本文介绍了使用 r 中的栅格包聚合季节性均值的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我正在尝试将每日数据(35 年)汇总到每月,然后使用 R 中的栅格包计算季节性平均值(我知道如何使用 CDO 进行计算).下面是我的代码,它输出所有年份的 4 个季节性平均值(140 层).如何循环输出仅 4 层(4 个季节)?.我感谢您的帮助.
I am attempting to aggregate daily data (35 years) to monthly then calculate seasonal mean using the raster package in R (I know how to do it with CDO). Below is my code, which outputs 4 seasonal means for all years (140 layers). How can I loop to output only 4 layers ( for the 4 seasons)?. I appreciate your help.
dailydata <- brick ("dailyrain.nc")
dates <- seq(as.Date("1981-01-01"), as.Date("2015-12-31"), by="day")
months <- format(dates, "%Y-%m")
Aggregate2Monthly <- function(x) {
agg <- aggregate(x, by=list(months), sum)
return(agg$x)
}
mothlydata <- calc(dailydata, Aggregate2Monthly)
mondates <- seq(as.Date("1981-01-01"), as.Date("2015-12-31"), by="month")
years <- format(mondates, "%Y")
seasons.def=c(1, 1, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4)
years.seasons <- paste(years, seasons.def, sep="-")
nyears <- years[!duplicated(years)]
nseas <- seasons.def[!duplicated(seasons.def)]
Aggregate2Seasons <- function(x) {
agg <- aggregate(x, by=list(years.seasons), mean)
return(agg$x)
}
seasonsdata <- calc(mothlydata, Aggregate2Seasons)
推荐答案
您希望按年和月的组合进行聚合.
You want to aggregate by a combination of year and month.
months <- format(dates, "%Y-%m")
分组月份(根据您的评论):
Grouping months (as per your comment):
groups <- function(x) {
d <- as.POSIXlt(x)
ans <- character(length(x))
ans[d$mon %in% 0:1] <- "JF"
ans[d$mon %in% 2:4] <- "MAM"
ans[d$mon %in% 5:8] <- "JJAS"
ans[d$mon %in% 9:11] <- "OND"
ans
}
现在使用 groups(dates)
作为分组变量.检查:
Now use groups(dates)
as the grouping variable. Check:
data.frame(dates, groups(dates))
## dates groups.dates.
## 1 1981-01-01 JF
## 2 1981-01-02 JF
## 3 1981-01-03 JF
## 4 1981-01-04 JF
## 5 1981-01-05 JF
## 6 1981-01-06 JF
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