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See detailImproved spectral fitting of nitrogen dioxide from OMI in the 405-465 nm window
van Geffen, J H G M; Boersma, K F; Van Roozendael, M et al

in Atmospheric Measurement Techniques. Papers in Open Discussion (2014), 7

An improved nitrogen dioxide (NO2) slant column density retrieval for the Ozone Monitoring Instrument (OMI) in the 405–465 nm spectral region is presented. Since the launch of OMI on board NASA's EOS-Aura ... [more ▼]

An improved nitrogen dioxide (NO2) slant column density retrieval for the Ozone Monitoring Instrument (OMI) in the 405–465 nm spectral region is presented. Since the launch of OMI on board NASA's EOS-Aura satellite in 2004, DOAS retrievals of NO2 slant column densities have been the starting point for the KNMI DOMINO (v2.0) and NASA SP (v2.1) retrievals. However, recent intercomparisons between NO2 retrievals from OMI and other UV/Vis and limb spectrometers, as well as ground-based measurements, clearly suggested that OMI stratospheric NO2 is biased high. This study revises the OMI NO2 retrieval in detail. The representation of the OMI slit function to convolve high-resolution reference spectra onto the relevant spectral grid is improved. The window used for the wavelength calibration is optimised, leading to much-reduced fitting errors. Ozone and water vapour spectra used in the fit are updated, reflecting the recently improved knowledge on their absorption cross section as documented in the literature. The improved spectral fit also accounts for absorption by the O2–O2 collision complex and by liquid water over clear-water areas. The main changes in the improved spectral fitting result from the updates related to the wavelength calibration: the RMS error of the fit is reduced by 23% and the NO2 slant column by 0.85 × 1015 molec cm-2, independent of latitude, solar zenith angle and NO2 value. Including O2–O2 and liquid water absorption and updating the O3 and water vapour cross-section spectra further reduces NO2 slant columns on average by 0.35 × 1015 molec cm-2, accompanied with a further 9% reduction in the RMS error of the fit. The improved OMI NO2 slant columns are consistent with independent NO2 retrievals to within a range that can be explained by photo-chemically driven diurnal increases in stratospheric NO2 and by small differences in fitting window and fitting approach. The revisions indicate that current OMI NO2 slant columns suffered mostly from an additive, positive offset that is removed by the improved wavelength calibration and representation of the OMI slit function. It is therefore anticipated that the improved NO2 slant columns are most important to retrievals of spatially homogeneous stratospheric NO2 rather than to heterogeneous tropospheric NO2. [less ▲]

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See detailUsing XCO2 retrievals fo rassessing the long-term consistency of NDACC/FTIR data sets
Barthlott; Schneider, M; Hase, F et al

in Atmospheric Measurement Techniques. Papers in Open Discussion (2014), 7

Within the NDACC (Network for the Detection of Atmospheric Composition Change), more than 20 FTIR (Fourier–Transform InfraRed) spectrometers, spread worldwide, provide long-term data records of many ... [more ▼]

Within the NDACC (Network for the Detection of Atmospheric Composition Change), more than 20 FTIR (Fourier–Transform InfraRed) spectrometers, spread worldwide, provide long-term data records of many atmospheric trace gases. We present a method that uses measured and modelled XCO2 for assessing the consistency of these data records. Our NDACC XCO2 retrieval setup is kept simple so that it can easily be adopted for any NDACC/FTIR-like measurement made since the late 1950s. By a comparison to coincident TCCON (Total Carbon Column Observing Network) measurements, we empirically demonstrate the useful quality of this NDACC XCO2 product (empirically obtained scatter between TCCON and NDACC is about 4‰ for daily mean as well as monthly mean comparisons and the bias is 25 ‰). As XCO2 model we developed and used a simple regression model fitted to CarbonTracker results and the Mauna Loa CO2 in-situ records. A comparison to TCCON data suggests an uncertainty of the model for monthly mean data of below 3 ‰. We apply the method to the NDACC/FTIR spectra that are used within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) and demonstrate that there is a good consistency for these globally representative set of spectra measured since 1996: the scatter between the modelled and measured XCO2 on a yearly time scale is only 3 ‰. [less ▲]

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See detailLong-term evolution and seasonal modulation above Jungfraujoch (46.5°N, 8.0°E): Optimisation of the retrieval strategy, comparison with model and independant observations
Bader, Whitney ULg; Stavrakou, T; Muller, J-F et al

in Atmospheric Measurement Techniques. Papers in Open Discussion (2014), 7

Methanol (CH3OH) is the second most abundant organic compound in the Earth's atmosphere after methane. In this work, we present the first long-term time series of methanol total, lower tropospheric and ... [more ▼]

Methanol (CH3OH) is the second most abundant organic compound in the Earth's atmosphere after methane. In this work, we present the first long-term time series of methanol total, lower tropospheric and upper tropospheric-lower stratospheric partial columns derived from the analysis of high resolution Fourier transform infrared solar spectra recorded at the Jungfraujoch station (46.5° N, 3580 m a.s.l.). The retrieval of methanol is very challenging due to strong absorptions of ozone in the region of the selected υ8 band of CH3OH. Two wide spectral intervals have been defined and adjusted in order to maximize the information content. Methanol does not exhibit a significant trend over the 1995–2012 time period, but a strong seasonal modulation characterized by maximum values and variability in June–July, minimum columns in winter and a peak-to-peak amplitude of 130%. In situ measurements performed at the Jungfraujoch and ACE-FTS occultations give similar results for the methanol seasonal variation. The total and lower tropospheric columns are also compared with IMAGESv2 model simulations. There is no systematic bias between the observations and IMAGESv2 but the model underestimates the peak-to-peak amplitude of the seasonal modulations. [less ▲]

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