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See detailComparison of ground-based remote sensing and in-situ observations of CO, CH4 and O3, accounting for representativeness uncertainty
Henne, S.; Steinbacher, M.; Mahieu, Emmanuel ULg et al

Conference (2013, April)

The EC project NORS (Demonstration Network Of ground-based Remote Sensing Observations in support of the GMES Atmospheric Service) aims at demonstrating the value of ground-based remote sensing data for ... [more ▼]

The EC project NORS (Demonstration Network Of ground-based Remote Sensing Observations in support of the GMES Atmospheric Service) aims at demonstrating the value of ground-based remote sensing data for quality assessment and improvement of the GMES products. As part of NORS CO, CH4, O3 and NO2 tropospheric products as obtained by ground-based remote sensing within the Network for the Detection of Atmospheric Composition Change (NDACC) are compared to continuous surface in-situ measurements that are reported on common international reference scales within the Global Atmospheric Watch (GAW) Programme. However, a direct comparison between the different methods is hindered by different sampling volumes, introducing uncertainties due to representativeness. Here we present a novel method that utilises high-resolution, backward Lagrangian particle dispersion modelling to characterise the transport history of different sampling volumes. Sampling volumes are defined as infinitesimally small point volumes for the in-situ observations and as separate profile segments with horizontal and vertical extent for the remote sensing observations. The characterisation is then used (a) to filter times for which a direct comparison between in-situ and remote sensing data is unfavourable (large representativeness uncertainty) and (b) to construct vertical profiles from the in-situ observations, taking additional information from large scale atmospheric composition models into account. These so called “in-situ” profiles are supposed to be more comparable to the remote sensing profile as the surface value itself, while conserving the high accuracy information of the latter and projecting it onto the profile. Therefore, these profiles allow for a more direct comparison and validation of the remotely sensed profiles. The technique was first applied at two of the four NORS demonstration sites (Jungfraujoch, Switzerland and Izana, Spain) and to the comparison of remote sensing Fourier-transform infrared spectrometer (FTIR) measurements of CO, CH4, and O3 with the responding in-situ observations. While previous studies generally showed good agreement between the two kinds of observation, considerable amounts of scatter were evident. Selecting only situations with relatively small representativeness uncertainty reduces this scatter. Folding the “in-situ” profiles with the averaging kernels of the FTIR retrieval gives a more realistic comparison result that is not influenced by any a-priori assumptions. Results are also discussed with respect to season, time of day and weather type. [less ▲]

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See detailNORS: Demonstration Network Of ground-based Remote Sensing observations in support of the GMES atmospheric service
De Mazière, M; Hocke, K; Richter, A et al

Poster (2012, September 17)

NORS (Demonstration Network Of ground-based Remote Sensing Observations in support of the GMES Atmospheric Service) aims at demonstrating the value of ground – based remote sensing data from the Network ... [more ▼]

NORS (Demonstration Network Of ground-based Remote Sensing Observations in support of the GMES Atmospheric Service) aims at demonstrating the value of ground – based remote sensing data from the Network for the Detection of Atmospheric Composition Change for quality assessment and improvement of the GMES Atmospheric Service products. [less ▲]

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See detail1997–2007 CO trend at the high Alpine site Jungfraujoch: a comparison between NDIR surface in situ and FTIR remote sensing observations
Dils, B.; Cui, J.; Henne, S. et al

in Atmospheric Chemistry and Physics (2011), 11(13), 6735--6748

Within the atmospheric research community, there is a strong interest in integrated datasets, combining data from several instrumentations. This integration is complicated by the different characteristics ... [more ▼]

Within the atmospheric research community, there is a strong interest in integrated datasets, combining data from several instrumentations. This integration is complicated by the different characteristics of the datasets, inherent to the measurement techniques. Here we have compared two carbon monoxide time series (1997 till 2007) acquired at the high-Alpine research station Jungfraujoch (3580 m above sea level), with two well-established measurement techniques, namely in situ surface concentration measurements using Non-Dispersive Infrared Absorption technology (NDIR), and ground-based remote sensing measurements using solar absorption Fourier Transform Infrared spectrometry (FTIR). The profile information available in the FTIR signal allowed us to extract an independent layer with a top height of 7.18 km above sea level, appropriate for comparison with our in situ measurements. We show that, even if both techniques are able to measure free troposphere CO concentrations, the datasets exhibit marked differences in their overall trends (−3.21 ± 0.03 ppb/year for NDIR vs. −0.8 ± 0.4 ppb/year for FTIR). Removing measurements that are polluted by uprising boundary layer air has a strong impact on the NDIR trend (now −2.62 ± 0.03 ppb/year), but its difference with FTIR remains significant. Using the LAGRANTO trajectory model, we show that both measurement techniques are influenced by different source regions and therefore are likely subject to exhibit significant differences in their overall trend behaviour. However the observation that the NDIR-FTIR trend difference is as significant before as after 2001 is at odds with available emission databases which claim a significant Asian CO increase after 2001 only. [less ▲]

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