메뉴 건너뛰기




Volumn 61, Issue 2, 2012, Pages 291-313

Combining outputs from the North American Regional Climate Change Assessment Program by using a Bayesian hierarchical model

Author keywords

Downscaling; North American Regional Climate Change Assessment Program; Posterior distribution; Regional climate model; Spatial random effects model

Indexed keywords


EID: 84858157918     PISSN: 00359254     EISSN: 14679876     Source Type: Journal    
DOI: 10.1111/j.1467-9876.2011.01010.x     Document Type: Article
Times cited : (29)

References (44)
  • 1
    • 39849083922 scopus 로고    scopus 로고
    • Bayesian hierarchical spatially correlated functional data analysis with application to colon carcinogenesis
    • Baladandayuthapani, V., Mallick, B. K., Hong, M. Y., Lupton, J. R., Turner, N. D. and Carroll, R. J. (2008) Bayesian hierarchical spatially correlated functional data analysis with application to colon carcinogenesis. Biometrics, 64, 64-73.
    • (2008) Biometrics , vol.64 , pp. 64-73
    • Baladandayuthapani, V.1    Mallick, B.2    Hong, M.3    Lupton, J.4    Turner, N.5    Carroll, R.6
  • 3
    • 47649103974 scopus 로고    scopus 로고
    • Gaussian predictive process models for large spatial data sets
    • Banerjee, S., Gelfand, A. E., Finley, A. O. and Sang, H. (2008) Gaussian predictive process models for large spatial data sets. J. R. Statist. Soc. B, 70, 825-848.
    • (2008) J. R. Statist. Soc. B , vol.70 , pp. 825-848
    • Banerjee, S.1    Gelfand, A.E.2    Finley, A.O.3    Sang, H.4
  • 4
    • 45249118445 scopus 로고    scopus 로고
    • Bayesian design and analysis for superensemble-based climate forecasting
    • Berliner, L. M. and Kim, Y. (2008) Bayesian design and analysis for superensemble-based climate forecasting. J. Clim., 21, 1891-1910.
    • (2008) J. Clim. , vol.21 , pp. 1891-1910
    • Berliner, L.1    Kim, Y.2
  • 5
    • 0034484835 scopus 로고    scopus 로고
    • Long-lead prediction of Pacific SSTs via Bayesian dynamic modeling
    • Berliner, L. M., Wikle, C. K. and Cressie, N. (2000) Long-lead prediction of Pacific SSTs via Bayesian dynamic modeling. J. Clim., 13, 3953-3968.
    • (2000) J. Clim. , vol.13 , pp. 3953-3968
    • Berliner, L.1    Wikle, C.2    Cressie, N.3
  • 6
    • 77953977961 scopus 로고    scopus 로고
    • Biases and uncertainty in climate projections
    • Buser, C. M., Künsch, H. R. and Weber, A. (2010) Biases and uncertainty in climate projections. Scand. J. Statist., 37, 179-199.
    • (2010) Scand. J. Statist. , vol.37 , pp. 179-199
    • Buser, C.1    Künsch, H.2    Weber, A.3
  • 7
    • 84860916023 scopus 로고    scopus 로고
    • Latent variable modeling for integrating output from multiple climate models
    • doi 10.1007/s11004-011-9321-1, to be published.
    • Christensen, W. F. and Sain, S. R. (2011) Latent variable modeling for integrating output from multiple climate models. Math. Geosci., doi 10.1007/s11004-011-9321-1, to be published.
    • (2011) Math. Geosci.
    • Christensen, W.1    Sain, S.2
  • 9
    • 37849041594 scopus 로고    scopus 로고
    • Fixed rank kriging for very large spatial data sets
    • Cressie, N. and Johannesson, G. (2008) Fixed rank kriging for very large spatial data sets. J. R. Statist. Soc. B, 70, 209-226.
    • (2008) J. R. Statist. Soc. B , vol.70 , pp. 209-226
    • Cressie, N.1    Johannesson, G.2
  • 10
    • 77956698575 scopus 로고    scopus 로고
    • High-resolution digital soil mapping: Kriging for very large datasets
    • (eds R. Viscarra-Rossel, A. B. McBratney and B. Minasny). Dordrecht: Springer.
    • Cressie, N. and Kang, E. L. (2010) High-resolution digital soil mapping: Kriging for very large datasets. In Proximal Soil Sensing (eds R. Viscarra-Rossel, A. B. McBratney and B. Minasny), pp. 49-63. Dordrecht: Springer.
    • (2010) Proximal Soil Sensing , pp. 49-63
    • Cressie, N.1    Kang, E.2
  • 11
    • 85052713100 scopus 로고
    • Bayesian meta-analysis
    • (ed. D. A. Berry). New York: Dekker.
    • DuMouchel, W. (1990) Bayesian meta-analysis. In Statistical Methods for Pharmacology (ed. D. A. Berry), pp. 509-529. New York: Dekker.
    • (1990) Statistical Methods for Pharmacology , pp. 509-529
    • DuMouchel, W.1
  • 12
    • 0034233118 scopus 로고    scopus 로고
    • Seasonal prediction over North America with a regional model nested in a global model
    • Fennessy, M. J. and Shukla, J. (2000) Seasonal prediction over North America with a regional model nested in a global model. J. Clim., 13, 2605-2627.
    • (2000) J. Clim. , vol.13 , pp. 2605-2627
    • Fennessy, M.1    Shukla, J.2
  • 13
    • 34249874205 scopus 로고    scopus 로고
    • Multivariate Bayesian analysis of atmosphere-ocean general circulation models
    • Furrer, R., Sain, S. R., Nychka, D. and Meehl, G. A. (2007) Multivariate Bayesian analysis of atmosphere-ocean general circulation models. Environ. Ecol. Statist., 14, 249-266.
    • (2007) Environ. Ecol. Statist. , vol.14 , pp. 249-266
    • Furrer, R.1    Sain, S.2    Nychka, D.3    Meehl, G.4
  • 16
    • 79958208557 scopus 로고    scopus 로고
    • Bayesian inference for the spatial random effects model
    • doi: 10.1198/jasa.2011.tm09680, to be published.
    • Kang, E. L. and Cressie, N. (2011) Bayesian inference for the spatial random effects model. J. Am. Statist. Ass., doi: 10.1198/jasa.2011.tm09680, to be published.
    • (2011) J. Am. Statist. Ass.
    • Kang, E.1    Cressie, N.2
  • 17
    • 77955119363 scopus 로고    scopus 로고
    • Using temporal variability to improve spatial mapping of satellite data
    • Kang, E. L., Cressie, N. and Shi, T. (2010) Using temporal variability to improve spatial mapping of satellite data. Can. J. Statist., 38, 271-289.
    • (2010) Can. J. Statist. , vol.38 , pp. 271-289
    • Kang, E.1    Cressie, N.2    Shi, T.3
  • 18
    • 77954524672 scopus 로고    scopus 로고
    • Bayesian functional ANOVA modeling using Gaussian process prior distributions
    • Kaufman, C. and Sain, S. R. (2010) Bayesian functional ANOVA modeling using Gaussian process prior distributions. Baysn Anal., 5, 123-150.
    • (2010) Baysn Anal. , vol.5 , pp. 123-150
    • Kaufman, C.1    Sain, S.2
  • 19
    • 0442293854 scopus 로고    scopus 로고
    • Prediction of spatial cumulative distribution functions using subsampling
    • Lahiri, S. N., Kaiser, M. S., Cressie, N. and Hsu, N.-J. (1999) Prediction of spatial cumulative distribution functions using subsampling. J. Am. Statist. Ass., 94, 86-97.
    • (1999) J. Am. Statist. Ass. , vol.94 , pp. 86-97
    • Lahiri, S.1    Kaiser, M.2    Cressie, N.3    Hsu, N.-J.4
  • 20
    • 70349947771 scopus 로고    scopus 로고
    • Spatial dynamic factor analysis
    • Lopes, H. F., Salazar, E. and Gamerman, D. (2008) Spatial dynamic factor analysis. Baysn Anal., 3, 759-792.
    • (2008) Baysn Anal. , vol.3 , pp. 759-792
    • Lopes, H.1    Salazar, E.2    Gamerman, D.3
  • 21
    • 84858161362 scopus 로고    scopus 로고
    • Prior distributions for covariance/precision matrices, part 1
    • Massam, H. (2009) Prior distributions for covariance/precision matrices, part 1. Int. Soc. Baysn Anal. Bull., 16, 8-11.
    • (2009) Int. Soc. Baysn Anal. Bull. , vol.16 , pp. 8-11
    • Massam, H.1
  • 22
    • 84858159638 scopus 로고    scopus 로고
    • Prior distributions for covariance/precision matrices, part 2
    • Massam, H. (2010) Prior distributions for covariance/precision matrices, part 2. Int. Soc. Baysn Anal. Bull., 17, 5-7.
    • (2010) Int. Soc. Baysn Anal. Bull. , vol.17 , pp. 5-7
    • Massam, H.1
  • 28
    • 77954426383 scopus 로고    scopus 로고
    • Combining climate model output via model correlations
    • Sain, S. R. and Furrer, R. (2010) Combining climate model output via model correlations. Stoch. Environ. Res. Risk Assessmnt, 24, 821-829.
    • (2010) Stoch. Environ. Res. Risk Assessmnt , vol.24 , pp. 821-829
    • Sain, S.1    Furrer, R.2
  • 29
    • 83555179381 scopus 로고    scopus 로고
    • Combining ensembles of regional climate model output via a multivariate Markov random field model
    • Sain, S. R., Furrer, R. and Cressie, N. (2011a) Combining ensembles of regional climate model output via a multivariate Markov random field model. Ann. Appl. Statist., 5, 150-175.
    • (2011) Ann. Appl. Statist. , vol.5 , pp. 150-175
    • Sain, S.1    Furrer, R.2    Cressie, N.3
  • 30
    • 80052595146 scopus 로고    scopus 로고
    • Functional ANOVA and regional climate experiments: a statistical analysis of dynamic downscaling
    • Sain, S. R., Nychka, D. and Mearns, L. (2011b) Functional ANOVA and regional climate experiments: a statistical analysis of dynamic downscaling. Environmetrics, 22, 700-711.
    • (2011) Environmetrics , vol.22 , pp. 700-711
    • Sain, S.1    Nychka, D.2    Mearns, L.3
  • 31
    • 77951977046 scopus 로고    scopus 로고
    • A comparison study of extreme precipitation from six different regional climate models via spatial hierarchical modeling
    • Schliep, E. M., Cooley, D., Sain, S. R. and Hoeting, J. A. (2010) A comparison study of extreme precipitation from six different regional climate models via spatial hierarchical modeling. Extremes, 13, 219-239.
    • (2010) Extremes , vol.13 , pp. 219-239
    • Schliep, E.1    Cooley, D.2    Sain, S.3    Hoeting, J.4
  • 32
    • 0035799690 scopus 로고    scopus 로고
    • What is ''dangerous'' climate change?
    • Schneider, S. H. (2001) What is ''dangerous'' climate change? Nature, 411, 17-19.
    • (2001) Nature , vol.411 , pp. 17-19
    • Schneider, S.1
  • 33
    • 35349012069 scopus 로고    scopus 로고
    • Global statistical analysis of MISR aerosol data: a massive data product from NASA's Terra satellite
    • Shi, T. and Cressie, N. (2007) Global statistical analysis of MISR aerosol data: a massive data product from NASA's Terra satellite. Environmetrics, 18, 665-680.
    • (2007) Environmetrics , vol.18 , pp. 665-680
    • Shi, T.1    Cressie, N.2
  • 34
    • 70350345571 scopus 로고    scopus 로고
    • Bayesian modeling of uncertainty in ensembles of climate models
    • Smith, R. L., Tebaldi, C., Nychka, D. and Mearns, L. O. (2009) Bayesian modeling of uncertainty in ensembles of climate models. J. Am. Statist. Ass., 104, 97-116.
    • (2009) J. Am. Statist. Ass. , vol.104 , pp. 97-116
    • Smith, R.1    Tebaldi, C.2    Nychka, D.3    Mearns, L.4
  • 36
    • 57849156930 scopus 로고    scopus 로고
    • Joint projections of temperature and precipitation change from multiple climate models: a hierarchical Bayesian approach
    • Tebaldi, C. and Sansó, B. (2009) Joint projections of temperature and precipitation change from multiple climate models: a hierarchical Bayesian approach. J. R. Statist. Soc. A, 172, 83-106.
    • (2009) J. R. Statist. Soc. A , vol.172 , pp. 83-106
    • Tebaldi, C.1    Sansó, B.2
  • 37
    • 14544287376 scopus 로고    scopus 로고
    • Quantifying uncertainty in projections of regional climate change: a Bayesian approach to the analysis of multimodel ensembles
    • Tebaldi, C., Smith, R. L., Nychka, D. and Mearns, L. O. (2005) Quantifying uncertainty in projections of regional climate change: a Bayesian approach to the analysis of multimodel ensembles. J. Clim., 18, 1524-1540.
    • (2005) J. Clim. , vol.18 , pp. 1524-1540
    • Tebaldi, C.1    Smith, R.2    Nychka, D.3    Mearns, L.4
  • 38
    • 0344668828 scopus 로고    scopus 로고
    • Communicating climate change uncertainty to policy-makers and the public
    • Webster, M. (2003) Communicating climate change uncertainty to policy-makers and the public. Clim. Change, 61, 1-9.
    • (2003) Clim. Change , vol.61 , pp. 1-9
    • Webster, M.1
  • 39
    • 0035919689 scopus 로고    scopus 로고
    • Interpretation of high projections for global mean warming
    • Wigley, T. M. L. and Raper, S. C. B. (2001) Interpretation of high projections for global mean warming. Science, 293, 451-454.
    • (2001) Science , vol.293 , pp. 451-454
    • Wigley, T.1    Raper, S.2
  • 40
    • 0000414912 scopus 로고    scopus 로고
    • A dimension-reduced approach to space-time Kalman filtering
    • Wikle, C. K. and Cressie, N. (1999) A dimension-reduced approach to space-time Kalman filtering. Biometrika, 86, 815-829.
    • (1999) Biometrika , vol.86 , pp. 815-829
    • Wikle, C.1    Cressie, N.2
  • 41
    • 34548479033 scopus 로고    scopus 로고
    • Assessment of dynamic downscaling of the continental U.S. regional climate using the Eta/SSiB regional climate model
    • Xue, Y., Vasic, R., Janjic, Z., Mesinger, F. and Mitchell, K. E. (2007) Assessment of dynamic downscaling of the continental U.S. regional climate using the Eta/SSiB regional climate model. J. Clim., 20, 4172-4193.
    • (2007) J. Clim. , vol.20 , pp. 4172-4193
    • Xue, Y.1    Vasic, R.2    Janjic, Z.3    Mesinger, F.4    Mitchell, K.5
  • 42
    • 21844496542 scopus 로고
    • Estimation of a covariance matrix using the reference prior
    • Yang, R. and Berger, J. O. (1994) Estimation of a covariance matrix using the reference prior. Ann. Statist., 22, 1195-1211.
    • (1994) Ann. Statist. , vol.22 , pp. 1195-1211
    • Yang, R.1    Berger, J.2
  • 43
    • 46749151367 scopus 로고    scopus 로고
    • Loss function approaches to predict a spatial quantile and its exceedance region
    • Zhang, J., Craigmile, P. F. and Cressie, N. (2008) Loss function approaches to predict a spatial quantile and its exceedance region. Technometrics, 50, 216-227.
    • (2008) Technometrics , vol.50 , pp. 216-227
    • Zhang, J.1    Craigmile, P.2    Cressie, N.3
  • 44
    • 33745929657 scopus 로고    scopus 로고
    • General design Bayesian generalized linear mixed models
    • Zhao, Y., Staudenmayer, J., Coull, B. A. and Wand, M. P. (2006) General design Bayesian generalized linear mixed models. Statist. Sci., 21, 35-51.
    • (2006) Statist. Sci. , vol.21 , pp. 35-51
    • Zhao, Y.1    Staudenmayer, J.2    Coull, B.3    Wand, M.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.