Statistical downscaling of general circulation model output: A comparison of methods
Statistical downscaling of general circulation model output: A comparison of methods
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DOI：
10.1029/98wr02577
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发表时间：
1998-11
影响因子：
5.4
通讯作者：
R. Wilby;T. Wigley;D. Conway;P. Jones;B. Hewitson;J. Main;D. Wilks
中科院分区：
文献类型：
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作者：
R. Wilby;T. Wigley;D. Conway;P. Jones;B. Hewitson;J. Main;D. Wilks
一系列不同的统计降尺度模型进行了校准，使用观测和大气环流模型（GCM）生成的日降水时间序列和相互比较。使用的GCM是英国。哈德利中心的海洋/大气耦合模式（HadCM 2），由CO2和硫酸盐气溶胶变化共同驱动。气候模式的结果，1980-1999年（现在）和2080-2099年（未来），在美国的六个地区。对比的降尺度方法包括不同的天气生成器技术（标准的“WGEN”方法和基于持续时间的方法）、使用网格点涡度数据作为大气预测变量的两种不同方法（B-Circ和C-Circ）以及使用环流数据和环流加温度数据作为预测变量的人工神经网络（ANN）传递函数技术的两种变体。通过使用标准的观测和GCM导出的预测变量集以及使用标准的诊断统计数据集，有助于结果的比较。技能水平的显着差异，发现之间的降尺度方法。天气生成技术能够准确地拟合一些每日降水量统计数据，在观测和模拟的每日降水量之间产生最小的差异。人工神经网络方法表现不佳，因为未能充分模拟雨天发生统计。由统计降尺度方法产生的当前和未来情景之间的降水变化一般小于由GCM直接产生的降水变化。因此，1980-1999年和2080-2099年期间GCM产生的日降水量变化被认为主要不是由于大气环流的变化。根据这些结果和详细的模型比较，为今后的研究和模型改进的建议。
A range of different statistical downscaling models was calibrated using both observed and general circulation model (GCM) generated daily precipitation time series and intercompared. The GCM used was the U.K. Meteorological Office, Hadley Centre's coupled ocean/atmosphere model (HadCM2) forced by combined CO2 and sulfate aerosol changes. Climate model results for 1980–1999 (present) and 2080–2099 (future) were used, for six regions across the United States. The downscaling methods compared were different weather generator techniques (the standard “WGEN” method, and a method based on spell‐length durations), two different methods using grid point vorticity data as an atmospheric predictor variable (B‐Circ and C‐Circ), and two variations of an artificial neural network (ANN) transfer function technique using circulation data and circulation plus temperature data as predictor variables. Comparisons of results were facilitated by using standard sets of observed and GCM‐derived predictor variables and by using a standard suite of diagnostic statistics. Significant differences in the level of skill were found among the downscaling methods. The weather generation techniques, which are able to fit a number of daily precipitation statistics exactly, yielded the smallest differences between observed and simulated daily precipitation. The ANN methods performed poorly because of a failure to simulate wet‐day occurrence statistics adequately. Changes in precipitation between the present and future scenarios produced by the statistical downscaling methods were generally smaller than those produced directly by the GCM. Changes in daily precipitation produced by the GCM between 1980–1999 and 2080–2099 were therefore judged not to be due primarily to changes in atmospheric circulation. In the light of these results and detailed model comparisons, suggestions for future research and model refinements are presented.