BCCAQ is a method developed at the Pacific Climate Impacts Consortium for downscaling daily climate model projections of temperature and precipitation, including indices of extremes. This methodology, a hybrid of BCCA (Maurer et al. 2010) and QMAP (Gudmundsson et al. 2012), combines quantile-mapping bias correction with a constructed analogues approach using daily large-scale temperature and precipitation fields. The method was developed to correct the bias in daily precipitation series from climate models so that the distributional properties, e.g., means, variances and quantiles, more closely match those of the historical observations (provided in this case by the ANUSPLIN dataset). The robustness of the methodology was tested by examining three criteria: the day-to-day sequencing of precipitation events, the distribution characteristics, and spatial correlation. BCCAQv2 is a modification of BCCAQ which preserves the coarse-scale projected changes at each quantile during the quantile mapping step, which other quantile mapping methods have a tendency to amplify (the “inflation” problem), including the method used in BCCAQv1. Preserving the precipitation change signal is important for maintaining the physical scaling relationships with model-projected temperature changes.
For more information see Cannon, A.J., S.R. Sobie, and T.Q. Murdock, 2015: Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes? Journal of Climate, 28(17), 6938-6959, doi:10.1175/JCLI-D-14-00754.1.
Additional references: Gudmundsson, L., J. Bremnes, J. Haugen and T. Engen-Skaugen, 2012: Technical note: Downscaling RCM precipitation to the station scale using statistical transformations – A comparison of methods. Hydrol. Earth Syst. Sci., 16, 3383-3390, doi:10.5194/hess-16-3383-2012.
Maurer, E.P., H. Hidalgo, T. Das, M. Dettinger and D. Cayan, 2010: The utility of daily large-scale climate data in the assessment of climate change impacts on daily streamflow in California. Hydrol. Earth Syst. Sci., 14, 1125-1138, doi:10.5194/hess-14-1125-2010.