Data · dataset · 2026
Assessing the near surface sensitivity of SCIAMACHY atmospheric COâ retrieved using (FSI) WFM/DOAS
Listed in National Center for Atmospheric Research
Satellite observations of atmospheric COâ offer the potential to identify regional carbon surface sources and sinks and to investigate carbon cycle processes.
Description
The extent to which satellite measurements are useful however, depends on the near surface sensitivity of the chosen sensor. In this paper, the capability of the SCIAMACHY instrument on board ENVISAT, to observe lower tropospheric and surface COâ variability is examined.
To achieve this, atmospheric COâ retrieved from SCIAMACHY near infrared (NIR) spectral measurements, using the Full Spectral Initiation (FSI) WFM-DOAS algorithm, is compared to in-situ aircraft observations over Siberia and additionally to tower and surface COâ data over Mongolia, Europe and North America. Preliminary validation of daily averaged SCIAMACHY/FSI COâ against ground based Fourier Transform Spectrometer (FTS) column measurements made at Park Falls, reveal a negative bias of about -2.0% for collocated measurements within ±1.0° of the site.
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However, at this spatial threshold SCIAMACHY can only capture the variability of the FTS observations at monthly timescales. To observe day to day variability of the FTS observations, the collocation limits must be increased. Furthermore, comparisons to in-situ COâ observations demonstrate that SCIAMACHY is capable of observing a seasonal signal that is representative of lower tropospheric variability on (at least) monthly timescales.
Out of seventeen time series comparisons, eleven have correlation coefficients of 0.7 or more, and have similar seasonal cycle amplitudes. Additional evidence of the near surface sensitivity of SCIAMACHY, is provided through the significant correlation of FSI derived COâ with MODIS vegetation indices at over twenty selected locations in the United States. The SCIAMACHY/MODIS comparison reveals that at many of the sites, the amount of COâ variability is coincident with the amount of vegetation activity.
The presented analysis suggests that SCIAMACHY has the potential to detect COâ variability within the lowermost troposphere arising from the activity of the terrestrial biosphere.
Links
Get the data
- Publisher page n2t.org/ark:/85065/d7zp46cn ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/assessing-the-near-surface-sensitivity-of-sciamachy-at… ↗
National Center for Atmospheric Research dataset page
landing page · from data ucar edu
Catalogue records · 1
- CKAN API data.ucar.edu/api/3/action/package_show?id=b1ae91c4-da4e-4052-b76b-0c1b006dd… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
- Inferred from text
- Satellite remote sensing 65%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | b1ae91c4-da4e-4052-b76b-0c1b006ddbeb | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[modality].local:modality:remote-sensing | enrichment · data ucar edu | keyword-concept-rules@1.0.0 | title+description (65%) |
| created_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| description | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /notes |
| publication_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| title | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /title |
| updated_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 |