has been a 5 % increase in SH cloud reflection during December 2020 compared to previous years. This suggests that the observed increase by EPIC is mostly from an increase in cloud cover and not from enhanced backscatter. In the NH RSE values at large EPIC BA (177.5° in June 2020 and 178.2° in June 2021) between 30° N to 60° N show a percent decrease 4.8 % in RSE at 45° N during June 2021 and a 6 % increase during June 2020 at 55° N compared to the previous 4 years. This also suggests that the increase and decrease in RSE are probably related to changes in cloud cover and not backscatter angle effects. Annual integrals of percent reflected solar energy over complete years are almost constant at all latitudes.

The annular solar eclipse on 21 June 2020 passed over desert areas (parts of Central and Eastern Africa, the southern Arabian Peninsula), partly cloudy regions (parts of South Asia and the Himalayas), and the mostly cloudy region in East Asia. Moving around the Earth-Sun Lagrange point 1 (L1), the Earth Polychromatic Imaging Camera (EPIC) instrument on the Deep Space Climate Observatory (DSCOVR) spacecraft captured three sets of images of the sunlit Earth during the eclipse, allowing us to study the impact of the solar eclipse on reflected solar radiation when the underlying surface and/or cloudy conditions in the Moon’s shadow are quite different. We analyzed EPIC images acquired during the 21 June 2020 and 21 August 2017 eclipses. We found that (1) EPIC-observed average spectral as well as spectrally averaged reflectance reductions of the entire sunlit Earth during the 21 June 2020 solar eclipse are distinctly different from those during the total solar eclipse of 21 August 2017; (2) the reduction of spectral reflectance depends strongly on underlying reflector properties, including the brightness, the area coverage of each reflector in the penumbra and the average distance to the center of the Moon’s shadow.

Earth Polychromatic Imaging Camera occupies a unique point of view for an Earth imager by being located approximately 1.5 million km from the planet at Earth-Sun Lagrange point, L1. This creates a number of unique challenges in geolocation, some of which are distance and mission specific. To solve these problems, algorithmic adaptations need to be made for calculations used for standard geolocation solutions, as well as artificial intelligence-based corrections for star tracker attitude and optical issues. This paper discusses methods for resolving these issues and bringing the geolocation solution to within requirements.

The inactivation time for the SARS CoV-2 virus, mostly by a portion of UVB spectrum (290–315 nm) in sunlight, has been estimated using radiative transfer calculations and a relative wavelength sensitivity virus inactivation action spectrum A LS . The action spectrum is adjusted for the SARS CoV-2 virus using a derived UV dose D 90 = 3.2 J/m 2 for 90% inactivation to match laboratory results for the inactivation of SARS CoV-2 virus droplets on steel mesh. Estimation of the time for 90% inactivation T 90 at a specific geographic location can be simplified using the commonly published or calculated UV index (UVI). The use of UVI has the advantage that information on the amount of ozone, the site altitude, and the degree of cloud cover are built into the published UVI calculation. Simple power-law T 90 (UVI) = a UVI b fitting equations are derived that provide estimates of T 90 (UVI) for 270 specific locations. Using the results from the 270 locations, a generalized latitude θ dependence is presented for the coefficients a (θ) and b (θ) that enables T 90 (θ, UVI) to be estimated for 60°S ≤ θ ≤ 60°N and for noon and 2 h around local solar noon.

Discrete wavelength radiance measurements from the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) allows derivation of global synoptic maps of total and tropospheric ozone columns every hour during Northern Hemisphere (NH) Summer or 2 hours during Northern Hemisphere winter. In this study, we present version 3 retrieval of Earth Polychromatic Imaging Camera ozone that covers the period from June 2015 to the present with improved geolocation, calibration, and algorithmic updates. The accuracy of total and tropospheric ozone measurements from EPIC have been evaluated using correlative satellite and ground-based total and tropospheric ozone measurements at time scales from daily averages to monthly means. The comparisons show good agreement with increased differences at high latitudes. The agreement improves if we only accept retrievals derived from the EPIC 317 nm triplet and limit solar zenith and satellite looking angles to 70°. With such filtering in place, the comparisons of EPIC total column ozone retrievals with correlative satellite and ground-based data show mean differences within ±5-7 Dobson Units (or 1.5–2.5%). The biases with other satellite instruments tend to be mostly negative in the Southern Hemisphere while there are no clear latitudinal patterns in ground-based comparisons. Evaluation of the EPIC ozone time series at different ground-based stations with the correlative ground-based and satellite instruments and ozonesondes demonstrated good consistency in capturing ozone variations at daily, weekly and monthly scales with a persistently high correlation (r 2 > 0.9) for total and tropospheric columns. We examined EPIC tropospheric ozone columns by comparing with ozonesondes at 12 stations and found that differences in tropospheric column ozone are within ±2.5 DU (or ∼±10%) after removing a constant 3 DU offset at all stations between EPIC and sondes. The analysis of the time series of zonally averaged EPIC tropospheric ozone revealed a statistically significant drop of ∼2–4 DU (∼5–10%) over the entire NH in spring and summer of 2020. This drop in tropospheric ozone is partially related to the unprecedented Arctic stratospheric ozone losses in winter-spring 2019/2020 and reductions in ozone precursor pollutants due to the COVID-19 pandemic.

School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA 8 National Center for Atmospheric Research, Boulder, Colorado, USA 9 University of Maryland Baltimore County JCET, Baltimore, Maryland, USA 10 Royal Netherlands Meteorological Institute, De Bilt, the Netherlands 11 Wageningen University, Meteorology and Air Quality Group, Wageningen, the Netherlands 12 NASA Goddard Space Flight Center, Greenbelt, Maryland, USA 13 Universities Space Research Association, Columbia, Maryland, USA 14 National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection 15

Earth Polychromatic Imaging Camera (EPIC) raw level-0 (L0) data in one channel is a 12-bit 2,048 × 2,048 pixels image array plus auxiliary data such as telemetry, temperature, 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 convert counts to 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.

Nitrogen oxides (NO x =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 night-time, 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 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 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 NO x emissions in the National Emissions Inventory (NEI) 2011.