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Title: Suitability of global circulation model downscaled BCCA daily precipitation for local hydrologic applications

Author
item Gyawali, Rabi
item Garbrecht, Jurgen
item Zhang, Xunchang

Submitted to: Journal Hydrologic Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/29/2016
Publication Date: 8/12/2016
Citation: Gyawali, R., Garbrecht, J.D., Zhang, X.J. 2016. Suitability of global circulation model downscaled BCCA daily precipitation for local hydrologic applications. Journal Hydrologic Engineering. 21(12). doi:10.1061/(ASCE)HE.1943-5584.0001452.

Interpretive Summary: Monthly precipitation projections for various climate change scenarios have been available for over a decade. More recently, Bias Corrected Constructed Analogue (BCCA) daily precipitation projections have been available for climate change investigations. In this study, the direct use of BCCA precipitation for field-scale hydrologic applications was examined for central Oklahoma climatic conditions. Three daily precipitation data sets were considered: (i) the 1961-1999 BCCA precipitation projections for a 12 km grid in central Oklahoma; (ii) the 1961-1999 spatially interpolated daily precipitation data used in the BCCA downscaling procedure; (iii) the 1961-1999 observed daily precipitation observations at the Weatherford COOP weather station located within the 12 km grid of the BCCA projections. The BCCA daily precipitation projections showed a larger number of rainy days, lower rainfall amounts per rainy day, and longer sequences of consecutive rainy-day clusters than found in observations at the Weatherford station. These differences were large enough to suggest that BCCA daily precipitation projections may not reflect the characteristics of actual precipitation observations at a point location, i.e. weather station. The underlying cause for the noted differences was traced back to the different spatial scale of the BCCA projections and observed daily precipitation at a station. Thus, caution is advised when using available BCCA daily rainfall projections directly in local and field-scale water investigations. Alternately, a statistical downscaling method based on stochastic weather generation that includes wet-day dry-day transition probabilities would provide the desired temporal disaggregation and sequencing of daily rainfall events.

Technical Abstract: Monthly precipitation projections for various climate change scenarios have been available for over a decade. More recently, Bias Corrected Constructed Analogue (BCCA) daily precipitation projections have been available for climate change investigations. In this study, the direct use of BCCA precipitation for field-scale hydrologic applications was examined for central Oklahoma climatic conditions. Three daily precipitation data sets were considered: (i) the 1961-1999 BCCA precipitation projections for a 12 km grid in central Oklahoma; (ii) the 1961-1999 spatially interpolated daily precipitation data used in the BCCA downscaling procedure; (iii) the 1961-1999 observed daily precipitation observations at the Weatherford COOP weather station located within the 12 km grid of the BCCA projections. The BCCA daily precipitation projections showed a larger number of rainy days, lower rainfall amounts per rainy day, and longer sequences of consecutive rainy-day clusters than found in observations at the Weatherford station. These differences were large enough to suggest that BCCA daily precipitation projections may not reflect the characteristics of actual precipitation observations at a point location, i.e. weather station. The underlying cause for the noted differences was traced back to the different spatial scale of the BCCA projections and observed daily precipitation at a station. Thus, caution is advised when using available BCCA daily rainfall projections directly in local and field-scale water investigations. Alternately, a statistical downscaling method based on stochastic weather generation that includes wet-day dry-day transition probabilities would provide the desired temporal disaggregation and sequencing of daily rainfall events.