Rank histograms are popular tools for assessing the reliability of meteorological ensemble forecast systems. A reliable forecast system leads to a uniform rank histogram, and deviations from uniformity can indicate miscalibrations. However, the ability to identify such deviations by visual inspection of rank histogram plots crucially depends on the number of bins chosen for the histogram. If too few bins are chosen, the rank histogram is likely to miss miscalibrations; if too many are chosen, even perfectly calibrated forecast systems can yield rank histograms that do not appear uniform. In this paper we address this trade‐off and propose a method for choosing the number of bins for a rank histogram. The goal of our method is to select a number of bins such that the intuitive decision whether a histogram is uniform or not is as close as possible to a formal statistical test. Our results indicate that it is often appropriate to choose fewer bins than the usual choice of ensemble size plus one, especially when the number of observations available for verification is small.

中文翻译：

---

关于等级直方图中的箱数

等级直方图是用于评估气象集成预报系统可靠性的流行工具。可靠的预测系统可得出一致的秩直方图，并且偏离一致性可能表示校准错误。但是，通过视觉检查等级直方图来识别此类偏差的能力主要取决于为直方图选择的分箱数。如果选择的仓位太少，则等级直方图可能会错过校准错误；如果选择太多，则即使经过完美校准的预测系统也可能会产生看起来不一致的排名直方图。在本文中，我们解决了这一折衷问题，并提出了一种用于选择秩直方图的箱数的方法。我们方法的目标是选择多个bin，以使直方图是否均匀的直觉决策尽可能接近正式的统计检验。我们的结果表明，通常应选择比通常选择的合奏大小加一的格数少的格数，特别是在可用于验证的观察数较少的情况下。