SCanning Imaging Absorption spectroMeter For Atmospheric CHartographY Research Articles

Unusual Enhancement of the Optical Depth on the Continental Shelf Depth Latitudinal Variation in the Stratospheric Polar Vortex

The Antarctic ozone hole has attracted attention concerning global climate change. Breakthroughs regarding ozone observation methods and the formation principles of ozone holes have occurred. This study compared the slant column ozone obtained from SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) Level 1 optical spectroscopy data processed by QDOAS software with that reconstructed from SCIAMACHY Level 2 ozone data using geographic information to obtain the optical depth coefficients. The global distribution of optical depth coefficients reveals latitudinal homogeneity, whereas the distribution of coefficients in the polar regions reveals heterogeneity. This heterogeneity has an annual variation pattern, alternating between strong and weak distributions in the Arctic and Antarctic regions. It is most evident in the Palmer Peninsula of Antarctica, where the optical depth coefficients were significantly higher than those of the surrounding regions at the same latitude. This analysis excluded the atmospheric pressure influence and suggested the influence of the continental shelf depth. The protrusion of the continental shelf depth changes the optical depth coefficients owing to the geographical proximity of the Antarctic Palmer Peninsula to South America, which separates the Atlantic and Pacific Oceans in an east–west direction.

Investigation of three-dimensional radiative transfer effects for UV–Vis satellite and ground-based observations of volcanic plumes

Abstract. We investigate effects of the three-dimensional (3D) structure of volcanic plumes on the retrieval results of satellite and ground-based UV–Vis observations. For the analysis of such measurements, 1D scenarios are usually assumed (the atmospheric properties only depend on altitude). While 1D assumptions are well suited for the analysis of many atmospheric phenomena, they are usually less appropriate for narrow trace gas plumes. For UV–Vis satellite instruments with large ground pixel sizes like the Global Ozone Monitoring Experiment-2 (GOME-2), the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) or the Ozone Monitoring Instrument (OMI), 3D effects are of minor importance, but usually these observations are not sensitive to small volcanic plumes. In contrast, observations of the TROPOspheric Monitoring Instrument (TROPOMI) on board Sentinel-5P have a much smaller ground pixel size (3.5 × 5.5 km2). Thus, on the one hand, TROPOMI can detect much smaller plumes than previous instruments. On the other hand, 3D effects become more important, because the TROPOMI ground pixel size is smaller than the height of the troposphere and also smaller than horizontal atmospheric photon path lengths in the UV–Vis spectral range. In this study we investigate the following 3D effects using Monte Carlo radiative transfer simulations: (1) the light-mixing effect caused by horizontal photon paths, (2) the saturation effect for strong SO2 absorption, (3) geometric effects related to slant illumination and viewing angles and (4) plume side-effects related to slant illumination angles and photons reaching the sensor from the sides of volcanic plumes. The first two effects especially can lead to a strong and systematic underestimation of the true trace gas content if 1D retrievals are applied (more than 50 % for the light-mixing effect and up to 100 % for the saturation effect). Besides the atmospheric radiative transfer, the saturation effect also affects the spectral retrievals. Geometric effects have a weaker influence on the quantitative analyses but can lead to a spatial smearing of elevated plumes or even to virtual double plumes. Plume side-effects are small for short wavelengths but can become large for longer wavelengths (up to 100 % for slant viewing and illumination angles). For ground-based observations, most of the above-mentioned 3D effects are not important because of the narrow field of view (FOV) and the closer distance between the instrument and the volcanic plume. However, the light-mixing effect shows a similar strong dependence on the horizontal plume extension as for satellite observations and should be taken into account for the analysis of ground-based observations.

Spatiotemporal Variations of XCH4 across China during 2003–2021 Based on Observations from Multiple Satellites

Atmospheric methane (CH4) is an important greenhouse gas that can reflect variations of CH4 emissions and sinks. This study aimed to detect spatial and temporal variations of atmospheric CH4 concentrations in China during 2003–2021 based on CH4 column-averaged dry-air mole fraction (XCH4) products from three satellites, namely, Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), Greenhouse Gases Observing Satellite (GOSAT), and Copernicus Sentinel-5 Precursor (S5P). The results revealed that XCH4 observed from three satellites showed high agreement in spatiotemporal variations and demonstrated good consistency with ground station measurements. The correlation coefficients (r) between the three satellites were 0.72 and 0.73, and the correlation coefficients for the ground stations were 0.79, 0.66, 0.03, 0.21, 0.70, and 0.80. The spatial distribution of XCH4 in China was generally high in the east and low in the west and close to that of CH4 emissions, indicating that CH4 emission sources dominated the spatial variations of atmospheric XCH4. From 2003 to 2006, XCH4 remained stable with an annual growth rate of 0.51 ppb·yr−1 and then abruptly increased with an overall growth rate of 6.96 ppb·yr−1. There were obvious seasonal changes in XCH4, with peaks in autumn and summer and nadir in winter and spring. These seasonal variations of XCH4 were related to CH4 emissions from rice planting. Rice cultivation areas generally had high XCH4 concentrations, and the growth cycle of rice plants significantly contributed to seasonal variations of XCH4 in the main rice planting areas. These results provide scientific data that could encourage decision-makers to enact policies and processes to reduce methane emissions.

Sensitivity Analysis of Ozone Profiles Retrieved from SCIAMACHY Limb Radiance Based on the Weighted Multiplicative Algebraic Reconstruction Technique

A detailed sensitivity analysis of ozone density profile retrieval was applied to scattering solar radiance spectra measured with the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument aboard the ENVIronmental SATellite (ENVISAT). The vertical density distribution of ozone between 10 and 69 km was obtained using the weighted multiplicative algebraic reconstruction technique and the radiative transfer model for SCIAMACHY. This study investigates the error sources for the retrieved ozone profiles, which are relevant to explain the difference between two independent instruments. The numerical simulation method was adapted to quantify the impact of various error sources on the retrieval accuracy of ozone profiles. First, the tangent height (TH) registration was found to be the largest error source. Assuming an aerosol-free atmosphere, under the condition of background aerosol, the ozone profile showed a negative deviation of ~2–10% below 40 km. With an incorrect a priori profile, ozone estimates may result in a 5–10% average error at the upper and lower boundaries. The ozone retrieval error caused by the uncertainty of surface albedo, ozone absorption cross-section, temperature, pressure profile, and low clouds was relatively small. The random error caused by the disturbance of the measurement vector obeying a Gaussian distribution did not exceed 5%. Second, the estimation of various error sources for different solar zenith angles was investigated. The error sources most strongly dependent on SZAs were aerosols, surface albedo, and clouds. Finally, the error estimation of the ozone retrieval between the northern hemisphere (NH) and the southern hemisphere (SH) was investigated, revealing that there were no strong interhemispheric differences, except for cloud height. These results can be used for interpretation of instrumental comparisons and validation of SCIAMACHY ozone profiles retrieved from different algorithms in a rigorous manner.

Evaluation of 10-Year NOAA/NASA Suomi NPP and NOAA-20 VIIRS Reflective Solar Band (RSB) Sensor Data Records (SDR) over Deep Convective Clouds

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument onboard the Suomi NPP (S-NPP) and the NOAA-20 satellites that provides state-of-the-art Earth observations for ocean, land, aerosol, and cloud applications. VIIRS Reflective Solar Band (RSB) Sensor Data Records (SDR, or Level 1b products) are calibrated and produced independently by The National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) VIIRS science teams. Multiple versions of S-NPP and NOAA-20 VIIRS SDRs are available to date. This study evaluates the long-term calibration stability, biases, and inter-channel consistency of S-NPP and NOAA-20 VIIRS SDRs generated by NOAA and NASA over Deep Convective Clouds (DCC) to support downstream applications, especially climate data record studies. Five VIIRS RSB SDRs were analyzed in this study: (1) NOAA version 2 S-NPP VIIRS reprocessed SDRs (NOAA-NPP-V2, 2012–2020), (2) NASA Collection 1 S-NPP VIIRS SDRs (NASA-NPP-C1, 2012–2021), (3) NASA Collection 2 S-NPP VIIRS SDRs (NASA-NPP-C2, 2012–2021), (4) NOAA constant F-factor calibrated NOAA-20 VIIRS SDRs (NOAA-N20-ConstF, 2018–2021), and (5) NASA Collection 2 NOAA-20 VIIRS SDRs (NASA-N20-C2, 2018–2021). The DCC time series analysis results indicate that the calibrations of the three S-NPP VIIRS RSB SDRs are generally stable, with trends within ±0.1%/year for all RSBs, except for M3–M4 (all three S-NPP SDRs) and I3 (NASA-NPP-C1 only). The calibration of NASA-NPP-C2 SDRs is more uniform at individual detector levels. NOAA-NPP-V2 and NASA-NPP-C1 SDRs exhibit non-negligible time-dependent detector level degradation in M1–M4 (up to 1.5% in 2020–2021), causing striping in the SDR imagery. The biases between NOAA and NASA S-NPP VIIRS RSB SDRs are from 0.1% to 2.4%. The calibrations of the two NOAA-20 VIIRS RSB SDRs are also generally stable, with trends within ±0.16%/year. Small downward trends were observed in the visible and near-infrared (VIS/NIR) bands, and small upward trends were observed in the shortwave infrared (SWIR) bands for both NOAA and NASA NOAA-20 SDRs. The biases between NOAA and NASA NOAA-20 VIIRS RSB SDRs are nearly constant over time and within ±0.2% for VIS/NIR bands and ±0.7% for SWIR bands. There exists large inter-satellite biases between S-NPP and NOAA-20 VIIRS SDRs, especially in the VIS/NIR bands (up to 4.5% for NOAA SDRs and up to 7% for NASA SDRs). In addition, the DCC reflectance of S-NPP VIIRS RSB spectral bands is more consistent with that of the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) than that of NOAA-20. Bands M4 and M9 seem out of family in all five S-NPP and NOAA-20 RSB SDRs evaluated.

An optimal estimation-based retrieval of upper atmospheric oxygen airglow and temperature from SCIAMACHY limb observations

Abstract. An optimal estimation-based algorithm is developed to retrieve the number density of excited oxygen (O2) molecules that generate airglow emissions near 0.76 µm (b1Σg+ or A band) and 1.27 µm (a1Δg or 1Δ band) in the upper atmosphere. Both oxygen bands are important for the remote sensing of greenhouse gases. The algorithm is applied to the limb spectra observed by the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument in both the nominal (tangent heights below ∼ 90 km) and mesosphere–lower thermosphere (MLT) modes (tangent heights spanning 50–150 km). The number densities of emitting O2 in the a1Δg band are retrieved in an altitude range of 25–100 km near-daily in 2010, providing a climatology of O2 a1Δg-band airglow emission. This climatology will help disentangle the airglow from backscattered light in nadir remote sensing of the a1Δg band. The global monthly distributions of the vertical column density of emitting O2 in a1Δg state show mainly latitudinal dependence without other discernible geographical patterns. Temperature profiles are retrieved simultaneously from the spectral shapes of the a1Δg-band airglow emission in the nominal limb mode (valid altitude range of 40–100 km) and from both a1Δg- and b1Σg+-band airglow emissions in the MLT mode (valid range of 60–105 km). The temperature retrievals from both airglow bands are consistent internally and in agreement with independent observations from the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), with the absolute mean bias near or below 5 K and root mean squared error (RMSE) near or below 10 K. The retrieved emitting O2 number density and temperature provide a unique dataset for the remote sensing of greenhouse gases and constraining the chemical and physical processes in the upper atmosphere.

Total water vapour columns derived from Sentinel 5P using the AMC-DOAS method

Abstract. Water vapour is the most abundant natural greenhouse gas in the Earth's atmosphere, and global data sets are required for meteorological applications and climate research. The Tropospheric Monitoring Instrument (TROPOMI) on board Sentinel-5 Precursor (S5P) launched on 13 October 2017 has a high spatial resolution of around 5 km and a daily global coverage. Currently, there is no operational total water vapour product for S5P measurements. Here, we present first results of a new scientific total column water vapour (TCWV) product for S5P using the so-called air-mass-corrected differential optical absorption spectroscopy (AMC-DOAS) scheme. This method analyses spectral data between 688 and 700 nm and has already been successfully applied to measurements from the Global Monitoring Experiment (GOME) on ERS-2, the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on Envisat and GOME-2 on MetOp. The adaptation of the AMC-DOAS method to S5P data requires an additional post-processing procedure to correct the influences of surface albedo, cloud height and cloud fraction. The quality of the new AMC-DOAS S5P water vapour product is assessed by comparisons with data from GOME-2 on MetOp-B retrieved also with the AMC-DOAS algorithm and with four independent data sets, namely reanalysis data from the European Centre for Medium range Weather Forecast (ECMWF ERA5), data obtained by the Special Sensor Microwave Imager and Sounder (SSMIS) flown on the Defense Meteorological Satellite Program (DMSP) platform 16 and two scientific S5P TCWV products derived from TROPOMI measurements. Both are recently published TCWV products for S5P provided by the Max Planck Institute for Chemistry (MPIC) in Mainz and the Netherlands Institute for Space Research (SRON), Utrecht. The SRON TCWV is limited to clear-sky scenes over land. These comparisons reveal a good agreement between the various data sets but also some systematic differences between all of them. On average, the daily derived offset between AMC-DOAS S5P TCWV and AMC-DOAS GOME-2B TCWV is negative (around −1.5 kg m−2) over land and positive over ocean surfaces (more than 1.5 kg m−2). In contrast, SSMIS TCWV is on average lower than AMC-DOAS S5P TCWV by about 3 kg m−2. Monthly averaged ERA5 TCWV and AMC-DOAS S5P TCWV comparison shows spatial features over both land and water surface. Over land, there are systematic spatial structures. There are larger differences between AMC-DOAS S5P TCWV and ERA5 TCWV in tropical regions. Over sea, AMC-DOAS S5P TCWV is slightly lower than ERA5 TCWV by around 2 kg m−2. The AMC-DOAS S5P TCWV and S5P TCWV from MPIC agree on average within 1 kg m−2 over both land and ocean. TCWV from SRON shows daily global averaged differences to AMC-DOAS S5P TCWV of around 1.2 kg m−2. All of these differences are in line with the accuracy of these products and with the typical range of differences of 5 kg m−2 obtained when comparing different TCWV data sets. The AMC-DOAS TCWV product for S5P provides therefore a valuable new and independent data set for atmospheric applications which also has a higher spatial coverage than the other S5P TCWV products.

Simultaneous Retrievals of Nighttime O(3P) and Total OH Densities From Satellite Observations of Meinel Band Emissions

AbstractRetrieving the total number density [OH], which is used in the chemical balance equations and is the sum of both ground and excited vibrational state populations, is a challenging problem to such a degree there exist no such estimates from recent space observations. We present a novel retrieval approach to simultaneously and self‐consistently derive both [O(3P)] and total [OH] in the nighttime mesosphere and lower thermosphere which operates with the Meinel band volume emission rates and their ratios. Its application to the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) and Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) observations shows a good agreement of the retrieved [O(3P)] taking into account the measurement uncertainties and variation of model inputs used. However, retrieved [OH] show a large discrepancy, mainly above 90 km. SCIAMACHY [OH] is generally in good agreement with WACCM [OH] after accounting for uncertainties, while SABER OH is larger than WACCM [OH] by up to a factor of 2.

Spatially resolved evaluation of Earth system models with satellite column-averaged CO<sub>2</sub>

Abstract. Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) showed large uncertainties in simulating atmospheric CO2 concentrations. We utilize the Earth System Model Evaluation Tool (ESMValTool) to evaluate emission-driven CMIP5 and CMIP6 simulations with satellite data of column-average CO2 mole fractions (XCO2). XCO2 time series show a large spread among the model ensembles both in CMIP5 and CMIP6. Compared to the satellite observations, the models have a bias of +25 to −20 ppmv in CMIP5 and +20 to −15 ppmv in CMIP6, with the multi-model mean biases at +10 and +2 ppmv, respectively. The derived mean atmospheric XCO2 growth rate (GR) of 2.0 ppmv yr−1 is overestimated by 0.4 ppmv yr−1 in CMIP5 and 0.3 ppmv yr−1 in CMIP6 for the multi-model mean, with a good reproduction of the interannual variability. All models capture the expected increase of the seasonal cycle amplitude (SCA) with increasing latitude, but most models underestimate the SCA. Any SCA derived from data with missing values can only be considered an “effective” SCA, as the missing values could occur at the peaks or troughs. The satellite data are a combined data product covering the period 2003–2014 based on the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)/Envisat (2003–2012) and Thermal And Near infrared Sensor for carbon Observation Fourier transform spectrometer/Greenhouse Gases Observing Satellite (TANSO-FTS/GOSAT) (2009–2014) instruments. While the combined satellite product shows a strong negative trend of decreasing effective SCA with increasing XCO2 in the northern midlatitudes, both CMIP ensembles instead show a non-significant positive trend in the multi-model mean. The negative trend is reproduced by the models when sampling them as the observations, attributing it to sampling characteristics. Applying a mask of the mean data coverage of each satellite to the models, the effective SCA is higher for the SCIAMACHY/Envisat mask than when using the TANSO-FTS/GOSAT mask. This induces an artificial negative trend when using observational sampling over the full period, as SCIAMACHY/Envisat covers the early period until 2012, with TANSO-FTS/GOSAT measurements starting in 2009. Overall, the CMIP6 ensemble shows better agreement with the satellite data than the CMIP5 ensemble in all considered quantities (XCO2, GR, SCA and trend in SCA). This study shows that the availability of column-integral CO2 from satellite provides a promising new way to evaluate the performance of Earth system models on a global scale, complementing existing studies that are based on in situ measurements from single ground-based stations.

Stratospheric aerosol extinction profiles from SCIAMACHY solar occultation

Abstract. The Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument on Envisat provided, between August 2002 and April 2012, measurements of solar and Earthshine spectra from the UV to the shortwave infrared spectral region in multiple viewing geometries. We present a new approach to derive stratospheric aerosol extinction profiles from SCIAMACHY solar occultation measurements based on an onion-peeling method similar to the onion-peeling differential optical absorption spectroscopy (DOAS) retrieval, which has already been successfully used for the derivation of greenhouse gas profiles. Since the retrieval of aerosol extinction requires as input measured transmissions in absolute units, an improved radiometric calibration of the SCIAMACHY solar occultation measurements has been developed, which considers various instrumental and atmospheric effects specific to solar occultation. The aerosol extinction retrieval can in principle be applied to all wavelengths measured by SCIAMACHY. As a first application, we show results for 452, 525 and 750 nm. The SCIAMACHY solar occultation time series has been processed, covering a latitudinal range of about 50–70∘ N. Reasonable aerosol extinctions are derived between about 15 and 30 km with typically larger uncertainties at higher altitudes due to decreasing aerosol extinction. Comparisons with collocated Stratospheric Aerosol and Gas Experiment II (SAGE-II) and SCIAMACHY limb aerosol data products revealed good agreement with essentially no mean bias. However, dependent on altitude, differences of up to ±20 %–30% to SAGE-II at 452 and 525 nm are observed. Similar results are obtained from comparisons with SAGE-III. SCIAMACHY solar occultation data at 750 nm have been compared with corresponding SAGE-III, Optical Spectrograph and InfraRed Imager System (OSIRIS) and SCIAMACHY limb results. The agreement with SCIAMACHY limb data at 750 nm is within 5 %–20 % between 17 and 27 km. SAGE-III and OSIRIS show at this wavelength and altitude range on average about 40 % and 25 % smaller values, with some additional 10 %–20 % modulation with altitude. The altitude variations in the differences are mainly caused by systematic vertical oscillations in the SCIAMACHY occultation data of up to 30 % below about 25 km. These oscillations decrease to amplitudes below 10 % with increasing number of collocations and are no longer visible in monthly anomalies. Major volcanic eruptions as well as occurrences of polar stratospheric clouds (PSCs) can be identified in the time series of aerosol extinction data and related anomalies. The influence of the quasi-biennial oscillation (QBO) is visible above 25 km.

Optimised degradation correction for SCIAMACHY satellite solar measurements from 330 to 1600 nm by using the internal white light source

Abstract. SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) on-board the European Environmental Satellite (Envisat) provided spectrally resolved measurements in the wavelength range from 0.24 to 2.4 µm by looking into the Earth's atmosphere using different viewing geometries (limb, nadir, solar, and lunar occultation). These observations were used to derive a multitude of parameters, in particular atmospheric trace gas amounts. In addition to radiance measurements solar spectral irradiances (SSIs) were measured on a daily basis. The instrument was operating for nearly a decade, from August 2002 to April 2012. Due to the harsh space environment, it suffered from continuous optical degradation. As part of recent radiometric calibration activities an optical (physical) model was introduced that describes the behaviour of the scanner unit of SCIAMACHY with time (Krijger et al., 2014). This model approach accounts for optical degradation by assuming contamination layers on optical surfaces in the scanner unit. The variation in layer thicknesses of the various optical components is determined from the combination of solar measurements from different monitoring light paths available for SCIAMACHY. In this paper, we present an optimisation of this degradation correction approach, which in particular improves the solar spectral data. An essential part of the modification is the use of measurements from SCIAMACHY's internal white light source (WLS) in combination with direct solar measurements. The WLS, as an independent light source, therefore, gives an opportunity to better separate instrument variations and natural solar variability. However, the WLS emission depends on its burning time and changes with time as well. To use these measurements in the optimised degradation correction, the change in the WLS emission in space needs to be characterised first. The changes in the WLS with accumulated burning time are in good agreement with detailed laboratory lamp studies by Sperling et al. (1996). Although the optimised degradation-corrected SCIAMACHY SSIs still show some instrumental issues when compared to SSI measurements from other instruments and model reconstructions, our study demonstrates the potential for the use of an internal WLS for degradation monitoring.

The use of the 1.27 µm O<sub>2</sub> absorption band for greenhouse gas monitoring from space and application to MicroCarb

Abstract. Monitoring CO2 from space is essential to characterize the spatiotemporal distribution of this major greenhouse gas and quantify its sources and sinks. The mixing ratio of CO2 to dry air can be derived from the CO2∕O2 column ratio. The O2 column is usually derived from its absorption signature on the solar reflected spectra over the O2 A band (e.g. Orbiting Carbon Observatory-2 (OCO-2), Thermal And Near infrared Sensor for carbon Observation (TANSO)/Greenhouse Gases Observing Satellite (GOSAT), TanSat). As a result of atmospheric scattering, the atmospheric path length varies with the aerosols' load, their vertical distribution, and their optical properties. The spectral distance between the O2 A band (0.76 µm) and the CO2 absorption band (1.6 µm) results in significant uncertainties due to the varying spectral properties of the aerosols over the globe. There is another O2 absorption band at 1.27 µm with weaker lines than in the A band. As the wavelength is much closer to the CO2 and CH4 bands, there is less uncertainty when using it as a proxy of the atmospheric path length to the CO2 and CH4 bands. This O2 band is used by the Total Carbon Column Observing Network (TCCON) implemented for the validation of space-based greenhouse gas (GHG) observations. However, this absorption band is contaminated by the spontaneous emission of the excited molecule O2*, which is produced by the photo-dissociation of O3 molecules in the stratosphere and mesosphere. From a satellite looking nadir, this emission has a similar shape to the absorption signal that is used. In the frame of the CNES (Centre National d'Études Spatiales – the French National Centre for Space Studies) MicroCarb project, scientific studies have been performed in 2016–2018 to explore the problems associated with this O2* airglow contamination and methods to correct it. A theoretical synthetic spectrum of the emission was derived from an approach based on A21 Einstein coefficient information contained in the line-by-line high-resolution transmission molecular absorption (HITRAN) 2016 database. The shape of our synthetic spectrum is validated when compared to O2* airglow spectra observed by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)/Envisat in limb viewing. We have designed an inversion scheme of SCIAMACHY limb-viewing spectra, allowing to determine the vertical distribution of the volume emission rate (VER) of the O2* airglow. The VER profiles and corresponding integrated nadir intensities were both compared to a model of the emission based on the Reactive Processes Ruling the Ozone Budget in the Stratosphere (REPROBUS) chemical transport model. The airglow intensities depend mostly on the solar zenith angle (both in model and data), and the model underestimates the observed emission by ∼15 %. This is confirmed with SCIAMACHY nadir-viewing measurements over the oceans: in such conditions, we have disentangled and retrieved the nadir O2* emission in spite of the moderate spectral resolving power (∼860) and found that the nadir SCIAMACHY intensities are mostly dictated by solar zenith angle (SZA) and are larger than the model intensities by a factor of ∼1.13. At a fixed SZA, the model airglow intensities show very little horizontal structure, in spite of ozone variations. It is shown that with the MicroCarb spectral resolution power (25 000) and signal-to-noise ratio (SNR), the contribution of the O2* emission at 1.27 µm to the observed spectral radiance in nadir viewing may be disentangled from the lower atmosphere/ground absorption signature with a great accuracy. Indeed, simulations with 4ARCTIC radiative transfer inversion tool have shown that the CO2 mixing ratio may be retrieved with the accuracy required for quantifying the CO2 natural sources and sinks (pressure-level error ≤1 hPa; XCO2 accuracy better than 0.4 ppmv) with the O2 1.27 µm band only as the air proxy (without the A band). As a result of these studies (at an intermediate phase), it was decided to include this band (B4) in the MicroCarb design, while keeping the O2 A band for reference (B1). Our approach is consistent with the approach of Sun et al. (2018), who also analysed the potential of the O2 1.27 µm band and concluded favourably for GHG monitoring from space. We advocate for the inclusion of this O2 band on other GHG monitoring future space missions, such as GOSAT-3 and EU/European Space Agency (ESA) CO2-M missions, for a better GHG retrieval.

A comparison of OH nightglow volume emission rates as measured by SCIAMACHY and SABER

Abstract. Hydroxyl (OH) short-wave infrared emissions arising from OH(4-2, 5-2, 8-5, 9-6) as measured by channel 6 of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) are used to derive concentrations of OH(v=4, 5, 8, and 9) between 80 and 96 km. Retrieved concentrations are used to simulate OH(5-3, 4-2) integrated radiances at 1.6 µm and OH(9-7, 8-6) at 2.0 µm as measured by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument, which are not fully covered by the spectral range of SCIAMACHY measurements. On average, SABER “unfiltered” data are on the order of 40 % at 1.6 µm and 20 % at 2.0 µm larger than the simulations using SCIAMACHY data. “Unfiltered” SABER data are a product, which accounts for the shape, width, and transmission of the instrument's broadband filters, which do not cover the full ro-vibrational bands of the corresponding OH transitions. It is found that the discrepancy between SCIAMACHY and SABER data can be reduced by up to 50 %, if the filtering process is carried out manually using published SABER interference filter characteristics and the latest Einstein coefficients from the HITRAN database. Remaining differences are discussed with regard to model parameter uncertainties and radiometric calibration.

Comparison of south-east Atlantic aerosol direct radiative effect over clouds from SCIAMACHY, POLDER and OMI–MODIS

Abstract. The direct radiative effect (DRE) of aerosols above clouds has been found to be significant over the south-east Atlantic Ocean during the African biomass burning season due to elevated smoke layers absorbing radiation above the cloud deck. So far, global climate models have been unsuccessful in reproducing the high DRE values measured by various satellite instruments. Meanwhile, the radiative effects by aerosols have been identified as the largest source of uncertainty in global climate models. In this paper, three independent satellite datasets of DRE during the biomass burning season in 2006 are compared to constrain the south-east Atlantic radiation budget. The DRE of aerosols above clouds is derived from the spectrometer SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), the polarimeter Polarization and Directionality of the Earth's Reflectances (POLDER), and collocated measurements by the spectrometer Ozone Monitoring Instrument (OMI) and the imager Moderate Resolution Imaging Spectroradiometer (MODIS). All three datasets confirm the high DRE values during the biomass season, underlining the relevance of local aerosol effects. Differences between the instruments can be attributed mainly to sampling issues. When these are accounted for, the remaining differences can be explained by a higher cloud optical thickness (COT) derived from POLDER compared to the other instruments and a neglect of aerosol optical thickness (AOT) at shortwave infrared (SWIR) wavelengths in the method used for SCIAMACHY and OMI–MODIS. The higher COT from POLDER by itself can explain the difference found in DRE between POLDER and the other instruments. The AOT underestimation is mainly evident at high values of the aerosol DRE and accounts for about a third of the difference between POLDER and OMI–MODIS DRE. The datasets from POLDER and OMI–MODIS effectively provide lower and upper bounds for the aerosol DRE over clouds over the south-east Atlantic, which can be used to challenge global circulation models (GCMs). Comparisons of model and satellite datasets should also account for sampling issues. The complementary DRE retrievals from OMI–MODIS and POLDER may benefit from upcoming satellite missions that combine spectrometer and polarimeter measurements.

CO2 Concentration, A Critical Factor Influencing the Relationship between Solar-induced Chlorophyll Fluorescence and Gross Primary Productivity

The uncertainty of carbon fluxes of the terrestrial ecosystem is the highest among all flux components, calling for more accurate and efficient means to monitor land sinks. Gross primary productivity (GPP) is a key index to estimate the terrestrial ecosystem carbon flux, which describes the total amount of organic carbon fixed by green plants through photosynthesis. In recent years, the solar-induced chlorophyll fluorescence (SIF), which is a probe for vegetation photosynthesis and can quickly reflect the state of vegetation growth, emerges as a novel and promising proxy to estimate GPP. The launch of Orbiting Carbon Observatory 2 (OCO-2) further makes it possible to estimate GPP at a finer spatial resolution compared with Greenhouse Gases Observing Satellite (GOSAT), Global Ozone Monitoring Experiment-2 (GOME-2) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). However, whether the relationship between GPP and SIF is linear or non-linear has always been controversial. In this research, we proposed a new model to estimate GPP using SIF and the atmospheric CO2 concentration from OCO-2 as critical driven factors simultaneously (SIF-CO2-GPP model). Evidences from all sites show that the introduction of the atmospheric CO2 concentration improves accuracies of estimated GPP. Compared with the SIF-CO2-GPP linear model, we found the SIF-GPP model overestimated GPP in summer and autumn but underestimated it in spring and winter. A series of simulation experiments based on SCOPE (Soil-Canopy Observation of Photosynthesis and Energy) was carried out to figure out the possible mechanism of improved estimates of GPP due to the introduction of atmospheric CO2 concentrations. These experiments also demonstrate that there could be a non-linear relationship between SIF and GPP at half an hour timescale. Moreover, such relationships vary with CO2 concentration. As OCO-2 is capable of providing SIF and XCO2 products with identical spatial and temporal scales, the SIF-CO2-GPP linear model would be implemented conveniently to monitor GPP using remotely sensed data. With the help of OCO-3 and its successors, the proposed SIF-CO2-GPP linear model would play a significant role in monitoring GPP accurately in large geographical extents.

Impact of Molecular Spectroscopy on Carbon Monoxide Abundances from SCIAMACHY

High-quality observations have indicated the need for improved molecular spectroscopy for accurate atmospheric characterization. Line data provided by the new SEOM-IAS (Scientific Exploitation of Operational Missions—Improved Atmospheric Spectroscopy) database in the shortwave infrared (SWIR) region were used to retrieve CO total vertical columns from a selected set of nadir SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) observations. In order to assess the quality of the retrieval results, differences in the spectral fitting residuals with respect to the HITRAN 2016 (High-resolution TRANsmission molecular absorption) and GEISA 2015 (Gestion et Etude des Informations Spectroscopiques Atmosphériques) line lists were quantified and column-averaged dry-air CO mole fractions were compared to NDACC (Network for the Detection of Atmospheric Composition Change) and TCCON (Total Carbon Column Observing Network) ground-based measurements. In general, it was found that using SEOM-IAS line data with corresponding line models improve the spectral quality of the retrieval (smaller residuals) and increase the fitted CO columns, thereby reducing the bias to both ground-based networks.

A framework for harmonizing multiple satellite instruments to generate a long-term global high spatial-resolution solar-induced chlorophyll fluorescence (SIF)

Several decade-long satellite retrievals of solar-induced chlorophyll fluorescence (SIF) have become available during the past few years, but understanding the long-term dynamics of SIF and elucidating its co-variation with historical gross primary production (GPP) remains a challenge. Part of the challenge is due to the lack of direct comparability among these SIF products as they are derived from various satellite platforms with different retrieval methods, instruments characteristics, overpass time, and viewing-illumination geometries. This study presents a framework that circumvents these discrepancies and allows the harmonization of SIF products from multiple instruments to achieve long-term coverage. We demonstrate this framework by fusing SIF retrievals from SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) and Global Ozone Monitoring Experiment 2 (GOME-2) onboard MetOp-A developed at German Research Center for Geosciences (GFZ). We first downscale both original SIF datasets from their native resolutions to 0.05° (SIF¯GOME2_005 and SIF¯SCIA_005 respectively) using machine learning (ML) algorithms imposed with regionalization constraints to account for the varying relationships between predictors and SIF in space and time. We then apply the cumulative distribution function (CDF) matching technique to correct the offset between SIF¯GOME2_005 and SIF¯SCIA_005 inherited from the original instrumental discrepancies to generate a harmonized SIF time series from 2002 to present (SIF¯005). Finally, we quantify the uncertainty of SIF¯005. SIF¯005 is validated with 1) the original retrievals to ensure the spatial and temporal variabilities are preserved, 2) airborne SIF derived from the Chlorophyll Fluorescence Imaging Spectrometer (CFIS, R2 = 0.73), and 3) ground-based SIF measurements at a subalpine coniferous forest (R2 = 0.91). The SIFyield derived from SIF¯005 has high seasonal consistency with the ground measurements (R2 = 0.93), suggesting that the harmonized product SIF¯005 carries physiological information beyond the absorbed photosynthetically active radiation. Additionally, SIF¯005 has a good capability for large-scale stress monitoring as demonstrated with several major historical drought and heatwave events. The framework developed in this study sets the stage for future development of even more advanced SIF products from all SIF-capable satellite platforms once issues related to inter-sensor calibration are resolved and SIF physiology is better understood.

Linking variability of monsoon precipitation with satellite-based observations of stable water isotopes over Northeast India

Isotopic composition of atmospheric water vapor provides information on transport, mixing and phase change of water in the atmosphere. It provides a useful tool for understanding various aspects of the hydrological cycle. SCanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY) onboard ENVISAT-1 was a spectrometer designed to measure the composition of trace gases in troposphere and stratosphere. It provided global measurements of total columnar HDO and H2O concentrations using the spectral window between 2338.5 and 2382.5 nm. Temporal variability of columnar δD was studied over Northeast (NE) India and mean columnar δD for pre-monsoon and monsoon months were correlated with precipitation data obtained from Global System for Mapping of Precipitation (GSMaP). It was observed that δD during the pre-monsoon months of April–May showed good correlation (r > 0.7, p < 0.05) with total precipitation during June–August for the corresponding year over forested regions of Meghalaya and parts of Assam. Analysis was also carried out to understand the relationship between SCIAMACHY derived gridded monthly δD and Multivariate El-Nino Index (MEI) with zero and one month lag periods. Positive correlation was observed between δD and MEI over parts of Central India, Myanmar and Thailand. Isotope ratio of water vapor provides additional information compared to traditional meteorological observations and holds the potential to improve forecasting models.

Determination of Global Mean Eddy Diffusive Transport in the Mesosphere and Lower Thermosphere From Atomic Oxygen and Carbon Dioxide Climatologies

AbstractQuantifying the eddy diffusion coefficient profile in the mesosphere and lower thermosphere (MLT) is critical to the constituent density distributions in the upper mesosphere and thermosphere. Previous work by Swenson et al. (2018, https://doi.org/10.1016/j.jastp.2018.05.014) estimated the global mean eddy diffusion (kzz) values in the upper mesosphere using atomic oxygen (O), derived from Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) hydroxyl (OH). In this study, vertical eddy diffusive transport velocities of O were determined from continuity of mass in the mesopause region (80–97 km), primarily via the HOx chemistry. Global average constituent climatology from previously deduced SABER ozone (O3) and atomic hydrogen (H) was applied. Furthermore, we extended the global mean eddy transport velocities to new heights (105 km) in the MLT using the newly available global mean Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) data. The combined method of determining O3 loss and O density climatology from SCIAMACHY, as well as an improved global mean background atmosphere from SABER, provides new information for eddy diffusion determination in the MLT. Three prominent results to emerge from this study include (i) global mean kzz profiles between 80 and 105 km derived from MLT constituent climatologies, SABER, and SCIAMACHY global mean O density profiles averaged for approximately one solar cycle, (ii) determination of O eddy diffusion velocities in the MLT consistent between two satellite measurements and the thermosphere‐ionosphere‐mesosphere‐electrodynamics general circulation model, and (iii) resolution of historically large differences between deduced kzz determined from O versus CO2 by analysis of SABER and SCIAMACHY measurements.

Global nighttime atomic oxygen abundances from GOMOS hydroxyl airglow measurements in the mesopause region

Abstract. This paper presents a new dataset of nighttime atomic oxygen density [O], derived from OH(8–4) ro-vibrational band emissions, using a non-local thermal equilibrium model, with the aim of offering new insight into the atomic oxygen abundances in the mesopause region. The dataset is derived from the level-1 atmospheric background measurements observed by the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument aboard Envisat, with the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) measurements for the atmospheric background. Raw data are reprocessed into monthly zonal mean values in 10∘ latitude bins with a fixed altitude grid of 3 km. The dataset spans from 70∘ S to 70∘ N in latitude and from 80 to 100 km in altitude, covering a time period from May 2002 to December 2011 at local times from 22:00 to 00:00 LT. The atomic oxygen density peaks at about 95 km and the highest values are in the range of 3–8 × 1011 atoms cm−3, depending on latitude and season. There is a rapid decrease of [O] below the peak. The annual oscillation (AO), semiannual oscillation (SAO) and the solar cycle impact are distinguished from the [O] longtime series variations. This new GOMOS [O] dataset conforms to other published datasets and is consistent with the [O] datasets obtained from the Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY) OH airglow measurements within about ±20 %.