我正在处理一个.nc文件。该文件可以file size: 35 M下载 这里.我以前没有在 R.I
中与nc或raster合作过raster并根据其他问题的不同堆栈答案中的建议探索ncdf4包。
library(raster)
library(ncdf4)
file <- # location to file you downloaded from the link above
rfile <- raster(file)
# this is what I got
> rfile
class : RasterLayer
band : 1 (of 1128 bands)
dimensions : 64, 128, 8192 (nrow, ncol, ncell)
resolution : 2.8125, 2.789327 (x, y)
extent : -1.40625, 358.5938, -89.25846, 89.25846 (xmin, xmax, ymin, ymax)
coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0
data source : D:STUDYCMIP5_GCM_monthprrcp26pr_Amon_bcc-csm1-1_rcp26_r1i1p1_200601-209912.nc
names : Precipitation
z-value : 2006-01-16
zvar : pr
我被困在这一点上。我不知道如何进一步进行。我遇到了@运算符的使用，但我无法提取有意义的东西。
> print(rfile)
File D:STUDYCMIP5_GCM_monthprrcp26pr_Amon_bcc-csm1-1_rcp26_r1i1p1_200601-209912.nc (NC_FORMAT_CLASSIC):
4 variables (excluding dimension variables):
double time_bnds[bnds,time]
double lat_bnds[bnds,lat]
double lon_bnds[bnds,lon]
float pr[lon,lat,time]
standard_name: precipitation_flux
long_name: Precipitation
comment: at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)
units: kg m-2 s-1
original_name: PRECC+PRECL
cell_methods: time: mean (interval: 20 mintues)
cell_measures: area: areacella
missing_value: 1.00000002004088e+20
_FillValue: 1.00000002004088e+20
associated_files: baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_bcc-csm1-1_rcp26_r0i0p0.nc areacella: areacella_fx_bcc-csm1-1_rcp26_r0i0p0.nc
4 dimensions:
time Size:1128 *** is unlimited ***
bounds: time_bnds
units: days since 2006-01-01
calendar: noleap
axis: T
long_name: time
standard_name: time
lat Size:64
bounds: lat_bnds
units: degrees_north
axis: Y
long_name: latitude
standard_name: latitude
lon Size:128
bounds: lon_bnds
units: degrees_east
axis: X
long_name: longitude
standard_name: longitude
bnds Size:2
27 global attributes:
institution: Beijing Climate Center(BCC),China Meteorological Administration,China
institute_id: BCC
experiment_id: rcp26
source: bcc-csm1-1:atmosphere: BCC_AGCM2.1 (T42L26); land: BCC_AVIM1.0;ocean: MOM4_L40 (tripolar, 1 lon x (1-1/3) lat, L40);sea ice: SIS (tripolar,1 lon x (1-1/3) lat)
model_id: bcc-csm1-1
forcing: Nat Ant GHG SD Oz Sl SS Ds BC OC
parent_experiment_id: historical
parent_experiment_rip: r1i1p1
branch_time: 2006
contact: Dr. Tongwen Wu (twwu@cma.gov.cn)
history: Output from monthly mean data 2011-06-27T08:46:28Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
comment: Future projection (2006-2099) forced with prescribed concentration scenario of RCP2.6. The carbon cycle in land and ocean component model is considered, but the time-evolution of CO2 concentration in atmospheric component is prescribed.
initialization_method: 1
physics_version: 1
tracking_id: 93654a27-6561-4263-9ee4-6411ab913c62
product: output
experiment: RCP2.6
frequency: mon
creation_date: 2011-06-27T08:46:28Z
Conventions: CF-1.4
project_id: CMIP5
table_id: Table Amon (11 April 2011) 1cfdc7322cf2f4a32614826fab42c1ab
title: bcc-csm1-1 model output prepared for CMIP5 RCP2.6
parent_experiment: historical
modeling_realm: atmos
realization: 1
cmor_version: 2.5.6
输入文件是 2006 年至 2100 年的月降水量数据。
我需要一份列表，其中包含从2010 - 2020、2021 - 2030等每隔 10 年间隔的降水量平均值。有人可以指导我如何做到这一点以及从哪里开始吗？
您可以计算降水annual sums，然后计算every 10 years的平均值：
library(raster)
p <- stack(file.choose())
# create annual sums
id <- rep(1:1128, each = 12)
p_annual <- stackApply(p,indices = id, fun="sum" )
# use only 2010 to 2100 years
p_annual <- p_annual[[5:94]]
# compute decadal averages
id2 <- rep(1:90,each = 10)
p_decade <- stackApply(p_annual,indices = id2, fun="mean" )