Improved Constraints on Northern Extratropical CO2 Fluxes Obtained by Combining Surface-Based and Space-Based Atmospheric CO2 Measurements

© 2020. The Authors. Top-down estimates of CO2 fluxes are typically constrained by either surface-based or space-based CO2 observations. Both of these measurement types have spatial and temporal gaps in observational coverage that can lead to differences in inferred fluxes. Assimilating both surface-based and space-based measurements concurrently in a flux inversion framework improves observational coverage and reduces sampling related artifacts. This study examines the consistency of flux constraints provided by these different observations and the potential to combine them by performing a series of 6-year (2010–2015) CO2 flux inversions. Flux inversions are performed assimilating surface-based measurements from the in situ and flask network, measurements from the Total Carbon Column Observing Network (TCCON), and space-based measurements from the Greenhouse Gases Observing Satellite (GOSAT), or all three data sets combined. Combining the data sets results in more precise flux estimates for subcontinental regions relative to any of the data sets alone. Combining the data sets also improves the accuracy of the posterior fluxes, based on reduced root-mean-square differences between posterior flux-simulated CO2 and aircraft-based CO2 over midlatitude regions (0.33–0.56 ppm) in comparison to GOSAT (0.37–0.61 ppm), TCCON (0.50–0.68 ppm), or in situ and flask measurements (0.46–0.56 ppm) alone. These results suggest that surface-based and GOSAT measurements give complementary constraints on CO2 fluxes in the northern extratropics and can be combined in flux inversions to improve constraints on regional fluxes. This stands in contrast with many earlier attempts to combine these data sets and suggests that improvements in the NASA Atmospheric CO2 Observations from Space (ACOS) retrieval algorithm have significantly improved the consistency of space-based and surface-based flux constraints

TCCON Philippines: First Measurement Results, Satellite Data and Model Comparisons in Southeast Asia

The Total Carbon Column Observing Network (TCCON) is a global network dedicated to the precise and accurate measurements of greenhouse gases (GHG) in the atmosphere. The TCCON station in Burgos, Ilocos Norte, Philippines was established with the primary purpose of validating the upcoming Greenhouse gases Observing SATellite-2 (GOSAT-2) mission and in general, to respond to the need for reliable ground-based validation data for satellite GHG observations in the region. Here, we present the first 4 months of data from the new TCCON site in Burgos, initial comparisons with satellite measurements of CO2 and model simulations of CO. A nearest sounding from Japan\u27s GOSAT as well as target mode observations from NASA\u27s Orbiting Carbon Observatory 2 (OCO-2) showed very good consistency in the retrieved column-averaged dry air mole fractions of CO2, yielding TCCON - satellite differences of 0.86 ± 1.06 ppm for GOSAT and 0.83 ± 1.22 ppm for OCO-2. We also show measurements of enhanced CO, probably from East Asia. GEOS-Chem model simulations were used to study the observed CO variability. However, despite the model capturing the pattern of the CO variability, there is an obvious underestimation in the CO magnitude in the model. We conclude that more measurements and modeling are necessary to adequately sample the variability over different seasons and to determine the suitability of current inventories

Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) X\u3csub\u3eCO2\u3c/sub\u3e measurements with TCCON

NASA\u27s Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dry-air mole fraction, XCO2, in the Earth\u27s atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and XCO2 from OCO-2\u27s primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 XCO2 retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 XCO2 data quality throughout its mission

Tropospheric water vapour isotopologue data (H\u3csub\u3e2\u3c/sub\u3e\u3csup\u3e16\u3c/sup\u3eO, H\u3csub\u3e2\u3c/sub\u3e\u3csup\u3e18\u3c/sup\u3eO, and HD\u3csup\u3e16\u3c/sup\u3eO) as obtained from NDACC/FTIR solar absorption spectra

We report on the ground-based FTIR (Fourier transform infrared) tropospheric water vapour isotopologue remote sensing data that have been recently made available via the database of NDACC (Network for the Detection of Atmospheric Composition Change; ftp://ftp.cpc.ncep.noaa.gov/ndacc/MUSICA/) and via doi:10.5281/zenodo.48902. Currently, data are available for 12 globally distributed stations. They have been centrally retrieved and quality-filtered in the framework of the MUSICA project (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). We explain particularities of retrieving the water vapour isotopologue state (vertical distribution of H216O, H218O, and HD16O) and reveal the need for a new metadata template for archiving FTIR isotopologue data. We describe the format of different data components and give recommendations for correct data usage. Data are provided as two data types. The first type is best-suited for tropospheric water vapour distribution studies disregarding different isotopologues (comparison with radiosonde data, analyses of water vapour variability and trends, etc.). The second type is needed for analysing moisture pathways by means of H2O, δD-pair distributions

Validation of XCO2 and XCH4 retrieved from a portable Fourier transform spectrometer with those from in situ profiles from aircraft-borne instruments

Column-averaged dry-air mole fractions of carbon dioxide (XCO2) and methane (XCH4) measured by a solar viewing portable Fourier transform spectrometer (FTS, EM27/SUN) have been characterized and validated by comparison using in situ profile measurements made during the transfer flights of two aircraft campaigns: Korea-United States Air Quality Study (KORUS-AQ) and Effect of Megacities on the Transport and Transformation of Pollutants at Regional and Global Scales (EMeRGe). The aircraft flew over two Total Carbon Column Observing Network (TCCON) sites: Rikubetsu, Japan (43.46∘ N, 143.77∘ E), for the KORUS-AQ campaign and Burgos, Philippines (18.53∘ N, 120.65∘ E), for the EMeRGe campaign. The EM27/SUN was deployed at the corresponding TCCON sites during the overflights. The mole fraction profiles obtained by the aircraft over Rikubetsu differed between the ascending and the descending flights above approximately 8 km for both CO2 and CH4. Because the spatial pattern of tropopause heights based on potential vorticity values from the ERA5 reanalysis shows that the tropopause height over the Rikubetsu site was consistent with the descending profile, we used only the descending profile to compare with the EM27/SUN data. Both the XCO2 and XCH4 derived from the descending profiles over Burgos were lower than those from the ascending profiles. Output from the Weather Research and Forecasting Model indicates that higher CO2 for the ascending profile originated in central Luzon, an industrialized and densely populated region about 400 km south of the Burgos TCCON site. Air masses observed with the EM27/SUN overlap better with those from the descending aircraft profiles than those from the ascending aircraft profiles with respect to their properties such as origin and atmospheric residence times. Consequently, the descending aircraft profiles were used for the comparison with the EM27/SUN data. The EM27/SUN XCO2 and XCH4 data were derived by using the GGG2014 software without applying air-mass-independent correction factors (AICFs). The comparison of the EM27/SUN observations with the aircraft data revealed that, on average, the EM27/SUN XCO2 data were biased low by 1.22 % and the EM27/SUN XCH4 data were biased low by 1.71 %. The resulting AICFs of 0.9878 for XCO2 and 0.9829 for XCH4 were obtained for the EM27/SUN. Applying AICFs being utilized for the TCCON data (0.9898 for XCO2 and 0.9765 for XCH4) to the EM27/SUN data induces an underestimate for XCO2 and an overestimate for XCH4

Evaluation of MOPITT Version 7 joint TIR-NIR XCO retrievals with TCCON

Observations of carbon monoxide (CO) from the Measurements Of Pollution In The Troposphere (MOPITT) instrument aboard the Terra spacecraft were expected to have an accuracy of 10 % prior to the launch in 1999. Here we evaluate MOPITT Version 7 joint (V7J) thermal-infrared and near-infrared (TIR-NIR) retrieval accuracy and precision and suggest ways to further improve the accuracy of the observations. We take five steps involving filtering or bias corrections to reduce scatter and bias in the data relative to other MOPITT soundings and ground-based measurements. (1) We apply a preliminary filtering scheme in which measurements over snow and ice are removed. (2) We find a systematic pairwise bias among the four MOPITT along-track detectors (pixels) on the order of 3-4 ppb with a small temporal trend, which we remove on a global scale using a temporally trended bias correction. (3) Using a small-region approximation (SRA), a new filtering scheme is developed and applied based on additional quality indicators such as the signal-to-noise ratio (SNR). After applying these new filters, the root-mean-squared error computed using the local median from the SRA over 16 years of global observations decreases from 3.84 to 2.55 ppb. (4) We also use the SRA to find variability in MOPITT retrieval anomalies that relates to retrieval parameters. We apply a bias correction to one parameter from this analysis. (5) After applying the previous bias corrections and filtering, we compare the MOPITT results with the GGG2014 ground-based Total Carbon Column Observing Network (TCCON) observations to obtain an overall global bias correction. These comparisons show that MOPITT V7J is biased high by about 6 %-8 %, which is similar to past studies using independent validation datasets on V6J. When using TCCON spectrometric column retrievals without the standard airmass correction or scaling to aircraft (WMO scale), the ground- and satellite-based observations overall agree to better than 0.5 %. GEOS-Chem data assimilations are used to estimate the influence of filtering and scaling to TCCON on global CO and tend to pull concentrations away from the prior fluxes and closer to the truth. We conclude with suggestions for further improving the MOPITT data products