scholarly journals Impact of Molecular Spectroscopy on Carbon Monoxide Abundances from SCIAMACHY

2020 ◽  
Vol 12 (7) ◽  
pp. 1084 ◽  
Author(s):  
Philipp Hochstaffl ◽  
Franz Schreier
Keyword(s):  
Molecular Spectroscopy ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Spectral Quality ◽  
Composition Change ◽  
Molecular Absorption ◽  
Spectral Fitting ◽  
Scanning Imaging ◽  
Shortwave Infrared

High-quality observations have indicated the need for improved molecular spectroscopy for accurate atmospheric characterization. Line data provided by the new SEOM-IAS (Scientific Exploitation of Operational Missions—Improved Atmospheric Spectroscopy) database in the shortwave infrared (SWIR) region were used to retrieve CO total vertical columns from a selected set of nadir SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) observations. In order to assess the quality of the retrieval results, differences in the spectral fitting residuals with respect to the HITRAN 2016 (High-resolution TRANsmission molecular absorption) and GEISA 2015 (Gestion et Etude des Informations Spectroscopiques Atmosphériques) line lists were quantified and column-averaged dry-air CO mole fractions were compared to NDACC (Network for the Detection of Atmospheric Composition Change) and TCCON (Total Carbon Column Observing Network) ground-based measurements. In general, it was found that using SEOM-IAS line data with corresponding line models improve the spectral quality of the retrieval (smaller residuals) and increase the fitted CO columns, thereby reducing the bias to both ground-based networks.

scholarly journals Impact of Molecular Spectroscopy on Carbon Monoxide Abundances from TROPOMI

2020 ◽  
Vol 12 (21) ◽  
pp. 3486
Author(s):  
Philipp Hochstaffl ◽  
Franz Schreier ◽  
Manfred Birk ◽  
Georg Wagner ◽  
Dietrich G. Feist ◽  
...  
Keyword(s):  
Molecular Spectroscopy ◽  
Atmospheric Composition ◽  
Spectral Fitting ◽  
Spectroscopic Information ◽  
Retrieval Errors ◽  
The Difference ◽  
Shortwave Infrared ◽  
The Impact ◽  
Total Column

The impact of SEOM–IAS (Scientific Exploitation of Operational Missions–Improved Atmospheric Spectroscopy) spectroscopic information on CO columns from TROPOMI (Tropospheric Monitoring Instrument) shortwave infrared (SWIR) observations was examined. HITRAN 2016 (High Resolution Transmission) and GEISA 2015 (Gestion et Etude des Informations Spectroscopiques Atmosphériques 2015) were used as a reference upon which the spectral fitting residuals, retrieval errors and inferred quantities were assessed. It was found that SEOM–IAS significantly improves the quality of the CO retrieval by reducing the residuals to TROPOMI observations. The magnitude of the impact is dependent on the climatological region and spectroscopic reference used. The difference in the CO columns was found to be rather small, although discrepancies reveal, for selected scenes, in particular, for observations with elevated molecular concentrations. A brief comparison to Total Column Carbon Observing Network (TCCON) and Network for the Detection of Atmospheric Composition Change (NDACC) also demonstrated that both spectroscopies cause similar columns; however, the smaller retrieval errors in the SEOM with Speed-Dependent Rautian and line-Mixing (SDRM) inferred CO turned out to be beneficial in the comparison of post-processed mole fractions with ground-based references.

scholarly journals Retrieval of xCO<sub>2</sub> from ground-based mid-infrared (NDACC) solar absorption spectra and comparison to TCCON

2016 ◽  
Vol 9 (2) ◽  
pp. 577-585 ◽  
Author(s):  
Matthias Buschmann ◽  
Nicholas M. Deutscher ◽  
Vanessa Sherlock ◽  
Mathias Palm ◽  
Thorsten Warneke ◽  
...  
Keyword(s):  
Absorption Spectra ◽  
Seasonal Cycle ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Solar Absorption ◽  
Mid Infrared ◽  
Infrared Spectral ◽  
Ftir Spectrometer ◽  
Total Column

Abstract. High-resolution solar absorption spectra, taken within the Network for the Detection of Atmospheric Composition Change Infrared Working Group (NDACC-IRWG) in the mid-infrared spectral region, are used to infer partial or total column abundances of many gases. In this paper we present the retrieval of a column-averaged mole fraction of carbon dioxide from NDACC-IRWG spectra taken with a Fourier transform infrared (FTIR) spectrometer at the site in Ny-Ålesund, Spitsbergen. The retrieved time series is compared to colocated standard TCCON (Total Carbon Column Observing Network) measurements of column-averaged dry-air mole fractions of CO2 (denoted by xCO2). Comparing the NDACC and TCCON retrievals, we find that the sensitivity of the NDACC retrieval is lower in the troposphere (by a factor of 2) and higher in the stratosphere, compared to TCCON. Thus, the NDACC retrieval is less sensitive to tropospheric changes (e.g., the seasonal cycle) in the column average.

scholarly journals First intercalibration of column-averaged methane from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change

2012 ◽  
Vol 5 (1) ◽  
pp. 1355-1379
Author(s):  
F. Forster ◽  
R. Sussmann ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
D. W. T. Griffith ◽  
...  
Keyword(s):  
Time Series ◽  
Near Infrared ◽  
Calibration Factor ◽  
Time Dependent ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Data Set ◽  
The Difference ◽  
Difference Time

Abstract. We present the intercalibration of dry-air column-averaged mole fractions of methane (XCH4) retrieved from solar FTIR measurements of the Network for the Detection of Atmospheric Composition Change (NDACC) in the mid-infrared (MIR) versus near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON). The study uses multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch, Germany (47.48° N, 11.06° E, 743 m a.s.l.) and Wollongong, Australia (34.41° S, 150.88° E, 30 m a.s.l.). Direct comparison of the retrieved MIR and NIR time series shows a phase shift in XCH4 seasonality, i.e. a significant time-dependent bias leading to a standard deviation (stdv) of the difference time series (NIR-MIR) of 8.4 ppb. After eliminating differences in a prioris by using ACTM-simulated profiles as a common prior, the seasonalities of the (corrected) MIR and NIR time series agree within the noise (stdv = 5.2 ppb for the difference time series). The difference time series (NIR-MIR) do not show a significant trend. Therefore it is possible to use a simple scaling factor for the intercalibration without a time-dependent linear or seasonal component. Using the Garmisch and Wollongong data together, we obtain an overall calibration factor MIR/NIR = 0.9926(18). The individual calibration factors per station are 0.9940(14) for Garmisch and 0.9893(40) for Wollongong. They agree within their error bars with the overall calibration factor which can therefore be used for both stations. Our results suggest that after applying the proposed intercalibration concept to all stations performing both NIR and MIR measurements, it should be possible to obtain one refined overall intercalibration factor for the two networks. This would allow to set up a harmonized NDACC and TCCON XCH4 data set which can be exploited for joint trend studies, satellite validation, or the inverse modeling of sources and sinks.

scholarly journals Intercomparison of Arctic ground-based XH<sub>2</sub>O observations from COCCON, TCCON and NDACC, and application of COCCON XH<sub>2</sub>O for IASI and TROPOMI validation

2020 ◽  
Author(s):  
Qiansi Tu ◽  
Frank Hase ◽  
Thomas Blumenstock ◽  
Matthias Schneider ◽  
Andreas Schneider ◽  
...  
Keyword(s):  
A Priori ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Satellite Validation ◽  
Atmospheric Sounding ◽  
Ftir Spectrometer ◽  
Atmospheric State ◽  
Validation Tool ◽  
Good Agreement

Abstract. In this paper, we compare column-averaged dry-air mole fractions of water vapor (XH2O) retrievals from COCCON (COllaborative Carbon Column Observing Network) with retrievals from two co-located high-resolution FTIR (Fourier transform infrared) spectrometers as references at two boreal sites, Kiruna, Swedenand Sodankylä, Finland. In the framework of the NDACC (Network for the Detection of Atmospheric Composition Change) an FTIR spectrometer is operated in Kiruna. The H2O product derived from these observations has been generated with the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) processor. In Sodankylä, a TCCON (Total Carbon Column Observing Network) spectrometer is operated, and the official XH2O 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 = 0.9992) compared to MUSICA NDACC and (56.32 ± 45.63) ppm ((3.44 ± 1.77) %, R2 = 0.9997) compared to TCCON. Furthermore, the a priori H2O VMR (volume mixing ratio) profiles (MAP) used as a priori 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 good correlation of integrated XH2O, indicating that MAP is a reasonable approximation for 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 (−1.66 %) in comparison to TCCON (−5.63 %) with respect to radiosonde XH2O and this small bias indicates that besides XCO2 and XCH4 COCCON is also able to serve as validation tool for space-borne XH2O measurements. Finally, we investigate the quality of satellite data at high latitudes. For this purpose, the COCCON XH2O 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 show generally good agreement and similar correlations at the two sites. COCCON measures 4.64 % less XH2O at Kiruna and 3.36 % at Sodankylä with respect to MUSICA IASI, while COCCON measures 9.71 % more XH2O at Kiruna and 7.75 % at Sodankylä compared with TROPOMI. Our study supports the assumption that COCCON also delivers a well-characterized XH2O data product. This emphasizes the approach of supplementing the TCCON network for satellite validation efforts. This is the first published study where COCCON XH2O is compared with MUSICA NDACC and TCCON retrievals, and for MUSICA IASI and TROPOMI validation.

scholarly journals Characterisation and potential for reducing optical resonances in FTIR spectrometers of the Network for the Detection of Atmospheric Composition Change (NDACC)

2020 ◽  
Author(s):  
Thomas Blumenstock ◽  
Frank Hase ◽  
Axel Keens ◽  
Denis Czurlok ◽  
Orfeo Colebatch ◽  
...  
Keyword(s):  
Beam Splitter ◽  
Background Level ◽  
Air Gap ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Infrared Source ◽  
Optical Components ◽  
Optical Resonances ◽  
Ftir Spectrometer

Abstract. Although optical components in Fourier transform infrared (FTIR) spectrometers are preferably wedged, in practice, infrared spectra typically suffer from the effects of optical resonances (“channeling”) affecting the retrieval of weakly absorbing gases. This study investigates the level of channeling of each FTIR spectrometer within the Network for the Detection of Atmospheric Composition Change (NDACC). Dedicated spectra were recorded by more than twenty NDACC FTIR spectrometers using a laboratory mid-infrared source and two detectors. In the InSb detector domain (1900–5000 cm−1), we find that the amplitude of the most pronounced channeling frequency amounts to 0.1 to 2.0 ‰ of the spectral background level, with a mean of (0.68 ± 0.48) ‰ and a median of 0.60 ‰. In the HgCdTe detector domain (700–1300 cm−1), we find even stronger effects, with the largest amplitude ranging from 0.3 to 21 ‰ with a mean of (2.45 ± 4.50) ‰ and a median of 1.2 ‰. For both detectors, the leading channeling frequencies are 0.9 and 0.11 or 0.23 cm−1 in most spectrometers. These observed spectral frequencies correspond to the optical thickness of the air gap in between the beam splitter and compensator plate (0.9 cm−1) and the beam splitter substrate itself (0.11 and 0.23 cm−1). Since the air gap is a significant source of channeling and the corresponding amplitude differs strongly between spectrometers, we propose new beam splitters with the wedge of the air gap increased to at least 0.8°. We tested the insertion of spacers in a beam splitter’s air gap to demonstrate that increasing the wedge of the air gap decreases the 0.9 cm−1 channeling amplitude significantly. This study shows the potential for reducing channeling in the FTIR spectrometers operated by the NDACC, thereby increasing the quality of recorded spectra across the network.

scholarly journals Using XCO<sub>2</sub> retrievals for assessing the long-term consistency of NDACC/FTIR data sets

2014 ◽  
Vol 7 (10) ◽  
pp. 10513-10558
Author(s):  
S. Barthlott ◽  
M. Schneider ◽  
F. Hase ◽  
A. Wiegele ◽  
E. Christner ◽  
...  
Keyword(s):  
Total Carbon ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Mauna Loa ◽  
Simple Regression Model ◽  
Good Consistency ◽  
Term Data

Abstract. 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‰.

scholarly journals First intercalibration of column-averaged methane from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change

2013 ◽  
Vol 6 (2) ◽  
pp. 397-418 ◽  
Author(s):  
R. Sussmann ◽  
A. Ostler ◽  
F. Forster ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
...  
Keyword(s):  
Time Series ◽  
Near Infrared ◽  
A Priori ◽  
Time Dependent ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Data Set ◽  
The Difference ◽  
Difference Time

Abstract. We present the first intercalibration of dry-air column-averaged mole fractions of methane (XCH4) retrieved from solar Fourier transform infrared (FTIR) measurements of the Network for the Detection of Atmospheric Composition Change (NDACC) in the mid-infrared (MIR) versus near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON). The study uses multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch, Germany (47.48° N, 11.06° E, 743 m a.s.l.), and Wollongong, Australia (34.41° S, 150.88° E, 30 m a.s.l.). Direct comparison of the retrieved MIR and NIR XCH4 time series for Garmisch shows a quasi-periodic seasonal bias leading to a standard deviation (stdv) of the difference time series (NIR–MIR) of 7.2 ppb. After reducing time-dependent a priori impact by using realistic site- and time-dependent ACTM-simulated profiles as a common prior, the seasonal bias is reduced (stdv = 5.2 ppb). A linear fit to the MIR/NIR scatter plot of monthly means based on same-day coincidences does not show a y-intercept that is statistically different from zero, and the MIR/NIR intercalibration factor is found to be close to ideal within 2-σ uncertainty, i.e. 0.9996(8). The difference time series (NIR–MIR) do not show a significant trend. The same basic findings hold for Wollongong. In particular an overall MIR/NIR intercalibration factor close to the ideal 1 is found within 2-σ uncertainty. At Wollongong the seasonal cycle of methane is less pronounced and corresponding smoothing errors are not as significant, enabling standard MIR and NIR retrievals to be used directly, without correction to a common a priori. Our results suggest that it is possible to set up a harmonized NDACC and TCCON XCH4 data set which can be exploited for joint trend studies, satellite validation, or the inverse modeling of sources and sinks.

scholarly journals Intercomparison of stratospheric nitrogen dioxide columns retrieved from ground-based DOAS and FTIR and satellite DOAS instruments over the subtropical Izana station

2016 ◽  
Vol 9 (9) ◽  
pp. 4471-4485 ◽  
Author(s):  
Cristina Robles-Gonzalez ◽  
Mónica Navarro-Comas ◽  
Olga Puentedura ◽  
Matthias Schneider ◽  
Frank Hase ◽  
...  
Keyword(s):  
Relative Difference ◽  
Field Of View ◽  
Atmospheric Composition ◽  
Optical Absorption Spectroscopy ◽  
Data Series ◽  
Composition Change ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Ozone Monitoring ◽  
Scanning Imaging

Abstract. A 13-year analysis (2000–2012) of the NO2 vertical column densities derived from ground-based (GB) instruments and satellites has been carried out over the Izaña NDACC (Network for the Detection of the Atmospheric Composition Change) subtropical site. Ground-based DOAS (differential optical absorption spectroscopy) and FTIR (Fourier transform infrared spectroscopy) instruments are intercompared to test mutual consistency and then used for validation of stratospheric NO2 from OMI (Ozone Monitoring Instrument) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY). The intercomparison has been carried out taking into account the various differences existing in instruments, namely temporal coincidence, collocation, sensitivity, field of view, etc. The paper highlights the importance of considering an “effective solar zenith angle” instead of the actual one when comparing direct-sun instruments with zenith sky ones for a proper photochemical correction. Results show that NO2 vertical column densities mean relative difference between FTIR and DOAS instruments is 2.8 ± 10.7 % for a.m. data. Both instruments properly reproduce the NO2 seasonal and the interannual variation. Mean relative difference of the stratospheric NO2 derived from OMI and DOAS is −0.2 ± 8.7 % and from OMI and FTIR is −1.6 ± 6.7 %. SCIAMACHY mean relative difference is of 3.7 ± 11.7 and −5.7 ± 11.0 % for DOAS and FTIR, respectively. Note that the days used for the intercomparison are not the same for all the pairs of instruments since it depends on the availability of data. The discrepancies are found to be seasonally dependent with largest differences in winter and excellent agreement in the spring months (AMJ). A preliminary analysis of NO2 trends has been carried out with the available data series. Results show increases in stratospheric NO2 columns in all instruments but larger values in those that are GB than that expected by nitrous oxide oxidation. The possible reasons for the discrepancy between instruments and the positive trends are discussed in the text.

scholarly journals Using XCO<sub>2</sub> retrievals for assessing the long-term consistency of NDACC/FTIR data sets

2015 ◽  
Vol 8 (3) ◽  
pp. 1555-1573 ◽  
Author(s):  
S. Barthlott ◽  
M. Schneider ◽  
F. Hase ◽  
A. Wiegele ◽  
E. Christner ◽  
...  
Keyword(s):  
Total Carbon ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Mauna Loa ◽  
Simple Regression Model ◽  
Good Consistency ◽  
Term Data

Abstract. 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 NDACC data records. Our 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 suggested 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‰). Our XCO2 model is 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‰.

scholarly journals Intercomparison of arctic XH<sub>2</sub>O observations from three ground-based Fourier transform infrared networks and application for satellite validation

2021 ◽  
Vol 14 (3) ◽  
pp. 1993-2011
Author(s):  
Qiansi Tu ◽  
Frank Hase ◽  
Thomas Blumenstock ◽  
Matthias Schneider ◽  
Andreas Schneider ◽  
...  
Keyword(s):  
Fourier Transform ◽  
A Priori ◽  
Fourier Transform Infrared ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Satellite Validation ◽  
Ftir Spectrometer ◽  
Priori Information ◽  
Good Agreement

Abstract. In this paper, we compare column-averaged dry-air mole fractions of water vapor (XH2O) 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 H2O 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 XH2O 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=0.9992) compared with MUSICA NDACC and (56.32±45.63) ppm ((3.44±1.77) %, R2=0.9997) compared with TCCON. Furthermore, the a priori H2O 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 XH2O, 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 XH2O. Finally, we investigate the quality of satellite data at high latitudes. For this purpose, the COCCON XH2O 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 XH2O at Kiruna and 7.75 % more at Sodankylä compared with TROPOMI. Our study supports the assumption that COCCON also delivers a well-characterized XH2O 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 XH2O has been compared with MUSICA NDACC and TCCON retrievals and has been used for MUSICA IASI and TROPOMI validation.

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