Field significance tests have been widely used to detect climate change. In most cases, a local test is used to identify significant changes at individual locations, which is then followed by a field significance test that considers the number of locations in a region with locally significant changes. The choice of local test can affect the result, potentially leading to conflicting assessments of the impact of climate change on a region. We demonstrate that when considering changes in the annual extremes of daily precipitation, the simple Mann‐Kendall trend test is preferred as the local test over more complex likelihood ratio tests that compare the fits of stationary and nonstationary generalized extreme value distributions. This lesson allows us to report, with enhanced confidence, that the intensification of annual extremes of daily precipitation in China since 1961 became field significant much earlier than previously reported.

中文翻译：

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关于气候极端变化场意义测试的优化设计

现场重要性测试已广泛用于检测气候变化。在大多数情况下，使用局部测试来识别各个位置的显着变化，然后进行现场重要性测试，该测试考虑具有局部显着变化的区域中的位置数量。选择本地测试可能会影响结果，从而可能导致对气候变化对某个地区影响的评估相互矛盾。我们证明了，当考虑日降水的年极端值的变化时，简单的Mann-Kendall趋势检验作为本地检验，胜过比较固定和非平稳广义极值分布拟合的更复杂的似然比检验。本课使我们能够更加自信地进行报告，