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Application Papers

The Effects of Climate Change on Extreme Precipitation Events in the Upper Thames River Basin: A Comparison of Downscaling Approaches

, , , &
Pages 253-274 | Published online: 23 Jan 2013

Figures & data

Figure 1. The Upper Thames River basin, in southwestern Ontario, Canada.

Figure 1. The Upper Thames River basin, in southwestern Ontario, Canada.

Table 1.  Environment Canada and NARR climate variables used in the study.

Table 2.  Description of AOGCM and emissions scenarios used in the study.

Table 3.  Summary of selected large-scale predictor variables corresponding to selected predictands for SDSM. See for definitions of predictor variables.

Figure 2. Comparison of generated and observed climate variability from three weather generators. The first column shows results from SDSM, the second column shows LARS-WG and the third column shows WG-PCA. The observed values are represented with a solid line and the simulated values are represented with a dashed line. The top row of graphs show the absolute maximum TMAX (top lines) and absolute minimum TMIN (bottom lines). The second row contains boxplots of simulated total monthly precipitation from the weather generators, with historical medians plotted in black. The third row contains simulated and observed standard deviations and means (heavy lines) of daily precipitation.

Figure 2. Comparison of generated and observed climate variability from three weather generators. The first column shows results from SDSM, the second column shows LARS-WG and the third column shows WG-PCA. The observed values are represented with a solid line and the simulated values are represented with a dashed line. The top row of graphs show the absolute maximum TMAX (top lines) and absolute minimum TMIN (bottom lines). The second row contains boxplots of simulated total monthly precipitation from the weather generators, with historical medians plotted in black. The third row contains simulated and observed standard deviations and means (heavy lines) of daily precipitation.

Figure 3. Boxplots of simulated temperature indices from SDSM, LARS-WG and WG-PCA with the observed historical median and quartiles shown.

Figure 3. Boxplots of simulated temperature indices from SDSM, LARS-WG and WG-PCA with the observed historical median and quartiles shown.

Figure 4. Boxplots of simulated precipitation indices from SDSM, LARS-WG and WG-PCA with the observed historical median and quartiles shown.

Figure 4. Boxplots of simulated precipitation indices from SDSM, LARS-WG and WG-PCA with the observed historical median and quartiles shown.

Table 4.  Definitions of selected temperature and precipitation indices.

Table 5.  Coefficients of determination for the climate characteristics presented in .

Table 6.  Test results (p-values) of the Wilcoxon rank-sum test for the difference of means in observed and simulated daily precipitation, maximum temperatures and minimum temperature. Insignificant results are indicated in bold.

Table 7.  Test results (p-values) of the Levene's test for the equality of variances in observed and simulated daily precipitation, maximum temperatures and minimum temperatures. Insignificant results are indicated in bold.

Table 8.  AOGCM predicted percent change in average total seasonal precipitation and mean daily precipitation values, as simulated by SDSM, LARS-WG, and WG-PCA for the 2050's time period.

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