A Bayesian hierarchical model for heterogeneous RCM-GCM multimodel ensembles

Journal of Climate

Volumn 28, Issue 15, 2015, Pages 6249-6266

  Kerkhoff, Christian ^a   Künsch, Hans R ^a   Schär, Christoph ^b  

^a ETH ZURICH   (Switzerland)

^b Land Climate Dynamics Group   (Switzerland)

Author keywords

Bayesian methods; Bias; Climate models; Ensembles; Regional models; Statistics

Indexed keywords

BAYESIAN NETWORKS; CLIMATE CHANGE; HIERARCHICAL SYSTEMS; STATISTICS;

BAYESIAN HIERARCHICAL MODEL; BAYESIAN METHODS; BIAS; ENSEMBLES; MULTI-DECADAL TIME SCALE; PROBABILISTIC PROJECTIONS; REGIONAL CLIMATE MODELS; REGIONAL MODEL;

CLIMATE MODELS;

AIR TEMPERATURE; BAYESIAN ANALYSIS; CLIMATE MODELING; ENSEMBLE FORECASTING; GLOBAL CLIMATE; HIERARCHICAL SYSTEM; REGIONAL CLIMATE;

EUROPE;

EID: 84942916123     PISSN: 08948755     EISSN: None     Source Type: Journal    
DOI: 10.1175/JCLI-D-14-00606.1     Document Type: Article

References (60)

1. Annan, J. D., and J. C. Hargreaves, 2010: Reliability of the CMIP3 ensemble. Geophys. Res. Lett., 37, L02703, doi:10.1029/2009GL041994.
2. Bellprat, O., S. Kotlarski, D. Lüthi, and C. Schär, 2013: Physical constraints for temperature biases in climate models. Geophys. Res. Lett., 40, 4042-4047, doi:10.1002/grl.50737.
3. Boberg, F., and J. H. Christensen, 2012: Overestimation of Mediterranean summer temperature projections due to model deficiencies. Nat. Climate Change, 2, 433-436, doi:10.1038/nclimate1454.
4. Buser, C. M., H. R. Künsch, D. Lüthi, M. Wild, and C. Schär, 2009: Bayesian multi-model projection of climate: Bias assumptions and interannual variability. Climate Dyn., 33, 849-868, doi:10.1007/s00382-009-0588-6.
5. Buser, C. M., H. R. Künsch, and C. Schär, 2010a: Bayesian multi-model projections of climate: Generalization and application to ENSEMBLES results. Climate Res., 44, 227-241, doi:10.3354/cr00895.
6. Buser, C. M., H. R. Künsch, and A. Weber, 2010b: Biases and uncertainty in climate projections. Scand. J. Stat., 37, 179-199, doi:10.1111/j.1467-9469.2009.00686.x.
7. Chandler, R. E., 2013: Exploiting strength, discounting weakness: Combining information from multiple climate simulators. Philos. Trans. Roy. Soc. London, 371A, 20120388, doi:10.1098/rsta.2012.0388.
8. Christensen, J. H., and O. B. Christensen, 2007: A summary of the PRUDENCE model projections of changes in European climate by the end of this century. Climatic Change, 81, 7-30, doi:10.1007/s10584-006-9210-7.
9. Christensen, J. H., and F. Boberg, 2012: Temperature dependent climate projection deficiencies in CMIP5 models. Geophys. Res. Lett., 39, L24705, doi:10.1029/2012GL053650.
10. Déqué, M., and S. Somot, 2010: Weighted frequency distributions express modelling uncertainties in the ENSEMBLES regional climate experiments. Climate Res., 44, 195-209, doi:10.3354/cr00866.
11. Deser, C., R. Knutti, S. Solomon, and A. S. Phillips, 2012: Communication of the role of natural variability in future North American climate. Nat. Climate Change, 2, 775-779, doi:10.1038/nclimate1562.
12. Fischer, A. M., A. P. Weigel, C. M. Buser, R. Knutti, H. R. Künsch, M. A. Liniger, C. Schär, and C. Appenzeller, 2012: Climate change projections for Switzerland based on a Bayesian multimodel approach. Int. J. Climatol., 32, 2348-2371, doi:10.1002/joc.3396.
13. Fischer, E. M., J. Rajczak, and C. Schär, 2012: Changes in European summer temperature variability revisited. Geophys. Res. Lett., 39, L19702, doi:10.1029/2012GL052730.
14. Furrer, R., S. R. Sain, D. Nychka, and G. A. Meehl, 2007: Multivariate Bayesian analysis of atmosphere-ocean general circulation models. Environ. Ecol. Stat., 14, 249-266, doi:10.1007/s10651-007-0018-z.
15. Furrer, R., S. Geinitz, and S. R. Sain, 2012: Assessing variance components of general circulation model output fields. Environmetrics, 23, 440-450, doi:10.1002/env.2139.
16. Geinitz, S., R. Furrer, and S. R. Sain, 2015: Bayesian multilevel analysis of variance for relative comparison across sources of global climate model variability. Int. J. Climatol., 35, 433-443, doi:10.1002/joc.3991.
17. Gelman, A., J. B. Carlin, H. S. Stern, D. B. Dunson, A. Vehtari, and D. B. Rubin, 2013: Bayesian Data Analysis. 3rd ed.CRC Press, 675 pp.
18. Gilks, W. R., S. Richardson, and D. J. Spiegelhalter, 1996: Markov Chain Monte Carlo in Practice. Chapman and Hall, 512 pp.
19. Giorgi, F., and L. O. Mearns, 2002: Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the "reliability ensemble averaging" (REA) method. J. Climate, 15, 1141-1158, doi:10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2.
20. Giorgi, F., C. Jones, and G. R. Asrar, 2009: Addressing climate information needs at the regional level: The CORDEX framework. WMO Bull., 58, 175-183.
21. Greene, A. M., L. Goddard, and U. Lall, 2006: Probabilistic multimodel regional temperature change projections. J. Climate, 19, 4326-4343, doi:10.1175/JCLI3864.1.
22. Grimit, E. P., T. Gneiting, V. J. Berrocal, and N. A. Johnson, 2006: The continuous ranked probability score for circular variables and its application to mesoscale forecast ensemble verification. Quart. J. Roy. Meteor. Soc., 132, 2925-2942, doi:10.1256/qj.05.235.
23. Hastie, T., R. Tibshirani, and J. Friedman, 2009: The Elements of Statistical Learning-Data Mining, Inference and Prediction. 2nd ed. Springer-Verlag, 745 pp.
24. Hawkins, E., and R. Sutton, 2009: The potential to narrow uncertainty in regional climate predictions. Bull. Amer. Meteor. Soc., 90, 1095-1107, doi:10.1175/2009BAMS2607.1.
25. Haylock, M. R., N. Hofstra, A. M. G. Klein Tank, E. J. Klok, P. D. Jones, and M. New, 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation for 1950-2006. J. Geophys. Res., 113, D20119, doi:10.1029/2008JD010201.
26. Heaton, M., T. Greasby, and S. R. Sain, 2013: Modeling uncertainty in climate using ensembles of regional and global climate models and multiple observation-based data sets. SIAM/ASA J. Uncertainty Quantif., 1 (1), 535-559, doi:10.1137/12088505X.
27. Hewitt, C. D., and D. J. Griggs, 2004: Ensembles-based predictions of climate changes and their impacts. Eos, Trans. Amer. Geophys. Union, 85, 566, doi:10.1029/2004EO520005.
28. Ho, C. K., D. B. Stephenson, M. Collins, C. A. T. Ferro, and S. J. Brown, 2012: Calibration strategies: A source of additional uncertainty in climate change projections. Bull. Amer. Meteor. Soc., 93, 21-26, doi:10.1175/2011BAMS3110.1.
29. IPCC, 2013: Climate Change 2013: The Physical Science Basis. Cambridge University Press, 1535 pp., doi:10.1017/CBO9781107415324.
30. Jun, M., R. Knutti, and D. W. Nychka, 2008: Spatial analysis to quantify numerical model bias and dependence. J. Amer. Stat. Assoc., 103, 934-947, doi:10.1198/016214507000001265.
31. Kang, E. L., N. Cressie, and S. R. Sain, 2012: Combining outputs from the North American Regional Climate Change Assessment Program by using a Bayesian hierarchical model. J. Roy. Stat. Soc., 61C, 291-313, doi:10.1111/j.1467-9876.2011.01010.x.
32. Kaufman, C. G., and S. R. Sain, 2010: Bayesian functional ANOVAmodeling using Gaussian process prior distributions. Bayesian Anal., 5, 123-149, doi:10.1214/10-BA505.
33. Kerkhoff, C., H. R. Künsch, and C. Schär, 2014: Assessment of bias assumptions for climate models. J. Climate, 27, 6799-6818, doi:10.1175/JCLI-D-13-00716.1.
34. Knutti, R., R. Furrer, C. Tebaldi, J. Cermak, and G. A. Meehl, 2010: Challenges in combining projections from multiple climate models. J. Climate, 23, 2739-2758, doi:10.1175/2009JCLI3361.1.
35. Laprise, R., 2014: Comment on "The added value to global model projections of climate change by dynamical downscaling: A case study over the continental U.S. using the GISS-ModelE2 and WRF models" by Racherla et al. J. Geophys. Res. Atmos., 119, 3877-3881, doi:10.1002/2013JD019945.
36. Lenderink, G., 2010: Exploring metrics of extreme daily precipitation in a large ensemble of regional climate model simulations. Climate Res., 44, 151-166, doi:10.3354/cr00946.
37. Maraun, D., 2012: Nonstationarities of regional climate model biases in European seasonal mean temperature and precipitation sums. Geophys. Res. Lett., 39, L06706, doi:10.1029/2012GL051210.
38. Masson, D., and R. Knutti, 2011: Climate model genealogy. Geophys. Res. Lett., 38, L08703, doi:10.1029/2011GL046864.
39. Matheson, J. E., and R. L. Winkler, 1976: Scoring rules for continuous probability distributions. Manage. Sci., 22, 1087-1096, doi:10.1287/mnsc.22.10.1087.
40. Mearns, L. O., W. J. Gutowski, R. Jones, L.-Y. Leung, S. McGinnis, A. M. B. Nunes, and Y. Qian, 2009: A regional climate change assessment program for North America. Eos, Trans. Amer. Geophys. Union, 90, 311, doi:10.1029/2009EO360002.
41. Mueller, B., and S. I. Seneviratne, 2012: Hot days induced by precipitation deficits at the global scale. Proc. Natl. Acad. Sci. USA, 109, 12 398-12 403, doi:10.1073/pnas.1204330109.
42. Nakicenovic, N., and R. Swart, Eds., 2000: Special Report on Emission Scenarios. Cambridge University Press, 570 pp.
43. Nychka, D., and C. Tebaldi, 2003: Comments on "Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the 'reliability ensemble averaging' (REA) method." J. Climate, 16, 883-884, doi:10.1175/1520-0442(2003)016<0883:COCOAU>2.0.CO;2.
44. Piani, C., J. O. Haerter, and E. Coppola, 2010: Statistical bias correction for daily precipitation in regional climate models over Europe. Theor. Appl. Climatol., 99, 187-192, doi:10.1007/s00704-009-0134-9.
45. Rougier, J., M. Goldstein, and L. House, 2013: Second-order exchangeability analysis for multimodel ensembles. J. Amer. Stat. Assoc., 108, 852-863, doi:10.1080/01621459.2013.802963.
46. Sain, S. R., R. Furrer, and N. Cressie, 2011: A spatial analysis of multivariate output from regional climate models. Ann. Appl. Stat., 5, 150-175, doi:10.1214/10-AOAS369.
47. Salazar, E., B. Sansó, A. O. Finley, D. Hammerling, I. Steinsland, X. Wang, and P. Delamater, 2011: Comparing and blending regional climate model predictions for the American Southwest. J. Agric. Biol. Environ. Stat., 16, 586-605, doi:10.1007/s13253-011-0074-6.
48. Sanderson, B. M., and R. Knutti, 2012: On the interpretation of constrained climate model ensembles. Geophys. Res. Lett., 39, L16708, doi:10.1029/2012GL052665.
49. Schär, C., P. L. Vidale, D. Lüthi, C. Frei, C. Häberli, M. A. Liniger, and C. Appenzeller, 2004: The role of increasing temperature variability for European summer heat waves. Nature, 427, 332-336, doi:10.1038/nature02300.
50. Scinocca, J. F., D. B. Stephenson, T. C. Bailey, and J. Austin, 2010: Estimates of past and future ozone trends from multimodel simulations using a flexible smoothing spline methodology. J. Geophys. Res., 115, D00M12, doi:10.1029/2009JD013622.
51. Seneviratne, S. I., D. Lüthi, M. Litschi, and C. Schär, 2006: Land-atmosphere coupling and climate change in Europe. Nature, 443, 205-209, doi:10.1038/nature05095.
52. Smith, R. L., C. Tebaldi, D. Nychka, and L. O. Mearns, 2009: Bayesian modeling of uncertainty in ensembles of climate models. J. Amer. Stat. Assoc., 104, 97-116, doi:10.1198/jasa.2009.0007.
53. Stephenson, D. B., M. Collins, J. C. Rougier, and R. E. Chandler, 2012: Statistical problems in the probabilistic prediction of climate change. Environmetrics, 23, 364-372, doi:10.1002/env.2153.
54. Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485-498, doi:10.1175/BAMS-D-11-00094.1.
55. Tebaldi, C., and R. Knutti, 2007: The use of the multi-model ensemble in probabilistic climate projections. Philos. Trans. Roy. Soc. London, 365A, 2053-2075, doi:10.1098/rsta.2007.2076.
56. Tebaldi, C., and B. Sansó, 2009: Joint projections of temperature and precipitation change from multiple climate models: A hierarchical Bayesian approach. J. Roy. Stat. Soc., 172A, 83-106, doi:10.1111/j.1467-985X.2008.00545.x.
57. Tebaldi, C., R. L. Smith, D. Nychka, and L. O. Mearns, 2005: Quantifying uncertainty in projections of regional climate change: A Bayesian approach to the analysis of multimodel ensembles. J. Climate, 18, 1524-1540, doi:10.1175/JCLI3363.1.
58. van der Linden, P., and J. F. B. Mitchell, 2009: ENSEMBLES: Climate change and its impacts: Summary of research and results from the ENSEMBLES project. Met Office Hadley Centre Tech. Rep., 160 pp.
59. Vidale, P. L., D. Lüthi, R. Wegmann, and C. Schär, 2007: European summer climate variability in a heterogeneous multi-model ensemble. Climatic Change, 81, 209-232, doi:10.1007/s10584-006-9218-z.
60. Weigel, A. P., R. Knutti, M. A. Liniger, and C. Appenzeller, 2010: Risks of model weighting in multimodel climate projections. J. Climate, 23, 4175-4191, doi:10.1175/2010JCLI3594.1.