A geostatistical approach to surface flux estimation of atmospheric trace gases

Journal of Geophysical Research D: Atmospheres

Volumn 109, Issue 14, 2004, Pages

  Michalak, Anna M ^a   Bruhwiler, Lori ^a   Tans, Pieter P ^a  

^a EARTH SYSTEM RESEARCH LABORATORY   (United States)

Author keywords

Bayesian inference; Carbon dioxide; Geostatistics; Surface flux estimation

Indexed keywords

ATMOSPHERE-BIOSPHERE INTERACTION; ATMOSPHERIC GAS; BAYESIAN ANALYSIS; CARBON DIOXIDE; GEOSTATISTICS; SURFACE FLUX; TRACE GAS;

EID: 5444275643     PISSN: 01480227     EISSN: None     Source Type: Journal    
DOI: 10.1029/2003JD004422     Document Type: Article

References (54)

1. Andres, R. J., G. Marland, I. Fung, and E. Matthews (1996), A 1° × 1° distribution of carbon dioxide emissions from fossil fuel consumption and cement manufacture, 1950-1990, Global Biogeochem. Cycles, 10(3), 419-430.
2. 2 sources and sinks: 1. Method and control inversion, J. Geophys. Res., 104(D21), 26,161-26,178.
3. Brenkert, A. L. (1998), Carbon dioxide emission estimates from fossil-fuel burning, hydraulic cement production, and gas flaring for 1995 on a one degree grid cell basis, http://cdiac.esd.ornl.gov/ndps/ndp058a.html, Carbon Dioxide Inf. Anal. Cent., Oak Ridge Natl. Lab., Oak Ridge, Tenn.
4. Brown, M. (1993), Deduction of emissions of source gases using an objective inversion algorithm and a chemical transport model, J. Geophys. Res., 98(D7), 12,639-12,660.
5. Committee on the Science of Climate Change, Division on Earth and Life Studies, National Research Council (2001), Climate Change Science: An Analysis of Some Key Questions, Natl. Acad. Press, Washington, D. C.
6. Cressie, N. A. C. (1991), Statistics for Spatial Data, Wiley-Intersci., New York.
7. Doyen, P. M. (1988), Porosity from seismic data: A geostatistical approach, Geophysics, 53(10), 1263-1275.
8. Enting, I. G. (2002), Inverse Problems in Atmospheric Constituent Transport, Cambridge Univ. Press, New York.
9. Enting, I. G., and G. N. Newsam (1990), Atmospheric constituent inversion problems: Implications for baseline monitoring, J. Atmos. Chem., 11, 69-87.
10. 2, Tellus, Ser. B, 47, 35-52.
11. Gelhar, L. W. (1993), Stochastic Subsurface Hydrology, Prentice-Hall, Old Tappan, N. J.
12. Gill, P. E., W. Murray, and M. H. Wright (1986), Practical Optimization, Academic, San Diego, Calif.
13. 2 sources and sinks using atmospheric transport models, Nature, 415, 626-630, doi:10.1038/415626a.
14. Gutjahr, A., et al. (1994), Joint conditional simulations and the spectral approach for flow modeling, Stochastic Hydrol. Hydraul., 8, 79-108.
15. Hartley, D., and R. Prinn (1993), Feasibility of determining surface emissions of trace gases using an inverse method in a three-dimensional chemical transport model, J. Geophys. Res., 98(D3), 5183-5197.
16. Heimann, M. (1996), The Global Atmospheric Tracer Model TM2, Tech. Rep. 10, 52 pp., Dtsch. Klimarechenzent., Hamburg, Germany.
17. Hein, R., P. J. Crutzen, and M. Heimann (1997), An inverse modeling approach to investigate the global atmospheric methane cycle, Global Biogeochem. Cycles, 11(1), 43-76.
18. Hoeksema, R. J., and P. K. Kitanidis (1984), An application of the geostatistical approach to the inverse problem in two-dimensional groundwater modeling, Water Resour. Res., 20(7), 1003-1020.
19. Houghton, J. T., et al. (Ed.) (2001), Climate Change 2001: The Scientific Basis, Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge Univ. Press, New York.
20. Houweling, S., T. Kaminski, F. Dentener, J. Lelieveld, and M. Heimann (1999), Inverse modeling of methane sources and sinks using the adjoint of a global transport model, J Geophys. Res., 104(D21), 26,137-26,160.
21. Kaminski, T., M. Heimann, and R. Giering (1999a), A coarse grid three-dimensional global inverse model of the atmospheric transport: 1. Adjoint model and Jacobian matrix, J. Geophys. Res., 104(D15), 18,535-18,554.
22. 2 in the 1980s, J. Geophys. Res., 104(D15), 18,555-18,582.
23. Kaminski, T., P. J. Rayner, M. Heimann, and I. G. Enting (2001), On aggregation errors in atmospheric transport inversions, J Geophys. Res., 106(D5), 4703-4716.
24. Kitanidis, P. K. (1986), Parameter uncertainty in estimation of spatial functions: Bayesian analysis, Water Resour. Res., 22(4), 499-507.
25. Kitanidis, P. K. (1993), Generalized covariance functions in estimation, Math. Geol., 25(5), 525-540.
26. Kitanidis, P. K. (1995), Quasi-linear geostatistical theory for inversing, Water Resour. Res., 31(10), 2411-2519.
27. Kitanidis, P. K. (1997a), Introduction to Geostatistics: Applications in Hydrogeology, Cambridge Univ. Press, New York.
28. Kitanidis, P. K. (1997b), A variance-ratio test for supporting a variable mean in kriging, Math. Geol., 29(3), 335-348.
29. Kitanidis, P. K., and K.-F. Shen (1996), Geostatistical interpolation of chemical concentration, Adv. Water Resour., 19(6), 369-378.
30. Kitanidis, P. K., and E. G. Vomvoris (1983), A geostatistical approach to inverse modeling in groundwater modeling and one-dimensional simulations, Water Resour. Res., 19(3), 677-690.
31. 2 inversions, Global Biogeochem. Cycles, 16(4), 1053, doi:10.1029/2001GB001593.
32. Matheron, G. (1963), Principles of geostatistics, Econ. Geol., 58, 1246-1266.
33. Matheron, G. (1971), The theory of regionalized variables and its applications, Cah. du Cent. de Morphol. Math. 5, 211 pp., Paris Sch. of Mines, Fontainebleau, France.
34. Matheron, G. (1973), The intrinsic random functions and their applications, Adv. Appl. Probab., 5, 439-468.
35. 2, climate and land use effects with four process-based ecosystem models, Global Biogeochem. Cycles, 15(1), 183-206.
36. Michalak, A. M., and P. K. Kitanidis (2002), Application of Bayesian inference methods to inverse modeling for contaminant source identification at Gloucester Landfill, Canada, in Computational Methods in Water Resources XIV, vol. 2, edited by S. M. Hassanizadeh et al., pp. 1259-1266, Elsevier Sci., New York.
37. Michalak, A. M., and P. K. Kitanidis (2003), A method for enforcing parameter nonnegativity in Bayesian inverse problems with an application to contaminant source identification, Water Resour. Res., 39(2), 1033, doi:10.1029/2002WR001480.
38. Michalak, A.- M., and P. K. Kitanidis (2004a), Application of geostatistical inverse modeling to contaminant source identification at Dover AFB, Delaware, J. Hydraul. Res., 42(extra issue), 9-18.
39. Michalak, A. M., and P. K. Kitanidis (2004b), Estimation of historical groundwater contaminant distribution using the adjoint state method applied to geostatistical inverse modeling, Water Resour. Res., 40, doi:10.1029/2004WR003214, in press.
40. Mulquiney, J. E., and J. P. Norton (1998), A new inverse method for trace gas estimation: 1. State-space model identification and constraints, J. Geophys. Res., 103(D1), 1417-1427.
41. 2 data, J. Geophys. Res., 107(D19 ), 4385, doi:10.1029/2001JD000857.
42. Plumb, R. A., and X. Zheng (1996), Source determination from trace gas observations: An orthogonal function approach and results for long-lived gases with surface sources, J. Geophys. Res., 101(D13), 18,569-18,585.
43. Randerson, J. T., M. V Thompson, T. J. Conway, I. Y. Fung, and C. B. Field (1997), The contribution of terrestrial sources and sinks to trends in the seasonal cycle of atmospheric carbon dioxide, Global Biogeochem. Cycles, 11(4), 535-560.
44. 2 observations, Tellus, Ser. B, 51, 213-232.
45. Rea, J., and R. Knight (1998), Geostatistical analysis of ground-penetrating radar data: A means of describing spatial variation in the subsurface, Water Resour. Res., 34(3), 329-339.
46. 2 flux history 1982-2001 inferred from atmospheric data using a global inversion of atmospheric transport, Atmos. Chem. Phys., 3, 1919-1964.
47. Schweppe, F. C. (1973), Uncertain Dynamic Systems, Prentice-Hall, Old Tappan, N. J.
48. Snodgrass, M. F., and P. K. Kitanidis (1997), A geostatistical approach to contaminant source identification, Water Resour. Res., 33(4),537-546.
49. 2, and seasonal biological and temperature effects, Deep Sea Res., Part II, 49(9-10), 1601-1622.
50. 2 budget, Science, 247, 1431-1438.
51. Tarantola, A. (1987), Inverse Problem Theory Methods for Data Fitting and Model Parameter Estimation, Elsevier Sci., New York.
52. Wofsy, S. C., and R. C. Harriss (2002), The North American Carbon Program (NACP): A report of the NACP Committee of the U.S. Carbon Cycle Science Steering Group, 56 pp., U.S. Global Change Res. Program, Washington, D. C.
53. Yeh, T.-C. J., and J. Zhang (1996), A geostatistical inverse method for variably saturated flow in the vadose zone, Water Resour. Res., 32(9), 2757-2766.
54. Zimmerman, D. A., et al. (1998), A comparison of seven geostatistically based inverse approaches to estimate transmissivities for modeling advective transport by groundwater flow, Water Resour. Res., 34(6), 1371-1413.