260-1 Evaluation of Downscaled Daily Precipitation for FIELD Scale Hydrologic Applications.
Rabi Gyawali, Jurgen Garbrecht, John X. Zhang
Hydrologic and agronomic applications often require a reliable representation of precipitation sequence as well as physical consistency of precipitation series for climate change impact assessment. Herein, we evaluate the daily sequence of the state –of –art downscaled Bias Corrected Constructed Analogue (BCCA) precipitation hind-casts to determine their suitability to study daily soil moisture dynamics at the field-scale for central Oklahoma climatic conditions. Three daily precipitation data sets were considered: (i) the 1961-1999 BCCA precipitation hind-casts 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 BCCA grid. The BCCA daily precipitation hind-casts 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. These differences were large enough to suggest that BCCA daily precipitation hind-casts 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 differences in spatial scales of the BCCA outputs and observed daily precipitation at a station. Thus, caution is advised to end users using BCCA daily rainfall projections directly in local and field-scale water investigations, particularly for applications requiring reliable representation of precipitation sequence. Alternatively, 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.