Multidataset study of optimal parameter and uncertainty estimation of a land surface model with Bayesian stochastic inversion and multicriteria method

Journal of Applied Meteorology

Volumn 43, Issue 10, 2004, Pages 1477-1497

  Xia, Youlong ^a   Sen, Mrinal K ^a   Jackson, Charles S ^a   Stoffa, Paul L ^a  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION; HEAT FLUX; LANDFORMS; MATHEMATICAL MODELS; METEOROLOGY; PARAMETER ESTIMATION; SOILS; VEGETATION;

BAYESIAN STOCHASTIC INVERSION (BSI); CHAMELON SURFACE MODEL (CHASM); OPTIMAL PARAMETERS;

RANDOM PROCESSES;

BAYESIAN ANALYSIS; BOUNDARY LAYER; HEAT FLUX; LAND SURFACE; MULTICRITERIA ANALYSIS; STOCHASTICITY;

EID: 10244222280     PISSN: 08948763     EISSN: None     Source Type: Journal    
DOI: 10.1175/JAM2145.1     Document Type: Article

References (59)

1. Alapaty, K., S. Raman, and D. S. Niyogi, 1997: Uncertainty in specification of surface characteristics: A study of prediction errors in the boundary layer. Bound.-Layer Meteor., 82, 473-500.
2. Bastidas, L. A., H. V. Gupta, S. Sorooshian, W. J. Shuttleworth, and Z. L. Yang, 1996: The land surface-atmosphere interaction: A review based on observational and global modeling perspectives. J. Geophys. Res. 101, 7209-7225.
3. Bastidas, L. A., H. V. Gupta, S. Sorooshian, W. J. Shuttleworth, and Z. L. Yang, 1999: Sensitivity analysis of a land surface scheme using multi-criteria methods. J. Geophys. Res., 104, 19 481-19 490.
4. Bates, B. C., and E. P. Campbell, 2001: A Markov chain Monte Carlo scheme for parameter estimation and inference in conceptual rainfall-runoff modeling. Water Resour. Res., 37, 937-947.
5. Beljaars, A. C. M., and F. Bosveld, 1997: Cabauw data for the validation of land surface parameterization schemes. J. Climate, 10, 172-1193.
6. Beringer, J., S. McIlwaine, A. H. Lynch, F S. Chapin III, and G. B. Bonan, 2002: The use of a reduced form model to assess the sensitivity of a land surface model to biotic surface parameters. Climate Dyn. 19, 455-466.
7. Bonan, G. B., D. Pollard, and S. L. Thompson, 1993: Influence of subgrid-scale heterogeneity in leaf area index, stomatal resistance, and soil moisture on grid-scale land-atmosphere interactions. J. Climate 6, 1882-1897.
8. Bowling, L. C., and Coauthors, 2003: Simulation of high latitude hydrological processes in the Torne-Kalix basin: PILPS Phase 2(e) 1. Experiment description and summary intercomparisons. Global Planet. Change, 38, 1-35.
9. Campbell, E. P., D. R. Fox, and B. C. Bates, 1999: A Bayesian approach to parameter estimation and pooling in nonlinear flood event models. Water Resour. Res., 35, 211-220.
10. Chen, T. H., and Coauthors, 1997: Cabauw experimental results from the Project for Intercomparison of Land-Surface Parameterization Schemes. J. Climate, 10, 1194-1215.
11. Collins, D. C., and R. Avissar, 1994: An evaluation with the Fourier amplitude sensitivity test (FAST) of which land-surface parameters are of greatest importance in atmospheric modeling. J. Climate, 7 681-703.
12. Crossley, J. F., J. Polcher, R M. Cox, N. Gedney, and S. Planton, 2000: Uncertainties linked to land-surface processes in climate change simulations. Climate Dyn., 16, 949-961.
13. Desborough, C. E., 1999: Surface energy balance complexity in GCM land surface models. Climate Dyn., 15, 389-403.
14. Desborough, C. E., A. J. Pitman, and B. McAvaney, 2001: Surface energy balance complexity in GCM land surface models. Part II: Coupled simulations. Climate Dyn., 17, 615-626.
15. Duan, Q., V. K. Gupta, and S. Sorooshian, 1992: Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resour. Res., 28, 1015-1031.
16. Duan, Q., S. Sorooshian, and V. K. Gupta, 1994: Optimal use of the SCEUA global optimization method for calibrating watershed models. J. Hydrol., 158, 265-284.
17. Franks, S. W., and K. J. Beven, 1997: Bayesian estimation of uncertainty in land surface-atmosphere flux predictions. J. Geophys. Res., 102, 23 991-23 999.
18. Gao, X., S. Sorooshian, and H. V. Gupta, 1996: Sensitivity analysis of the Biosphere-Atmosphere Transfer Scheme. J. Geophys. Res., 101 7279-7289.
19. Gelman, A., J. B. Carlin, H. S. Stern, and D. B. Rubin, 2003: Bayesian Data Analysis. 2d ed. Chapman and Hall, 696 pp.
20. Gupta, H. V., S. Sorooshian, and P. O. Yapo, 1998: Toward improved calibration of hydrologic models: Multiple and non-commensurable measures of information. Water Resour. Res., 34, 751-761.
21. Gupta, H. V., L. A. Bastidas, S. Sorooshian, W. J. Shuttleworth, and Z.-L. Yang, 1999: Parameter estimation of a land surface scheme using multicriteria methods. J. Geophys. Res., 104, 19 491-19 503.
22. Hastings, W. K., 1970: Monte Carlo sampling method using Markov chains and their applications. Biometrika, 57, 97-109.
23. Henderson-Sellers, A., 1993: A factorial assessment of the sensitivity of the BATS land-surface parameterization scheme. J. Climate, 6 227-247.
24. Henderson-Sellers, A., 1996: Soil moisture simulation: Achievements of the RICE and PILPS intercomparison workshop and future directions. Global Planet. Change, 13, 99-115.
25. Henderson-Sellers, A., K. McGuffie, and A. Pitman, 1996: The Project for Intercomparison of Land-surface Parameterization Schemes (PILPS): 1992-1995. Climate Dyn., 12, 849-859.
26. Houghton, J. T., L. G. Meria Filho, B. A. Callander, N. Harris, A. Kattenberg, and K. Maskell, Eds., 1996: Climate Change 1995: The Science of Climate Change. Contribution of Working Group I to the Second Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, 572 pp.
27. Jackson, C., Y. Xia, M. K. Sen, and P. Stoffa, 2003: Optimal parameter estimation and uncertainty analysis of a land surface model: A case study from Cabauw, Netherlands. J. Geophys. Res., 108, 4583, doi:10.1029/2002JD002991.
28. Jackson, C., M. Sen, and P. Stoffa, 2004: An efficient stochastic Bayesian approach to optimal parameter and uncertainty estimation for climate model predictions. J. Climate, 17, 2828-2841.
29. Jarvis, P. G., 1976: The interpretation of the variations in the leaf water potential and stomatal conductance found in canopies in the field. Philos. Trans. Roy. Soc. London, 273B, 593-610.
30. Koster, R. D., and M. J. Suarez, 1992: Modeling the land surface boundary in climate models as a composite of independent vegetation stands. J. Geophys. Res., 97, 2697-2715.
31. Kuczera, G., and E. Parent, 1998: Monte Carlo assessment of parameter uncertainty in conceptual catcbment models: The Metropolis algorithm. J. Hydrol., 211, 69-85.
32. Leplastrier, M., A. J. Pitman, H. V. Gupta, and Y. Xia, 2002: Exploring the relationship between complexity and performance in a land surface model using the multicriteria method. J. Geophys. Res., 107, 4443, doi:10.1029/2001JD000931.
33. Manabe, S., 1969: Climate and the ocean circulation. I: The atmospheric circulation and the hydrology of the earth's surface. Mon. Wea. Rev. 97, 739-805.
34. Margulis, S. A., and D. Entekhabi, 2001: Feedback between the landsurface energy balance and atmospheric boundary layer diagnosed through a model and its adjoint. J. Hydrometeor., 2, 599-619.
35. McWilliam, A. L. C., O. M. R. Cabral, B. M. Gomes, J. L. Esteves, and J. M. Roberts, 1996: Forest and pature leaf-gas exchange in south-west Amazonia. Amazon Deforestation and Climate, J. H. C. Gash et al., Eds., John Wiley, 265-286.
36. Metropolis, N., A. Rosenbluth, M. Rosenbluth, A. Teller, and E. Teller, 1953: Equation of state calculations by fast computing machines. J. Chem. Phys., 21, 1087-1092.
37. Niyogi, D. S., S. Raman, and K. Alapaty, 1998: Comparison of four different stomatal resistance schemes using FIFE data. Part II: Analysis of terrestrial biospheric-atmospheric interactions. J. Appl. Meteor. 37, 1301-1320.
38. Niyogi, D. S., S. Raman, and K. Alapaty, 1999: Uncertainty in specification of surface characteristics, Part 2: Hierarchy of interaction explicit statistical analysis. Bound.-Layer Meteor., 91, 341-366.
39. Niyogi, D. S., Y. K. Xue, and S. Raman, 2002: Hydrological land surface response in a tropical regime and a midlatitudinal regime. J. Hydrometeor., 3, 39-56.
40. Pitman, A. J., 1994: Assessing the sensitivity of a land-surface scheme to the parameter values using a single column model. J. Climate, 7, 1856-1869.
41. Pitman, A. J., Y. Xia, M. Leplastrier, and A. Henderson-Sellers, 2003: The CHAmeleon Surface Model (CHASM): Description and use with the PILPS Phase 2e forcing data. Global Planet. Change, 38, 121-135.
42. Roberts, J. M., O. M. R. Cabral, and L. F. de Aguiar, 1990: Stomatal and boundary layer conductances measured in a terra firme rain forest. J. Appl. Ecol., 27, 336-353.
43. Roberts, J. M., O. M. R. Cabral, J. P. da Costa, A. C. L. McWilliam, and T. D. A. Sa, 1996: An overview of the leaf area index and physiological measurements during ABRACOS. Amazon Deforestation and Climate, J. H. C. Gash et al., Eds., John Wiley and Sons, 287-306.
44. Schlosser, C. A., and Coauthors, 2000: Simulations of a boreal grassland hydrology at Valdai, Russia: PILPS phase 2(d). Mon. Wea. Rev., 128, 301-321.
45. Sellers, P. J., and Coauthors, 1997: Modeling the exchanges of energy, water and carbon between continents and the atmosphere. Science, 275, 502-509.
46. Sen, M. K., and P. L. Stoffa, 1995: Global Optimization Methods in Geophysical Inversion. Elsevier, 281 pp.
47. Sen, M. K., and P. L. Stoffa, 1996: Bayesian inference, Gibbs' sampler and uncertainty estimation in geophysical inversion. Geophys. Prospect., 44, 313-350.
48. Sen, O. L., L. A. Bastidas, W. J. Shuttleworth, Z.-L. Yang, H. V. Gupta, and S. Sorooshian, 2001: Impact of field-calibrated vegetation parameters on GCM climate simulations. Quart. J. Roy. Meteor. Soc. 127, 1199-1223.
49. Shuttleworth, W. J., 1984: Observations of radiation exchange above and below Amazonian forest. Quart. J. Roy. Meteor. Soc., 110, 1163-1169.
50. Skaggs, T H., and D. A. Barry, 1996: Sensitivity methods for time-continuous, spatially discrete groundwater contaminant transport models. Water Resour. Res., 32, 2409-2420.
51. Slater, A. G., and Coauthors, 2001: The representation of snow in land surface schemes: Results from PILPS 2(d). J. Hydrometeor., 2 7-25.
52. Thiemann, M., M. Trosser, H. Gupta, and S. Sorooshian, 2001: Bayesian recursive parameter estimation for hydrologic models. Water Resour. Res., 37, 2521-2535.
53. Unland, H. E., R R. Houser, W. J. Shuttleworth, and Z. L. Yang, 1996: Surface flux measurement and modeling at a semi-arid Sonoran Desert site. Agric. For. Meteor., 82, 119-153.
54. Wang, Q. J., 1991: The genetic algorithm and its application to calibrating conceptual rainfall-runoff models. Water Resour. Res., 27, 2467-2471.
55. Wilson, M. F., A. Henderson-Sellers, R. E. Dickinson, and P. J. Kennedy, 1987: Sensitivity of the Biosphere-Atmosphere Transfer Scheme (BATS) to the inclusion of variable soil characteristics. J. Climate Appl. Meteor., 26, 341-362.
56. Wood, E. F., and Coauthors, 1998: The Project for Intercomparison of Land Surface Parameterization Schemes (PILPS) phase 2(c) Red-Arkansas River basin experiment. I. Experiment description and summary intercomparisons. Global Planet. Change, 19, 115-135.
57. Xia, Y., A. J. Pitman, H. V. Gupta, M. Leplastrier, A. Henderson-Sellers, and L. A. Bastidas, 2002: Calibrating a land surface model of varying complexity using multicriteria methods and the Cabauw dataset. J. Hydrometeor., 3, 181-194.
58. Yapo, P. O., H. V. Gupta, and S. Sorooshian, 1998: Multi-objective global optimization for hydrologic models. J. Hydrol., 204, 83-97.
59. Zhang, H., A. Henderson-Sellers, A. J. Pitman, J. L. McGregor, C. E. Desborough, and J. J. Katzfey, 2001: Limited-area model sensitivity to the complexity of representation of the land surface energy balance. J. Climate, 14, 3965-3986.