scholarly journals FTS measurements of column CO<sub>2</sub> at Sodankylä

2016 ◽  
Author(s):  
R. Kivi ◽  
P. Heikkinen

Abstract. Fourier Transform Spectrometer (FTS) observations at Sodankylä have been per formed since early 2009. The FTS instrument is participating in the Total Carbon Column Observing Network (TCCON) and has been optimized to measure abundances of the key greenhouse gases in the atmosphere. Here we report the measured CO2 time series over a six year period (2009–2014) and provide a description of the FTS system and data processing at Sodankylä. We find the lowest monthly column CO2 values in August and the highest monthly values during the February to May season. Inter-annual variability is the highest in June–September period, which correlates with the growing season. During the time period of FTS measurements from 2009 until 2014 we have observed a 2.4 &amp;pm; 0.3 ppm increase per year in column CO2. The monthly mean column CO2 values have exceeded 400 ppm level for the first time in February 2014.

2016 ◽  
Vol 5 (2) ◽  
pp. 271-279 ◽  
Author(s):  
Rigel Kivi ◽  
Pauli Heikkinen

Abstract. Fourier transform spectrometer (FTS) observations at Sodankylä, Finland (67.4° N, 26.6° E) have been performed since early 2009. The FTS instrument is participating in the Total Carbon Column Observing Network (TCCON) and has been optimized to measure abundances of the key greenhouse gases in the atmosphere. Sodankylä is the only TCCON station in the Fennoscandia region. Here we report the measured CO2 time series over a 7-year period (2009–2015) and provide a description of the FTS system and data processing at Sodankylä. We find the lowest monthly column CO2 values in August and the highest monthly values during the February–May season. Inter-annual variability is the highest in the June–September period, which correlates with the growing season. During the time period of FTS measurements from 2009 to 2015, we have observed a 2.2 ± 0.2 ppm increase per year in column CO2. The monthly mean column CO2 values have exceeded 400 ppm level for the first time in February 2014.


2020 ◽  
Author(s):  
Hiroki Ogawa ◽  
Yuki Hama ◽  
Koichi Asamori ◽  
Takumi Ueda

Abstract In the magnetotelluric (MT) method, the responses of the natural electromagnetic fields are evaluated by transforming time-series data into spectral data and calculating the apparent resistivity and phase. The continuous wavelet transform (CWT) can be an alternative to the short-time Fourier transform, and the applicability of CWT to MT data has been reported. There are, however, few cases of considering the effect of numerical errors derived from spectral transform on MT data processing. In general, it is desirable to adopt a window function narrow in the time domain for higher-frequency components and one in the frequency domain for lower-frequency components. In conducting the short-time Fourier transform, because the size of the window function is fixed unless the time-series data are decimated, there might be difference between the calculated MT responses and the true ones due to the numerical errors. Meanwhile, CWT can strike a balance between the resolution of the time and frequency domains by magnifying or reducing the wavelet, according to the value of frequency. Although the types of wavelet functions and their parameters influence the resolution of time and frequency, those calculation settings of CWT are often determined empirically. In this study, focusing on the frequency band between 0.001 Hz and 10 Hz, we demonstrated the superiority of utilizing CWT in MT data processing and determined its proper calculation settings in terms of restraining the numerical errors caused by the spectral transform of time-series data. The results obtained with the short-time Fourier transform accompanied with gradual decimation of the time-series data, called cascade decimation, were compared with those of CWT. The shape of the wavelet was changed by using different types of wavelet functions or their parameters, and the respective results of data processing were compared. Through these experiments, this study indicates that CWT with the complex Morlet function with its wavelet parameter k set to 6 ≤ k < 10 will be effective in restraining the numerical errors caused by the spectral transform.


2019 ◽  
Vol 12 (11) ◽  
pp. 6125-6141 ◽  
Author(s):  
Minqiang Zhou ◽  
Bavo Langerock ◽  
Mahesh Kumar Sha ◽  
Nicolas Kumps ◽  
Christian Hermans ◽  
...  

Abstract. The Total Carbon Column Observing Network (TCCON) column-averaged dry air mole fraction of CH4 (XCH4) measurements have been widely used to validate satellite observations and to estimate model simulations. The GGG2014 code is the standard TCCON retrieval software used in performing a profile scaling retrieval. In order to obtain several vertical pieces of information in addition to the total column, in this study, the SFIT4 retrieval code is applied to retrieve the CH4 mole fraction vertical profile from the Fourier transform spectrometer (FTS) spectrum at six sites (Ny-Ålesund, Sodankylä, Bialystok, Bremen, Orléans and St Denis) during the time period of 2016–2017. The retrieval strategy of the CH4 profile retrieval from ground-based FTS near-infrared (NIR) spectra using the SFIT4 code (SFIT4NIR) is investigated. The degree of freedom for signal (DOFS) of the SFIT4NIR retrieval is about 2.4, with two distinct pieces of information in the troposphere and in the stratosphere. The averaging kernel and error budget of the SFIT4NIR retrieval are presented. The data accuracy and precision of the SFIT4NIR retrievals, including the total column and two partial columns (in the troposphere and stratosphere), are estimated by TCCON standard retrievals, ground-based in situ measurements, Atmospheric Chemistry Experiment – Fourier Transform Spectrometer (ACE-FTS) satellite observations, TCCON proxy data and AirCore and aircraft measurements. By comparison against TCCON standard retrievals, it is found that the retrieval uncertainty of SFIT4NIR XCH4 is similar to that of TCCON standard retrievals with systematic uncertainty within 0.35 % and random uncertainty of about 0.5 %. The tropospheric and stratospheric XCH4 from SFIT4NIR retrievals are assessed by comparison with AirCore and aircraft measurements, and there is a 1.0 ± 0.3 % overestimation in the SFIT4NIR tropospheric XCH4 and a 4.0 ± 2.0 % underestimation in the SFIT4NIR stratospheric XCH4, which are within the systematic uncertainties of SFIT4NIR-retrieved partial columns in the troposphere and stratosphere respectively.


1984 ◽  
Vol 62 (12) ◽  
pp. 1420-1425 ◽  
Author(s):  
R. J. Winkel Jr. ◽  
Sumner P. Davis

The (1–0), (2–1), and (3–2) infrared vibration–rotation bands of the X2Π ground state of sulfur monohydride were observed in emission from a furnace. Multiplet splitting produces two subbands, each of which exhibits lambda splitting. The band heads were observed for the first time, 285 lines were measured, and a calculation of lambda-doubling parameters was made. The spectrum was recorded using the Fourier transform spectrometer at the National Solar Observatory (Kitt Peak).


2008 ◽  
Author(s):  
Trevor R. Fulton ◽  
David A. Naylor ◽  
Jean-Paul Baluteau ◽  
Matt Griffin ◽  
Peter Davis-Imhof ◽  
...  

2019 ◽  
Author(s):  
Ilya Stanevich ◽  
Dylan B. A. Jones ◽  
Kimberly Strong ◽  
Robert J. Parker ◽  
Hartmut Boesch ◽  
...  

Abstract. The GEOS-Chem simulation of atmospheric CH4 was evaluated against observations from the Thermal And Near infrared Sensor for carbon Observations Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse gases Observing SATellite (GOSAT), the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), and the Total Carbon Column Observing Network (TCCON). We focused on the model simulations at the 4° × 5° and 2° × 2.5° horizontal resolutions for the period of February–May 2010. Compared to the GOSAT, TCCON, and ACE-FTS data, we found that the 2° × 2.5° model produced a better simulation of CH4, with smaller biases and a higher correlation to the independent data. We found large resolution-dependent differences such as a latitude-dependent XCH4 bias, with higher columns abundances of CH4 at high latitudes and lower abundances at low latitudes at the 4° × 5° resolution than at 2° × 2.5°. We also found large differences in CH4 column abundances between the two resolutions over major source regions such as China. These differences resulted in up to 30 % differences in inferred regional CH4 emission estimates from the two model resolutions. We performed several experiments using 222Rn, 7Be and CH4 to determine the origins of the resolution-dependent errors. The results suggested that the major source of the latitude-dependent errors is excessive mixing in the upper troposphere and lower stratosphere, including mixing at the edge of the polar vortex, that is pronounced at the 4° × 5° resolution. At the coarser resolution, there is weakened vertical transport in the troposphere at mid- to high latitudes due to the loss of sub-grid tracer eddy mass flux in the storm track regions. We also identified reduced vertical transport at the coarser resolution. The vertical air mass fluxes are calculated in the model from the degraded coarse-resolution wind fields and the model does not conserve the air mass flux between model resolutions; as a result, the low resolution does not fully capture the vertical transport. This produces significant localized discrepancies, such as much greater CH4 abundances in the lower troposphere over China at 4° × 5° than at 2° × 2.5°. Although we found that the CH4 simulation is significantly better at 2° × 2.5° than at 4° × 5°, biases may still be present at 2° × 2.5° resolution. Their importance, particularly, in regards to inverse modeling of CH4 emissions, should be evaluated in future studies using on-line transport in the native general circulation model as a benchmark simulation.


2010 ◽  
Author(s):  
Trevor R. Fulton ◽  
Jean-Paul Baluteau ◽  
George Bendo ◽  
Dominique Benielli ◽  
Rene Gastaud ◽  
...  

2013 ◽  
Vol 6 (8) ◽  
pp. 1981-1992 ◽  
Author(s):  
S. Dohe ◽  
V. Sherlock ◽  
F. Hase ◽  
M. Gisi ◽  
J. Robinson ◽  
...  

Abstract. The Total Carbon Column Observing Network (TCCON) has been established to provide ground-based remote sensing measurements of the column-averaged dry air mole fractions (DMF) of key greenhouse gases. To ensure network-wide consistency, biases between Fourier transform spectrometers at different sites have to be well controlled. Errors in interferogram sampling can introduce significant biases in retrievals. In this study we investigate a two-step scheme to correct these errors. In the first step the laser sampling error (LSE) is estimated by determining the sampling shift which minimises the magnitude of the signal intensity in selected, fully absorbed regions of the solar spectrum. The LSE is estimated for every day with measurements which meet certain selection criteria to derive the site-specific time series of the LSEs. In the second step, this sequence of LSEs is used to resample all the interferograms acquired at the site, and hence correct the sampling errors. Measurements acquired at the Izaña and Lauder TCCON sites are used to demonstrate the method. At both sites the sampling error histories show changes in LSE due to instrument interventions (e.g. realignment). Estimated LSEs are in good agreement with sampling errors inferred from the ratio of primary and ghost spectral signatures in optically bandpass-limited tungsten lamp spectra acquired at Lauder. The original time series of Xair and XCO2 (XY: column-averaged DMF of the target gas Y) at both sites show discrepancies of 0.2–0.5% due to changes in the LSE associated with instrument interventions or changes in the measurement sample rate. After resampling, discrepancies are reduced to 0.1% or less at Lauder and 0.2% at Izaña. In the latter case, coincident changes in interferometer alignment may also have contributed to the residual difference. In the future the proposed method will be used to correct historical spectra at all TCCON sites.


2004 ◽  
Author(s):  
David A. Naylor ◽  
Trevor R. Fulton ◽  
Peter W. Davis ◽  
Ian M. Chapman ◽  
Brad G. Gom ◽  
...  

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