Assessing the magnitude of CO2 flux uncertainty in atmospheric CO2 records using products from NASA’s Carbon Monitoring Flux Pilot Project

Journal of Geophysical Research

Volumn 120, Issue 2, 2015, Pages 734-765

  Ott, Lesley E ^a   Pawson, Steven ^a   Collatz, George J ^a   Gregg, Watson W ^a   Menemenlis, Dimitris ^b   Brix, Holger ^c,d   Rousseaux, Cecile S ^a,e   Bowman, Kevin W ^b   Liu, Junjie ^b   Eldering, Annmarie ^b   Gunson, Michael R ^b   Kawa, Stephan R ^a  

^a NASA GODDARD SPACE FLIGHT CENTER   (United States)

^b CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d INSTITUTE OF MATERIALS RESEARCH   (Germany)

^e UNIVERSITIES SPACE RESEARCH ASSOCIATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOSPHERE; CARBON DIOXIDE; CARBON FLUX; GLOBAL CHANGE; GOSAT; NSCAT; SEASONAL VARIATION; UNCERTAINTY ANALYSIS;

EID: 84923200307     PISSN: 01480227     EISSN: 21562202     Source Type: Journal    
DOI: 10.1002/2014JD022411     Document Type: Article

References (110)

1. Adcroft, A., J. Campin, C. Hill, and J. Marshall (2004), Implementation of an atmosphere-ocean general circulation model on the expanded spherical cube, Mon. Weather Rev., 132, 2845-2863.
2. 2, Atmos. Chem. Phys. Discuss., 14, 13,909-13,962, doi: 10.5194/acpd-14-13909-2014.
3. 2 over China based on satellite observations, Chin. Sci. Bull., 55(31), 3612-3618.
4. Bala, G., N. Devaraju, R. K. Chaturvedi, K. Caldeira, and R. Nemani (2013), Nitrogen deposition: How important is it for global terrestrial carbon uptake?, Biogeosciences, 10, 7147-7160, doi: 10.5194/bg-10-7147-2013.
5. Ballantyne, A. P., C. B. Alden, J. B. Miller, P. P. Tans, and J. W. C. White (2012), Increase in observed net carbon dioxide uptake by land and oceans during the last 50 years, Nature, 488, 70-72.
6. 2, Atmos. Chem. Phys. Discuss., 13, 4535-4600, doi: 10.5194/acpd-13-4535-2013.
7. 2 flux over Tropical Asia estimated from GOSAT, CONTRAIL, and IASI, Geophys. Res. Lett., 41, 1809-1815, doi: 10.1002/2013GL059105.
8. Bellassen, V., N. Viovy, S. Luyssaert, G. Le Maire, M.-J. Schelhaas, and P. Ciais (2011), Reconstruction and attribution of the carbon sink of European forests between 1950 and 2000, Global Change Biol., 17, 3274-3292, doi: 10.1111/j.1365-2486.2011.02476.x.
9. 2 Emissions, Carbon Dioxide Inf. Anal. Cent., Oak Ridge Natl. Lab., U.S. Dep. of Energy, Oak Ridge, Tenn., doi: 10.3334/CDIAC/00001_V2011.
10. 2 sources and sinks: 1 Method and control inversion, J. Geophys. Res., 104(D21), 26,161-26,178, doi: 10.1029/1999JD900342.
11. 2, Geophys. Res. Lett., 35, L17807, doi: 10.1029/2008GL035022.
12. 2, Geophys. Res. Lett., 32, L22803, doi: 10.1029/2005GL024165.
13. 2 data assimilation, J. Geophys. Res. Atmos., 118, 10,140-10,154, doi: 10.1002/jgrd.50654.
14. Chevallier, F., R. J. Engelen, C. Carouge, T. J. Conway, P. Peylin, C. Pickett-Heaps, M. Ramonet, P. J. Rayner, and I. Xueref-Remy (2009), AIRS-based versus flask-based estimation of carbon surface fluxes, J. Geophys. Res., 114, D20303, doi: 10.1029/2009JD012311.
15. 2 total column, Geophys. Res. Lett., 38, L24810, doi: 10.1029/2011GL049899.
16. 2, Geophys. Res. Lett., 41, 1065-1070, doi: 10.1002/2013GL058772.
17. 2, Global Biogeochem. Cycles, 21, GB2014, doi: 10.1029/2006GB002741.
18. Conway, J., P. P. Tans, L. S. Waterman, K. W. Thoning, D. R. Kitzis, K. A. Masarie, and N. Zhang (1994), Evidence of interannual variability of the carbon cycle from the NOAA/CMDL global air sampling network, J. Geophys. Res., 99(D11), 22,831-22,855, doi: 10.1029/94JD01951.
19. 2 data characterization, Atmos. Meas. Tech., 5, 687-707, doi: 10.5194/amt-5-687-2012.
20. Doney, S. C., et al. (2004), Evaluating global ocean carbon models: The importance of realistic physics, Global Biogeochem. Cycles, 18, GB3017, doi: 10.1029/2003GB002150.
21. Dutkiewicz, S., M. Follows, and J. Bragg (2009), Modeling the coupling of ocean ecology and biogeochemistry, Global Biogeochem. Cycles, 23, GB4017, doi: 10.1029/2008GB003405.
22. 2 using AIRS observations, J. Geophys. Res., 114, D03303, doi: 10.1029/2008JD010739.
23. Esser, G., J. Kattge, and A. Sakalli (2011), Feedback of carbon and nitrogen cycles enhances carbon sequestration in the terrestrial biosphere, Global Change Biol., 17, 819-842, doi: 10.1111/j.1365-2486.2010.02261.x.
24. 2 using ground-based, aircraft, and space-borne data, Atmos. Chem. Phys., 11, 2789-2803, doi: 10.5194/acp-11-2789-2011.
25. Fleischer, K., et al. (2013), The contribution of nitrogen deposition to the photosynthetic capacity of forests, Global Biogeochem. Cycles, 27, 187-199, doi: 10.1002/gbc.20026.
26. Follows, M., and S. Dutkiewicz (2011), Modeling diverse communities of marine microbes, Annu. Rev. Mar. Sci., 3, 427-451.
27. Follows, M., T. Ito, and S. Dutkiewicz (2006), On the solution of the carbonate chemistry system in ocean biogeochemistry models, Ocean Modell., 12, 290-301.
28. Follows, M., S. Dutkiewicz, S. Grant, and S. Chisholm (2007), Emergent biogeography of microbial communities in a model ocean, Science, 315, 1843-1846.
29. Gerber, S., L. O. Hedin, S. G. Keel, S. W. Pacala, and E. Shevliakova (2013), Land use change and nitrogen feedbacks constrain the trajectory of the land carbon sink, Geophys. Res. Lett., 40, 5218-5222, doi: 10.1002/grl.50957.
30. 2 fluxes: A synthetic data study, Atmos. Chem. Phys., 10, 6151-6167, doi: 10.5194/acp-10-6151-2010.
31. Gregg, W. W., and N. W. Casey (2007), Modeling coccolithophores in the global oceans, Deep Sea Res., Part II, 54, 447-477.
32. Gregg, W. W., P. Ginoux, P. S. Schopf, and N. W. Casey (2003), Phytoplankton and Iron: Validation of a global three-dimensional ocean biogeochemical model, Deep Sea Res., Part II, 50, 3143-3169.
33. Gregg, W. W., N. W. Casey, and C. S. Rousseaux (2013), Global Surface Ocean Estimates in a Model Forced by MERRA, NASA Global Model. and Assimilation Ser., vol. 31, edited by M. Suarez, Tech. Rep., 104606 V31, NASA.
34. Guerlet, S., S. Basu, A. Butz, M. Krol, P. Hahne, S. Houweling, O. P. Hasekamp, and I. Aben (2013), Reduced carbon uptake during the 2010 Northern Hemisphere summer from GOSAT, Geophys. Res. Lett., 40, 2378-2383, doi: 10.1002/grl.50402.
35. 2 sources and sinks using atmospheric transport models, Nature, 415, 626-630.
36. Heimbach, P., D. Menemenlis, M. Losch, J. Campin, and C. Hill (2010), On the formulation of sea-ice models. Part 2: Lessons from multi-year adjoint sea ice export sensitivities through the Canadian Arctic Archipelago, Ocean Modell., 33, 145-158.
37. 2 exchange, Global Change Biol., 10, 1689-1706, doi: 10.1111/j.1365-2486.2004.00847.x.
38. 2 flux variability, J. Geophys. Res., 116, D06110, doi: 10.1029/2010JD015048.
39. Huntzinger, D. N., et al. (2012), North American Carbon Program (NACP) regional interim synthesis: Terrestrial biospheric model intercomparison, Ecol. Modell., 232, 144-157.
40. 2 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data, Atmos. Chem. Phys. Discuss., 13, 3203-3246, doi: 10.5194/acpd-13-3203-2013.
41. 2 from Atmospheric Infrared Sounder, Geophys. Res. Lett., 37, L13801, doi: 10.1029/2010GL042823.
42. Keppel-Aleks, G., et al. (2012), The imprint of surface fluxes and transport on variations in total column carbon dioxide, Biogeosciences, 9, 875-891, doi: 10.5194/bg-9-875-2012.
43. Keppel-Aleks, G., et al. (2013), Atmospheric carbon dioxide variability in the Community Earth System Model: Evaluation and transient dynamic during the 20th and 21st centuries, J. Clim., 26, 4447-4475, doi: 10.1175/JCLI-D-12-00589.1.
44. Kipling, Z., P. Stier, J. P. Schwarz, A. E. Perring, J. R. Spackman, G. W. Mann, C. E. Johnson, and P. J. Telford (2013), Constraints on aerosol processes in climate models from vertically-resolved aircraft observations of black carbon, Atmos. Chem. Phys., 13, 5969-5986, doi: 10.5194/acp-13-5969-2013.
45. Kort, A. E., C. Frankenberg, C. E. Miller, and T. Oda (2012), Space-based observations of megacity carbon dioxide, Geophys. Res. Lett., 39, L17806, doi: 10.1029/2012GL052738.
46. Kuze, A., S. Hiroshi, N. Masakatsu, and H. Takashi (2009), Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring, Appl. Opt., 48, 6716-6733, doi: 10.1364/AO.48.006716.
47. Lafleur, P. M., N. T. Roulet, J. L. Bubier, S. Frolking, and T. R. Moore (2003), Interannual variability in the peatland-atmosphere carbon dioxide exchange at an ombrotrophic bog, Global Biogeochem. Cycles, 17(2), 1036, doi: 10.1029/2002GB001983.
48. 2: Experimental overview and diurnal cycle results for 2002, Global Biogeochem. Cycles, 22, GB3009, doi: 10.1029/2007GB003050.
49. Le Quéré, C., et al. (2013), The global carbon budget 1959-2011, Earth Syst. Sci. Data, 5, 165-185, doi: 10.5194/essd-5-165-2013.
50. 2 variability driven by the Madden-Julian oscillation, Proc. Natl. Acad. Sci. U.S.A., 107(45), 19,171-19,175, doi: 10.1073/pnas.1008222107.
51. Lin, S.-J. (2004), A “vertically Lagrangian” finite-volume dynamical core for global models, Mon. Weather Rev., 132(10), 2293-2307.
52. 2 and meteorological observations in a carbon climate model with an ensemble Kalman filter, J. Geophys. Res., 117, D05309, doi: 10.1029/2011JD016642.
53. Lock, A. P., A. R. Brown, M. R. Bush, G. M. Martin, and R. N. B. Smith (2000), A new boundary layer mixing scheme. Part I: Scheme description and single-column model tests, Mon. Weather Rev., 128, 3187-3199.
54. 2 fertilization effect in global vegetation, Global Biogeochem. Cycles, 27, 318-330, doi: 10.1002/gbc.20027.
55. Los, S. O., G. J. Collatz, P. J. Sellers, C. M. Malmstrom, N. H. Pllack, R. S. DeFries, L. Bounoua, M. T. Parris, C. J. Tucker, and D. A. Dazlich (2000), A global 9-yr biophysical land surface dataset from NOAA AVHRR data, J. Hydrometeorol., 1, 183-199.
56. Losch, M., D. Menemenlis, P. Heimbach, J. Campin, and C. Hill (2010), On the formulation of sea-ice models. Part 1: Effects of different solver implementations and parameterizations, Ocean Modell., 33, 129-144.
57. 2 observations, Atmos. Chem. Phys., 13, 9351-9373, doi: 10.5194/acp-13-9351-2013.
58. Mann, G. W., et al. (2012), Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model, Atmos. Chem. Phys., 12, 4449-4476, doi: 10.5194/acp-12-4449-2012.
59. Marshall, J., A. Adcroft, C. Hill, L. Perelman, and C. Heisey (1997a), A finite-volume, incompressible Navier-Stokes model for studies of the ocean on parallel computers, J. Geophys. Res., 102(C3), 5753-5766, doi: 10.1029/96JC02775.
60. Marshall, J., C. Hill, L. Perelman, and A. Adcroft (1997b), Hydrostatic, quasi-hydrostatic and non-hydrostatic ocean modeling, J. Geophys. Res., 102(C3), 5733-5752, doi: 10.1029/96JC02776.
61. Menemenlis, D., et al. (2005a), NASA supercomputer improves prospects for ocean climate research, Eos Trans. AGU, 86(89), 95-96.
62. Menemenlis, D., I. Fukumori, and T. Lee (2005b), Using Green’s functions to calibrate an ocean general circulation model, Mon. Weather Rev., 133, 1224-1240.
63. 2: High resolution global ocean and sea ice data synthesis, Mercator Ocean Quart. Newslett., 31, 13-21.
64. Messerschmidt, J., et al. (2012), Automated ground-based remote sensing measurements of greenhouse gases at the Białystok site in comparison with collocated in situ measurements and model data, Atmos. Chem. Phys., 12(15), 6741-6755, doi: 10.5194/acp-12-6741-2012.
65. Michalak, A. M., L. Bruhwiler, and P. P. Tans (2004), A geostatistical approach to surface flux estimation of atmospheric trace gases, J. Geophys. Res., 109, D14109, doi: 10.1029/2003JD004422.
66. Moorthi, S., and M. J. Suarez (1992), Relaxed Arakawa-Schubert: A parameterization of moist convection for general circulation models, Mon. Weather Rev., 120, 978-1002.
67. Mu, M., et al. (2011), Daily and 3-hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide, J. Geophys. Res., 116, D24303, doi: 10.1029/2011JD016245.
68. Najjar, R. G., et al. (2007), Impact of circulation on export production, dissolved organic matter, and dissolved oxygen in the ocean: Results from Phase II of the Ocean Carbon-cycle Model Intercomparison Project (OCMIP-2), Global Biogeochem. Cycles, 21, GB3007, doi: 10.1029/2006GB002857.
69. Novelli, P. C., L. P. Steele, and P. P. Tans (1992), Mixing ratios of carbon monoxide in the troposphere, J. Geophys. Res., 97(D18), 20,731-20,750, doi: 10.1029/92JD02010.
70. 2 retrieval algorithm-Part 1: Description and validation against synthetic observations, Atmos. Meas. Tech., 5, 99-121, doi: 10.5194/amt-5-99-2012.
71. 2 and implications for carbon cycle research, J. Geophys. Res., 109, D02301, doi: 10.1029/2003JD003968.
72. Orr, J. C., et al. (2001), Estimates of anthropogenic carbon uptake from four three-dimensional global ocean models, Global Biogeochem. Cycles, 15(1), 43-60, doi: 10.1029/2000GB001273.
73. Ott, L., B. Duncan, S. Pawson, P. Colarco, M. Chin, C. Randles, T. Diehl, and J. E. Nielsen (2010), Influence of the 2006 Indonesian biomass burning aerosols on tropical dynamics studied with the GEOS-5 AGCM, J. Geophys. Res., 115, D14121, doi: 10.1029/2009JD013181.
74. Ott, L., S. Pawson, and J. Bacmeister (2011), An analysis of the impact of convective parameter sensitivity on simulated global atmospheric CO distributions, J. Geophys. Res., 116, D21310. doi: 10.1029/2011JD016077.
75. 2 trends, Global Change Biol., 19, 2117-2132, doi: 10.1111/gcb.12187.
76. Pinzon, J. E., and C. J. Tucker (2014), A non-stationary 1981-2012 AVHRR NDVI3g time series, Remote Sens., 6, 6929-6960.
77. Popova, E. E., A. Yool, A. C. Coward, F. Dupont, C. Deal, S. Elliott, E. Hunke, M. Jin, M. Steele, and J. Zhang (2012), What controls primary production in the Arctic Ocean? Results from an intercomparison of five general circulation models with biogeochemistry, J. Geophys. Res., 117, C00D12, doi: 10.1029/2011JC007112.
78. Potter, C. S. (1997), An ecosystem simulation model for methane production and emission from wetlands, Global Biogeochem. Cycles, 11(4), 495-506, doi: 10.1029/97GB02302.
79. Potter, C. S., J. T. Randerson, C. B. Field, P. A. Matson, P. M. Vitousek, H. A. Mooney, and S. A. Klooster (1993), Terrestrial ecosystem production-A process model based on global satellite and surface data, Global Biogeochem. Cycles, 7(4), 811-841, doi: 10.1029/93GB02725.
80. Potter, C., S. Klooster, A. Huete, and V. Genovese (2007), Terrestrial carbon sinks for the United States predicted from MODIS satellite data and ecosystem modeling, Earth Interact., 11, 1-21, doi: 10.1175/EI228.1.
81. Potter, C., S. Klooster, V. Genovese, C. Hiatt, S. Boriah, V. Kumar, V. Mithal, and A. Garg (2012). Terrestrial ecosystem carbon fluxes predicted from MODIS satellite data and large-scale disturbance modeling, Int. J. Geosci., doi: 10.4236/ijg.2012.
82. Raczka, B. M., et al. (2013), Evaluation of continental carbon cycle simulations with North American flux tower observations, Ecol. Monogr., 83(4), 531-556.
83. 2, Global Biogeochem. Cycles, 10(4), 585-602, doi: 10.1029/96GB01981.
84. Randerson, J. T., et al. (2009), Systematic assessment of terrestrial biogeochemistry in coupled climate-carbon models, Global Change Biol., 15, 2462-2484, doi: 10.1111/j.1365-2486.2009.01912.
85. Reinecker,M. M., et al. (2008), The GEOS-5 Data Assimilation System-Documentation of Versions 5.0.1, 5.1.0, and 5.2.0, Tech. Rep. 104606 V27, NASA.
86. Rienecker, M. M., et al. (2011), MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications, J. Clim., 24, 3624-3648.
87. 2 variability from global satellite data, J. Clim., doi: 10.1175/JCLI-D-11-00223.1.
88. Schaefer, K., et al. (2012), A model-data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis, J. Geophys. Res., 117, G03010, doi: 10.1029/2012JG001960.
89. Schuh, A. E., A. S. Denning, K. D. Corbin, I. T. Baker, M. Uliasz, N. Parazoo, A. E. Andrews, and D. E. J. Worthy (2010), A regional high-resolution carbon flux inversion of North America for 2004, Biogeosciences, 7(5), 1625-1644, doi: 10.5194/bg-7-1625-2010.
90. 2 exchange across North America: Results from the North American Carbon Program site synthesis, J. Geophys. Res., 115, G00H05, doi: 10.1029/2009JG001229.
91. Sentman, L. T., E. Shevliakova, R. J. Stouffer, and S. Malyshev (2011), Time scales of terrestrial carbon response related to land-use application: Implications for initializing an Earth system model, Earth Interact., 15, 1-16, doi: 10.1175/2011EI401.1.
92. 2 fluxes, SOLA, 7, 161-164, doi: 10.2151/sola.2011-041.
93. 2, and seasonal biological and temperature effects, Deep Sea Res., Part II, 49, 1601-1622.
94. 2 flux over the global oceans, Deep Sea Res., Part II, 56, 554-577.
95. 2 budget, Science, 247, 1431-1438.
96. Tucker, C. J., J. E. Pinzon, M. E. Brown, D. A. Slayback, E. W. Pak, R. Mahoney, E. F. Vermote, and N. El Saleous (2005), An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data, Int. J. Remote Sens., 26(20), 4485-4498.
97. van der Werf, G. R., J. T. Randerson, G. J. Collatz, L. Giglio, P. S. Kasibhatla, A. F. Arellano, S. C. Olsen, and E. S. Kasischke (2004), Continental-scale partitioning of fire emissions during the 1997 to 2001 El Niño/La Niña period, Science, 303, 73-76.
98. van der Werf, G. R., J. T. Randerson, L. Giglio, G. J. Collatz, P. S. Kasibhatla, and A. F. Arellano (2006), Interannual variability of global biomass burning emissions from 1997 to 2004, Atmos. Chem. Phys., 6, 3423-3441.
99. van der Werf, G. R., J. T. Randerson, L. Giglio, G. J. Collatz, M. Mu, P. S. Kasibhatla, D. C. Morton, R. S. DeFries, Y. Jin, and T. T. van Leeuwen (2010), Global fire emissions and the contribution of deforestation, agriculture, and peat fires (1997-2009), Atmos. Chem. Phys., 10, 11,707-11,735.
100. 2, Agric. Forest Meteorol., 151, 1753-1762, doi: 10.1016/j.agrformet.2011.07.011.
101. 2 flux inversions using satellite data, Atmos. Chem. Phys., 9, 7313-7323, doi: 10.5194/acp-9-7313-2009.
102. Wanninkhof, R. (1992), Relationship between wind speed and gas exchange over the ocean, J. Geophys. Res., 97(C5), 7373-7382, doi: 10.1029/92JC00188.
103. 4 concentration profiles at the Zotino Tall Tower Observatory (ZOTTO) on regional summertime ecosystem fluxes, Biogeosciences, 11, 2055-2068, doi: 10.5194/bg-11-2055-2014.
104. Wofsy, S. C., et al. (2011), HIAPER Pole-to-Pole Observations (HIPPO): Fine-grained, global-scale measurements of climatically important atmospheric gases and aerosols, Proc. R. Soc. A, 369, 2073-2086, doi: 10.1098/rsta.2010.0313.
105. Wunch, D., et al. (2010), Calibration of the total carbon column observing network using aircraft profile data, Atmos. Measure. Tech., 3(5), 1351-1362, doi: 10.5194/amt-3-1351-2010.
106. Wunch, D., G. C. Toon, J.-F. L. Blavier, R. A. Washenfelder, J. Notholt, B. J. Connor, D. W. T. Griffith, V. Sherlock, and P. O. Wennberg (2011a), The total carbon column observing network, Philos. Trans. R. Soc. London, Ser. A, 369(1943), 2087-2112, doi: 10.1098/rsta.2010.0240.
107. 2 total columns from space, Atmos. Chem. Phys., 11(23), 12,317-12,337, doi: 10.5194/acp-11-12317-2011.
108. Wunsch, C., and P. Heimbach (2007), Practical global ocean state estimation, Phys. D, 230, 197-208.
109. 4 retrieved from GOSAT: First preliminary results, SOLA, 5, 160-163.
110. Zhu, Y., and R. Gelaro (2008), Observation sensitivity calculations using the adjoint of the Gridpoint Statistical Interpolation (GSI) analysis system, Mon. Weather Rev., 136, 335-351.