scholarly journals SCIAMACHY CO over land and oceans: 2003–2007 interannual variability

2009 ◽  
Vol 9 (11) ◽  
pp. 3799-3813 ◽  
Author(s):  
A. M. S. Gloudemans ◽  
A. T. J. de Laat ◽  
H. Schrijver ◽  
I. Aben ◽  
J. F. Meirink ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Biomass Burning ◽  
Accurate Determination ◽  
Likelihood Method ◽  
Retrieval Algorithm ◽  
Data Set ◽  
Noise Error ◽  
A Minor ◽  
Iterative Maximum Likelihood ◽  
Good Agreement

Abstract. We present a new method to obtain accurate SCIAMACHY CO columns over clouded ocean scenes. Based on an improved version of the Iterative Maximum Likelihood Method (IMLM) retrieval algorithm, we now have retrieved five years of data over both land and clouded ocean scenes between 2003 and 2007. The ocean-cloud method uses the CH4 columns retrieved simultaneously with the CO columns to determine the cloud top height. The CH4 cloud top height is in good agreement with the FRESCO+ cloud top height determined from UV-VIS oxygen-A band measurements, providing confidence that the CH4 cloud top height is a good diagnostic of the cloud top height over (partially) clouded ocean scenes. The CO measurements over clouded ocean scenes have been compared with collocated modeled CO columns over the same clouds and agree well. Using clouded ocean scenes quadruples the number of useful CO measurements compared to land-only measurements. The five-year CO data set over land and clouded ocean scenes presented here is based on an improved version of the IMLM algorithm which includes a more accurate determination of the random instrument-noise error for CO. This leads to a smaller spread in the differences between single CO measurements and the corresponding model values. The new version, IMLM version 7.4, also uses updated spectroscopic parameters for H2O and CH4 but this has only a minor impact on the retrieved CO columns. The five-year data set shows significant interannual variability over land and over clouded ocean scenes. Three examples are highlighted: the Asian outflow of pollution over the northern Pacific, the biomass-burning outflow over the Indian Ocean originating from Indonesia, and biomass burning in Brazil. In general there is good agreement between observed and modeled seasonal cycles and interannual variability.

scholarly journals SCIAMACHY CO over the oceans: 2003–2007 interannual variability

2009 ◽  
Vol 9 (2) ◽  
pp. 5583-5621
Author(s):  
A. M. S. Gloudemans ◽  
A. T. J. de Laat ◽  
H. Schrijver ◽  
I. Aben ◽  
J. F. Meirink ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Biomass Burning ◽  
Accurate Determination ◽  
Likelihood Method ◽  
Retrieval Algorithm ◽  
Data Set ◽  
Noise Error ◽  
A Minor ◽  
Iterative Maximum Likelihood ◽  
Good Agreement

Abstract. We present a new method to obtain accurate SCIAMACHY CO columns over clouded ocean scenes. Based on an improved version of the Iterative Maximum Likelihood Method (IMLM) retrieval algorithm, we now have retrieved five years of data over both land and clouded ocean scenes between 2003 and 2007. The ocean-cloud method uses the CH4 columns retrieved simultaneously with the CO columns to determine the cloud top height. The CH4 cloud top height is in good agreement with the FRESCO+ cloud top height determined from UV-VIS oxygen-A band measurements, providing confidence that the CH4 cloud top height is a good diagnostic of the cloud top height over (partially) clouded ocean scenes. The CO measurements over clouded ocean scenes have been compared with collocated modeled CO columns over the same clouds and agree well. Using clouded ocean scenes quadruples the number of useful CO measurements compared to land-only measurements. The five-year CO data set over land and clouded ocean scenes presented here is based on an improved version of the IMLM algorithm which includes a more accurate determination of the random instrument-noise error for CO. This leads to a smaller spread in the differences between single CO measurements and the corresponding model values. The new version, IMLM version 7.4, also uses updated spectroscopic parameters for H2O and CH4 but this has only a minor impact on the retrieved CO columns. The five-year data set shows significant interannual variability over land and over clouded ocean scenes. Three examples are highlighted: the Asian outflow of pollution over the northern Pacific, the biomass-burning outflow over the Indian Ocean originating from Indonesia, and biomass burning in Brazil. In general there is good agreement between observed and modeled seasonal cycles and interannual variability.

scholarly journals A climatology of the diurnal variations in stratospheric and mesospheric ozone over Bern, Switzerland

2014 ◽  
Vol 14 (12) ◽  
pp. 5905-5919 ◽  
Author(s):  
S. Studer ◽  
K. Hocke ◽  
A. Schanz ◽  
H. Schmidt ◽  
N. Kämpfer
Keyword(s):  
Interannual Variability ◽  
Climate Model ◽  
Stratospheric Ozone ◽  
Diurnal Variations ◽  
Interannual Variations ◽  
Data Set ◽  
Unique Data ◽  
Ozone Variation ◽  
Mesospheric Ozone ◽  
Good Agreement

Abstract. The ground-based radiometer GROMOS, stationed in Bern (47.95° N, 7.44° E), Switzerland, has a unique data set: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equivalent quality during night- and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 years of GROMOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The diurnal ozone cycle from GROMOS is compared to two models: the Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized Atmosphere (HAMMONIA). Generally, observation and models show a good agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25% less than midnight ozone. In the stratosphere, ozone reaches its maximum in the afternoon showing values several percent larger than the midnight value. Further, GROMOS and models indicate a seasonal behaviour of the diurnal ozone variations in the stratosphere with a larger afternoon maximum during daytime in summer than in winter. Using the 17 years of ozone profiles from GROMOS, we find strong interannual variations in the diurnal ozone cycle for both the stratosphere and the mesosphere. Interannual variability in temperature, atmospheric circulation and composition may explain the observed interannual variability of the diurnal ozone cycle above Bern.

scholarly journals Five years of CO, HCN, C<sub>2</sub>H<sub>6</sub>, C<sub>2</sub>H<sub>2</sub>, CH<sub>3</sub>OH, HCOOH and H<sub>2</sub>CO total columns measured in the Canadian high Arctic

2014 ◽  
Vol 7 (6) ◽  
pp. 1547-1570 ◽  
Author(s):  
C. Viatte ◽  
K. Strong ◽  
K. A. Walker ◽  
J. R. Drummond
Keyword(s):  
Time Series ◽  
Fourier Transform ◽  
Biomass Burning ◽  
Atmospheric Chemistry ◽  
A Priori ◽  
Estimation Method ◽  
Optimal Estimation ◽  
High Arctic ◽  
Retrieval Algorithm ◽  
Data Set

Abstract. We present a five-year time series of seven tropospheric species measured using a ground-based Fourier transform infrared (FTIR) spectrometer at the Polar Environment Atmospheric Research Laboratory (PEARL; Eureka, Nunavut, Canada; 80°05' N, 86°42' W) from 2007 to 2011. Total columns and temporal variabilities of carbon monoxide (CO), hydrogen cyanide (HCN) and ethane (C2H6) as well as the first derived total columns at Eureka of acetylene (C2H2), methanol (CH3OH), formic acid (HCOOH) and formaldehyde (H2CO) are investigated, providing a new data set in the sparsely sampled high latitudes. Total columns are obtained using the SFIT2 retrieval algorithm based on the optimal estimation method. The microwindows as well as the a priori profiles and variabilities are selected to optimize the information content of the retrievals, and error analyses are performed for all seven species. Our retrievals show good sensitivities in the troposphere. The seasonal amplitudes of the time series, ranging from 34 to 104%, are captured while using a single a priori profile for each species. The time series of the CO, C2H6 and C2H2 total columns at PEARL exhibit strong seasonal cycles with maxima in winter and minima in summer, in opposite phase to the HCN, CH3OH, HCOOH and H2CO time series. These cycles result from the relative contributions of the photochemistry, oxidation and transport as well as biogenic and biomass burning emissions. Comparisons of the FTIR partial columns with coincident satellite measurements by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) show good agreement. The correlation coefficients and the slopes range from 0.56 to 0.97 and 0.50 to 3.35, respectively, for the seven target species. Our new data set is compared to previous measurements found in the literature to assess atmospheric budgets of these tropospheric species in the high Arctic. The CO and C2H6concentrations are consistent with negative trends observed over the Northern Hemisphere, attributed to fossil fuel emission decrease. The importance of poleward transport for the atmospheric budgets of HCN and C2H2 is highlighted. Columns and variabilities of CH3OH and HCOOH at PEARL are comparable to previous measurements performed at other remote sites. However, the small columns of H2CO in early May might reflect its large atmospheric variability and/or the effect of the updated spectroscopic parameters used in our retrievals. Overall, emissions from biomass burning contribute to the day-to-day variabilities of the seven tropospheric species observed at Eureka.

scholarly journals Error analysis for CO and CH<sub>4</sub> total column retrievals from SCIAMACHY 2.3 μm spectra

2008 ◽  
Vol 8 (14) ◽  
pp. 3999-4017 ◽  
Author(s):  
A. M. S. Gloudemans ◽  
H. Schrijver ◽  
O. P. Hasekamp ◽  
I. Aben
Keyword(s):  
Sensitivity Analysis ◽  
Likelihood Method ◽  
Retrieval Algorithm ◽  
Polarization Sensitivity ◽  
Line Intensities ◽  
Aerosol Scattering ◽  
Detailed Assessment ◽  
Instrument Noise ◽  
Iterative Maximum Likelihood ◽  
The Impact

Abstract. A detailed sensitivity analysis of the Iterative Maximum Likelihood Method (IMLM) algorithm and its application to the SCIAMACHY 2.3 μm spectra is presented. The sensitivity analysis includes a detailed assessment of the impact of aerosols in the 2.3 μm range. Results show that near strong aerosol sources mineral dust and biomass aerosols can have an effect of ~7–10% on the CH4 total columns retrieved from this wavelength range if aerosol scattering is neglected in the retrieval algorithm. Similar but somewhat larger effects are found for CO, but due to the larger variability of CO these errors are less important. Away from strong sources much smaller effects of a few percent are found. Using CH4 as a proxy for CO and/or including aerosol information in the retrieval algorithm significantly reduces these errors for both CO and CH4. Spectroscopic uncertainties are mostly negligible except for uncertainties in the CH4 intrinsic line intensities, which can be important. Application of the IMLM algorithm to the SCIAMACHY 2.3 μm spectra shows that the quality of the retrieved CO and CH4 total columns is good, except for a bias for large instrument-noise errors which is partly due to remaining calibration issues. Polarization sensitivity of the SCIAMACHY instrument has a negligible effect on the retrieved CO and CH4 total columns. The H2O total columns, which have to be retrieved simultaneously with CO and CH4 due to overlapping absorption lines, agree well with H2O total columns from ECMWF data. This ensures that the fit to the H2O absorptions is of sufficient quality not to hamper the retrieved CO and CH4 total columns from SCIAMACHY spectra.

scholarly journals Three years of global carbon monoxide from SCIAMACHY: comparison with MOPITT and first results related to the detection of enhanced CO over cities

2007 ◽  
Vol 7 (9) ◽  
pp. 2399-2411 ◽  
Author(s):  
M. Buchwitz ◽  
I. Khlystova ◽  
H. Bovensmann ◽  
J. P. Burrows
Keyword(s):  
Carbon Monoxide ◽  
Near Infrared ◽  
Retrieval Algorithm ◽  
Vertical Column ◽  
Data Set ◽  
Retrieval Method ◽  
First Results ◽  
Long Time ◽  
Global Carbon ◽  
Good Agreement

Abstract. Carbon monoxide (CO) is an important atmospheric constituent affecting air quality and climate. SCIAMACHY on ENVISAT is currently the only satellite instrument that can measure the vertical column of CO with nearly equal sensitivity at all altitudes down to the Earth's surface because of its near-infrared nadir observations of reflected solar radiation. Here we present three years' (2003–2005) of SCIAMACHY CO columns consistently retrieved with the latest version of our retrieval algorithm (WFMDv0.6). We describe the retrieval method and discuss the multi-year global CO data set focusing on a comparison with the operational CO column data product of MOPITT. We found reasonable to good agreement (~20%) with MOPITT, with the best agreement for 2004. We present detailed results for various regions (Europe, Middle East, India, China) and discuss to what extent enhanced levels of CO can be detected over populated areas including individual cities. The expected CO signal from cities is close to or even below the detection limit of individual measurements. We show that cities can be identified when averaging long time series.

scholarly journals Cloud<i>_</i>cci ATSR-2 and AATSR data set version 3: a 17-year climatology of global cloud and radiation properties

2020 ◽  
Vol 12 (3) ◽  
pp. 2121-2135
Author(s):  
Caroline A. Poulsen ◽  
Gregory R. McGarragh ◽  
Gareth E. Thomas ◽  
Martin Stengel ◽  
Matthew W. Christensen ◽  
...  
Keyword(s):  
Liquid Water ◽  
European Space Agency ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Data Set ◽  
Water Path ◽  
Cloud Properties ◽  
Wide Range ◽  
Good Agreement

Abstract. We present version 3 (V3) of the Cloud_cci Along-Track Scanning Radiometer (ATSR) and Advanced ATSR (AATSR) data set. The data set was created for the European Space Agency (ESA) Cloud_cci (Climate Change Initiative) programme. The cloud properties were retrieved from the second ATSR (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) spanning 1995–2003 and the AATSR on board Envisat, which spanned 2002–2012. The data are comprised of a comprehensive set of cloud properties: cloud top height, temperature, pressure, spectral albedo, cloud effective emissivity, effective radius, and optical thickness, alongside derived liquid and ice water path. Each retrieval is provided with its associated uncertainty. The cloud property retrievals are accompanied by high-resolution top- and bottom-of-atmosphere shortwave and longwave fluxes that have been derived from the retrieved cloud properties using a radiative transfer model. The fluxes were generated for all-sky and clear-sky conditions. V3 differs from the previous version 2 (V2) through development of the retrieval algorithm and attention to the consistency between the ATSR-2 and AATSR instruments. The cloud properties show improved accuracy in validation and better consistency between the two instruments, as demonstrated by a comparison of cloud mask and cloud height with co-located CALIPSO data. The cloud masking has improved significantly, particularly in its ability to detect clear pixels. The Kuiper Skill score has increased from 0.49 to 0.66. The cloud top height accuracy is relatively unchanged. The AATSR liquid water path was compared with the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) in regions of stratocumulus cloud and shown to have very good agreement and improved consistency between ATSR-2 and AATSR instruments. The correlation with MAC-LWP increased from 0.4 to over 0.8 for these cloud regions. The flux products are compared with NASA Clouds and the Earth's Radiant Energy System (CERES) data, showing good agreement within the uncertainty. The new data set is well suited to a wide range of climate applications, such as comparison with climate models, investigation of trends in cloud properties, understanding aerosol–cloud interactions, and providing contextual information for co-located ATSR-2/AATSR surface temperature and aerosol products. The following new digital identifier has been issued for the Cloud_cci ATSR-2/AATSRv3 data set: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003 (Poulsen et al., 2019).

scholarly journals Retrieval of ozone profiles from OMPS limb scattering observations

2017 ◽  
Author(s):  
Carlo Arosio ◽  
Alexei Rozanov ◽  
Elizaveta Malinina ◽  
Kai-Uwe Eichmann ◽  
Thomas von Clarmann ◽  
...  
Keyword(s):  
Visible Spectral Range ◽  
Retrieval Algorithm ◽  
Tropical Region ◽  
Data Sets ◽  
Absorption Bands ◽  
Data Set ◽  
Northern Latitudes ◽  
The University ◽  
Combined Data ◽  
Good Agreement

Abstract. This study describes a retrieval algorithm developed at the University of Bremen to retrieve vertical profiles of ozone from limb observations performed by the Ozone Mapper and Profiler Suite (OMPS). This algorithm was originally developed for use with data from the SCIAMACHY instrument. As both instruments make limb measurements of the scattered solar radiation in the ultraviolet and visible spectral range, an overarching objective of the study is to facilitate the provision of consolidated and consistent ozone profiles from the two satellites and to produce a combined data set. The optimization of the retrieval algorithm for OMPS takes into account the instrument-specific spectral coverage by exploiting information from spectral windows in the Hartley, Huggins and Chappuis ozone absorption bands. Thereby, ozone concentrations in the 12–60 km altitude range can be retrieved. Observations at altitudes where the measurements are contaminated by clouds are rejected by applying a cloud filter. An independent aerosol retrieval is performed beforehand and its results are used to account for the aerosol load in the stratosphere during the ozone retrieval. Results for seven months of data (July 2016–January 2017) are compared and validated against independent data sets from both satellite-based and balloon-borne measurements, indicating a good agreement. Between 20 and 50 km, the OMPS ozone profiles typically agree with the MLS v4.2 results within 5–10 %, with the exception of high northern latitudes (> 70° N above 40 km) and the tropical lower stratosphere. The comparison of OMPS profiles with those from ozonesondes shows an agreement within ±5 % between 14 and 30 km at northern mid-latitudes. At southern mid-latitudes, an agreement within 5–10 % is achieved, although these results are less reliable because of a limited number of available coincidences. An unexpected bias of approximately 10 % is detected in the tropical region at all altitudes. The processing of the 2013 data set using the same retrieval settings and its validation against ozonesondes reveals a much smaller bias; possible reasons are under investigation.

scholarly journals Testing aerosol properties in MODIS Collection 4 and 5 using airborne sunphotometer observations in INTEX-B/MILAGRO

2009 ◽  
Vol 9 (21) ◽  
pp. 8159-8172 ◽  
Author(s):  
J. Redemann ◽  
Q. Zhang ◽  
J. Livingston ◽  
P. Russell ◽  
Y. Shinozuka ◽  
...  
Keyword(s):  
Retrieval Algorithm ◽  
Average Increase ◽  
Data Set ◽  
Study Region ◽  
Transport Experiment ◽  
Satellite Sensors ◽  
Fine Mode ◽  
Shortwave Infrared ◽  
Aerosol Properties ◽  
Good Agreement

Abstract. The 14-channel Ames Airborne Tracking Sunphotometer (AATS) was operated on a Jetstream 31 (J31) aircraft in March 2006 during MILAGRO/INTEX-B (Megacity Initiative-Local And Global Research Observations/Phase B of the Intercontinental Chemical Transport Experiment). We compare AATS retrievals of spectral aerosol optical depth (AOD) and related aerosol properties with corresponding spatially coincident and temporally near-coincident measurements acquired by the MODIS-Aqua and MODIS-Terra satellite sensors. These comparisons are carried out for the older MODIS Collection 4 (C4) and the new Collection 5 (C5) data set, the latter representing a reprocessing of the entire MODIS data set completed during 2006 with updated calibration and aerosol retrieval algorithm. Our analysis yields a direct, validated assessment of the differences between select MODIS C4 and C5 aerosol retrievals. Our analyses of 37 coincident observations by AATS and MODIS-Terra and 18 coincident observations between AATS and MODIS-Aqua indicate notable differences between MODIS C4 and C5 and between the two sensors. For MODIS-Terra, we find an average increase in AOD of 0.02 at 553 nm and 0.01 or less at the shortwave infrared (SWIR) wavelengths. The change from C4 to C5 results in less good agreement with the AATS derived spectral AOD, with average differences at 553 nm increasing from 0.03 to 0.05. For MODIS-Aqua, we find an average increase in AOD of 0.008 at 553 nm, but an increase of nearly 0.02 at the SWIR wavelengths. The change from C4 to C5 results in slightly less good agreement to the AATS derived visible AOD, with average differences at 553 nm increasing from 0.03 to 0.04. However, at SWIR wavelengths, the changes from C4 to C5 result in improved agreement between MODIS-Aqua and AATS, with the average differences at 2119 nm decreasing from −0.02 to −0.003. Comparing the Angstrom exponents calculated from AOD at 553nm and 855nm, we find an increased rms difference from AATS derived Angstrom exponents in going from C4 to C5 for MODIS-Terra, and a decrease in rms difference, hence an improvement, for the transition from C4 to C5 in MODIS-Aqua. Combining the AATS retrievals with in situ measurements of size-dependent aerosol extinction, we derive a suborbital measure of the aerosol submicron fraction (SMF) of AOD and compare it to MODIS retrievals of aerosol fine mode fraction (FMF). Our analysis shows a significant rms-difference between the MODIS-Terra FMF and suborbitally-derived SMF of 0.17 for both C4 and C5. For MODIS-Aqua, there is a slight improvement in the transition from C4 to C5, with the rms-difference from AATS dropping from 0.23 to 0.16. The differences in MODIS C4 and C5 AOD in this limited data set can be traced to changes in the reflectances input to the aerosol retrievals. An extension of the C4-C5 comparisons from the area along the J31 flight track to a larger study region between 18–23° N and 93–100° W on each of the J31 flight days supports the finding of significant differences between MODIS C4 and C5.

scholarly journals Validation of two independent retrievals of SCIAMACHY water vapour columns using radiosonde data

2013 ◽  
Vol 6 (1) ◽  
pp. 665-702 ◽  
Author(s):  
A. du Piesanie ◽  
A. J. M. Piters ◽  
I. Aben ◽  
H. Schrijver ◽  
P. Wang ◽  
...  
Keyword(s):  
Water Vapour ◽  
Correction Method ◽  
Short Wave ◽  
Mean Difference ◽  
Likelihood Method ◽  
Radiosonde Data ◽  
Retrieval Algorithm ◽  
Infrared Wavelength ◽  
Integrated Water Vapour ◽  
Iterative Maximum Likelihood

Abstract. Two independently derived SCIAMACHY total water vapour column (WVC) products are compared with integrated water vapour data calculated from radiosonde measurements, and with each other. The two SCIAMACHY WVC products are retrieved with two different retrieval algorithms applied in the visible and short wave infrared wavelength regions respectively. The first SCIAMACHY WVC product used in the comparison is ESA's level 2 version 5.01 WVC product derived with the Air Mass Corrected Differential Absorption Spectroscopy (AMC-DOAS) retrieval algorithm (SCIAMACHY-ESA). The second SCIAMACHY WVC product is derived using the Iterative Maximum Likelihood Method (IMLM) developed by Netherlands Institute for Space Research (SCIAMACHY-IMLM). Both SCIAMACHY WVC products are compared with collocated water vapour amounts determined from daily relative humidity radiosonde measurements obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) radiosonde network, over an 18 month and 2 yr period respectively. Results indicate a good agreement between the WVC amounts of SCIAMACHY-ESA and the radiosonde, and a mean difference of 0.03 g cm−2 is found for cloud free conditions. Overall the SCIAMACHY-ESA WVC amounts are smaller than the radiosonde WVC amounts, especially over oceans. For cloudy conditions the WVC bias has a clear dependence on the cloud top height and increases with increasing cloud top heights larger than approximately 2 km. A likely cause for this could be the different vertical profile shapes of water vapour and O2 leading to different relative changes in their optical thickness, which makes the AMF correction method used in the algorithm less suitable for high clouds. The SCIAMACHY-IMLM WVC amounts compare well to the radiosonde WVC amounts during cloud free conditions over land. A mean difference of 0.08 g cm−2 is found which is consistent with previous results when comparing daily averaged SCIAMACHY-IMLM WVC amounts with ECMWF model data globally. Furthermore, we show that the measurements for cloudy conditions (cloud fraction ≥ 0.5) with low clouds (cloud pressure ≥ 930 hPa) above the ocean and land compare quite well with radiosonde data.

scholarly journals Validation of six years of SCIAMACHY carbon monoxide observations using MOZAIC CO profile measurements

2012 ◽  
Vol 5 (1) ◽  
pp. 1985-2010
Author(s):  
A. T. J. de Laat ◽  
R. Dijkstra ◽  
H. Schrijver ◽  
P. Nédélec ◽  
I. Aben
Keyword(s):  
Carbon Monoxide ◽  
Validation Study ◽  
Likelihood Method ◽  
Mean Values ◽  
Airborne Measurements ◽  
Time Period ◽  
Scanning Imaging ◽  
Good Signal ◽  
Iterative Maximum Likelihood ◽  
Good Agreement

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 vertically integrated profile aircraft measurements obtained within the MOZAIC project for the six year time period of 2003–2008. Overall we find a good agreement between SCIAMACHY and airborne measurements for both mean values – also on a year-to-year basis – as well as seasonal variations. Several locations show large biases that are attributed to local effects like orography and proximity of large emission sources. Differences were detected for individual years: 2003, 2004 and 2006 have larger biases than 2005, 2007 and 2008, which appear to be related to SCIAMACHY instrumental issues but require more research. Results from this study are consistent with, and complementary to, findings from a previous validation study using ground-based measurements (de Laat et al., 2010). Despite the presence of some biases, this study provides additional confidence that SCIAMACHY, if individual measurements are of sufficient quality – good signal-to-noise – can be used to determine the spatial distribution and seasonal cycles of CO total columns.

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