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6 of (R220%) are to be considered as ��less-skilled�� indicators (as bolded in Table 2). Under this evaluation rule, it is observed that each downscaling run has certain skilled and less-skilled indictors, meaning no downscaling run can be concluded to be overwhelmingly superior to the others. Despite the result, uncorrected Er1-d seems to be more skilled in term of the numbers of more skilled indictors, particularly in the index WD. However, considerable biases in the indices Iwet and PQ95 still exist and suggest post-processing correction is necessary to derive realistic downscaling output. The evaluation results for the corrected downscaling runs in the validation period are shown in Table 2. Similarly, more-skilled (highlighted) and less-skilled (bold) indicators in Table 3 are used to quantify the effectiveness of corrected precipitation. As for the indices Iwet and PQ95, http://www.selleckchem.com/products/AP24534.html the common overestimations, particularly over the HI region, are effectively mitigated by both correction approaches http://en.wikipedia.org/wiki/MERTK ( Table 3). Relatively speaking, the corrections for the annual wet days (WD) are less effective. This is mainly because the rain/no-rain physics is controlled primarily by the downscaling model. In addition, the bias-correction approaches that simply modify the raw dry/wet frequencies to match the reference frequencies based on the defined dry/wet threshold in the control period are less influential regarding this index. Altogether, the more-skilled indicators (%BIAS and R2) suggest that the corrected downscaling runs are effectively modified in terms of not only the quantitative biases but also the misrepresented spatial features of the indices. Overall, the proposed corrections improve the raw downscaling runs, but the improvement degrees regarding any specific index highly correlate with the selection of correction approaches and raw downscaling runs. By inter-comparing the skilled and unskilled statistics of each index among the correction combinations, corrected Er1-d and Er3-d runs are identified as the most- and least-skilled runs. However, the performance differences between the two correction approaches are highly related to the raw downscaling runs. QM-corrected Er1-d and Er3-d are generally more skilled, but two approaches seem to have similar effects on Er2-d. Taking the present-day (1971�C2000) NCEP-d data as http://www.selleckchem.com/products/Imatinib-Mesylate.html the reference, the changes of future (2035�C2065) precipitation under the SRES A1B scenario are assessed by the built evaluation approach and indices adopted for the present-day evaluation presented in Section 5.3. The distribution maps (Fig. 6) and statistics (Table 4) of index�Cpercent changes between the two periods conceptually illustrate the trends of future precipitation properties. To make those significant changes stand out, notable increasing and decreasing signals are highlighted in Table 4 by bold (i.e., >+20%) and underlined (i.e.,