SCanning Imaging Absorption spectroMeter For Atmospheric CHartographY Research Articles

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 %.

Aerosol direct radiative effect over clouds from a synergy of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) reflectances

Abstract. The retrieval of geophysical parameters is increasingly dependent on synergistic use of satellite instruments. More sophisticated parameters can be retrieved and the accuracy of retrievals can be increased when more information is combined. In this paper, a synergistic application of Ozone Monitoring Instrument (OMI), on the Aura platform, and Moderate Resolution Imaging Spectroradiometer (MODIS), on the Aqua platform, Level 1B reflectances is described, enabling the retrieval of the aerosol direct radiative effect (DRE) over clouds using the differential aerosol absorption (DAA) technique. This technique was first developed for reflectances from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on the Environmental Satellite (Envisat), which had the unique capability of measuring contiguous radiances from the ultraviolet (UV) at 240 to 1750 nm in the shortwave-infrared (SWIR), at a moderate spectral resolution of 0.2 to 1.5 nm. However, the spatial resolution and global coverage of SCIAMACHY was limited, and Envisat stopped delivering data in 2012. In order to continue the DRE data retrieval, reflectances from OMI and MODIS, flying in formation, were combined from the UV to the SWIR. This resulted in reflectances at a limited but sufficient spectral resolution, available at the OMI pixel grid, which have a much higher spatial resolution and coverage than SCIAMACHY. The combined reflectance spectra allow the retrieval of cloud microphysical parameters in the SWIR, and the subsequent retrieval of aerosol DRE over cloud scenes using the DAA technique. For liquid cloud scenes in the south-east Atlantic region with cloud fraction (CF) &gt;0.3, the area-averaged instantaneous aerosol DRE over clouds in June to August 2006 was 25 Wm−2 with a standard deviation of 30 Wm−2. The maximum area-averaged instantaneous DRE from OMI–MODIS in August 2006 was 75.6±13 Wm−2. The new aerosol DRE over-cloud dataset from OMI–MODIS is compared to the SCIAMACHY dataset for the period 2006 to 2009, showing a very high correlation. The OMI–MODIS DRE dataset over the Atlantic Ocean is highly correlated to above-cloud AOT measurements from OMI and MODIS. It is related to AOT measurements over Ascension Island in 2016, showing the transport of smoke all the way from its source region in Africa over the Atlantic to Ascension and beyond.

Consistent Nighttime Atomic Oxygen Concentrations From O2A‐band, O(1S) Green‐Line, and OH Airglow Measurements as Performed by SCIAMACHY

AbstractA new atomic oxygen data set was derived from nighttime SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) O2A‐band measurements. It is compared to atomic oxygen obtained from SCIAMACHY O(1S) green‐line and OH(9‐6)‐band measurements. The three data sets are considered independent of radiometry and, to some extent, methodology. A detailed comparison of atomic oxygen retrieved from these three nightglow measurements is reported for the first time. The agreement of absolute values within 15% supports the current understanding of the photochemistry of the three atomic oxygen proxies involved. As an alternative approach, the O2A‐band model recently proposed by Kalogerakis (2019) is used as well. It is striking that the SCIAMACHY data sets using different atomic oxygen proxies and mostly independent methodology agree much better with each other than with SABER data.

Comparison of ground-based and satellite measurements of water vapour vertical profiles over Ellesmere Island, Nunavut

Abstract. Improving measurements of water vapour in the upper troposphere and lower stratosphere (UTLS) is a priority for the atmospheric science community. In this work, UTLS water vapour profiles derived from Atmospheric Chemistry Experiment (ACE) satellite measurements are assessed with coincident ground-based measurements taken at a high Arctic observatory at Eureka, Nunavut, Canada. Additional comparisons to satellite measurements taken by the Atmospheric Infrared Sounder (AIRS), Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), Microwave Limb Sounder (MLS), Scanning Imaging Absorption Spectrometer for Atmospheric CHartography (SCIAMACHY), and Tropospheric Emission Spectrometer (TES) are included to put the ACE Fourier transform spectrometer (ACE-FTS) and ACE Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) results in context. Measurements of water vapour profiles at Eureka are made using a Bruker 125HR solar absorption Fourier transform infrared spectrometer at the Polar Environment Atmospheric Research Laboratory (PEARL) and radiosondes launched from the Eureka Weather Station. Radiosonde measurements used in this study were processed with software developed by the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) to account for known biases and calculate uncertainties in a well-documented and consistent manner. ACE-FTS measurements were within 11 ppmv (parts per million by volume; 13 %) of 125HR measurements between 6 and 14 km. Between 8 and 14 km ACE-FTS profiles showed a small wet bias of approximately 8 % relative to the 125HR. ACE-FTS water vapour profiles had mean differences of 13 ppmv (32 %) or better when compared to coincident radiosonde profiles at altitudes between 6 and 14 km; mean differences were within 6 ppmv (12 %) between 7 and 11 km. ACE-MAESTRO profiles showed a small dry bias relative to the 125HR of approximately 7 % between 6 and 9 km and 10 % between 10 and 14 km. ACE-MAESTRO profiles agreed within 30 ppmv (36 %) of the radiosondes between 7 and 14 km. ACE-FTS and ACE-MAESTRO comparison results show closer agreement with the radiosondes and PEARL 125HR overall than other satellite datasets – except for AIRS. Close agreement was observed between AIRS and the 125HR and radiosonde measurements, with mean differences within 5 % and correlation coefficients above 0.83 in the troposphere between 1 and 7 km. Comparisons to MLS at altitudes around 10 km showed a dry bias, e.g. mean differences between MLS and radiosondes were −25.6 %. SCIAMACHY comparisons were very limited due to minimal overlap between the vertical extent of the measurements. TES had no temporal overlap with the radiosonde dataset used in this study. Comparisons between TES and the 125HR showed a wet bias of approximately 25 % in the UTLS and mean differences within 14 % below 5 km.

Shortwave Spectral Radiative Signatures and Their Physical Controls

AbstractThe spectrum of reflected solar radiation emerging at the top of the atmosphere is rich with Earth system information. To identify spectral signatures in the reflected solar radiation and directly relate them to the underlying physical properties controlling their structure, over 90 000 solar reflectance spectra are computed over West Africa in 2010 using a fast radiation code employing the spectral characteristics of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). Cluster analysis applied to the computed spectra reveals spectral signatures related to distinct surface properties, and cloud regimes distinguished by their spectral shortwave cloud radiative effect (SWCRE). The cloud regimes exhibit a diverse variety of mean broadband SWCREs, and offer an alternative approach to define cloud type for SWCRE applications that does not require any prior assumptions. The direct link between spectral signatures and distinct physical properties extracted from clustering remains robust between spatial scales of 1, 20, and 240 km, and presents an excellent opportunity to understand the underlying properties controlling real spectral reflectance observations. Observed SCIAMACHY spectra are assigned to the calculated spectral clusters, showing that cloud regimes are most frequent during the active West African monsoon season of June–October in 2010, and all cloud regimes have a higher frequency of occurrence during the active monsoon season of 2003 compared with the inactive monsoon season of 2004. Overall, the distinct underlying physical properties controlling spectral signatures show great promise for monitoring evolution of the Earth system directly from solar spectral reflectance observations.

Trends and trend reversal detection in 2 decades of tropospheric NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; satellite observations

Abstract. In this work, a ∼21-year global dataset from four different satellite sensors with a mid-morning overpass (GOME/ERS-2, SCIAMACHY/ENVISAT, GOME-2/Metop-A, and GOME-2/Metop-B) is compiled to study the long-term tropospheric NO2 patterns and trends. The Global Ozone Monitoring Experiment (GOME) and GOME-2 data are “corrected” relative to the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data to produce a self-consistent dataset that covers the period April 1996–September 2017. The highest tropospheric NO2 concentrations are seen over urban, industrialized, and highly populated areas and over ship tracks in the oceans. Tropospheric NO2 has generally decreased during the last 2 decades over the industrialized and highly populated regions of the western world (a total decrease of the order of ∼49 % over the US, the Netherlands, and the UK; ∼36 % over Italy and Japan; and ∼32 % over Germany and France) and increased over developing regions (a total increase of ∼160 % over China and ∼33 % over India). It is suggested here that linear trends cannot be used efficiently worldwide for such long periods. Tropospheric NO2 is very sensitive to socioeconomic changes (e.g., environmental protection policies, economic recession, warfare, etc.) which may cause either short-term changes or even a reversal of the trends. The application of a method capable of detecting the year when a reversal of trends happened shows that tropospheric NO2 concentrations switched from positive to negative trends and vice versa over several regions around the globe. A country-level analysis revealed clusters of countries that exhibit similar positive-to-negative or negative-to-positive trend reversals, while 29 out of a total of 64 examined megacities and large urban agglomerations experienced a trend reversal at some point within the last 2 decades.

FRESCO-B: a fast cloud retrieval algorithm using oxygen B-band measurements from GOME-2

Abstract. The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A band) algorithm is a simple, fast and robust algorithm used to retrieve cloud information in operational satellite data processing. It has been applied to GOME-1 (Global Ozone Monitoring Experiment), SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography), GOME-2 and more recently to TROPOMI (Tropospheric Monitoring Instrument). FRESCO retrieves effective cloud fraction and cloud pressure from measurements in the oxygen A band around 761 nm. In this paper, we propose a new version of the algorithm, called FRESCO-B, which is based on measurements in the oxygen B band around 687 nm. Such a method is interesting for vegetated surfaces where the surface albedo is much lower in the B band than in the A band, which limits the ground contribution to the top-of-atmosphere reflectances. In this study we first perform retrieval simulations. These show that the retrieved cloud pressures from FRESCO-B and FRESCO differ only between −10 and +10 hPa, except for high, thin clouds over vegetation where the difference is larger (about +15 to +30 hPa), with FRESCO-B yielding higher pressure. Next, inter-comparison between FRESCO-B and FRESCO retrievals over 1 month of GOME-2B data reveals that the effective cloud fractions retrieved in the O2 A and B bands are very similar (mean difference of 0.003), while the cloud pressures show a mean difference of 11.5 hPa, with FRESCO-B retrieving higher pressures than FRESCO. This agrees with the simulations and is partly due to deeper photon penetrations of the O2 B band in clouds compared to the O2 A-band photons and partly due to the surface albedo bias in FRESCO. Finally, validation with ground-based measurements shows that the FRESCO-B cloud pressure represents an altitude within the cloud boundaries for clouds that are not too far from the Lambertian reflector model, which occurs in about 50 % of the cases.

Merging of ozone profiles from SCIAMACHY, OMPS and SAGE II observations to study stratospheric ozone changes

Abstract. This paper presents vertically and zonally resolved merged ozone time series from limb measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) and the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP). In addition, we present the merging of the latter two data sets with zonally averaged profiles from Stratospheric Aerosol and Gas Experiment (SAGE) II. The retrieval of ozone profiles from SCIAMACHY and OMPS-LP is performed using an inversion algorithm developed at the University of Bremen. To optimize the merging of these two time series, we use data from the Microwave Limb Sounder (MLS) as a transfer function and we follow two approaches: (1) a conventional method involving the calculation of deseasonalized anomalies and (2) a “plain-debiasing” approach, generally not considered in previous similar studies, which preserves the seasonal cycles of each instrument. We find a good correlation and no significant drifts between the merged and MLS time series. Using the merged data set from both approaches, we apply a multivariate regression analysis to study ozone changes in the 20–50 km range over the 2003–2018 period. Exploiting the dense horizontal sampling of the instruments, we investigate not only the zonally averaged field, but also the longitudinally resolved long-term ozone variations, finding an unexpected and large variability, especially at mid and high latitudes, with variations of up to 3 %–5 % per decade at altitudes around 40 km. Significant positive linear trends of about 2 %–4 % per decade were identified in the upper stratosphere between altitudes of 38 and 45 km at mid latitudes. This is in agreement with the predicted recovery of upper stratospheric ozone, which is attributed to both the adoption of measures to limit the release of halogen-containing ozone-depleting substances (Montreal Protocol) and the decrease in stratospheric temperature resulting from the increasing concentration of greenhouse gases. In the tropical stratosphere below 25 km negative but non-significant trends were found. We compare our results with previous studies and with short-term trends calculated over the SCIAMACHY period (2002–2012). While generally a good agreement is found, some discrepancies are seen in the tropical mid stratosphere. Regarding the merging of SAGE II with SCIAMACHY and OMPS-LP, zonal mean anomalies are taken into consideration and ozone trends before and after 1997 are calculated. Negative trends above 30 km are found for the 1985–1997 period, with a peak of −6 % per decade at mid latitudes, in agreement with previous studies. The increase in ozone concentration in the upper stratosphere is confirmed over the 1998–2018 period. Trends in the tropical stratosphere at 30–35 km show an interesting behavior: over the 1998–2018 period a negligible trend is found. However, between 2004 and 2011 a negative long-term change is detected followed by a positive change between 2012 and 2018. We attribute this behavior to dynamical changes in the tropical middle stratosphere.

Model results of OH airglow considering four different wavelength regions to derive night-time atomic oxygen and atomic hydrogen in the mesopause region

Abstract. Based on the zero-dimensional box model Module Efficiently Calculating the Chemistry of the Atmosphere/Chemistry As A Box model Application (CAABA/MECCA-3.72f), an OH airglow model was developed to derive night-time number densities of atomic oxygen ([O(3P)]) and atomic hydrogen ([H]) in the mesopause region (∼75–100 km). The profiles of [O(3P)] and [H] were calculated from OH airglow emissions measured at 2.0 µm by the Sounding of the Atmosphere using Broadband Emission Radiography (SABER) instrument on board NASA's Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite. The two target species were used to initialize the OH airglow model, which was empirically adjusted to fit four different OH airglow emissions observed by the satellite/instrument configuration TIMED/SABER at 2.0 µm and at 1.6 µm as well as measurements by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instrument on board the Environmental Satellite (ENVISAT) of the transitions OH(6-2) and OH(3-1). Comparisons between the “best-fit model” obtained here and the satellite measurements suggest that deactivation of vibrationally excited OH(ν) via OH(ν≥7)+O2 might favour relaxation to OH(ν′≤5)+O2 by multi-quantum quenching. It is further indicated that the deactivation pathway to OH(ν′=ν-5)+O2 dominates. The results also provide general support of the recently proposed mechanism OH(ν)+O(3P)→OH(0≤ν′≤ν-5)+O(1D) but suggest slower rates of OH(ν=8,7,6,5)+O(3P), partly disagreeing with laboratory experiments. Additionally, deactivation to OH(ν′=ν-5)+O(1D) might be preferred. The profiles of [O(3P)] and [H] derived here are plausible between 80 and 95 km but should be regarded as an upper limit. The values of [O(3P)] obtained in this study agree with the corresponding TIMED/SABER values between 80 and 85 km but are larger from 85 to 95 km due to different relaxation assumptions of OH(ν)+O(3P). The [H] profile found here is generally larger than TIMED/SABER [H] by about 50 % from 80 to 95 km, which is primarily attributed to our faster OH(ν=8)+O2 rate.

Dynamically controlled ozone decline in the tropical mid-stratosphere observed by SCIAMACHY

Abstract. Despite the recently reported beginning of a recovery in global stratospheric ozone (O3), an unexpected O3 decline in the tropical mid-stratosphere (around 30–35 km altitude) was observed in satellite measurements during the first decade of the 21st century. We use SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) measurements for the period 2004–2012 to confirm the significant O3 decline. The SCIAMACHY observations show that the decrease in O3 is accompanied by an increase in NO2. To reveal the causes of these observed O3 and NO2 changes, we performed simulations with the TOMCAT 3-D chemistry-transport model (CTM) using different chemical and dynamical forcings. For the 2004–2012 time period, the TOMCAT simulations reproduce the SCIAMACHY-observed O3 decrease and NO2 increase in the tropical mid-stratosphere. The simulations suggest that the positive changes in NO2 (around 7 % decade−1) are due to similar positive changes in reactive odd nitrogen (NOy), which are a result of a longer residence time of the source gas N2O and increased production via N2O + O(1D). The model simulations show a negative change of 10 % decade−1 in N2O that is most likely due to variations in the deep branch of the Brewer–Dobson Circulation (BDC). Interestingly, modelled annual mean “age of air” (AoA) does not show any significant changes in transport in the tropical mid-stratosphere during 2004–2012. However, further analysis of model results demonstrates significant seasonal variations. During the autumn months (September–October) there are positive AoA changes that imply transport slowdown and a longer residence time of N2O allowing for more conversion to NOy, which enhances O3 loss. During winter months (January–February) there are negative AoA changes, indicating faster N2O transport and less NOy production. Although the variations in AoA over a year result in a statistically insignificant linear change, non-linearities in the chemistry–transport interactions lead to a statistically significant negative N2O change.

Precipitable water vapor over oceans from the Maritime Aerosol Network: Evaluation of global models and satellite products under clear sky conditions

We present results from an evaluation of precipitable water vapor (W) over remote oceanic areas as derived from global reanalysis models and from satellites against observations from the Maritime Aerosol Network (MAN) for cloudless skies during the period of 2004–2017. They cover polar, mid latitude and tropical oceanic regions and represent a first effort to use MAN observations for such evaluation. The global reanalysis model products evaluated in this study are from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2), the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA I), and the Climate Forecast System Reanalysis (CFSR) model. The satellite products evaluated are from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Polarization and Directionality of the Earth's Reflectances (POLDER), the Global Ozone Monitoring Experiment (GOME-2), the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and the Atmospheric Infra-red Sounder (AIRS). Satellite retrievals of W are based on the attenuation of solar reflected light by water vapor absorption bands, except those from AIRS that rely on brightness temperature measurements. A very good agreement is observed between the model estimates and MAN, with mean differences of ~5% and standard deviations of ~15%. These results are within the uncertainties associated with the models and the measurements, indicating the skill of the reanalysis models to estimate W over oceans under clear sky conditions. Mean differences of W between the satellite and MAN products are ~11, 6.7, 12, −7, and 3% for MODIS, POLDER, GOME-2, SCIAMACHY and AIRS respectively, while their standard deviations are 31, 29, 28, 20 and 17%. These differences reveal the need to address inconsistencies among different satellite sensors and ground-based measurements to reduce the uncertainties associated with the retrievals.

Atomic Oxygen Abundance Retrieved From SCIAMACHY Hydroxyl Nightglow Measurements

AbstractWe present a new atomic oxygen data set based on Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY) hydroxyl short‐wave infrared data. The OH spectra stem from the OH(9‐6) ro‐vibrational transition. These data and atomic oxygen obtained from SCIAMACHY O(1S) green line measurements, which is an independent data set in terms of methodology and radiometry, typically agree within 10–20%. This confirms the corresponding models of OH and O(1S), in particular, the relevance of the reaction between atomic oxygen and ozone in the photochemical model. The agreement between the SCIAMACHY data and the most recent Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) atomic oxygen data set of Mlynczak et al. (2018, https://doi.org/10.1029/2018GL077377) is significantly better than for the previous SABER data set of Mlynczak et al. (2013, https://doi.org/10.1002/jgrd.50401). The agreement decreases if the SCIAMACHY forward model parameters are applied to SABER data. A similar agreement is achieved with the data of Panka et al. (2018, https://doi.org/10.1029/2018GL077677), which was retrieved from SABER data using a principally different retrieval approach.

A full-mission data set of H&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;O and HDO columns from SCIAMACHY 2.3 µm reflectance measurements

Abstract. A new data set of vertical column densities of the water vapour isotopologues H2O and HDO from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument for the whole of the mission period from January 2003 to April 2012 is presented. The data are retrieved from reflectance measurements in the spectral range 2339 to 2383 nm with the Shortwave Infrared CO Retrieval (SICOR) algorithm, ignoring atmospheric light scattering in the measurement simulation. The retrievals are validated with ground-based Fourier transform infrared measurements obtained within the Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) project. A good agreement for low-altitude stations is found with an average bias of −3.6×1021 for H2O and −1.0×1018 molec cm−2 for HDO. The a posteriori computed δD shows an average bias of −8 ‰, even though polar stations have a larger negative bias. The latter is due to the large amount of sensor noise in SCIAMACHY in combination with low albedo and high solar zenith angles. To demonstrate the benefit of accounting for light scattering in the retrieval, the quality of the data product fitting effective cloud parameters simultaneously with trace gas columns is evaluated in a dedicated case study for measurements round high-altitude stations. Due to a large altitude difference between the satellite ground pixel and the mountain station, clear-sky scenes yield a large bias, resulting in a δD bias of 125 ‰. When selecting scenes with optically thick clouds within 1000 m above or below the station altitude, the bias in a posteriori δD is reduced from 125 to 44 ‰. The insights from the present study will also benefit the analysis of the data from the new Sentinel-5 Precursor mission.

Comparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY

Abstract. Atmospheric water vapour plays a key role in the Arctic radiation budget, hydrological cycle and hence climate, but its measurement with high accuracy remains an important challenge. Total column water vapour (TCWV) datasets derived from ground-based GNSS measurements are used to assess the quality of different existing satellite TCWV datasets, namely from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Atmospheric Infrared Sounder (AIRS) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The comparisons between GNSS and satellite data are carried out for three reference Arctic observation sites (Sodankylä, Ny-Ålesund and Thule) where long homogeneous GNSS time series of more than a decade (2001–2014) are available. We select hourly GNSS data that are coincident with overpasses of the different satellites over the three sites and then average them into monthly means that are compared with monthly mean satellite products for different seasons. The agreement between GNSS and satellite time series is generally within 5 % at all sites for most conditions. The weakest correlations are found during summer. Among all the satellite data, AIRS shows the best agreement with GNSS time series, though AIRS TCWV is often slightly too high in drier atmospheres (i.e. high-latitude stations during autumn and winter). SCIAMACHY TCWV data are generally drier than GNSS measurements at all the stations during the summer. This study suggests that these biases are associated with cloud cover, especially at Ny-Ålesund and Thule. The dry biases of MODIS and SCIAMACHY observations are most pronounced at Sodankylä during the snow season (from October to March). Regarding SCIAMACHY, this bias is possibly linked to the fact that the SCIAMACHY TCWV retrieval does not take accurately into account the variations in surface albedo, notably in the presence of snow with a nearby canopy as in Sodankylä. The MODIS bias at Sodankylä is found to be correlated with cloud cover fraction and is also expected to be affected by other atmospheric or surface albedo changes linked for instance to the presence of forests or anthropogenic emissions. Overall, the results point out that a better estimation of seasonally dependent surface albedo and a better consideration of vertically resolved cloud cover are recommended if biases in satellite measurements are to be reduced in the polar regions.

Evaluation of SCIAMACHY Level-1 data versions using nadir ozone profile retrievals in the period 2003–2011

Abstract. Ozone profile retrieval from nadir-viewing satellite instruments operating in the ultraviolet–visible range requires accurate calibration of Level-1 (L1) radiance data. Here we study the effects of calibration on the derived Level-2 (L2) ozone profiles for three versions of SCanning Imaging Absorption spectroMeter for Atmospheric ChartograpHY (SCIAMACHY) L1 data: version 7 (v7), version 7 with m-factors (v7mfac) and version 8 (v8). We retrieve nadir ozone profiles from the SCIAMACHY instrument that flew on board Envisat using the Ozone ProfilE Retrieval Algorithm (OPERA) developed at KNMI with a focus on stratospheric ozone. We study and assess the quality of these profiles and compare retrieved L2 products from L1 SCIAMACHY data versions from the years 2003 to 2011 without further radiometric correction. From validation of the profiles against ozone sonde measurements, we find that the v8 performs better than v7 and v7mfac due to correction for the scan-angle dependency of the instrument's optical degradation. Validation for the years 2003 and 2009 with ozone sondes shows deviations of SCIAMACHY ozone profiles of 0.8–15 % in the stratosphere (corresponding to pressure range ∼ 100–10 hPa) and 2.5–100 % in the troposphere (corresponding to pressure range ∼ 1000–100 hPa), depending on the latitude and the L1 version used. Using L1 v8 for the years 2003–2011 leads to deviations of ∼ 1–11 % in stratospheric ozone and ∼ 1–45 % in tropospheric ozone. The SCIAMACHY L1 v8 data can still be improved upon in the 265–330 nm range used for ozone profile retrieval. The slit function can be improved with a spectral shift and squeeze, which leads to a few percent residue reduction compared to reference solar irradiance spectra. Furthermore, studies of the ratio of measured to simulated reflectance spectra show that a bias correction in the reflectance for wavelengths below 300 nm appears to be necessary.

First results on the retrieval of noctilucent cloud albedo and occurrence rate from SCIAMACHY/Envisat satellite nadir measurements

We present the first results on the retrieval of noctilucent cloud (NLC) albedos and occurrence rates from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartography) nadir data. The applicability of already available algorithms is discussed and necessary changes are reasoned. The occurrence rates for different latitude ranges are presented. During the summer period, when NLCs occur, the NLC occurrence rates show a maximum which is strongest at the highest latitudes. This is consistent with other observation methods. For the spring and autumn period, however, false NLC detections are observed at latitudes between 45°N and 65°N, where no NLCs are expected. The reason for this, and why it does not affect the retrieval during the NLC season is discussed. We also compared the SCIAMACHY nadir NLC occurrence rates with the ones retrieved from the SCIAMACHY limb measurements and the ones of SBUV and found qualitative agreement of these data sets.

Retrieval of ozone profiles from OMPS limb scattering observations

Abstract. This study describes a retrieval algorithm developed at the University of Bremen to obtain vertical profiles of ozone from limb observations performed by the Ozone Mapper and Profiler Suite (OMPS). This algorithm is based on the technique originally developed for use with data from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument. As both instruments make limb measurements of the scattered solar radiation in the ultraviolet (UV) and visible (Vis) spectral ranges, an underlying objective of the study is to obtain consolidated and consistent ozone profiles from the two satellites and to produce a combined data set. The retrieval algorithm uses radiances in the UV and Vis wavelength ranges normalized to the radiance at an upper tangent height to obtain ozone concentrations in the altitude range of 12–60 km. Measurements at altitudes contaminated by clouds in the instrument field of view are identified and filtered out. An independent aerosol retrieval is performed beforehand and its results are used to account for the stratospheric aerosol load in the ozone inversion. The typical vertical resolution of the retrieved profiles varies from ∼ 2.5 km at lower altitudes ( &lt; 30 km) to ∼ 1.5 km (about 45 km) and becomes coarser at upper altitudes. The retrieval errors resulting from the measurement noise are estimated to be 1–4 % above 25 km, increasing to 10–30 % in the upper troposphere. OMPS data are processed for the whole of 2016. The results are compared with the NASA product and validated against profiles derived from passive satellite observations or measured in situ by balloon-borne sondes. Between 20 and 60 km, OMPS ozone profiles typically agree with data from the Microwave Limb Sounder (MLS) v4.2 within 5–10 %, whereas in the lower altitude range the bias becomes larger, especially in the tropics. The comparison of OMPS profiles with ozonesonde measurements shows differences within ±5 % between 13 and 30 km at northern middle and high latitudes. At southern middle and high latitudes, an agreement within 5–7 % is also achieved in the same altitude range. An unexpected bias of approximately 10–20 % is detected in the lower tropical stratosphere. The processing of the 2013 data set using the same retrieval settings and its validation against ozonesondes reveals a much smaller bias; a possible reason for this behaviour is discussed.