carbon monoxide total columns from sciamachy 2.3 µm atmospheric reflectance measurements: towards a full-mission data product (2003–2012)
Clicks: 290
ID: 135484
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
30.0
/100
290 views
50 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #19 of 183 articles by views in bioorganic & medicinal chemistry
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 183 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
We present a full-mission data product of carbon monoxide (CO) vertical column
densities using the 2310–2338 nm SCIAMACHY reflectance measurements
over clear-sky land scenes for the period January 2003–April 2012. The
retrieval employs the SICOR algorithm, which will be used for operational data
processing of the Sentinel-5 Precursor mission. The retrieval approach infers
simultaneously carbon monoxide, methane and water vapour column densities
together with a Lambertian surface albedo from individual SCIAMACHY
measurements employing
a non-scattering radiative transfer model. To account for the
radiometric instrument degradation including the formation of an
ice-layer on the 2.3 µm detector array, we consider
clear-sky measurements over the Sahara as a natural calibration
target. For these specific measurements, we spectrally calibrate the
SCIAMACHY measurements and determine a spectral radiometric offset
and the width of the instrument spectral response function as
a function of time for the entire operational phase of the mission.
We show that the smoothing error of individual clear-sky CO
retrievals is less than ±1 ppb and thus this error
contribution does not need to be accounted for in the validation
considering the much higher retrieval noise. The CO data product is
validated against measurements of ground-based Fourier transform
infrared spectrometers at 27 stations of the NDACC-IRWG and TCCON
network and MOZAIC/IAGOS aircraft measurements at 26 airports
worldwide. Overall, we find a good agreement with TCCON
measurements with a mean bias b = −1.2 ppb and
a station-to-station bias with σ = 7.2 ppb.
The negative sign of the bias means a low bias of SCIAMACHY CO with respect to TCCON.
For the NDACC-IRWG network, we obtain a larger
mean station bias of b = −9.2 ppb with
σ = 8.1 ppb and for the MOZAIC/IAGOS
measurements we find b = −6.4 ppb with
σ = 5.6 ppb. The SCIAMACHY data set is
subject to a small but significant bias trend of 1.47 ± 0.25 ppb yr−1. After trend correction, the bias with
respect to MOZAIC/IAGOS observation is 2.5 ppb, with respect
to TCCON measurements it is −4.6 ppb and with respect to
NDACC-IRWG measurements −8.4 ppb. Hence, a discrepancy of
3.8 ppb remains between the global biases with NDACC-IRWG
and TCCON, which is confirmed by directly comparing NDACC-IRWG and
TCCON measurements. Generally, the scatter of the individual
SCIAMACHY CO retrievals is high and dominated by large measurement
noise. Hence, for practical usage of the data set, averaging of
individual retrievals is required. As an example, we show that
monthly mean SCIAMACHY CO retrievals, averaged separately over
Northern and Southern Africa, reflect the spatial and temporal
variability of biomass burning events in agreement with the global
chemical transport model TM5.
| Reference Key |
borsdorff2016atmosphericcarbon
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;T. Borsdorff;P. Tol;J. E. Williams;J. de Laat;J. aan de Brugh;P. Nédélec;I. Aben;J. Landgraf |
| Journal | bioorganic & medicinal chemistry |
| Year | 2016 |
| DOI |
10.5194/amt-9-227-2016
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.