SCanning Imaging Absorption spectroMeter For Atmospheric CHartographY Measurements Research Articles

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.

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.

Comparison of global datasets of sodium densities in the mesosphere and lower thermosphere from GOMOS, SCIAMACHY and OSIRIS measurements and WACCM model simulations from 2008 to 2012

Abstract. During the last decade, several limb sounding satellites have measured the global sodium (Na) number densities in the mesosphere and lower thermosphere (MLT). Datasets are now available from Global Ozone Monitoring by Occultation of Stars (GOMOS), the SCanning Imaging Absorption spectroMeter for Atmospheric CHartography (SCIAMACHY) (both on Envisat) and the Optical Spectrograph and InfraRed Imager System (OSIRIS) (on Odin). Furthermore, global model simulations of the Na layer in the MLT simulated by the Whole Atmosphere Community Climate Model, including the Na species (WACCM-Na), are available. In this paper, we compare these global datasets.The observed and simulated monthly averages of Na vertical column densities agree reasonably well with each other. They show a clear seasonal cycle with a summer minimum most pronounced at the poles. They also show signs of a semi-annual oscillation in the equatorial region. The vertical column densities vary from 0. 5 × 109 to 7 × 109 cm−2 near the poles and from 3 × 109 to 4 × 109 cm−2 at the Equator. The phase of the seasonal cycle and semi-annual oscillation shows small differences between the Na amounts retrieved from different instruments. The full width at half maximum of the profiles is 10 to 16 km for most latitudes, but significantly smaller in the polar summer. The centroid altitudes of the measured sodium profiles range from 89 to 95 km, whereas the model shows on average 2 to 4 km lower centroid altitudes. This may be explained by the mesopause being 3 km lower in the WACCM simulations than in measurements. Despite this global 2–4 km shift, the model captures well the latitudinal and temporal variations. The variation of the WACCM dataset during the year at different latitudes is similar to the one of the measurements. Furthermore, the differences between the measured profiles with different instruments and therefore different local times (LTs) are also present in the model-simulated profiles. This capturing of latitudinal and temporal variations is also found for the vertical column densities and profile widths.

Improved pointing information for SCIAMACHY from in-flight measurements of the viewing directions towards sun and moon

Abstract. The SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on Envisat (2002–2012) performed nadir, limb, solar/lunar occultation and various monitoring measurements. The pointing information of the instrument is determined by the attitude information of the Envisat platform with its star trackers together with the encoder readouts of both the azimuth and the elevation scanner of SCIAMACHY. In this work, we present additional sources of attitude information from the SCIAMACHY measurements itself. The basic principle is the same as used by the star tracker: we measure the viewing direction towards celestial objects, i.e. sun and moon, to detect possible mispointings. In sun over limb port observations, we utilise the vertical scans over the solar disk. In horizontal direction, SCIAMACHY's sun follower device (SFD) is used to adjust the viewing direction. Moon over limb port measurements use for both the vertical and the horizontal direction the adjustment by the SFD. The viewing direction is steered towards the intensity centroid of the illuminated part of the lunar disk. We use reference images from the USGS Robotic Lunar Observatory (ROLO) to take into account the inhomogeneous surface and the variations by lunar libration and phase to parameterise the location of the intensity centroid from the observation geometry. Solar observations through SCIAMACHY's so-called sub-solar port (with a viewing direction closely to zenith) also use the SFD in the vertical direction. In the horizontal direction the geometry of the port defines the viewing direction. Using these three type of measurements, we fit improved mispointing parameters by minimising the pointing offsets in elevation and azimuth. The geolocation of all retrieved products will benefit from this; the tangent heights are especially improved. The altitudes assigned to SCIAMACHY's solar occultation measurements are changed in the range of −130 to −330 m, the lunar occultation measurements are changed in the range of 0 to +130 m and the limb measurements are changed in the range of −50 to +60 m (depending on season, altitude and azimuth angle). The horizontal location of the tangent point is changed by about 5 km for all measurements. These updates are implemented in version 9 of the SCIAMACHY Level 1b products and Level 2 version 7 (based on L1b version 9).

Consistent evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON

Abstract. Consistent validation of satellite CO2 estimates is a prerequisite for using multiple satellite CO2 measurements for joint flux inversion, and for establishing an accurate long-term atmospheric CO2 data record. Harmonizing satellite CO2 measurements is particularly important since the differences in instruments, observing geometries, sampling strategies, etc. imbue different measurement characteristics in the various satellite CO2 data products. We focus on validating model and satellite observation attributes that impact flux estimates and CO2 assimilation, including accurate error estimates, correlated and random errors, overall biases, biases by season and latitude, the impact of coincidence criteria, validation of seasonal cycle phase and amplitude, yearly growth, and daily variability. We evaluate dry-air mole fraction (XCO2) for Greenhouse gases Observing SATellite (GOSAT) (Atmospheric CO2 Observations from Space, ACOS b3.5) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) (Bremen Optimal Estimation DOAS, BESD v2.00.08) as well as the CarbonTracker (CT2013b) simulated CO2 mole fraction fields and the Monitoring Atmospheric Composition and Climate (MACC) CO2 inversion system (v13.1) and compare these to Total Carbon Column Observing Network (TCCON) observations (GGG2012/2014). We find standard deviations of 0.9, 0.9, 1.7, and 2.1 ppm vs. TCCON for CT2013b, MACC, GOSAT, and SCIAMACHY, respectively, with the single observation errors 1.9 and 0.9 times the predicted errors for GOSAT and SCIAMACHY, respectively. We quantify how satellite error drops with data averaging by interpreting according to error2 = a2 + b2/n (with n being the number of observations averaged, a the systematic (correlated) errors, and b the random (uncorrelated) errors). a and b are estimated by satellites, coincidence criteria, and hemisphere. Biases at individual stations have year-to-year variability of ∼ 0.3 ppm, with biases larger than the TCCON-predicted bias uncertainty of 0.4 ppm at many stations. We find that GOSAT and CT2013b underpredict the seasonal cycle amplitude in the Northern Hemisphere (NH) between 46 and 53° N, MACC overpredicts between 26 and 37° N, and CT2013b underpredicts the seasonal cycle amplitude in the Southern Hemisphere (SH). The seasonal cycle phase indicates whether a data set or model lags another data set in time. We find that the GOSAT measurements improve the seasonal cycle phase substantially over the prior while SCIAMACHY measurements improve the phase significantly for just two of seven sites. The models reproduce the measured seasonal cycle phase well except for at Lauder_125HR (CT2013b) and Darwin (MACC). We compare the variability within 1 day between TCCON and models in JJA; there is correlation between 0.2 and 0.8 in the NH, with models showing 10–50 % the variability of TCCON at different stations and CT2013b showing more variability than MACC. This paper highlights findings that provide inputs to estimate flux errors in model assimilations, and places where models and satellites need further investigation, e.g., the SH for models and 45–67° N for GOSAT and CT2013b.

Mapping Global Atmospheric CO2 Concentration at High Spatiotemporal Resolution

Satellite measurements of the spatiotemporal distributions of atmospheric CO2 concentrations are a key component for better understanding global carbon cycle characteristics. Currently, several satellite instruments such as the Greenhouse gases Observing SATellite (GOSAT), SCanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY), and Orbiting Carbon Observatory-2 can be used to measure CO2 column-averaged dry air mole fractions. However, because of cloud effects, a single satellite can only provide limited CO2 data, resulting in significant uncertainty in the characterization of the spatiotemporal distribution of atmospheric CO2 concentrations. In this study, a new physical data fusion technique is proposed to combine the GOSAT and SCIAMACHY measurements. On the basis of the fused dataset, a gap-filling method developed by modeling the spatial correlation structures of CO2 concentrations is presented with the goal of generating global land CO2 distribution maps with high spatiotemporal resolution. The results show that, compared with the single satellite dataset (i.e., GOSAT or SCIAMACHY), the global spatial coverage of the fused dataset is significantly increased (reaching up to approximately 20%), and the temporal resolution is improved by two or three times. The spatial coverage and monthly variations of the generated global CO2 distributions are also investigated. Comparisons with ground-based Total Carbon Column Observing Network (TCCON) measurements reveal that CO2 distributions based on the gap-filling method show good agreement with TCCON records despite some biases. These results demonstrate that the fused dataset as well as the gap-filling method are rather effective to generate global CO2 distribution with high accuracies and high spatiotemporal resolution.

Tropospheric column amount of ozone retrieved from SCIAMACHY limb–nadir-matching observations

Abstract. Tropospheric ozone (O3), has two main sources: transport from the stratosphere and photochemical production in the troposphere. It plays important roles in atmospheric chemistry and climate change. Its amount and destruction are being modified by anthropogenic activity. Global measurements are needed to test our understanding of its sources and sinks. In this paper, we describe the retrieval of tropospheric O3 columns (TOCs) from the combined limb and nadir observations (hereinafter referred to as limb–nadir-matching (LNM)) of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument, which flew as part of the payload onboard the European Space Agency (ESA) satellite Envisat (2002–2012). The LNM technique used in this study is a residual approach that subtracts stratospheric O3 columns (SOCs), retrieved from the limb observations, from the total O3 columns (TOZs), derived from the nadir observations. The technique requires accurate knowledge of the SOCs, TOZs, tropopause height, and their associated errors. The SOCs were determined from the stratospheric O3 profiles retrieved in the Hartley and Chappuis bands from SCIAMACHY limb scattering measurements. The TOZs were also derived from SCIAMACHY measurements, but in this case from the nadir viewing mode using the Weighting Function Differential Optical Absorption Spectroscopy (WFDOAS) technique in the Huggins band. Comparisons of the TOCs from SCIAMACHY and collocated measurements from ozonesondes in both hemispheres between January 2003 and December 2011 show agreement to within 2–5 DU (1 DU = 2.69 × 1016 molecules cm−2). TOC values from SCIAMACHY have also been compared to the results from the Tropospheric Emission Spectrometer (TES) and from the LNM technique exploiting Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) data (hereinafter referred to as OMI/MLS). All compared data sets agree within the given data product error range and exhibit similar seasonal variations, which, however, differ in amplitude. The spatial distributions of tropospheric O3 in the SCIAMACHY LNM TOC product show characteristic variations related to stratosphere–troposphere exchange (STE) processes, anthropogenic activities and biospheric emissions.

Increasing in Tropospheric Nitrogen Dioxide over the North-South Transect of Northeast Asia during 1996-2010

Measurements of the global distribution of the tropospheric NO2 column densities have become available with the GOME (Global Ozone Monitoring Experiment) and SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric Chartography) instruments. The spatial and temporal characters of NO2 over the North-South Transect of Northeast Asia (NSTNA) was analyzed using monthly averaged tropospheric NO2 column densities from GOME and SCIAMACHY measurements taken from April 1996 to December 2010. In addition to NO2 (1996-2010) column densities data, land-cover data and characters of NO2 concentration over different ecosystem have been analyzed over the NSTNA. The results indicated that the tropospheric NO2 column densities over the region show distinct regional and seasonal variation characteristics for between 1996 and 2009. The highest concentration was in winter and lowest in autumn. The data also presents zonal distribution and decreasing from northern to southern. Under the influence of the urbanization process, the highest NO2 column densities appeared at cities and metropolitan areas which are located in the north plain of China and the southern areas of the NSTNA. Moreover the lowest column densities appeared at the northern areas of the NSTNA. The tropospheric NO2 column densities have shown significant differences over other ecosystems. In addition, the higher NO2 column density was found over forest and grass land while lower values over lake, tundra and semi-desert. There are different characteristics in five land use types along with the NO2 column densities increasing year by year. The highest values appeared in winter over the forest, grass, lake and tundra while in summer over the semi-desert.

Comparison of CH4 inversions based on 15 months of GOSAT and SCIAMACHY observations

Over the past decade the development of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) retrievals has increased the interest in the use of satellite measurements for studying the global sources and sinks of methane. Meanwhile, measurements are becoming available from the more advanced Greenhouse Gases Observing Satellite (GOSAT). The aim of this study is to investigate the application of GOSAT retrievals to inverse modeling, for which we make use of the TM5‐4DVAR inverse modeling framework. Inverse modeling calculations are performed using data from two different retrieval approaches: a full physics and a lightpath proxy ratio method. The performance of these inversions is analyzed in comparison with inversions using SCIAMACHY retrievals and measurements from the National Oceanic and Atmospheric Administration‐Earth System Research Laboratory flask‐sampling network. In addition, we compare the inversion results against independent surface, aircraft, and total‐column measurements. Inversions with GOSAT data show good agreement with surface measurements, whereas for SCIAMACHY a similar performance can only be achieved after significant bias corrections. Some inconsistencies between surface and total‐column methane remain in the Southern Hemisphere. However, comparisons with measurements from the Total Column Carbon Observing Network in situ Fourier transform spectrometer network indicate that those may be caused by systematic model errors rather than by shortcomings in the GOSAT retrievals. The global patterns of methane emissions derived from SCIAMACHY (with bias correction) and GOSAT retrievals are in remarkable agreement and allow an increased resolution of tropical emissions. The satellite inversions increase tropical methane emission by 30 to 60 TgCH4/yr compared to initial a priori estimates, partly counterbalanced by reductions in emissions at midlatitudes to high latitudes.

Global Distribution of Cloud Top Height as Retrieved from SCIAMACHY Onboard ENVISAT Spaceborne Observations

The spatial and temporal analysis of the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard ENVISAT global cloud top height data for 2003–2006 is presented. The cloud top height is derived using a semi-analytical cloud top height retrieval algorithm based on an asymptotic solution of the radiative transfer equation in the oxygen A-band. The analysis is valid for thick clouds only. As expected, clouds are higher in the equatorial region. The cloud altitudes decrease towards the Poles due to the general decrease of the troposphere height. The global average cloud top height as derived from SCIAMACHY measurements is 7.3 km. We also studied the planetary reflectivity R at 443 nm and found that the annual average is R = 0.49 ± 0.08 for the years analyzed.

Validation of five years (2003–2007) of SCIAMACHY CO total column measurements using ground-based spectrometer observations

Abstract. This paper presents a validation study of SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) carbon monoxide (CO) total column measurements from the Iterative Maximum Likelihood Method (IMLM) algorithm using ground-based spectrometer observations from twenty surface stations for the five year time period of 2003–2007. Overall we find a good agreement between SCIAMACHY and ground-based observations for both mean values as well as seasonal variations. For high-latitude Northern Hemisphere stations absolute differences between SCIAMACHY and ground-based measurements are close to or fall within the SCIAMACHY CO 2σ precision of 0.2 × 1018 molecules/cm2 (∼10%) indicating that SCIAMACHY can observe CO accurately at high Northern Hemisphere latitudes. For Northern Hemisphere mid-latitude stations the validation is complicated due to the vicinity of emission sources for almost all stations, leading to higher ground-based measurements compared to SCIAMACHY CO within its typical sampling area of 8° × 8°. Comparisons with Northern Hemisphere mountain stations are hampered by elevation effects. After accounting for these effects, the validation provides satisfactory results. At Southern Hemisphere mid- to high latitudes SCIAMACHY is systematically lower than the ground-based measurements for 2003 and 2004, but for 2005 and later years the differences between SCIAMACHY and ground-based measurements fall within the SCIAMACHY precision. The 2003–2004 bias is consistent with previously reported results although its origin remains under investigation. No other systematic spatial or temporal biases could be identified based on the validation presented in this paper. Validation results are robust with regard to the choices of the instrument-noise error filter, sampling area, and time averaging required for the validation of SCIAMACHY CO total column measurements. Finally, our results show that the spatial coverage of the ground-based measurements available for the validation of the 2003–2007 SCIAMACHY CO columns is sub-optimal for validation purposes, and that the recent and ongoing expansion of the ground-based network by carefully selecting new locations may be very beneficial for SCIAMACHY CO and other satellite trace gas measurements validation efforts.

First steps towards the assimilation of IASI ozone data into the MOCAGE-PALM system

Abstract. With the use of data assimilation, we study the quality of the Infrared Atmospheric Sounding Interferometer (IASI) total ozone column measurements. The IASI data are provided by the inversion of IASI radiances performed at the Laboratoire ATmosphères, Milieux, Observations Spatiales (LATMOS). This data set is initially compared on a five-month period to a three-dimensional time varying ozone field that we take as a reference. This reference field results from the combined assimilation of ozone profiles from the Microwave Limb Sounder (MLS) instrument and of total ozone columns from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument. It has low systematic and random errors when compared to ozonesondes and Ozone Monitoring Instrument (OMI) data. The comparison shows that on average, the LATMOS-IASI data tends to overestimate the total ozone columns by 2% to 8%. The random observation error of the LATMOS-IASI data is estimated to about 7%, except over polar regions and deserts where it is higher. The daytime data have generally lower biases but higher random error than the nighttime data. Using this information, the LATMOS-IASI data are then assimilated, combined with the MLS data. This first LATMOS-IASI data assimilation experiment shows that the resulting analysis is quite similar to the one obtained from the combined MLS and SCIAMACHY data assimilation. The differences are mainly due to the lack of SCIAMACHY measurements during polar night, and to the higher LATMOS-IASI random errors especially over the southern polar region.

Tropospheric NO 2 columns over East Central China: Comparisons between SCIAMACHY measurements and nested CMAQ simulations

Tropospheric NO 2 vertical column densities over East Central China (ECC) simulated with a regional air quality model are compared with those measured by the remote sensor SCIAMACHY (SCanning Imaging Absorption Spectrometer for Atmospheric CHartographY). A 3D Eulerian air quality model (Models-3/CMAQ) and a best available emission inventory are employed in the simulations. The objectives are to delve into (i) the suitability of the emission inventory employed, (ii) the reliability of SCIAMACHY observations over ECC, and (iii) the role of model resolution on predictions. The predicted NO 2 concentrations are integrated from the bottom to the model top and converted from the model grid to satellite pixel bases. The model reproduces the spatial distribution of SCIAMACHY-observed NO 2 vertical column densities satisfactorily with a correlation coefficient of about 0.76, but with a large normalized mean bias ∼−60%. The latter bias is ascribed to the sharp increase of emissions that have occurred in ECC owing to rapid industrialization ever since the compilation of the emission inventory. When the model grid size is larger than the size of a satellite pixel, a decrease of grid size improves the CMAQ predictions when compared with SCIAMACHY, although higher resolutions in general do not necessarily improve CMAQ predictions. A critical cloud fraction of 0.2 is found to give the best comparisons between SCIAMACHY data and simulations.

Scanning Imaging Absorption Spectrometer for Atmospheric Chartography carbon monoxide total columns: Statistical evaluation and comparison with chemistry transport model results

This paper presents a detailed statistical analysis of one year (September 2003 to August 2004) of global Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) carbon monoxide (CO) total column retrievals from the Iterative Maximum Likelihood Method (IMLM) algorithm, version 6.3. SCIAMACHY provides the first solar reflectance measurements of CO and is uniquely sensitive down to the boundary layer. SCIAMACHY measurements and chemistry transport model (CTM) results are compared and jointly evaluated. Significant improvements in agreement occur, especially close to biomass burning emission regions, when the new Global Fire Emissions Database version 2 (GFEDv2) is used with the CTM. Globally, the seasonal variation of the model is very similar to that of the SCIAMACHY measurements. For certain locations, significant differences were found, which are likely related to modeling errors due to CO emission uncertainties. Statistical analysis shows that differences between single SCIAMACHY CO total column measurements and corresponding model results are primarily explained by random instrument noise errors. This strongly suggests that the random instrument noise errors are a good diagnostic for the precision of the measurements. The analysis also indicates that noise in single SCIAMACHY CO measurements is generally greater than actual variations in total columns. It is thus required to average SCIAMACHY data over larger temporal and spatial scales to obtain valuable information. Analyses of monthly averaged SCIAMACHY measurements over 3° × 2° geographical regions indicates that they are of sufficient accuracy to reveal valuable information about spatial and temporal variations in CO columns and provide an important tool for model validation. A large spatial and temporal variation in instrument noise errors exists which shows a close correspondence with the spatial distribution of surface albedo and cloud cover. This large spatial variability is important for the use of monthly and annual mean SCIAMACHY CO total column measurements. The smallest instrument noise errors of monthly mean 3° × 2° SCIAMACHY CO total columns measurements are 0.01 × 1018 molecules/cm2 for high surface albedo areas over the Sahara. Errors in SCIAMACHY CO total column retrievals due to errors other than instrument noise, like cloud cover, calibration, retrieval uncertainties and averaging kernels are estimated to be about 0.05–0.1 × 1018 molecules/cm2 in total. The bias found between model and observations is around 0.05–0.1 1018 molecules/cm2 (or about 5%) which also includes model errors. This thus provides a best estimate of the currently achievable measurement accuracy for SCIAMACHY CO monthly mean averages.

The semianalytical cloud retrieval algorithm for SCIAMACHY II. The application to MERIS and SCIAMACHY data

Abstract. The SemiAnalytical CloUd Retrieval Algorithm (SACURA) is applied to the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. In particular, we derive simultaneously cloud optical thickness (COT) and cloud top height (CTH), using SCIAMACHY measurements in the visible (442 nm, COT) and in the oxygen A-band (755–775 nm, CTH). Some of the results obtained are compared with those derived from the Medium Resolution Imaging Spectrometer (MERIS), which has better spatial resolution and observes almost the same scene as SCIAMACHY. The same cloud algorithm is applied to both MERIS and SCIAMACHY data. In addition, we perform the vicarious calibration of SCIAMACHY at the wavelength 442 nm, using MERIS measurements at the same wavelength. Differences in the retrieved COT for the same cloud field obtained using MERIS and SCIAMACHY measurements are discussed.

BrO emission from volcanoes: A survey using GOME and SCIAMACHY measurements

Volcanic eruptions are known to be a major source of SO2 and some reactive halogen species notably HCl and HF. Recent studies have however observed the presence of large amounts of BrO with tight correlation to SO2 in a volcanic plume by ground‐based spectroscopic measurements. In this work, upper limits of BrO columns have been estimated for a number of volcanic eruptions observed in measurements made by two satellite instruments ‐ the Global Ozone Monitoring Experiment (GOME), and the new SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The results obtained for the eruptions covered by satellite overpasses over the Etna, Nyamuragira, Popocatépetl, and Reventador volcanoes show no correlation between enhanced volcanic SO2 during large eruptions and the corresponding BrO columns. Evidence for BrO enhancement was also not found in the vicinity of the Soufrière Hills volcanoes. The possible reasons for the differences between ground‐based and satellite observations are considered.

First retrieval of global water vapour column amounts from SCIAMACHY measurements

Abstract. Global water vapour column amounts have been derived for the first time from measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on the European environmental satellite ENVISAT. For this purpose, two different existing retrieval algorithms have been adapted, namely the Air Mass Corrected Differential Absorption Spectroscopy (AMC-DOAS) which was originally designed for GOME and the Weighting Function Modified Differential Absorption Spectroscopy (WFM-DOAS) which was mainly designed for the retrieval of CH4, CO2 and CO from SCIAMACHY near-infrared spectra. Here, both methods have been applied to SCIAMACHY's nadir measurements in the near-visible spectral region around 700 nm. Taking into account a systematic offset of 10%, the results of these two methods agree within a scatter of about ±0.5 g/cm2 with corresponding SSM/I and ECMWF water vapour data. This deviation includes contributions from the temporal and spatial variability of water vapour. In fact, the mean deviation between the SCIAMACHY and the correlative data sets is much smaller: the SCIAMACHY total water vapour columns are typically about 0.15 g/cm2 lower than the SSM/I values and less than 0.1 g/cm2 lower than corresponding ECMWF data. The SCIAMACHY water vapour results agree well with correlative data not only over ocean but also over land, thus showing the capability of SCIAMACHY to derive water vapour concentrations on the global scale.

NLC detection and particle size determination: first results from SCIAMACHY on ENVISAT

Measurements of limb scattered radiance spectra performed with the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) aboard ENVISAT are used to detect noctilucent clouds (NLCs) in the northern hemisphere during summer 2002. The NLCs are easily identified by enhanced limb radiances around 80 km tangent height. Using limb radiances in the UV-B/C spectral range, where multiple scattering is negligible, the spectral signature of the NLC backscatter can be determined directly. Mie-calculations are used to estimate particle sizes of these clouds from SCIAMACHY measurements. In particular, we use the information contained in the spectral exponent of the NLC limb backscatter signal. The derived particle radii assuming a log-normal NLC particle size distribution are 40–50 nm and they are in excellent agreement with previous particle size estimates.

The SCIAMACHY calibration/monitoring concept and first results

The Scanning Imaging Absorption Spectro meter for Atmospheric Chartograph y (SCIAMACHY) is a contribution to the ENVISAT satellite, which has been launched successfully in March 2002. SCIAMACHY determines the amount and distributions of a large number of atmospheric constituents by measuring Earthshine radiance and solar irradiance spectra simultaneously from the UV to the NIR in various viewing geometries. The scientific goals of the SCIAMACHY mission can only be reached by an instrument having a high spectral and radiometric accuracy and stability. For example, to determine global NO 2 concentrations SCIAMACHY measurements need to be sensitive to differential spectral structures down to the order of 10 −4. These requirements can only be met by an appropriate instrument design in combination with both on-ground and in-flight calibration and monitoring. This paper gives an overview on the SCIAMACHY calibration and monitoring concept and activities which are essential to ensure the high quality of SCIAMACHY data products throughout the instrument lifetime. Furthermore, first in-flight monitoring results are presented.

Nadir, limb, and occultation measurements with SCIAMACHY

The Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) is a contribution to the ENVISAT-1 satellite, which is to be launched in mid 2001. The SCIAMACHY instrument is designed to measure sunlight transmitted, reflected and scattered by the Earth's atmosphere or surface simultaneously from the UV to the NIR spectral spectral region (240 – 2380 nm) in various viewing geometries. Inversion of the SCIAMACHY measurements will provide the amount and distributions of a large number of atmospheric constituents in the stratosphere and troposphere (O 3, NO 2, H 2O, CO 2, CH 4, N 2O, BrO, CO, O 2, O 2( 1Δ g ), NO, SO 2, H 2CO, (ClO,) and OClO). This paper concentrates on the characteristics of the SCIAMACHY mission. In particular, the measurement strategies for the different observational modes — nadir, limb, and both solar and lunar occultation — and their operational implementation are described.