A multisite daily rainfall data generation model for climate change conditions

18th World IMACS Congress and MODSIM 2009 - International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, Proceedings

Volumn , Issue , 2009, Pages 3976-3982

  Srikanthan, R ^a  

^a BUREAU OF METEOROLOGY   (Australia)

Author keywords

Climate Change; Daily Rainfall; Stochastic Model

Indexed keywords

CATCHMENTS; CLIMATE MODELS; PROBABILITY DISTRIBUTIONS; RAIN; RUNOFF; TIME MEASUREMENT;

COMPARISON OF MODELS; GENERAL CIRCULATION MODEL; HYDROLOGIC MODELLING; INVERSE DISTANCE WEIGHTING; MAX PLANCK INSTITUTE; MURRUMBIDGEE RIVER CATCHMENT; STATISTICAL DOWNSCALING; TRANSITION PROBABILITIES;

CLIMATE CHANGE;

EID: 85086245604     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Bates, B. C., Jakeman, A. J., Charles, S. P., Sumner, N. R. and Fleming, P. M., (1994) Impact of climate change on Australia's surface water resources. In: Greenhouse, Coping with climate change, W. J.Bouma, G. I. Pearman and M. R. Manning, (Eds.), 248-262.
2. Chandler, R. E. (2002). GLIMCLIM: Generalized linear modelling for daily climate time series (software and user guide). Department of Statistical Science, University College London.
3. Charles, S. P., B. C. Bates, I. N. Smith, J. P. Hughes (2004). Statistical downscaling of daily precipitation from observed and modelled atmospheric fields. Hydrological Processes, 18(8): 1373-1394.
4. Chiew, F. H. S., Harrold, T. I., Siriwardena, L., Jones, R. N. and Srikanthan, R. (2003) Simulation of climate change impacts on runoff using rainfall scenarios that consider daily patterns of change in GCMs. MODSIM 2003, Townsville, 1, 154-159.
5. Frost, A. F, Charles, S. P., Mehrotra, R., Timbal, B., Nguyen, K. C., Chiew, F. H. S., Fu, G., Chandler, R. E., McGregor, J., Kirono, D., Fernandez, E., and Kent, D. (2009 - In preparation) A comparison of multi-site daily rainfall downscaling techniques under Australian conditions.
6. Harrold, T. I. and Jones, R. N. (2003) Generation of local scale scenarios using changes in GCM rainfall: a refinement of the perturbation method. MODSIM 2003, Townsville, 1, 11-16.
7. Harrold, T. I., Chiew, F. H. S. and Siriwardena, L. (2005) A method for estimating climate change impacts on mean and extreme rainfall and runoff.MODSIM 2005, Melbourne, 497-504.
8. Hughes, J. P., Guttorp, P. and Charles, S. P. (1999) A non-homogeneous hidden Markov model for precipitation occurrence. Applied Statistics, 48(1), 15-30.
9. Lettenmaier, D. P. and Gan, T. Y. (1990), Hydrologic sensitivities of the Sacramento-San Joaquin River basin, Califronia for global warming. Water Resources Research, 26(1): 69-86.
10. Panagoulia, D. (1992) Impacts of GISS-modelled climate changes on catchment hydrology. Hydrological Sciences Journal, 37, 141-163.
11. Mehrotra, R. and A. Sharma (2005). A nonparametric nonhomogeneous hidden Markov model for downscaling of multisite daily rainfall occurrences. Journal of Geophysical Research 110(D16108).
12. Srikanthan, R. and Pegram, G. G. S. (2009) A nested multisite daily rainfall stochastic generation model. Accepted for publication in Journal of Hydrology.
13. Wilks, D. S. (1992) Adopting stochastic weather generation algorithms for climate change studies. Climate Change, 22, 67-84.
14. Wilby, R. L., Dawson, C. W. and Barrow, E. M. (2002), SDSM - a decision support tool for the assessment of regional climate change impacts, Environmental Modelling and Software, 17(2), 145- 157.