Bias correction of daily precipitation for ungauged locations using geostatistical approaches: A case study for the CORDEX‐Africa ensemble
DOI: https://doi.org/10.1002/joc.7649
Persistent URL: http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/10383
Persistent URL: http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/10383
Lorenz, Manuel; Bliefernicht, Jan; Kunstmann, Harald, 2022: Bias correction of daily precipitation for ungauged locations using geostatistical approaches: A case study for the CORDEX‐Africa ensemble. In: International Journal of Climatology, Band 42, 12: 6596 - 6615, DOI: 10.1002/joc.7649.
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Climate model simulations typically exhibit a bias, which can be corrected using statistical approaches. In this study, a geostatistical approach for bias correction of daily precipitation at ungauged locations is presented. The method utilizes a double quantile mapping with dry day correction for future periods. The transfer function of the bias correction for the ungauged locations is established using distribution functions estimated by ordinary kriging with anisotropic variograms. The methodology was applied to the daily precipitation simulations of the entire CORDEX‐Africa ensemble for a study region located in the West African Sudanian Savanna. This ensemble consists of 23 regional climate models (RCM) that were run for three different future scenarios (RCP 2.6, RCP 4.5, and RCP 8.5). The evaluation of the approach for a historical 50‐year period (1950–2005) showed that the method can reduce the inherent strong precipitation bias of RCM simulations, thereby reproducing the main climatological features of the observed data. Moreover, the bias correction technique preserves the climate change signal of the uncorrected RCM simulations. However, the ensemble spread is increased due to an overestimation of the rainfall probability of uncorrected RCM simulations. The application of the bias correction method to the future period (2006–2100) revealed that annual precipitation increases for most models in the near (2020–2049) and far future (2070–2099) with a mean increase of up to 165mm⋅a−1 (18%). An analysis of the monthly and daily time series showed a slightly delayed onset and intensification of the rainy season. Adapting water management strategies to future precipitation projected by climate models is associated with high uncertainty in sparsely gauged catchments. Kriging was utilized to estimate distribution parameters for ungauged locations in a West African region to perform a bias correction of the CORDEX‐Africa ensemble. The application of the bias correction method revealed higher annual precipitation amounts and an intensifaction of the rainy season but only little change to the onset of the rainy season.
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Subjects:
bias correctionclimate change
CORDEX‐Africa
geostatistical approaches
precipitation
quantile mapping
West Africa
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