我有以下问题。基本上我有遵循公历的数据和遵循 360 天日历和 365 天日历（无闰年）的数据。它是提供数据的模型的一个功能。我只能在库（PCICt）的帮助下为具有 360 或 365 天日历的数据创建时间索引，因此时间索引属于 PCICt 类，而不是那些具有 360 天或 365 天日历的数据集的日期类。
我成功地轻松更改了 365 天日历的数据时间索引的类别，因为它总是错过 2 月 29 日。总的来说，它的天数比公历数据少，这就是以下代码有效的原因：
index(Modellwind.IPSL.1971_2100.mat.5.zoo) <- as.Date(paste(index(Modellwind.IPSL.1971_2100.mat.5.zoo), "%Y-%m-%d"))
class(index(Modellwind.IPSL.1971_2100.mat.5.zoo))
any(is.na(Modellwind.IPSL.1971_2100.mat.5.zoo))
我可以使用以下代码将公历数据与 365 天日历数据（Modellwind.IPSL.1971_2100.mat.5.zoo 有 360 天日历）合并：
library(zoo)
library(PCICt)
Mergedata.Gregorian_cal.365d_cal <- merge(Modellwind.1971_2100.mat.5.zoo[,1],Modellwind.IPSL.1971_2100.mat.5.zoo[,1], fill = NA)
sum(is.na(Mergedata.Gregorian_cal.365d_cal)) #Gives you the number of leap years between the starting date and end date. Between 1971 and 2100, you have 32 leap years.
问题是，360 天的日历每月有 30 天。因为2月30日不存在，所以我无法使用上面的方法。是否可以使用公历数据集的索引来掩盖 360 天日历数据中的日期，而公历数据中不存在这些日期？在 360 天日历的数据中，我会在每个月的 31 日有 NA，该日历有 31 天，并且 2 月 30 日将始终被排除/“删除”。
所有这 2 种日历类型的 1972 年数据示例。 1972 年是闰年。
公历数据：
structure(c(18.0824119718086, 22.0984972927228, 15.6444417189609,
5.89666444009656, 18.1725165479582, 21.9512885928156, 4.88193965506205,
13.933395151291, 13.0150555148858, 12.2412020084762, 15.1707058527428,
11.9102181846508, 11.8373087451369, 4.88134153024087, 3.9195944541078,
8.15191977152853, 16.4878972832708, 22.3388856060094, 24.9339938808775,
9.40486557731387, 3.28778357417694, 5.4431969404311, 20.9010729191345,
21.576769300227, 23.5252763396514, 18.7725442737342, 19.7400816746119,
16.9286422645386, 11.5214494652195, 12.6356049638603, 7.8885628659944,
7.81687922456664, 4.76970848125104, 4.71443717941174, 4.3332862268629,
5.39949220500925, 17.2259740635503, 8.94893163333614, 10.5413637024979,
7.17270151460124, 13.1168987701018, 7.80375818376942, 9.19842495123789,
6.50186468363422, 2.72654917702192, 4.76044540462425, 9.33231780065151,
2.94546305078892, 4.67014980066904, 23.8062593679947, 20.0513022569902,
17.0747102447771, 22.1857749192152, 16.3213003571625, 5.59820337769238,
11.7719699596263, 2.80575446040357, 6.01800547567089, 8.40297112483879,
11.8088715968982, 4.98554106381165, 4.57889903991417, 5.46723000525948,
2.2046248257294, 6.50476062233784, 5.93160587570127, 2.66548923257402,
6.18402932922427, 6.90886137443288, 3.85090651354255, 8.24126904737149,
10.9654562975344, 26.2730566456532, 20.7006666233841, 6.82182724533744,
12.9025799024923, 9.59995956664874, 18.3086576464973, 8.53427988021107,
13.5057006787102, 2.58426562914531, 4.77444858313551, 4.01236032427182,
11.972201385, 19.541507043929, 12.7122726666622, 6.58520942950129,
10.0492820845097, 5.32566668447011, 2.57782664078923, 7.15092309537708,
13.5172698318347, 14.9398233030208, 14.5222484425227, 8.00143290635926,
11.5258287774697, 6.38313299466099, 1.79298307790425, 4.16626735598483,
10.4754961358211, 7.29533307327725, 6.14846988554932, 12.0495274648323,
5.53397133979113, 8.37782693478431, 7.52399322022154, 13.8764650137859,
10.9413294317165, 5.79402371881772, 7.61939719880655, 2.01218529630289,
4.15345219536974, 9.53346680530963, 14.4880341424594, 6.6395383447145,
12.2147086716578, 8.61151331855143, 4.96406162861823, 2.31444711425824,
9.18479155288269, 14.0394170749205, 12.9045375342084, 8.56014631714993,
4.45030804438492, 4.54819424494151, 9.14814577436106, 9.0203698734204,
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7.51027331456462, 5.64433360963038, 8.25879595299386, 11.1260560553349,
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6.58751650188931, 4.69084765180419, 2.37774148302349, 0.88406335422542,
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6.42699271186533, 7.34127100087814, 9.48351531950429, 3.731756550704,
2.97235842074357, 9.33755238371563, 8.45534306181479, 9.76758605452981,
7.10973204410344, 5.58659570577684, 6.73065557918815, 2.2443822565949,
10.0324385505791, 12.4468029449543, 8.54955485805234, 7.74625286400315,
8.76361852142208, 7.31040726702086, 10.9069555344467, 20.2240593355273,
18.8325145078602, 13.8646347231803, 6.18721686089014, 5.06959205667858,
1.88326841118378, 3.46887269480676, 10.466733322762, 10.0359820698446,
11.6007096598598, 9.40090116780089, 9.33769236702315, 9.95757914421451,
8.55990604010644, 10.4960731180582, 15.1722236227608, 11.1686532067003,
12.5359489386538, 9.08166190238287, 3.05025798629833, 8.2121249493627,
13.5877493909831, 17.366136605839, 10.1228300566323, 8.27402110802059,
9.36245413432149, 8.46450110123141, 1.84281651654745, 3.30160338329847,
6.3138195121321, 11.728173138611, 10.6622626897554, 16.4094777741508,
20.0381278953011, 19.9861861731441, 14.5139852521008, 5.48642303877599,
7.72640073447677, 6.40813436142624, 1.68384368141763, 4.77881376279741,
5.18058883352236, 2.98929028921609, 4.63220103226812, 4.16738796400037,
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7.21256528138117, 14.5616168774743, 6.49359376934273, 1.80947777511883,
1.05548742272005, 10.0100349138233, 12.9534450881407, 7.3887732493981,
2.06346550336316, 8.31717299234876, 7.78924597525132, 2.52953776616571,
8.82704926761683, 17.6640298084431, 13.3475985590147, 17.628200973858,
21.7018534179796, 18.5008930385254, 10.1186544078028, 20.3816253684839,
24.926808778224, 21.9880227371171, 20.1845589773564, 16.8169067228104,
10.2309882726068, 11.1248083859065, 20.5125621219226, 16.2733638505053,
18.8559651435026, 9.34653256821625, 16.1736806222654, 15.2975717551524,
14.5146239904197, 5.49088884606638, 10.6410636803798, 23.2390025461356,
17.9439644921709, 30.2719783889658, 17.8897458886807, 21.8089336705463,
21.181790238746, 7.74189585366475, 15.5669977526734, 22.2278845648006,
24.8537097755812, 23.4403701940983, 21.6831582162925, 2.51132630151019,
5.92677645017391, 10.9441543623409, 2.36029949616021, 1.16606557900293,
3.50793234808807, 9.61440088811323, 14.137409810834, 18.381771312848,
12.6572683827955, 18.797705699369, 20.8717521227799, 20.2278258689499,
12.9121727366459, 12.4660577833913, 19.7783723336818, 21.467091272057,
19.825201185869, 21.5289275033657, 25.2513848648435, 19.3231430907612,
14.4548913656037, 18.1364925154159, 25.6372229193355, 10.7132780942731,
3.39420618551996, 18.5659343284766, 21.7217416658684, 18.5067855518246,
17.6834051522095, 15.6325986696431, 11.6100239010514, 15.0764596715006,
8.46048294087618, 19.6747151949836, 10.0466139442861, 7.41836369302161,
19.4712502377319, 15.3111265245001, 6.54184803095167, 3.95906471757932,
4.6122997606339, 7.13881563394315, 2.48477412801708, 6.19131168025857,
7.82629557777152, 8.93410147891196, 6.27319459383102, 4.05195951965034,
8.77535610150876, 8.45968682510812, 6.27599562509301, 5.11571448525756,
1.68865280924914, 14.4333064594824, 20.5250630694977, 24.0600954370164,
13.4110946493079, 2.92078462265695, 9.06322147728374), index = structure(c(730,
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360天日历数据：
structure(c(16.2042726556084, 5.54411632675392, 8.39523962307452,
12.9056155820263, 2.61097842984656, 5.36226881021485, 6.11436671091439,
7.80097325957491, 2.6959250785196, 1.21734133687523, 9.83094824076473,
14.6123034310063, 22.5841804523832, 18.878943978969, 21.5918638597738,
21.6111797366467, 12.163190670239, 13.0688120229195, 13.1780838331026,
10.4636228871236, 24.5866766742838, 17.6333887432414, 13.5573702722517,
9.98750262602645, 6.60239076617993, 7.99851427184562, 10.7241814973962,
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8.69182806695981, 16.4062789963677, 23.1456317293811, 26.5321804559772,
23.0561436633882, 26.6478272830746, 26.6213654159103, 17.8004617644568,
18.8721032889994, 19.0042310175412, 21.9278326697278, 20.3999804074965,
21.9715743408936, 18.1198929013236, 20.8010363608164, 16.2125640673085,
22.7866237759357, 25.7292529258921, 19.9958794890251, 18.256654841611,
26.5258848098581, 19.3699454096059, 10.2084937593693, 7.09411455312409,
11.1030076686983, 11.1372661762985, 3.46190062236435, 5.55418460608178,
7.97804690731097, 5.74135886926954, 7.37374922730165, 21.7072129639493,
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5.59325194224167, 9.29484012593814, 6.31433046860712, 8.99969159771701,
12.9220576129017, 13.5931259265605, 3.13177632385839, 7.32634431180194,
3.65530722032479, 7.76414703436829, 8.81357616532502, 14.9915407274787,
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9.43772890502225, 10.7429797911477, 8.98128618812878, 6.14861396465088,
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6.41344157071221, 5.87633507183265, 5.49327509833653, 7.25912268522123,
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10.8397879874016, 8.72028550374256, 0.580257801954223, 4.39712796914426,
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), cal = "360", months = c(30, 30, 30, 30, 30, 30, 30, 30, 30,
30, 30, 30), class = "PCICt", dpy = 360, tzone = "GMT", units = "secs"), class = "zoo")
我不熟悉360天日历，但360天日历的索引似乎是纪元秒，起源于公历1970-01-01。如果是这种情况，此代码将起作用。
library(data.table)
library(dplyr)
date <- attr(vec360, "index") %>% as.numeric() %>% as.POSIXct(origin="1970-01-01") %>% as.Date()
dt360 <- data.table(vec360, date)
date <- attr(vec365, "index")
dt365 <- data.table(vec365, date)
merged <- merge(dt360, dt365, all = T)
print(merged)
# date vec360 vec365
# 1: 1971-12-22 16.204273 NA
# 2: 1971-12-23 5.544116 NA
# 3: 1971-12-24 8.395240 NA
# 4: 1971-12-25 12.905616 NA
# 5: 1971-12-26 2.610978 NA
# ---
# 372: 1972-12-27 NA 20.525063
# 373: 1972-12-28 NA 24.060095
# 374: 1972-12-29 NA 13.411095
# 375: 1972-12-30 NA 2.920785
# 376: 1972-12-31 NA 9.063221
# get a zoo object back
merged_zoo <- zoo(merged)
请确保检查 360 天向量索引中的第二个纪元的起源为 1970-01-01。
您显然正在使用来自三个不同模型的气候预测数据，每个模型使用不同的日历。正如您所说，这些日历是各个型号的功能，您应该尊重该功能。然后，该方法是不是合并原始数据然后进行分析，而是相反：首先分别分析每个模型，这通常涉及将每日数据聚合到每月数据，然后计算异常（即2081 - 2100 年期间 X 月的平均值与基线期间（例如 1971 - 2000 年）的同月平均值相比如何），然后finally 将各个模型的这些结果合并为最终结果（例如多模型集成）。
使用 CFtime 包（诚然，2017 年还没有），使用气候预测模型使用的不同日历变得轻而易举：
install.packages("CFtime")
library(CFtime)
library(ncdf4)
# Open the climate projection model
nc <- nc_open("./my_model.nc")
# Build the time series from the information in the data file
# No need to worry about the details of the calendar, the CFtime package manages
cf <- CFtime(nc$dim$time$units, nc$dim$time$calendar, nc$dim$time$vals)
# Read the data from the file
modellwind <- ncvar_get(nc, "var")
# Build a factor, as needed
fac <- CFfactor(cf, "month")
# Apply your function using the factor
res <- aperm(apply(modellwind, 1:2, tapply, fac, fun), c(2, 3, 1))
对其他型号重复此操作。现在，您可以合并不同模型的结果，假设您的
fun