scholarly journals Modulations of the 27 day solar rotation signal in stratospheric ozone from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) (2003–2008)

2010 ◽  
Vol 115 ◽  
Author(s):  
Sebastian Dikty ◽  
Mark Weber ◽  
Christian von Savigny ◽  
Thiranan Sonkaew ◽  
Alexei Rozanov ◽  
...  
Keyword(s):  
Solar Rotation ◽  
Stratospheric Ozone ◽  
Scanning Imaging ◽  
Absorption Spectrometer ◽  
Rotation Signal

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

2018 ◽  
Vol 11 (4) ◽  
pp. 2345-2360 ◽  
Author(s):  
Sweta Shah ◽  
Olaf N. E. Tuinder ◽  
Jacob C. A. van Peet ◽  
Adrianus T. J. de Laat ◽  
Piet Stammes
Keyword(s):  
Pressure Range ◽  
Stratospheric Ozone ◽  
Spectral Shift ◽  
Retrieval Algorithm ◽  
Visible Range ◽  
L1 Data ◽  
Ozone Profile ◽  
Level 1 ◽  
Scanning Imaging ◽  
Radiance Data

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.

scholarly journals SCIAMACHY Absorbing Aerosol Index – calibration issues and global results from 2002–2004

2005 ◽  
Vol 5 (3) ◽  
pp. 3367-3389 ◽  
Author(s):  
M. de Graaf ◽  
P. Stammes
Keyword(s):  
Good Representation ◽  
Correction Factors ◽  
Lookup Tables ◽  
Scanning Imaging ◽  
Aerosol Index ◽  
Reflectance Data ◽  
Absorption Spectrometer

Abstract. The validity of the Absorbing Aerosol Index (AAI) product from the SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) is discussed. The operational SCIAMACHY AAI product suffers from calibration errors in the reflectance as measured by SCIAMACHY and design errors. Therefore, the AAI product was recalculated, compensating for the errors, with reflectance data from the start of measurements of SCIAMACHY until December 2004. Appropriate correction factors were determined for the UV to correct for the radiometric error in the SCIAMACHY reflectances. The algorithm was provided with LookUp Tables in which a good representation of polarisation effects was incorporated, as opposed to the LookUp Tables of the operational product, in which polarisation effects were not accounted for. The results are presented, their validity discussed, and compared to the operational product. The AAI is very sensitive to calibration errors and can be used to monitor calibration errors and changes. From 2004 onwards, the new SCIAMACHY AAI is suitable to add to the continuation of the long-term AAI record. Recommendations are given for improvement of the operational AAI product.

scholarly journals The semianalytical cloud retrieval algorithm for SCIAMACHY – I. The validation

2005 ◽  
Vol 5 (2) ◽  
pp. 1995-2015 ◽  
Author(s):  
A. A. Kokhanovsky ◽  
V. V. Rozanov ◽  
T. Nauss ◽  
C. Reudenbach ◽  
J. S. Daniel ◽  
...  
Keyword(s):  
Retrieval Algorithm ◽  
Look Up Table ◽  
Ozone Monitoring ◽  
Scanning Imaging ◽  
Using Data ◽  
The Look ◽  
Along Track ◽  
Spectrometer Data ◽  
Resolution Spectrometer ◽  
Absorption Spectrometer

Abstract. A recently developed cloud retrieval algorithm for the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) is briefly presented and validated using independent and well tested cloud retrieval techniques based on the look-up-table approach for MODeration resolutIon Spectrometer data. The results of the cloud top height retrievals using measurements in the oxygen A-band by an airborne crossed Czerny-Turner spectrograph and the Global Ozone Monitoring Experiment (GOME) instrument are compared with those obtained from airborne dual photography and retrievals using data from Along Track Scanning Radiometer (ATSR-2), respectively.

scholarly journals Multi-year comparison of stratospheric BrO vertical profiles retrieved from SCIAMACHY limb and ground-based UV-visible measurements

2009 ◽  
Vol 2 (1) ◽  
pp. 273-285 ◽  
Author(s):  
F. Hendrick ◽  
A. Rozanov ◽  
P. V. Johnston ◽  
H. Bovensmann ◽  
M. De Mazière ◽  
...  
Keyword(s):  
Cross Sections ◽  
Relative Difference ◽  
Early Spring ◽  
Vertical Profiles ◽  
Altitude Range ◽  
Comparison Results ◽  
Uv Visible ◽  
Scanning Imaging ◽  
Relative Differences ◽  
Absorption Spectrometer

Abstract. Vertical profiles of stratospheric bromine monoxide (BrO) retrieved daily from ENVISAT/SCIAMACHY (ENVIronmental SATellite/SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) limb scatter data and from ground-based UV-visible observations performed at Harestua (60° N, 11° E), Observatoire de Haute-Provence (44° N, 5.5° E), and Lauder (45° S, 170° E) are compared in the 15–27 km altitude range for the 2002–2006, 2005–2006, and 2002–2005 periods, respectively. At the three stations, the SCIAMACHY and ground-based UV-visible mean profiles agree reasonably well, with relative difference smaller than 23%. When comparing the BrO partial columns, the agreement obtained is good, with mean relative differences smaller than 11% and corresponding standard deviations in the 13–19% range. These comparison results are obtained, however, using different BrO cross sections in SCIAMACHY limb and ground-based UV-visible retrievals. The seasonal variation of the BrO columns at the three stations is consistently captured by both retrievals as well as large BrO column events occurring during the winter and early spring at Harestua which are associated with bromine activation.

scholarly journals A method for colocating satellite <i>X</i><sub>CO<sub>2</sub></sub> data to ground-based data and its application to ACOS-GOSAT and TCCON

2014 ◽  
Vol 7 (8) ◽  
pp. 2631-2644 ◽  
Author(s):  
H. Nguyen ◽  
G. Osterman ◽  
D. Wunch ◽  
C. O'Dell ◽  
L. Mandrake ◽  
...  
Keyword(s):  
Mean Squared Error ◽  
Weighted Average ◽  
Satellite Observations ◽  
Total Carbon ◽  
Satellite Measurements ◽  
Temporal Window ◽  
Squared Error ◽  
Scanning Imaging ◽  
Total Column ◽  
Absorption Spectrometer

Abstract. Satellite measurements are often compared with higher-precision ground-based measurements as part of validation efforts. The satellite soundings are rarely perfectly coincident in space and time with the ground-based measurements, so a colocation methodology is needed to aggregate "nearby" soundings into what the instrument would have seen at the location and time of interest. We are particularly interested in validation efforts for satellite-retrieved total column carbon dioxide (XCO2), where XCO2 data from Greenhouse Gas Observing Satellite (GOSAT) retrievals (ACOS, NIES, RemoteC, PPDF, etc.) or SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) are often colocated and compared to ground-based column XCO2 measurement from Total Carbon Column Observing Network (TCCON). Current colocation methodologies for comparing satellite measurements of total column dry-air mole fractions of CO2 (XCO2) with ground-based measurements typically involve locating and averaging the satellite measurements within a latitudinal, longitudinal, and temporal window. We examine a geostatistical colocation methodology that takes a weighted average of satellite observations depending on the "distance" of each observation from a ground-based location of interest. The "distance" function that we use is a modified Euclidian distance with respect to latitude, longitude, time, and midtropospheric temperature at 700 hPa. We apply this methodology to XCO2 retrieved from GOSAT spectra by the ACOS team, cross-validate the results to TCCON XCO2 ground-based data, and present some comparisons between our methodology and standard existing colocation methods showing that, in general, geostatistical colocation produces smaller mean-squared error.

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

2019 ◽  
Vol 19 (2) ◽  
pp. 767-783 ◽  
Author(s):  
Evgenia Galytska ◽  
Alexey Rozanov ◽  
Martyn P. Chipperfield ◽  
Sandip. S. Dhomse ◽  
Mark Weber ◽  
...  
Keyword(s):  
Residence Time ◽  
Transport Model ◽  
Stratospheric Ozone ◽  
Satellite Measurements ◽  
Linear Change ◽  
Chemistry Transport Model ◽  
Negative Change ◽  
Time Period ◽  
Scanning Imaging ◽  
Odd Nitrogen

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.

SCIAMACHY—scanning imaging absorption spectrometer for atmospheric chartography

1995 ◽  
Vol 35 (7) ◽  
pp. 445-451 ◽  
Author(s):  
J.P. Burrows ◽  
E. Hölzle ◽  
A.P.H. Goede ◽  
H. Visser ◽  
W. Fricke
Keyword(s):  
Scanning Imaging ◽  
Absorption Spectrometer
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