%0 Journal Article %1 Osman.etal2014 %A Osman, Yassin Z. %A Fealy, Rowan %A Sweeney, John C. %D 2014 %J Journal of Water and Climate Change %K GPD POT covariate downscaling %R 10.2166/wcc.2013.071 %T Downscaling extreme precipitation in Ireland using combined peak-over-threshold generalised Pareto distribution model of varying parameters %X The paper describes downscaling of extreme precipitation in Ireland using a probabilistic method. The method described uses a combined peak-over-threshold (POT) – generalised Pareto distribution (GPD) approach in which the scale parameter of the GPD is allowed to vary with a dominant climate forcing at the location of interest. The dominant climatic forcing is represented by predictors selected from large-scale climatic variables provided by the NCEP/NCAR data. Data from six rainfall stations are used in the study to build the models for each station. The extRemes software is used to build the models as it allows parameters of the fitted distribution to vary as a function of covariate(s). The developed models were tested for goodness-of-fit with the observed data, and model fit was found to be much improved when the scale parameter was assumed to vary with the selected covariates. Return level – return period relations are developed based on the models developed and four future time periods are simulated to investigate the effects of climate change on both precipitation magnitude and frequency. Based on the findings of this research, significant changes in precipitation extremes are projected for Ireland, which includes wetter winters and drier summers, especially in inland areas.

@article{Osman.etal2014, abstract = {The paper describes downscaling of extreme precipitation in Ireland using a probabilistic method. The method described uses a combined peak-over-threshold (POT) – generalised Pareto distribution (GPD) approach in which the scale parameter of the GPD is allowed to vary with a dominant climate forcing at the location of interest. The dominant climatic forcing is represented by predictors selected from large-scale climatic variables provided by the NCEP/NCAR data. Data from six rainfall stations are used in the study to build the models for each station. The extRemes software is used to build the models as it allows parameters of the fitted distribution to vary as a function of covariate(s). The developed models were tested for goodness-of-fit with the observed data, and model fit was found to be much improved when the scale parameter was assumed to vary with the selected covariates. Return level – return period relations are developed based on the models developed and four future time periods are simulated to investigate the effects of climate change on both precipitation magnitude and frequency. Based on the findings of this research, significant changes in precipitation extremes are projected for Ireland, which includes wetter winters and drier summers, especially in inland areas.}, added-at = {2014-04-08T10:50:00.000+0200}, author = {Osman, Yassin Z. and Fealy, Rowan and Sweeney, John C.}, biburl = {https://www.bibsonomy.org/bibtex/2b182b760f8f5731490d17c500f0a5db4/marsianus}, doi = {10.2166/wcc.2013.071}, interhash = {40fd592683afbb78e7215934369c080b}, intrahash = {b182b760f8f5731490d17c500f0a5db4}, journal = {Journal of Water and Climate Change}, keywords = {GPD POT covariate downscaling}, timestamp = {2014-04-08T10:50:00.000+0200}, title = {Downscaling extreme precipitation in Ireland using combined peak-over-threshold generalised Pareto distribution model of varying parameters}, year = 2014 }