90 research outputs found

    Observation of unusual chlorine activation by ground-based infrared and microwave spectroscopy in the late Arctic winter 2000/01

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    International audienceDuring the Arctic winter of 2000/01, ground-based FTIR and millimetre-wave measurements revealed significant amounts of ClO over Kiruna after the final warming in February 2001. In fact, column amounts of ClO were still increased in March 2001 when temperatures were about 20K above the PSC (Polar Stratospheric Clouds) threshold. At these temperatures, chlorine activation due to heterogeneous processes on PSCs is not possible even in the presence of strong lee wave effects. In order to discuss possible reasons of this feature, time series of other chemical species will be presented and discussed, too. Measurements of HF and COF2 indicated that vortex air was still observed in mid-March 2001. Since the time series of HNO3 column amounts do not give any evidence of a denitrification later than 11 February, chlorine activation persisting for several weeks after the presence of PSCs due to denitrification is rather unlikely. The photolysis of ClONO2-rich air which had been formed at the end of February and beginning of March 2001 as well as chlorine activation due to the presence of an unusual aerosol layer are discussed as possible causes of the increased ClO column amounts after the final warming

    Trends of HCl, ClONOâ‚‚, and HF column abundances from ground-based FTIR measurements in Kiruna (Sweden) in comparison with KASIMA model calculations

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    Trends of hydrogen chloride (HCl), chlorine nitrate (ClONO2), and hydrogen fluoride (HF) total column abundances above Kiruna (Northern Sweden, 67.84∘N^\circ\text{N}, 20.41∘E^\circ\text{E}) derived from nearly 14 years (1996–2009) of measurement and model data are presented. The measurements have been performed with a Bruker 120HR (later Bruker 125 HR) Fourier transform infrared (FTIR) spectrometer and the chemistry-transport model (CTM) used was KASIMA (KArlsruhe SImulation model of the Middle Atmosphere). The total column abundances of ClONO2 and HF calculated by KASIMA agree quite well with the FTIR measurements while KASIMA tends to underestimate the HCl columns. To calculate the long-term trends, a linear function combined with an annual cycle was fitted to the data using a least squares method. The precision of the resulting trends was estimated with the bootstrap resampling method. For HF, both model and measurements show a positive trend that seems to decrease in the last few years. This suggests a stabilisation of the HF total column abundance. Between 1996 and 2009, KASIMA simulates an increase of (+1.51±0.07) %/yr which exceeds the FTIR result of (+0.65±0.25) %/yr. The trends determined for HCl and ClONO2 are significantly negative over the time period considered here. This is expected because the emission of their precursors (chlorofluorocarbons and hydrochlorofluorocarbons) has been restricted in the Montreal Protocol in 1987 and its amendments and adjustments. The trend for ClONO2 from the FTIR measurements amounts to (−3.28±0.56)%/yr and the one for HCl to (−0.81±0.23)%/yr. KASIMA simulates a weaker decrease: For ClONO2, the result is (−0.90±0.10) %/yr and for HCl (−0.17±0.06) %/yr. Part of the difference between measurement and model data can be explained by sampling and the stronger annual cycle indicated by the measurements. There is a factor of about four between the trends of HCl and ClONO2 above Kiruna for both measurement and model data

    Intercomparison of atmospheric CO2 and CH4 abundances on regional scales in boreal areas using Copernicus Atmosphere Monitoring Service (CAMS) analysis, COllaborative Carbon Column Observing Network (COCCON) spectrometers, and Sentinel-5 Precursor satellite observations

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    We compare the atmospheric column-averaged dry-air mole fractions of carbon dioxide (XCO2_{2}) and methane (XCH4_{4}) measured with a pair of COllaborative Carbon Column Observing Network (COCCON) spectrometers at Kiruna and Sodankylä (boreal areas). We compare model data provided by the Copernicus Atmosphere Monitoring Service (CAMS) between 2017 and 2019 with XCH4_{4} data from the recently launched Sentinel-5 Precursor (S5P) satellite between 2018 and 2019. In addition, measured and modeled gradients of XCO2_{2} and XCH4_{4} (ΔXCO2_{2} and ΔXCH4_{4}) on regional scales are investigated. Both sites show a similar and very good correlation between COCCON retrievals and the modeled CAMS XCO2_{2} data, while CAMS data are biased high with respect to COCCON by 3.72 ppm (±1.80 ppm) in Kiruna and 3.46 ppm (±1.73 ppm) in Sodankylä on average. For XCH4_{4}, CAMS values are higher than the COCCON observations by 0.33 ppb (±11.93 ppb) in Kiruna and 7.39 ppb (±10.92 ppb) in Sodankylä. In contrast, the S5P satellite generally measures lower atmospheric XCH4_{4} than the COCCON spectrometers, with a mean difference of 9.69 ppb (±20.51 ppb) in Kiruna and 3.36 ppb (±17.05 ppb) in Sodankylä. We compare the gradients of XCO2_{2} and XCH4_{4} (ΔXCO2_{2} and ΔXCH4_{4}) between Kiruna and Sodankylä derived from CAMS analysis and COCCON and S5P measurements to study the capability of detecting sources and sinks on regional scales. The correlations in ΔXCO2_{2} and ΔXCH4_{4} between the different datasets are generally smaller than the correlations in XCO2_{2} and XCH4_{4} between the datasets at either site. The ΔXCO2_{2} values predicted by CAMS are generally higher than those observed with COCCON with a slope of 0.51. The ΔXCH4_{4} values predicted by CAMS are mostly higher than those observed with COCCON with a slope of 0.65, covering a larger dataset than the comparison between S5P and COCCON. When comparing CAMS ΔXCH4_{4} with COCCON ΔXCH4_{4} only in S5P overpass days (slope = 0.53), the correlation is close to that between S5P and COCCON (slope = 0.51). CAMS, COCCON, and S5P predict gradients in reasonable agreement. However, the small number of observations coinciding with S5P limits our ability to verify the performance of this spaceborne sensor. We detect no significant impact of ground albedo and viewing zenith angle on the S5P results. Both sites show similar situations with the average ratios of XCH4_{4} (S5P/COCCON) of 0.9949±0.0118 in Kiruna and 0.9953±0.0089 in Sodankylä. Overall, the results indicate that the COCCON instruments have the capability of measuring greenhouse gas (GHG) gradients on regional scales, and observations performed with the portable spectrometers can contribute to inferring sources and sinks and to validating spaceborne greenhouse gas sensors. To our knowledge, this is the first published study using COCCON spectrometers for the validation of XCH4_{4} measurements collected by S5P

    Intercomparison of arctic XH2_{2}O observations from three ground-based Fourier transform infrared networks and application for satellite validation

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    In this paper, we compare column-averaged dry-air mole fractions of water vapor (XH2_{2}O) retrievals from the COllaborative Carbon Column Observing Network (COCCON) with retrievals from two co-located high-resolution Fourier transform infrared (FTIR) spectrometers as references at two boreal sites, Kiruna, Sweden, and Sodankylä, Finland, from 6 March 2017 to 20 September 2019. In the framework of the Network for the Detection of Atmospheric Composition Change (NDACC), an FTIR spectrometer is operated at Kiruna. The H2_{2}O product derived from these observations has been generated with the MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) processor. In Sodankylä, a Total Carbon Column Observing Network (TCCON) spectrometer is operated, and the official XH2_{2}O data as provided by TCCON are used for this study. The datasets are in good overall agreement, with COCCON data showing a wet bias of (49.20±58.61) ppm ((3.33±3.37) %, R2^{2}=0.9992) compared with MUSICA NDACC and (56.32±45.63) ppm ((3.44±1.77) %, R2^{2}=0.9997) compared with TCCON. Furthermore, the a priori H2_{2}O volume mixing ratio (VMR) profiles (MAP) used as a priori information in the TCCON retrievals (also adopted for COCCON retrievals) are evaluated with respect to radiosonde (Vaisala RS41) profiles at Sodankylä. The MAP and radiosonde profiles show similar shapes and a good linear correlation of integrated XH2_{2}O, indicating that MAP is a reasonable approximation of the true atmospheric state and an appropriate choice for the scaling retrieval methods as applied by COCCON and TCCON. COCCON shows a reduced dry bias (−14.96 %) in comparison with TCCON (−19.08 %) with respect to radiosonde XH2_{2}O. Finally, we investigate the quality of satellite data at high latitudes. For this purpose, the COCCON XH2_{2}O is compared with retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) generated with the MUSICA processor (MUSICA IASI) and with retrievals from the TROPOspheric Monitoring Instrument (TROPOMI). Both paired datasets generally show good agreement and similar correlations at the two sites. COCCON measures 4.64 % less XH2O at Kiruna and 3.36 % less at Sodankylä with respect to MUSICA IASI, whereas COCCON measures 9.71 % more XH2_{2}O at Kiruna and 7.75 % more at Sodankylä compared with TROPOMI. Our study supports the assumption that COCCON also delivers a well-characterized XH2_{2}O data product. This emphasizes that this approach might complement the TCCON network with respect to satellite validation efforts. This is the first published study where COCCON XH2_{2}O has been compared with MUSICA NDACC and TCCON retrievals and has been used for MUSICA IASI and TROPOMI validation

    A multi-instrument comparison of integrated water vapour measurements at a high latitude site

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    We compare measurements of integrated water vapour (IWV) over a subarctic site (Kiruna, Northern Sweden) from five different sensors and retrieval methods: Radiosondes, Global Positioning System (GPS), ground-based Fourier-transform infrared (FTIR) spectrometer, groundbased microwave radiometer, and satellite-based microwave radiometer (AMSU-B). Additionally, we compare also to ERA-Interim model reanalysis data. GPS-based IWV data have the highest temporal coverage and resolution and are chosen as reference data set. All datasets agree reasonably well, but the ground-based microwave instrument only if the data are cloud-filtered. We also address two issues that are general for such intercomparison studies, the impact of different lower altitude limits for the IWV integration, and the impact of representativeness error. We develop methods for correcting for the former, and estimating the random error contribution of the latter. A literature survey reveals that reported systematic differences between different techniques are study-dependent and show no overall consistent pattern. Further improving the absolute accuracy of IWV measurements and providing climate-quality time series therefore remain challenging problems

    Intercomparison of atmospheric CO2 and CH4 abundances on regional scales in boreal areas using Copernicus Atmosphere Monitoring Service (CAMS) analysis, COllaborative Carbon Column Observing Network (COCCON) spectrometers, and Sentinel-5 Precursor satellite observations

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    We compare the atmospheric column-averaged dry-air mole fractions of carbon dioxide (XCO2) and methane (XCH4) measured with a pair of COllaborative Carbon Column Observing Network (COCCON) spectrometers at Kiruna and Sodankyla (boreal areas). We compare model data provided by the Copernicus Atmosphere Monitoring Service (CAMS) between 2017 and 2019 with XCH4 data from the recently launched Sentinel-5 Precursor (S5P) satellite between 2018 and 2019. In addition, measured and modeled gradients of XCO2 and XCH4 (Delta XCO2 and Delta XCH4) on regional scales are investigated. Both sites show a similar and very good correlation between COCCON retrievals and the modeled CAMS XCO2 data, while CAMS data are biased high with respect to COCCON by 3.72 ppm (+/- 1.80 ppm) in Kiruna and 3.46 ppm (+/- 1.73 ppm) in Sodankyla on average. For XCH4, CAMS values are higher than the COCCON observations by 0.33 ppb (+/- 11.93 ppb) in Kiruna and 7.39 ppb (+/- 10.92 ppb) in Sodankyla. In contrast, the S5P satellite generally measures lower atmospheric XCH4 than the COCCON spectrometers, with a mean difference of 9.69 ppb (+/- 20.51 ppb) in Kiruna and 3.36 ppb (+/- 17.05 ppb) in So-dankyla. We compare the gradients of XCO2 and XCH4 (Delta XCO2 and Delta XCH4) between Kiruna and Sodankyla derived from CAMS analysis and COCCON and S5P measurements to study the capability of detecting sources and sinks on regional scales. The correlations in Delta XCO2 and Delta XCH4 between the different datasets are generally smaller than the correlations in XCO2 and XCH4 between the datasets at either site. The Delta XCO2 values predicted by CAMS are generally higher than those observed with COCCON with a slope of 0.51. The Delta XCH4 values predicted by CAMS are mostly higher than those observed with COCCON with a slope of 0.65, covering a larger dataset than the comparison between S5P and COCCON. When comparing CAMS Delta XCH4 with COCCON Delta XCH4 only in S5P overpass days (slope = 0.53), the correlation is close to that between S5P and COCCON (slope = 0.51). CAMS, COCCON, and S5P predict gradients in reasonable agreement. However, the small number of observations coinciding with S5P limits our ability to verify the performance of this spaceborne sensor. We detect no significant impact of ground albedo and viewing zenith angle on the S5P results. Both sites show similar situations with the average ratios of XCH4 (S5P/COCCON) of 0.9949 +/- 0.0118 in Kiruna and 0.9953 +/- 0.0089 in Sodankyla. Overall, the results indicate that the COCCON instruments have the capability of measuring greenhouse gas (GHG) gradients on regional scales, and observations performed with the portable spectrometers can contribute to inferring sources and sinks and to validating spaceborne greenhouse gas sensors. To our knowledge, this is the first published study using COCCON spectrometers for the validation of XCH4 measurements collected by S5P
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