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  • 1
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2008. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 113 (2008): G01010, doi:10.1029/2007JG000408.
    Description: Seasonal and interannual variability in atmospheric carbon dioxide (CO2) concentrations was simulated using fluxes from fossil fuel, ocean and terrestrial biogeochemical models, and a tracer transport model with time-varying winds. The atmospheric CO2 variability resulting from these surface fluxes was compared to observations from 89 GLOBALVIEW monitoring stations. At northern hemisphere stations, the model simulations captured most of the observed seasonal cycle in atmospheric CO2, with the land tracer accounting for the majority of the signal. The ocean tracer was 3–6 months out of phase with the observed cycle at these stations and had a seasonal amplitude only ∼10% on average of observed. Model and observed interannual CO2 growth anomalies were only moderately well correlated in the northern hemisphere (R ∼ 0.4–0.8), and more poorly correlated in the southern hemisphere (R 〈 0.6). Land dominated the interannual variability (IAV) in the northern hemisphere, and biomass burning in particular accounted for much of the strong positive CO2 growth anomaly observed during the 1997–1998 El Niño event. The signals in atmospheric CO2 from the terrestrial biosphere extended throughout the southern hemisphere, but oceanic fluxes also exerted a strong influence there, accounting for roughly half of the IAV at many extratropical stations. However, the modeled ocean tracer was generally uncorrelated with observations in either hemisphere from 1979–2004, except during the weak El Niño/post-Pinatubo period of the early 1990s. During that time, model results suggested that the ocean may have accounted for 20–25% of the observed slowdown in the atmospheric CO2 growth rate.
    Description: We acknowledge the support of NASA grant NNG05GG30G and NSF grant ATM0628472.
    Keywords: Atmospheric CO2 ; Interannual variability ; Seasonal cycles ; Transport model
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-05-25
    Description: Author Posting. © Blackwell, 2006. This is the author's version of the work. It is posted here by permission of Blackwell for personal use, not for redistribution. The definitive version was published in Tellus B 58 (2006):359-365, doi:10.1111/j.1600-0889.2006.00218.x.
    Description: The sources and sinks of important climatic trace gases such as carbon dioxide (CO2) are often deduced from spatial and temporal variations in atmospheric concentrations. Reducing uncertainties in our understanding of the contemporary carbon budget and its underlying dynamics, however, requires significantly denser observations globally than is practical with in situ measurements. Space-based measurements appear technically feasible but require innovations in data analysis approaches. We develop a variational data assimilation scheme to estimate surface CO2 fluxes at fine time/space scales from such dense atmospheric data. Global flux estimates at a daily time step and model-grid spatial resolution (4° × 5° here) are rapidly achieved after only a few dozen minimization steps. We quantify the flux errors from existing, planned and hypothetical surface and space-borne observing systems. Simulations show that the planned NASA Orbital Carbon Observatory (OCO) satellite should provide significant additional information beyond that from existing and proposed in situ observations. Improvements in data assimilation techniques and in mechanistic process models are both needed to fully exploit the emerging global carbon observing system.
    Description: This work was made possible through support from the Office of Global Programs (OGP) of the National Atmospheric and Oceanographic Administration (NOAA) (Grant NA16GP2935 at NCAR, NA16GP2008 at WHOI). NCAR is sponsored by the National Science Foundation.
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
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  • 3
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2008. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 22 (2008): GB3025, doi:10.1029/2007GB003082.
    Description: Interannually varying net carbon exchange fluxes from the TransCom 3 Level 2 Atmospheric Inversion Intercomparison Experiment are presented for the 1980 to 2005 time period. The fluxes represent the model mean, net carbon exchange for 11 land and 11 ocean regions after subtraction of fossil fuel CO2 emissions. Both aggregated regional totals and the individual regional estimates are accompanied by a model uncertainty and model spread. We find that interannual variability is larger on the land than the ocean, with total land exchange correlated to the timing of both El Niño/Southern Oscillation (ENSO) as well as the eruption of Mt. Pinatubo. The post-Pinatubo negative flux anomaly is evident across much of the tropical and northern extratropical land regions. In the oceans, the tropics tend to exhibit the greatest level of interannual variability, while on land, the interannual variability is slightly greater in the tropics and northern extratropics. The interannual variation in carbon flux estimates aggregated by land and ocean across latitudinal bands remains consistent across eight different CO2 observing networks. The interannual variation in carbon flux estimates for individual flux regions remains mostly consistent across the individual observing networks. At all scales, there is considerable consistency in the interannual variations among the 13 participating model groups. Finally, consistent with other studies using different techniques, we find a considerable positive net carbon flux anomaly in the tropical land during the period of the large ENSO in 1997/1998 which is evident in the Tropical Asia, Temperate Asia, Northern African, and Southern Africa land regions. Negative anomalies are estimated for the East Pacific Ocean and South Pacific Ocean regions. Earlier ENSO events of the 1980s are most evident in southern land positive flux anomalies.
    Keywords: Carbon cycle ; Atmospheric inversion ; Interannual variability
    Repository Name: Woods Hole Open Access Server
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  • 4
    Publication Date: 2022-05-26
    Description: © The Authors, 2010. This article is distributed under the terms of the Creative Commons Attribution 3.0 License. The definitive version was published in Atmospheric Chemistry and Physics 10 (2010): 4145-4165, doi:10.5194/acp-10-4145-2010.
    Description: We quantify how well column-integrated CO2 measurements from the Orbiting Carbon Observatory (OCO) should be able to constrain surface CO2 fluxes, given the presence of various error sources. We use variational data assimilation to optimize weekly fluxes at a 2°×5° resolution (lat/lon) using simulated data averaged across each model grid box overflight (typically every ~33 s). Grid-scale simulations of this sort have been carried out before for OCO using simplified assumptions for the measurement error. Here, we more accurately describe the OCO measurements in two ways. First, we use new estimates of the single-sounding retrieval uncertainty and averaging kernel, both computed as a function of surface type, solar zenith angle, aerosol optical depth, and pointing mode (nadir vs. glint). Second, we collapse the information content of all valid retrievals from each grid box crossing into an equivalent multi-sounding measurement uncertainty, factoring in both time/space error correlations and data rejection due to clouds and thick aerosols. Finally, we examine the impact of three types of systematic errors: measurement biases due to aerosols, transport errors, and mistuning errors caused by assuming incorrect statistics. When only random measurement errors are considered, both nadir- and glint-mode data give error reductions over the land of ~45% for the weekly fluxes, and ~65% for seasonal fluxes. Systematic errors reduce both the magnitude and spatial extent of these improvements by about a factor of two, however. Improvements nearly as large are achieved over the ocean using glint-mode data, but are degraded even more by the systematic errors. Our ability to identify and remove systematic errors in both the column retrievals and atmospheric assimilations will thus be critical for maximizing the usefulness of the OCO data.
    Description: SD and DB acknowledge support from NASA grant NNG06G127G. DB also acknowledges initial support from NOAA Grant NA16GP2935.
    Repository Name: Woods Hole Open Access Server
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    GPS solutions 3 (1999), S. 32-41 
    ISSN: 1521-1886
    Source: Springer Online Journal Archives 1860-2000
    Topics: Architecture, Civil Engineering, Surveying , Geosciences
    Notes: The hybridization of GPS with GLONASS has formed a first stage in GNSS development. We examine the performance of the hybrid system in the position domain for both code and carrier phase cases. Several major differences exist between GPS and GLONASS; most significant is GLONASS's signal frequency diversity, which can lead to measurement bias, particularly so when a pair of receivers are operating at different temperatures. Unless signal frequency diversity is addressed either on-receiver or at the data processing stage, positioning errors can occur at the centimeter level. We outline the difficulties of combining observations from the two systems and discuss how these may be overcome. © 1999 John Wiley & Sons, Inc.
    Type of Medium: Electronic Resource
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  • 6
  • 7
    Publication Date: 2007-03-07
    Electronic ISSN: 1750-0680
    Topics: Geosciences
    Published by BioMed Central
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  • 8
    Publication Date: 2018-12-11
    Description: Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2 (XCO2) for the roughly 100 000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25 %, is required in order to accurately infer carbon sources and sinks from XCO2, significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20 % over land and 40 % over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.
    Print ISSN: 1867-1381
    Electronic ISSN: 1867-8548
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 9
    Publication Date: 2018-05-24
    Description: We estimate the uncertainty of CO2 flux estimates in atmospheric inversions stemming from differences between different global transport models. Using a set of observing system simulation experiments (OSSEs), we estimate this uncertainty as represented by the spread between five different state-of-the-art global transport models (ACTM, LMDZ, GEOS-Chem, PCTM and TM5), for both traditional in situ CO2 inversions and inversions of XCO2 estimates from the Orbiting Carbon Observatory 2 (OCO-2). We find that, in the absence of relative biases between in situ CO2 and OCO-2 XCO2, OCO-2 estimates of terrestrial flux for TRANSCOM-scale land regions can be more robust to transport model differences than corresponding in situ CO2 inversions. This is due to a combination of the increased spatial coverage of OCO-2 samples and the total column nature of OCO-2 estimates. We separate the two effects by constructing hypothetical in situ networks with the coverage of OCO-2 but with only near-surface samples. We also find that the transport-driven uncertainty in fluxes is comparable between well-sampled northern temperate regions and poorly sampled tropical regions. Furthermore, we find that spatiotemporal differences in sampling, such as between OCO-2 land and ocean soundings, coupled with imperfect transport, can produce differences in flux estimates that are larger than flux uncertainties due to transport model differences. This highlights the need for sampling with as complete a spatial and temporal coverage as possible (e.g., using both land and ocean retrievals together for OCO-2) to minimize the impact of selective sampling. Finally, our annual and monthly estimates of transport-driven uncertainties can be used to evaluate the robustness of conclusions drawn from real OCO-2 and in situ CO2 inversions.
    Print ISSN: 1680-7316
    Electronic ISSN: 1680-7324
    Topics: Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 10
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