scholarly journals Multi-station intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability

2014 ◽  
Vol 7 (7) ◽  
pp. 6743-6790
Author(s):  
A. Ostler ◽  
R. Sussmann ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
S. Dohe ◽  
...  
Keyword(s):  
Near Infrared ◽  
A Priori ◽  
Polar Vortex ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Seasonal Cycles ◽  
Stratospheric Intrusion ◽  
Smoothing Effects ◽  
Key Factor ◽  
Source Sink

Abstract. Dry-air column-averaged mole fractions of methane (XCH4) retrieved from ground-based solar Fourier transform infrared (FTIR) measurements provide valuable information for satellite validation, evaluation of chemistry-transport models, and source-sink-inversions. In this context, Sussmann et al. (2013) have shown that mid-infrared (MIR) soundings from the Network for the Detection of Atmospheric Composition Change (NDACC) can be combined with near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON) without the need to apply an overall intercalibration factor. However, in spite of efforts to reduce a priori impact, some residual seasonal biases were identified, and the reasons behind remained unclear. In extension to this previous work, which was based on multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch (47.48° N, 11.06° E, 743 m a.s.l.) and Wollongong (34.41° S, 150.88° E, 30 m a.s.l.), we now investigate upgraded retrievals with longer temporal coverage and include three additional stations (Ny-Ålesund, 78.92° N, 11.93° E, 20 m a.s.l.; Karlsruhe, 49.08° N, 8.43° E, 110 m a.s.l.; Izaña, 28.31° N, 16.45° W, 2.370 m a.s.l.). Our intercomparison results (except for Ny-Ålesund) confirm that there is no overall bias between MIR and NIR XCH4 retrievals, and all MIR and NIR time series reveal a quasi-periodic seasonal bias for all stations, except for Izaña. We find that dynamical variability causes MIR–NIR differences of up to ~ 30 ppb for Ny-Ålesund, ~ 20 ppb for Wollongong, ~ 18 ppb for Garmisch, and ~ 12 ppb for Karlsruhe. The mechanisms behind this variability are elaborated via two case studies, one dealing with stratospheric subsidence induced by the polar vortex at Ny-Ålesund and the other with a deep stratospheric intrusion event at Garmisch. Smoothing effects caused by the dynamical variability during these events are different for MIR and NIR retrievals depending on the altitude of the perturbation area. MIR retrievals appear to be more realistic in the case of stratospheric subsidence, while NIR retrievals are more accurate in the case of stratosphere-troposphere exchange (STE) in the upper troposphere/lower stratosphere (UTLS) region. About 35% of the FTIR measurement days at Garmisch are impacted by STE, and about 23% of the measurement days at Ny-Ålesund are influenced by polar vortex subsidence. The exclusion of data affected by these dynamical situations resulted in improved agreement of MIR and NIR seasonal cycles for Ny-Ålesund and Garmisch. We found that dynamical variability is a key factor in constraining the accuracy of MIR and NIR seasonal cycles. The only way to avoid this problem is to use more realistic a priori profiles that take these dynamical events into account (e.g. via improved models), and/or to improve the FTIR retrievals to achieve a more uniform sensitivity at all altitudes (possibly including profile retrievals for the TCCON data).

scholarly journals Multistation intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability

2014 ◽  
Vol 7 (12) ◽  
pp. 4081-4101 ◽  
Author(s):  
A. Ostler ◽  
R. Sussmann ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
S. Dohe ◽  
...  
Keyword(s):  
Near Infrared ◽  
A Priori ◽  
Polar Vortex ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Seasonal Cycles ◽  
Stratospheric Intrusion ◽  
Smoothing Effects ◽  
Key Factor ◽  
Source Sink

Abstract. Dry-air column-averaged mole fractions of methane (XCH4) retrieved from ground-based solar Fourier transform infrared (FTIR) measurements provide valuable information for satellite validation, evaluation of chemical-transport models, and source-sink-inversions. In this context, Sussmann et al. (2013) have shown that midinfrared (MIR) soundings from the Network for the Detection of Atmospheric Composition Change (NDACC) can be combined with near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON) without the need to apply an overall intercalibration factor. However, in spite of efforts to reduce a priori impact, some residual seasonal biases were identified, and the reasons behind remained unclear. In extension to this previous work, which was based on multiannual quasi-coincident MIR and NIR measurements from the stations Garmisch (47.48° N, 11.06° E, 743 m a.s.l.) and Wollongong (34.41° S, 150.88° E, 30 m a.s.l.), we now investigate upgraded retrievals with longer temporal coverage and include three additional stations (Ny-Ålesund, 78.92° N, 11.93° E, 20 m a.s.l.; Karlsruhe, 49.08° N, 8.43° E, 110 m a.s.l.; Izaña, 28.31° N, 16.45° W, 2.370 m a.s.l.). Our intercomparison results (except for Ny-Ålesund) confirm that there is no overall bias between MIR and NIR XCH4 retrievals, and all MIR and NIR time series reveal a quasi-periodic seasonal bias for all stations, except for Izaña. We find that dynamical variability causes MIR–NIR differences of up to ~ 30 ppb (parts per billion) for Ny-Ålesund, ~ 20 ppb for Wollongong, ~ 18 ppb for Garmisch, and ~ 12 ppb for Karlsruhe. The mechanisms behind this variability are elaborated via two case studies, one dealing with stratospheric subsidence induced by the polar vortex at Ny-Ålesund and the other with a deep stratospheric intrusion event at Garmisch. Smoothing effects caused by the dynamical variability during these events are different for MIR and NIR retrievals depending on the altitude of the perturbation area. MIR retrievals appear to be more realistic in the case of stratospheric subsidence, while NIR retrievals are more accurate in the case of stratosphere–troposphere exchange (STE) in the upper troposphere/lower stratosphere (UTLS) region. About 35% of the FTIR measurement days at Garmisch are impacted by STE, and about 23% of the measurement days at Ny-Ålesund are influenced by polar vortex subsidence. The exclusion of data affected by these dynamical situations resulted in improved agreement of MIR and NIR seasonal cycles for Ny-Ålesund and Garmisch. We found that dynamical variability is a key factor in constraining the accuracy of MIR and NIR seasonal cycles. To mitigate this impact it is necessary to use more realistic a priori profiles that take these dynamical events into account (e.g., via improved models), and/or to improve the FTIR retrievals to achieve a more uniform sensitivity at all altitudes (possibly including profile retrievals for the TCCON data).

scholarly journals An intercomparison of total column-averaged nitrous oxide between ground-based FTIR TCCON and NDACC measurements at seven sites and comparisons with the GEOS-Chem model

2019 ◽  
Vol 12 (2) ◽  
pp. 1393-1408 ◽  
Author(s):  
Minqiang Zhou ◽  
Bavo Langerock ◽  
Kelley C. Wells ◽  
Dylan B. Millet ◽  
Corinne Vigouroux ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Southern Hemisphere ◽  
Near Infrared ◽  
A Priori ◽  
Polar Vortex ◽  
Inversion Method ◽  
Seasonal Cycles ◽  
A Posteriori ◽  
Model Simulations ◽  
N2o Fluxes

Abstract. Nitrous oxide (N2O) is an important greenhouse gas and it can also generate nitric oxide, which depletes ozone in the stratosphere. It is a common target species of ground-based Fourier transform infrared (FTIR) near-infrared (TCCON) and mid-infrared (NDACC) measurements. Both TCCON and NDACC networks provide a long-term global distribution of atmospheric N2O mole fraction. In this study, the dry-air column-averaged mole fractions of N2O (XN2O) from the TCCON and NDACC measurements are compared against each other at seven sites around the world (Ny-Ålesund, Sodankylä, Bremen, Izaña, Réunion, Wollongong, Lauder) in the time period of 2007–2017. The mean differences in XN2O between TCCON and NDACC (NDACC–TCCON) at these sites are between −3.32 and 1.37 ppb (−1.1 %–0.5 %) with standard deviations between 1.69 and 5.01 ppb (0.5 %–1.6 %), which are within the uncertainties of the two datasets. The NDACC N2O retrieval has good sensitivity throughout the troposphere and stratosphere, while the TCCON retrieval underestimates a deviation from the a priori in the troposphere and overestimates it in the stratosphere. As a result, the TCCON XN2O measurement is strongly affected by its a priori profile. Trends and seasonal cycles of XN2O are derived from the TCCON and NDACC measurements and the nearby surface flask sample measurements and compared with the results from GEOS-Chem model a priori and a posteriori simulations. The trends and seasonal cycles from FTIR measurement at Ny-Ålesund and Sodankylä are strongly affected by the polar winter and the polar vortex. The a posteriori N2O fluxes in the model are optimized based on surface N2O measurements with a 4D-Var inversion method. The XN2O trends from the GEOS-Chem a posteriori simulation (0.97±0.02 (1σ) ppb yr−1) are close to those from the NDACC (0.93±0.04 ppb yr−1) and the surface flask sample measurements (0.93±0.02 ppb yr−1). The XN2O trend from the TCCON measurements is slightly lower (0.81±0.04 ppb yr−1) due to the underestimation of the trend in TCCON a priori simulation. The XN2O trends from the GEOS-Chem a priori simulation are about 1.25 ppb yr−1, and our study confirms that the N2O fluxes from the a priori inventories are overestimated. The seasonal cycles of XN2O from the FTIR measurements and the model simulations are close to each other in the Northern Hemisphere with a maximum in August–October and a minimum in February–April. However, in the Southern Hemisphere, the modeled XN2O values show a minimum in February–April while the FTIR XN2O retrievals show different patterns. By comparing the partial column-averaged N2O from the model and NDACC for three vertical ranges (surface–8, 8–17, 17–50 km), we find that the discrepancy in the XN2O seasonal cycle between the model simulations and the FTIR measurements in the Southern Hemisphere is mainly due to their stratospheric differences.

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.

Independent a priori information for reduced intercomparison errors between TROPOMI and TCCON retrievals of methane and carbon monoxide

2020 ◽  
Author(s):  
Johannes Lutzmann ◽  
Ralf Sussmann ◽  
Huilin Chen ◽  
Frank Hase ◽  
Rigel Kivi ◽  
...  
Keyword(s):  
A Priori ◽  
Polar Vortex ◽  
Total Carbon ◽  
Space Agency ◽  
Ongoing Work ◽  
The Status ◽  
Priori Information ◽  
The Moment ◽  
Stratospheric Intrusions

<p>Ground-based column measurements of trace gases by FTIR spectrometers within the Total Carbon Column Observing Network (TCCON) provide accurate ground reference for the validation of the nadir-viewing hyperspectral Tropospheric Monitoring Instrument (TROPOMI) on-board the ESA satellite Sentinel 5 Precursor (S-5P). In such intercomparisons of two independent remote soundings, errors can occur as the a priori profiles used in the respective retrievals are i) differing from each other, and ii) both different from the true atmospheric state at the moment of observation. In certain conditions of atmospheric dynamics, e.g. polar vortex subsidence or stratospheric intrusions, which strongly alter the shape of vertical concentration profiles, these intercomparison errors can become considerable (Ostler et al., 2014).</p><p>In our work funded by the German Space Agency DLR and performed as part of the ESA AO project TCCON4S5P, we search for potential sources of realistic common a priori profiles for S-5P and TCCON CH<sub>4</sub> and CO measurements which reduce these large errors. We examine the performance of a number of chemical transport models and data assimilation systems in reproducing dynamical effects and in minimizing intercomparison errors. In-situ profiles measured by AirCores are used as validation where they are available. We present the status and results of our ongoing work.</p><p>Reference:</p><p>Ostler, A., Sussmann, R., Rettinger, M., Deutscher, N. M., Dohe, S., Hase, F., Jones, N., Palm, M., and Sinnhuber, B.-M.: Multistation intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability, Atmos. Meas. Tech., 7, 4081–4101, doi:10.5194/amt-7-4081-2014, 2014. Ostler, A., Sussmann, R., Rettinger, M., Deutscher, N. M., Dohe, S., Hase, F., Jones, N., Palm, M., and Sinnhuber, B.-M.: Multistation intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability, Atmos. Meas. Tech., 7, 4081–4101, doi:10.5194/amt-7-4081-2014, 2014.</p>

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 A new site: ground-based FTIR XCO<sub>2</sub>, XCH<sub>4</sub> and XCO measurements at Xianghe, China

2019 ◽  
Author(s):  
Yang Yang ◽  
Minqiang Zhou ◽  
Bavo Langerock ◽  
Mahesh Kumar Sha ◽  
Christian Hermans ◽  
...  
Keyword(s):  
North China ◽  
Near Infrared ◽  
Beam Splitter ◽  
Satellite Observations ◽  
Total Carbon ◽  
Seasonal Cycles ◽  
Near Infrared Spectra ◽  
Infrared Spectrometer ◽  
Global Coverage ◽  
Ingaas Detector

Abstract. The column-averaged dry-air mole fractions of CO2 (XCO2), CH4 (XCH4) and CO (XCO) have been measured with a Bruker IFS 125HR Fourier transform infrared spectrometer (FTIR) at Xianghe (39.75° N, 116.96° E, North China) since June 2018. The site and the FTIR system are described in this study. The instrumental setup follows the guidelines of the Total Carbon Column Observing Network (TCCON), and the near-infrared spectra are recorded by an InGaAs detector together with a CaF2 beam splitter. The HCl cell measurements that are recorded regularly to derive the instrument line shape (ILS) show that the instrument is correctly aligned. The Xianghe site lies in a polluted area in North China where there are currently no TCCON sites. It can fill the TCCON gap in this region and expand the global coverage of the TCCON measurements. The TCCON standard retrieval code (GGG2014) is applied to retrieve XCO2, XCH4 and XCO. The time series, seasonal cycles and day-to-day variations of XCO2, XCH4 and XCO measurements at Xianghe between June 2018 and July 2019 are shown and discussed. In addition, the FTIR measurements have been used to validate Orbiting Carbon Observatory-2 (OCO-2) and Tropospheric Monitoring Instrument (TROPOMI) satellite observations, as also shown in this paper. The Xianghe FTIR CO2, CH4 and CO data can be accessed at https://doi.org/10.18758/71021049 (Yang et al., 2019).

scholarly journals Quality assessment of ozone total column amounts as monitored by ground-based solar absorption spectrometry in the near infrared (> 3000 cm<sup>−1</sup>)

2014 ◽  
Vol 7 (3) ◽  
pp. 2071-2106
Author(s):  
O. E. García ◽  
M. Schneider ◽  
F. Hase ◽  
T. Blumenstock ◽  
E. Sepúlveda ◽  
...  
Keyword(s):  
Near Infrared ◽  
Absorption Spectrometry ◽  
Systematic Difference ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Solar Absorption ◽  
Annual Cycles ◽  
Long Term Stability ◽  
Total Column

Abstract. This study examines the possibility of ground-based remote sensing ozone total column amounts (OTC) from spectral signatures at 3040 and 4030 cm−1. These spectral regions are routinely measured by the NDACC (Network for the Detection of Atmospheric Composition Change) ground-based FTIR (Fourier Transform InfraRed) experiments. In addition, they are potentially detectable by the TCCON (Total Carbon Column Observing Network) FTIR instruments. The ozone retrieval strategy presented here estimates the OTC from NDACC FTIR high resolution spectra with a theoretical precision of about 2% and 5% in the 3040 cm−1 and 4030 cm−1 regions, respectively. Empirically, these OTC products are validated by inter-comparison to FTIR OTC reference retrievals in the 1000 cm−1 spectral region (standard reference for NDACC ozone products), using a 8 year FTIR time series (2005–2012) taken at the subtropical ozone super-site of the Izaña Observatory (Tenerife, Spain). Associated with the weaker ozone signatures at the higher wavenumber regions, the 3040 cm−1 and 4030 cm−1 retrievals show lower vertical sensitivity than the 1000 cm−1 retrievals. Nevertheless, we observe that the rather consistent variations are detected: the variances of the 3040 cm−1 and the 4030 cm−1 retrievals agree within 90% and 75%, respectively, with the variance of the 1000 cm−1 standard retrieval. Furthermore, all three retrievals show very similar annual cycles. However, we observe a large systematic difference of about 7% between the OTC obtained at 1000 cm−1 and 3040 cm−1, indicating a significant inconsistency between the spectroscopic ozone parameters (HITRAN 2012) of both regions. Between the 1000 cm−1 and the 4030 cm−1 retrieval the systematic difference is only 2–3%. Finally, the long-term stability of the OTC retrievals has also been examined, observing that both near infrared retrievals can monitor the long-term OTC evolution in consistency to the 1000 cm−1reference data.

scholarly journals Lower-tropospheric CO<sub>2</sub> from near-infrared ACOS-GOSAT observations

2017 ◽  
Vol 17 (8) ◽  
pp. 5407-5438 ◽  
Author(s):  
Susan S. Kulawik ◽  
Chris O'Dell ◽  
Vivienne H. Payne ◽  
Le Kuai ◽  
Helen M. Worden ◽  
...  
Keyword(s):  
Near Infrared ◽  
A Priori ◽  
New Products ◽  
Initial Guess ◽  
Average Error ◽  
Seasonal Cycles ◽  
Validation Data ◽  
Mixing Ratios ◽  
Monthly Average ◽  
The Difference

Abstract. We present two new products from near-infrared Greenhouse Gases Observing Satellite (GOSAT) observations: lowermost tropospheric (LMT, from 0 to 2.5 km) and upper tropospheric–stratospheric (U, above 2.5 km) carbon dioxide partial column mixing ratios. We compare these new products to aircraft profiles and remote surface flask measurements and find that the seasonal and year-to-year variations in the new partial column mixing ratios significantly improve upon the Atmospheric CO2 Observations from Space (ACOS) and GOSAT (ACOS-GOSAT) initial guess and/or a priori, with distinct patterns in the LMT and U seasonal cycles that match validation data. For land monthly averages, we find errors of 1.9, 0.7, and 0.8 ppm for retrieved GOSAT LMT, U, and XCO2; for ocean monthly averages, we find errors of 0.7, 0.5, and 0.5 ppm for retrieved GOSAT LMT, U, and XCO2. In the southern hemispheric biomass burning season, the new partial columns show similar patterns to MODIS fire maps and MOPITT multispectral CO for both vertical levels, despite a flat ACOS-GOSAT prior, and a CO–CO2 emission factor comparable to published values. The difference of LMT and U, useful for evaluation of model transport error, has also been validated with a monthly average error of 0.8 (1.4) ppm for ocean (land). LMT is more locally influenced than U, meaning that local fluxes can now be better separated from CO2 transported from far away.

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