更新IDF曲线到未来气候预测的有效方法
Efficient Method for Updating IDF Curves to Future Climate Projections
摘要：
如果气候平稳性已经死亡，那么工程设计标准应该如何修改以考虑极端降水的潜在变化？许多标准依赖于NOAA的Atlas 14中提供的降水强度-持续时间-频率（IDF）曲线。大气环流模型（GCM）预测整个美国的平均温度会上升，但对降水量的变化不太清楚。在许多地区，GCM预测总降水量的变化相对较小，但也表明极端事件的规模增加，因为温暖的空气可以容纳更多的水。不幸的是，GCM在预测个别风暴事件方面的技能有限。这项研究开发了一种有效的方法来解决这个问题，复制Atlas 14方法，将广义极值分布拟合到年最大值序列。GCM偏差通过等距分位数映射来解决，从GCM的历史模拟映射到未来预测，然后将此映射从拟合应用到Atlas 14中使用的数据。该方法是有效的，因为它只需要年度最大值，允许快速检查整个GCM预测范围内的结果。
英文摘要：
If climate stationarity is dead, how should engineering design standards be modified to account for potential changes in extreme precipitation? Many standards rely on precipitation intensity-duration-frequency (IDF) curves provided in NOAA's Atlas 14. General Circulation Models (GCMs) predict increases in average temperature throughout the US, but are less clear on changes in precipitation. In many areas GCMs predict relatively small changes in total precipitation volume, but also suggest increased magnitude of extreme events as warmer air can hold more water. Unfortunately, GCMs have limited skill in predicting individual storm events. This research developed an efficient approach to solve this problem that replicates Atlas 14 methods, which fit a generalized extreme value distribution to the annual maximum series. GCM biases are addressed through equidistant quantile mapping, mapping from a GCM's historical simulation to future predictions, then applying this mapping from the fit to data used in Atlas 14. The approach is efficient because it requires only the annual maxima, allowing rapid examination of results across the range of GCM projections.
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