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社区首页 >问答首页 >基于ncks的4Dnetcdf变量的超实验室

问基于ncks的4Dnetcdf变量的超实验室
EN

Stack Overflow用户
提问于 2019-01-25 14:30:48
回答 1查看 422关注 0票数 0

我有一个大的netcdf文件，其中我只需要某些数据。因此，我希望使用ncks创建这个netcdf文件的细分。netcdf文件如下：

代码语言：javascript
复制
Source:
           F:\LECOB\Model\20091208_195356.nc
Format:
           64bit
Global Attributes:
           Model = 's26.bobshelf.20141113'
           Title = 'S-NWM_BiP'
Dimensions:
           ni_t = 682
           nj_t = 712
           nk_t = 29
           time = 1     (UNLIMITED)
           ni_w = 682
           nj_w = 712
           nk_w = 30
           ni_u = 681
           nj_u = 712
           nk_u = 29
           ni_v = 682
           nj_v = 711
           nk_v = 29
           ni_f = 681
           nj_f = 711
           nk_f = 29
Variables:
    time 
           Size:       1x1
           Dimensions: time
           Datatype:   double
           Attributes:
                       units         = 'seconds from 2009-dec-08 17:00:14'
                       long_name     = 'time'
                       standard_name = 'time'
                       time_origin   = '2009-dec-08 17:00:14'
                       calendar      = 'gregorian'
                       content       = 'T'
                       axis          = 'T'
                       associate     = 'undefined'
    ni_t 
           Size:       682x1
           Dimensions: ni_t
           Datatype:   single
           Attributes:
                       long_name     = 'x_grid_index'
                       standard_name = 'x_grid_index'
                       content       = 'X'
                       axis          = 'X'
    nj_t 
           Size:       712x1
           Dimensions: nj_t
           Datatype:   single
           Attributes:
                       long_name     = 'y_grid_index'
                       standard_name = 'y_grid_index'
                       content       = 'Y'
                       axis          = 'Y'
    nk_t 
           Size:       29x1
           Dimensions: nk_t
           Datatype:   single
           Attributes:
                       long_name     = 'z_grid_index'
                       standard_name = 'z_grid_index'
                       content       = 'Z'
                       axis          = 'Z'
                       positive      = 'up'
    ni_w 
           Size:       682x1
           Dimensions: ni_w
           Datatype:   single
           Attributes:
                       long_name     = 'x_grid_index_at_w_location'
                       standard_name = 'x_grid_index_at_w_location'
                       content       = 'X'
                       axis          = 'X'
    nj_w 
           Size:       712x1
           Dimensions: nj_w
           Datatype:   single
           Attributes:
                       long_name     = 'y_grid_index_at_w_location'
                       standard_name = 'y_grid_index_at_w_location'
                       content       = 'Y'
                       axis          = 'Y'
    nk_w 
           Size:       30x1
           Dimensions: nk_w
           Datatype:   single
           Attributes:
                       long_name     = 'z_grid_index_at_w_location'
                       standard_name = 'z_grid_index_at_w_location'
                       content       = 'Z'
                       axis          = 'Z'
                       positive      = 'up'
    ni_u 
           Size:       681x1
           Dimensions: ni_u
           Datatype:   single
           Attributes:
                       long_name     = 'x_grid_index_at_u_location'
                       standard_name = 'x_grid_index_at_u_location'
                       content       = 'X'
                       axis          = 'X'
    nj_u 
           Size:       712x1
           Dimensions: nj_u
           Datatype:   single
           Attributes:
                       long_name     = 'y_grid_index_at_u_location'
                       standard_name = 'y_grid_index_at_u_location'
                       content       = 'Y'
                       axis          = 'Y'
    nk_u 
           Size:       29x1
           Dimensions: nk_u
           Datatype:   single
           Attributes:
                       long_name     = 'z_grid_index_at_u_location'
                       standard_name = 'z_grid_index_at_u_location'
                       content       = 'Z'
                       axis          = 'Z'
                       positive      = 'up'
    ni_v 
           Size:       682x1
           Dimensions: ni_v
           Datatype:   single
           Attributes:
                       long_name     = 'x_grid_index_at_v_location'
                       standard_name = 'x_grid_index_at_v_location'
                       content       = 'X'
                       axis          = 'X'
    nj_v 
           Size:       711x1
           Dimensions: nj_v
           Datatype:   single
           Attributes:
                       long_name     = 'y_grid_index_at_v_location'
                       standard_name = 'y_grid_index_at_v_location'
                       content       = 'Y'
                       axis          = 'Y'
    nk_v 
           Size:       29x1
           Dimensions: nk_v
           Datatype:   single
           Attributes:
                       long_name     = 'z_grid_index_at_v_location'
                       standard_name = 'z_grid_index_at_v_location'
                       content       = 'Z'
                       axis          = 'Z'
                       positive      = 'up'
    ssh  
           Size:       682x712x1
           Dimensions: ni_t,nj_t,time
           Datatype:   single
           Attributes:
                       units         = 'm'
                       long_name     = 'sea surface height above geoid'
                       standard_name = 'sea_surface_height_above_geoid'
                       content       = 'TYX'
                       associate     = 'time latitude_t longitude_t'
                       coordinates   = 'time latitude_t longitude_t'
                       _FillValue    = -9999
    CFL2D
           Size:       682x712x1
           Dimensions: ni_t,nj_t,time
           Datatype:   single
           Attributes:
                       units         = 's'
                       long_name     = 'CFL2D'
                       standard_name = 'CFL2D'
                       content       = 'TYX'
                       associate     = 'time latitude_t longitude_t'
                       coordinates   = 'time latitude_t longitude_t'
                       _FillValue    = -9999
    tem  
           Size:       682x712x29x1
           Dimensions: ni_t,nj_t,nk_t,time
           Datatype:   single
           Attributes:
                       units         = 'degrees_Celsius'
                       long_name     = 'sea_water_potential_temperature'
                       standard_name = 'sea_water_potential_temperature'
                       content       = 'TZYX'
                       associate     = 'time depth_t latitude_t longitude_t'
                       coordinates   = 'time depth_t latitude_t longitude_t'
                       _FillValue    = -9999
                       positive      = 'up'
    sal  
           Size:       682x712x29x1
           Dimensions: ni_t,nj_t,nk_t,time
           Datatype:   single
           Attributes:
                       units         = '1e-3'
                       long_name     = 'sea water salinity'
                       standard_name = 'sea_water_salinity'
                       content       = 'TZYX'
                       associate     = 'time depth_t latitude_t longitude_t'
                       coordinates   = 'time depth_t latitude_t longitude_t'
                       _FillValue    = -9999
                       positive      = 'up'
    vel_u
           Size:       681x712x29x1
           Dimensions: ni_u,nj_u,nk_u,time
           Datatype:   single
           Attributes:
                       units         = 'm s-1'
                       long_name     = 'sea_water_x_velocity_at_u_location'
                       standard_name = 'sea_water_x_velocity_at_u_location'
                       content       = 'TZYX'
                       associate     = 'time depth_u latitude_u longitude_u'
                       coordinates   = 'time depth_u latitude_u longitude_u'
                       _FillValue    = -9999
                       positive      = 'up'
    vel_v
           Size:       682x711x29x1
           Dimensions: ni_v,nj_v,nk_v,time
           Datatype:   single
           Attributes:
                       units         = 'm s-1'
                       long_name     = 'sea_water_y_velocity_at_v_location'
                       standard_name = 'sea_water_y_velocity_at_v_location'
                       content       = 'TZYX'
                       associate     = 'time depth_v latitude_v longitude_v'
                       coordinates   = 'time depth_v latitude_v longitude_v'
                       _FillValue    = -9999
                       positive      = 'up'
    kh   
           Size:       682x712x30x1
           Dimensions: ni_w,nj_w,nk_w,time
           Datatype:   single
           Attributes:
                       units         = 'm2/s'
                       long_name     = 'kh'
                       standard_name = 'kh'
                       content       = 'TZYX'
                       associate     = 'time depth_w latitude_t longitude_t'
                       coordinates   = 'time depth_w latitude_t longitude_t'
                       _FillValue    = -9999
                       positive      = 'up'
    tken 
           Size:       682x712x30x1
           Dimensions: ni_w,nj_w,nk_w,time
           Datatype:   single
           Attributes:
                       units         = '(m/s)2'
                       long_name     = 'tken'
                       standard_name = 'tken'
                       content       = 'TZYX'
                       associate     = 'time depth_w latitude_t longitude_t'
                       coordinates   = 'time depth_w latitude_t longitude_t'
                       _FillValue    = -9999
                       positive      = 'up'
    w    
           Size:       682x712x30x1
           Dimensions: ni_w,nj_w,nk_w,time
           Datatype:   single
           Attributes:
                       units         = 'm s-1'
                       long_name     = 'vertical_sea_water_velocity_at_w_location'
                       standard_name = 'vertical_sea_water_velocity_at_w_location'
                       content       = 'TZYX'
                       associate     = 'time depth_w latitude_t longitude_t'
                       coordinates   = 'time depth_w latitude_t longitude_t'
                       _FillValue    = -9999
                       positive      = 'up'

现在我对4D变量vel_u (ni_u,nj_u,nk_u,time)感兴趣。我想提取ni_u 151到152，nj_u 234到235，nk_u everything和time everything。这个问题帮助我完成了NCO: Extract a variable from NetCDF file using NCO ncks，下面的链接http://nco.sourceforge.net/nco.html#crd也使用了这些问题，我在我的linux计算机上尝试了以下代码：

代码语言：javascript
复制
ncks -C -F -d vel_u,151,152,1 20091208_195356.nc test.nc

这给了我两个问题：

  1. 它复制所有变量，而不仅仅是vel_u，即使我使用了问题NCO: Extract a variable from NetCDF file using NCO ncks中所建议的-C
  2. 我不知道如何指定只使用234-235维nj_u

那么，我如何将ni_u变量的这些部分( nj_u 151到152，nj_u 234到235 )放在test.nc文件中呢？

任何回答都是非常感谢的！

ncks
netcdf
EN

回答 1

Stack Overflow用户

回答已采纳

发布于 2019-01-25 16:04:51

我想我找到了答案：-d是维度的，-v是变量的，我的问题的答案如下：

代码语言：javascript
复制
ncks -C -F -d nj_u,234,235,1 -d ni_u,151,152,1 -v vel_u 20091208_195356.nc test.nc

-C，以确保只复制变量vel_u

-F，因为打车应该从1开始，而不是0

-d NameDimension，Min，Max，Step

-v NameVariable

input.nc

output.nc

这似乎给了我我想要的。

票数 2
EN
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：

https://stackoverflow.com/questions/54367298

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