我想分析气候投影数据为不同的rcp在北印度西部地区,干旱的气候。我选择用CORDEX MPI-ESM数据缩减规模。文件名是这样的:一个例子
pr_eas - 44 - _mpi - m - mpi - esm - lr_rcp45_r1i1p1_clmcom cclm5 - 0 - 2 - _v1_mon_208101 - 209012. - nc然而,尽管所有其他变量如温度、风速、相对湿度是在右边,规模,沉淀完全,单位在降水数控文件被指定为公斤m - 2 s - 1,相当于一个降水mm s - 1的高度。
以来我有月度数据,增加降水值86400应该让我天,乘以30.42应该让我几个月。如果我现在选择一个随机,cell-wise求和,我应该得到总年降水量。
结果是一个数量级。这里有一个直方图的细胞显示总年降水量在毫米EAS44域:
我的数据读入rasterbrick R,这给了我一个警告,
警告消息:1:在.getCRSfromGridMap4 (att):无法处理这些部分CRS: grid_north_pole_latitude = 77.6100006103516;grid_north_pole_longitude = -64.7799987792969 2:在.getCRSfromGridMap4 (att):不能创建一个有效的CRS grid_north_pole_latitude = 77.6100006103516;grid_north_pole_longitude = -64.7799987792969…因为它是在曲线的网格。然后我子集第一12个元素和计算值。我在某处读到规模因素和补偿在数控文件,然而,在我的例子中我找不到这样的一个提示。
编辑:数控文件的标题:
美元ncdump pr_eas - 44 - _mpi - m - mpi - esm - lr_rcp45_r1i1p1_clmcom cclm5 - 0 - 2 - _v1_mon_208101 - 209012。数控netcdf pr_eas - 44 - _mpi - m - mpi - esm - lr_rcp45_r1i1p1_clmcom cclm5 - 0 - 2 - _v1_mon_208101 - 209012{维度:bnd = 2;rlon = 203;rlat = 167;时间=无限;/ /目前(120年)变量:char rotated_pole;rotated_pole: grid_mapping_name =“rotated_latitude_longitude”;rotated_pole: grid_north_pole_latitude f = 77.61;rotated_pole: grid_north_pole_longitude f = -64.78;双rlon (rlon); rlon:axis = "X" ; rlon:standard_name = "grid_longitude" ; rlon:long_name = "longitude in rotated pole grid" ; rlon:units = "degrees" ; double lon(rlat, rlon) ; lon:standard_name = "longitude" ; lon:long_name = "longitude" ; lon:units = "degrees_east" ; double rlat(rlat) ; rlat:axis = "Y" ; rlat:standard_name = "grid_latitude" ; rlat:long_name = "latitude in rotated grid" ; rlat:units = "degrees" ; double lat(rlat, rlon) ; lat:standard_name = "latitude" ; lat:long_name = "latitude" ; lat:units = "degrees_north" ; double time(time) ; time:units = "days since 1949-12-01 00:00:00" ; time:standard_name = "time" ; time:long_name = "time" ; time:calendar = "proleptic_gregorian" ; time:bounds = "time_bnds" ; double time_bnds(time, bnds) ; time_bnds:long_name = "time bounds" ; float pr(time, rlat, rlon) ; pr:standard_name = "precipitation_flux" ; pr:long_name = "Precipitation" ; pr:units = "kg m-2 s-1" ; pr:cell_methods = "time: mean" ; pr:coordinates = "lon lat" ; pr:grid_mapping = "rotated_pole" ; pr:missing_value = 1.e+20f ; pr:_FillValue = 1.e+20f ; // global attributes: :Conventions = "CF-1.4" ; :conventionsURL = "http://www.cfconventions.org" ; :creation_date = "2017-09-07T11:34:35" ; :contact = "http://coastmod.hzg.de" ; :experiment_id = "rcp45" ; :driving_model_id = "MPI-M-MPI-ESM-LR" ; :driving_model_ensemble_member = "r1i1p1" ; :driving_experiment_name = "rcp45" ; :frequency = "mon" ; :institute_id = "CLMcom" ; :rcm_version_id = "v1" ; :model_id = "CLMcom-CCLM5-0-2" ; :project_id = "CORDEX" ; :CORDEX_domain = "EAS-44" ; :product = "output" ; :experiment = "rcp45" ; :driving_experiment = "MPI-M-MPI-ESM-LR, rcp45, r1i1p1" ; :Institution = "Helmholtz-Zentrum Geesthacht" ; :references = "http://cordex.clm-community.eu" ; :institution_run_id = "r15m4r4" ; :institution_data_path = "/hpss/arch/gg0302/g260068/CORDEX-EA/r15m4r4" ; :source = "Climate Limited-area Modelling Community (CLM-Community)" ; :title = "CLMcom-CCLM5-0-2 model output prepared for CORDEX rcp45" ; :comment = "Please use the following reference for this climate data: Climate projection performed by Helmholtz-Zentrum Geesthacht in the Climate Limited-area Modelling Community (CLM-Community)" ; data:这是我用于生成R代码中的数据图:
库(光栅)图书馆(purrr)图书馆(dplyr) raster_brick < -砖(' original_data / pr_eas - 44 - _mpi - m - mpi - esm - lr_rcp45_r1i1p1_clmcom cclm5 - 0 - 2 - _v1_mon_205101 - 206012. - nc) * 86400 * 30.42 #第一12个光栅映射到一组位图并将它们合并到一个新的rasterbrick first_year_rasters < - 1:12 % > %地图(~ raster_brick[[]]) % > %砖# cell-wise总和sum_raster < - sum (first_year_rasters)编辑:这里有两个截图ncview的月度数据为2053
显然单位是公斤每平方米,第二。2053年7月的数据是大约0.00375公斤m - 2 - s1,等于一个月降水量0.00375 * 86400 * 30.42 = 9.9米…
这里的截图从2006 - 2100年每月从RCP4.5沉淀值,CMIP5 MPI-ESM-MR模型。我使用了cdo运营商-yearsum,所以这些应该对应的年降水量公斤m - 2 s - 1。乘以86400 * 30.42我仍然到达几米的数量级。
公关变量。 \ endgroup美元