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Volumn 525, Issue , 2015, Pages 352-361

Multi-model ensemble analysis of runoff extremes for climate change impact assessments

Author keywords

Bayesian hierarchical; Bayesian model averaging; Climate change; Extreme events; Multi modeling

Indexed keywords

BAYESIAN NETWORKS; CLIMATE MODELS; RUNOFF; WIND;

EID: 84927640926     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2015.03.045     Document Type: Article
Times cited : (86)

References (57)
  • 1
    • 19944434306 scopus 로고    scopus 로고
    • The new GFDL global atmosphere and land model AM2-LM2: evaluation with prescribed SST simulations
    • Anderson J., et al. The new GFDL global atmosphere and land model AM2-LM2: evaluation with prescribed SST simulations. J. Climate 2004, 17(24):4641-4673.
    • (2004) J. Climate , vol.17 , Issue.24 , pp. 4641-4673
    • Anderson, J.1
  • 3
    • 77956636641 scopus 로고    scopus 로고
    • On the weighting of multimodel ensembles in seasonal and short-range weather forecasting
    • Casanova S., Ahrens B. On the weighting of multimodel ensembles in seasonal and short-range weather forecasting. Mon. Weather Rev. 2009, 137(11):3811-3822.
    • (2009) Mon. Weather Rev. , vol.137 , Issue.11 , pp. 3811-3822
    • Casanova, S.1    Ahrens, B.2
  • 4
    • 34248168039 scopus 로고    scopus 로고
    • A summary of the PRUDENCE model projections of changes in European climate by the end of this century
    • Christensen J.H., Christensen O.B. A summary of the PRUDENCE model projections of changes in European climate by the end of this century. Climatic Change 2007, 81:7-30.
    • (2007) Climatic Change , vol.81 , pp. 7-30
    • Christensen, J.H.1    Christensen, O.B.2
  • 6
    • 33744490657 scopus 로고    scopus 로고
    • The community climate system model version 3 (CCSM3)
    • Collins W.D., et al. The community climate system model version 3 (CCSM3). J. Climate 2006, 19(11):2122-2143.
    • (2006) J. Climate , vol.19 , Issue.11 , pp. 2122-2143
    • Collins, W.D.1
  • 7
    • 34548761070 scopus 로고    scopus 로고
    • Bayesian spatial modeling of extreme precipitation return levels
    • Cooley D., Nychka D., Naveau P. Bayesian spatial modeling of extreme precipitation return levels. J. Am. Stat. Assoc. 2007, 102(479):824-840.
    • (2007) J. Am. Stat. Assoc. , vol.102 , Issue.479 , pp. 824-840
    • Cooley, D.1    Nychka, D.2    Naveau, P.3
  • 8
    • 80055070051 scopus 로고    scopus 로고
    • Spatial hierarchical modeling of precipitation extremes from a regional climate model
    • Cooley D., Sain S.R. Spatial hierarchical modeling of precipitation extremes from a regional climate model. J. Agric. Biol. Environ. Stat. 2010, 15(3):381-402.
    • (2010) J. Agric. Biol. Environ. Stat. , vol.15 , Issue.3 , pp. 381-402
    • Cooley, D.1    Sain, S.R.2
  • 9
    • 84918841653 scopus 로고    scopus 로고
    • Toward a Reliable Prediction of Seasonal Forecast Uncertainty: Addressing Model and Initial Condition Uncertainty with Ensemble Data Assimilation and Sequential Bayesian Combination
    • DeChant C.M., Moradkhani H. Toward a Reliable Prediction of Seasonal Forecast Uncertainty: Addressing Model and Initial Condition Uncertainty with Ensemble Data Assimilation and Sequential Bayesian Combination. J. Hydrol. 2014, 519:2967-2977. 10.1016/j.jhydrol.2014.05.045.
    • (2014) J. Hydrol. , vol.519 , pp. 2967-2977
    • DeChant, C.M.1    Moradkhani, H.2
  • 10
    • 33847274843 scopus 로고    scopus 로고
    • Multi-model ensemble hydrologic prediction using Bayesian model averaging
    • Duan Q., Ajami N.K., Gao X., Sorooshian S. Multi-model ensemble hydrologic prediction using Bayesian model averaging. Adv. Water Resour. 2007, 30(5):1371-1386.
    • (2007) Adv. Water Resour. , vol.30 , Issue.5 , pp. 1371-1386
    • Duan, Q.1    Ajami, N.K.2    Gao, X.3    Sorooshian, S.4
  • 11
  • 12
    • 65649094446 scopus 로고    scopus 로고
    • Multi-model ensemble estimates of climate change impacts on UK seasonal precipitation extremes
    • Fowler H., Ekström M. Multi-model ensemble estimates of climate change impacts on UK seasonal precipitation extremes. Int. J. Climatol. 2009, 29(3):385-416.
    • (2009) Int. J. Climatol. , vol.29 , Issue.3 , pp. 385-416
    • Fowler, H.1    Ekström, M.2
  • 13
    • 36349001678 scopus 로고    scopus 로고
    • Estimating change in extreme European precipitation using a multimodel ensemble
    • Fowler H., Ekström M., Blenkinsop S., Smith A. Estimating change in extreme European precipitation using a multimodel ensemble. J. Geophys. Res. 2007, 112(D18):D18104.
    • (2007) J. Geophys. Res. , vol.112 , Issue.D18 , pp. D18104
    • Fowler, H.1    Ekström, M.2    Blenkinsop, S.3    Smith, A.4
  • 14
    • 33947237951 scopus 로고    scopus 로고
    • An intercomparison of statistical downscaling methods for Europe and European regions-assessing their performance with respect to extreme temperature and precipitation events
    • Goodess C., et al. An intercomparison of statistical downscaling methods for Europe and European regions-assessing their performance with respect to extreme temperature and precipitation events. Climatic Change 2007.
    • (2007) Climatic Change
    • Goodess, C.1
  • 15
    • 0034025893 scopus 로고    scopus 로고
    • The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments
    • Gordon C., et al. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Climate Dyn. 2000, 16(2):147-168.
    • (2000) Climate Dyn. , vol.16 , Issue.2 , pp. 147-168
    • Gordon, C.1
  • 16
    • 84881026147 scopus 로고    scopus 로고
    • Analysis of precipitation extremes with the assessment of regional climate models over the Willamette River Basin, USA
    • Halmstad A., Najafi M.R., Moradkhani H. Analysis of precipitation extremes with the assessment of regional climate models over the Willamette River Basin, USA. Hydrol. Processes 2012, 27:2579-2590. 10.1002/hyp.937.
    • (2012) Hydrol. Processes , vol.27 , pp. 2579-2590
    • Halmstad, A.1    Najafi, M.R.2    Moradkhani, H.3
  • 17
    • 84890175585 scopus 로고    scopus 로고
    • Evaluation of simple statistical downscaling methods for monthly regional climate model simulations with respect to the estimated changes in runoff in the Czech Republic
    • Hanel M., Mrkvičková M., Máca P., Vizina A., Pech P. Evaluation of simple statistical downscaling methods for monthly regional climate model simulations with respect to the estimated changes in runoff in the Czech Republic. Water Resour. Manage. 2013, 27(15):5261-5279.
    • (2013) Water Resour. Manage. , vol.27 , Issue.15 , pp. 5261-5279
    • Hanel, M.1    Mrkvičková, M.2    Máca, P.3    Vizina, A.4    Pech, P.5
  • 19
    • 84860687058 scopus 로고    scopus 로고
    • The coordinated regional downscaling experiment: CORDEX an international downscaling link to CMIP5
    • Jones C., Giorgi F., Asrar G. The coordinated regional downscaling experiment: CORDEX an international downscaling link to CMIP5. CLIVAR Exch. 2011, 16(2):34-40.
    • (2011) CLIVAR Exch. , vol.16 , Issue.2 , pp. 34-40
    • Jones, C.1    Giorgi, F.2    Asrar, G.3
  • 20
    • 84858157918 scopus 로고    scopus 로고
    • Combining outputs from the North American Regional Climate Change Assessment Program by using a Bayesian hierarchical model
    • Kang E.L., Cressie N., Sain S.R. Combining outputs from the North American Regional Climate Change Assessment Program by using a Bayesian hierarchical model. J. R. Stat. Soc.: Ser. C (Appl. Stat.) 2012.
    • (2012) J. R. Stat. Soc.: Ser. C (Appl. Stat.)
    • Kang, E.L.1    Cressie, N.2    Sain, S.R.3
  • 21
    • 0036539312 scopus 로고    scopus 로고
    • Climate predictions with multimodel ensembles
    • Kharin V.V., Zwiers F.W. Climate predictions with multimodel ensembles. J. Climate 2002, 15(7):793-799.
    • (2002) J. Climate , vol.15 , Issue.7 , pp. 793-799
    • Kharin, V.V.1    Zwiers, F.W.2
  • 22
    • 77954370030 scopus 로고    scopus 로고
    • Challenges in combining projections from multiple climate models
    • Knutti R., Furrer R., Tebaldi C., Cermak J., Meehl G.A. Challenges in combining projections from multiple climate models. J. Climate 2010, 23(10):2739-2758.
    • (2010) J. Climate , vol.23 , Issue.10 , pp. 2739-2758
    • Knutti, R.1    Furrer, R.2    Tebaldi, C.3    Cermak, J.4    Meehl, G.A.5
  • 25
    • 85027932033 scopus 로고    scopus 로고
    • Improved Bayesian multi-modeling: integration of copulas and Bayesian model averaging
    • Madadgar S., Moradkhani H. Improved Bayesian multi-modeling: integration of copulas and Bayesian model averaging. Water Resour. Res. 2014, 50:9586-9603. 10.1002/2014WR015965.
    • (2014) Water Resour. Res. , vol.50 , pp. 9586-9603
    • Madadgar, S.1    Moradkhani, H.2
  • 26
    • 84872647514 scopus 로고    scopus 로고
    • Future changes in intense precipitation over Canada assessed from multi-model NARCCAP ensemble simulations
    • Mailhot A., Beauregard I., Talbot G., Caya D., Biner S. Future changes in intense precipitation over Canada assessed from multi-model NARCCAP ensemble simulations. Int. J. Climatol. 2011.
    • (2011) Int. J. Climatol.
    • Mailhot, A.1    Beauregard, I.2    Talbot, G.3    Caya, D.4    Biner, S.5
  • 27
    • 0037113274 scopus 로고    scopus 로고
    • A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States
    • Maurer E., Wood A., Adam J., Lettenmaier D., Nijssen B. A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States. J. Climate 2002, 15(22):3237-3251.
    • (2002) J. Climate , vol.15 , Issue.22 , pp. 3237-3251
    • Maurer, E.1    Wood, A.2    Adam, J.3    Lettenmaier, D.4    Nijssen, B.5
  • 29
    • 84866986922 scopus 로고    scopus 로고
    • The North American regional climate change assessment program: overview of phase I results
    • Mearns L., et al. The North American regional climate change assessment program: overview of phase I results. Bull. Am. Meteorol. Soc. 2012, 93(9):1337-1362.
    • (2012) Bull. Am. Meteorol. Soc. , vol.93 , Issue.9 , pp. 1337-1362
    • Mearns, L.1
  • 30
    • 77951978217 scopus 로고    scopus 로고
    • A regional climate change assessment program for North America
    • Mearns L., et al. A regional climate change assessment program for North America. Eos Trans. AGU 2009, 90(36):311.
    • (2009) Eos Trans. AGU , vol.90 , Issue.36 , pp. 311
    • Mearns, L.1
  • 31
    • 35448939676 scopus 로고    scopus 로고
    • The WCRP CMIP3 multi-model dataset: a new era in climate change research
    • Meehl G., et al. The WCRP CMIP3 multi-model dataset: a new era in climate change research. Bull. Am. Meteorol. Soc. 2007, 88:1383-1394.
    • (2007) Bull. Am. Meteorol. Soc. , vol.88 , pp. 1383-1394
    • Meehl, G.1
  • 32
    • 0034104028 scopus 로고    scopus 로고
    • Pacific Northwest regional assessment: the impacts of climate variability and climate change on the water resources of the Columbia River Basin
    • Miles E.L., Snover A.K., Hamlet A.F., Callahan B., Fluharty D. Pacific Northwest regional assessment: the impacts of climate variability and climate change on the water resources of the Columbia River Basin. JAWRA J. Am. Water Resour. Assoc. 2000, 36(2):399-420.
    • (2000) JAWRA J. Am. Water Resour. Assoc. , vol.36 , Issue.2 , pp. 399-420
    • Miles, E.L.1    Snover, A.K.2    Hamlet, A.F.3    Callahan, B.4    Fluharty, D.5
  • 33
    • 84871364784 scopus 로고    scopus 로고
    • Evolution of ensemble data assimilation for uncertainty quantification using the particle filter-Markov chain Monte Carlo method
    • Moradkhani H., DeChant C.M., Sorooshian S. Evolution of ensemble data assimilation for uncertainty quantification using the particle filter-Markov chain Monte Carlo method. Water Resour. Res. 2012, 48:W12520. 10.1029/2012WR012144.
    • (2012) Water Resour. Res. , vol.48 , pp. W12520
    • Moradkhani, H.1    DeChant, C.M.2    Sorooshian, S.3
  • 34
    • 20844449766 scopus 로고    scopus 로고
    • Uncertainty assessment of hydrologic model states and parameters: sequential data assimilation using the particle filter
    • Moradkhani H., Hsu K.-L., Gupta H., Sorooshian S. Uncertainty assessment of hydrologic model states and parameters: sequential data assimilation using the particle filter. Water Resour. Res. 2005, 41(5):W05012.
    • (2005) Water Resour. Res. , vol.41 , Issue.5 , pp. W05012
    • Moradkhani, H.1    Hsu, K.-L.2    Gupta, H.3    Sorooshian, S.4
  • 36
    • 80051577111 scopus 로고    scopus 로고
    • Assessing the uncertainties of hydrologic model selection in climate change impact studies
    • Najafi M., Moradkhani H., Jung I. Assessing the uncertainties of hydrologic model selection in climate change impact studies. Hydrol. Processes 2011, 25(18):2814-2826.
    • (2011) Hydrol. Processes , vol.25 , Issue.18 , pp. 2814-2826
    • Najafi, M.1    Moradkhani, H.2    Jung, I.3
  • 37
    • 84861210595 scopus 로고    scopus 로고
    • Ensemble streamflow prediction: climate signal weighting methods vs. climate forecast system reanalysis
    • Najafi M., Moradkhani H., Piechota T. Ensemble streamflow prediction: climate signal weighting methods vs. climate forecast system reanalysis. J. Hydrol. 2012, 442-443:105-116.
    • (2012) J. Hydrol. , pp. 105-116
    • Najafi, M.1    Moradkhani, H.2    Piechota, T.3
  • 38
    • 84923858133 scopus 로고    scopus 로고
    • Attribution of Arctic temperature change to greenhouse gas and aerosol influences
    • Najafi M., Zwiers F.W., Gillett N.P. Attribution of Arctic temperature change to greenhouse gas and aerosol influences. Nature Climate Change 2015, 5:246-249.
    • (2015) Nature Climate Change , vol.5 , pp. 246-249
    • Najafi, M.1    Zwiers, F.W.2    Gillett, N.P.3
  • 39
    • 84885533219 scopus 로고    scopus 로고
    • Analysis of runoff extremes using spatial hierarchical Bayesian modeling
    • Najafi M.R., Moradkhani H. Analysis of runoff extremes using spatial hierarchical Bayesian modeling. Water Resour. Res. 2013, 49(10):6656-6670.
    • (2013) Water Resour. Res. , vol.49 , Issue.10 , pp. 6656-6670
    • Najafi, M.R.1    Moradkhani, H.2
  • 40
    • 84916908812 scopus 로고    scopus 로고
    • A hierarchical Bayesian approach for the analysis of climate change impact on runoff extremes
    • Najafi M.R., Moradkhani H. A hierarchical Bayesian approach for the analysis of climate change impact on runoff extremes. Hydrol. Processes 2014, 28:6292-6308. 10.1002/hyp.10113.
    • (2014) Hydrol. Processes , vol.28 , pp. 6292-6308
    • Najafi, M.R.1    Moradkhani, H.2
  • 41
    • 79961099571 scopus 로고    scopus 로고
    • Statistical downscaling of precipitation using machine learning with optimal predictor selection
    • Najafi M.R., Moradkhani H., Wherry S.A. Statistical downscaling of precipitation using machine learning with optimal predictor selection. J. Hydrol. Eng. 2011, 16(8):650-664.
    • (2011) J. Hydrol. Eng. , vol.16 , Issue.8 , pp. 650-664
    • Najafi, M.R.1    Moradkhani, H.2    Wherry, S.A.3
  • 42
    • 84858823339 scopus 로고    scopus 로고
    • Towards reduction of model uncertainty: integration of Bayesian model averaging and data assimilation
    • Parrish M.A., Moradkhani H., DeChant C.M. Towards reduction of model uncertainty: integration of Bayesian model averaging and data assimilation. Water Resour. Res. 2012, 48:W03519. 10.1029/2011WR011116.
    • (2012) Water Resour. Res. , vol.48 , pp. W03519
    • Parrish, M.A.1    Moradkhani, H.2    DeChant, C.M.3
  • 43
    • 20444497873 scopus 로고    scopus 로고
    • Using Bayesian model averaging to calibrate forecast ensembles
    • Raftery A.E., Gneiting T., Balabdaoui F., Polakowski M. Using Bayesian model averaging to calibrate forecast ensembles. Mon. Weather Rev. 2005, 133(5):1155-1174.
    • (2005) Mon. Weather Rev. , vol.133 , Issue.5 , pp. 1155-1174
    • Raftery, A.E.1    Gneiting, T.2    Balabdaoui, F.3    Polakowski, M.4
  • 44
    • 70349249491 scopus 로고    scopus 로고
    • Climate projections: past performance no guarantee of future skill?
    • Reifen C., Toumi R. Climate projections: past performance no guarantee of future skill?. Geophys. Res. Lett. 2009, 36(13).
    • (2009) Geophys. Res. Lett. , vol.36 , Issue.13
    • Reifen, C.1    Toumi, R.2
  • 45
    • 0000627958 scopus 로고
    • The Box-Cox transformation technique: a review
    • Sakia R. The Box-Cox transformation technique: a review. The statistician 1992, 169-178.
    • (1992) The statistician , pp. 169-178
    • Sakia, R.1
  • 46
    • 67651231033 scopus 로고    scopus 로고
    • Hierarchical modeling for extreme values observed over space and time
    • Sang H., Gelfand A.E. Hierarchical modeling for extreme values observed over space and time. Environ. Ecol. Stat. 2009, 16(3):407-426.
    • (2009) Environ. Ecol. Stat. , vol.16 , Issue.3 , pp. 407-426
    • Sang, H.1    Gelfand, A.E.2
  • 47
    • 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., Hoeting J.A. A comparison study of extreme precipitation from six different regional climate models via spatial hierarchical modeling. Extremes 2010, 13(2):219-239.
    • (2010) Extremes , vol.13 , Issue.2 , pp. 219-239
    • Schliep, E.M.1    Cooley, D.2    Sain, S.R.3    Hoeting, J.A.4
  • 48
    • 77952562085 scopus 로고    scopus 로고
    • Probabilistic wind speed forecasting using ensembles and Bayesian model averaging
    • Sloughter J.M.L., Gneiting T., Raftery A.E. Probabilistic wind speed forecasting using ensembles and Bayesian model averaging. J. Am. Stat. Assoc. 2010, 105(489):25-35.
    • (2010) J. Am. Stat. Assoc. , vol.105 , Issue.489 , pp. 25-35
    • Sloughter, J.M.L.1    Gneiting, T.2    Raftery, A.E.3
  • 49
    • 34248354794 scopus 로고    scopus 로고
    • Probabilistic quantitative precipitation forecasting using Bayesian model averaging
    • Sloughter J.M.L., Raftery A.E., Gneiting T., Fraley C. Probabilistic quantitative precipitation forecasting using Bayesian model averaging. Mon. Weather Rev. 2007, 135(9):3209-3220.
    • (2007) Mon. Weather Rev. , vol.135 , Issue.9 , pp. 3209-3220
    • Sloughter, J.M.L.1    Raftery, A.E.2    Gneiting, T.3    Fraley, C.4
  • 50
    • 70350345571 scopus 로고    scopus 로고
    • Bayesian modeling of uncertainty in ensembles of climate models
    • Smith R.L., Tebaldi C., Nychka D., Mearns L.O. Bayesian modeling of uncertainty in ensembles of climate models. J. Am. Stat. Assoc. 2009, 104(485):97-116.
    • (2009) J. Am. Stat. Assoc. , vol.104 , Issue.485 , pp. 97-116
    • Smith, R.L.1    Tebaldi, C.2    Nychka, D.3    Mearns, L.O.4
  • 52
    • 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., Mearns L.O. Quantifying uncertainty in projections of regional climate change: a Bayesian approach to the analysis of multimodel ensembles. J. Climate 2005, 18(10):1524-1540.
    • (2005) J. Climate , vol.18 , Issue.10 , pp. 1524-1540
    • Tebaldi, C.1    Smith, R.L.2    Nychka, D.3    Mearns, L.O.4
  • 53
    • 78650108146 scopus 로고    scopus 로고
    • ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project
    • FitzRoy Road, Exeter EX1 3PB, UK, 160.
    • Van der Linden, P., Mitchell, J., 2009. ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project. Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3PB, UK, 160.
    • (2009) Met Office Hadley Centre
    • Van der Linden, P.1    Mitchell, J.2
  • 54
    • 77955603386 scopus 로고    scopus 로고
    • Risks of model weighting in multimodel climate projections
    • Weigel A.P., Knutti R., Liniger M.A., Appenzeller C. Risks of model weighting in multimodel climate projections. J. Climate 2010, 23(15):4175-4191.
    • (2010) J. Climate , vol.23 , Issue.15 , pp. 4175-4191
    • Weigel, A.P.1    Knutti, R.2    Liniger, M.A.3    Appenzeller, C.4
  • 55
    • 1542381343 scopus 로고    scopus 로고
    • Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs
    • Wood A.W., Leung L.R., Sridhar V., Lettenmaier D. Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Climatic Change 2004, 62(1):189-216.
    • (2004) Climatic Change , vol.62 , Issue.1 , pp. 189-216
    • Wood, A.W.1    Leung, L.R.2    Sridhar, V.3    Lettenmaier, D.4
  • 56
    • 84927594752 scopus 로고    scopus 로고
    • Reducing biases in regional climate downscaling by applying Bayesian model averaging on large-scale forcing
    • Yang H., Wang B. Reducing biases in regional climate downscaling by applying Bayesian model averaging on large-scale forcing. Climate Dyn. 2012, 1-10.
    • (2012) Climate Dyn. , pp. 1-10
    • Yang, H.1    Wang, B.2
  • 57
    • 84927619304 scopus 로고    scopus 로고
    • Future projections and uncertainty assessment of extreme rainfall intensity in the United States from an ensemble of climate models
    • Zhu J., Forsee W., Schumer R., Gautam M. Future projections and uncertainty assessment of extreme rainfall intensity in the United States from an ensemble of climate models. Climatic Change 2012, 1-17.
    • (2012) Climatic Change , pp. 1-17
    • Zhu, J.1    Forsee, W.2    Schumer, R.3    Gautam, M.4


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