我有几个 netcdf 文件,想要删除具有某些特征的数据并保存到新的 netcdf 文件。
该文件具有纬度、经度和时间坐标,以及可变的温度和风。这个想法是,如果风变量小于 6 m/s,则风变量和温度变量的所有信息(该纬度、经度和时间)都将被删除。我怎样才能在Python中做到这一点?
目前我已经拿到了
编辑:文件.nc
from netCDF4 import Dataset
from datetime import *
import os
#-----------------------------------------------------------------------------------------------------------------------------------
path = '/home/Downloads/Arquivos_GOES_2018_OSISAF_NC/'
data_ini = datetime(2018,1,1,1,0,0)
data_end = datetime(2018,7,1,1,0,0)
IDval = 6 # minimo quality_level aceito
#-----------------------------------------------------------------------------------------------------------------------------------
DateTimeNow = data_ini
while DateTimeNow<=data_end:
namefile_net = DateTimeNow.strftime('%Y%m%d%H%M')+'00-OSISAF-L3C_GHRSST-SSTsubskin-GOES16-ssteqc_goes16_'+DateTimeNow.strftime('%Y%m%d_%H%M')+'00-v02.0-fv01.0.nc'
if os.path.isfile(path+namefile_net) == True:
data_net = Dataset(path+namefile_net)
tsm = data_net.variables['sea_surface_temperature'][0,:]-273.15
lat = data_net.variables['lat'][:]
lon = data_net.variables['lon'][:]
wind = data_net.variables['wind_speed'][0,:]
wind = np.where(qlv.mask==True,-1.0, qlv)
lon, lat = np.meshgrid(lon, lat) # criar uma matriz com lat e lon
tsm_area = tsm[yid,xid]
lon_area = lon[yid,xid]
lat_area = lat[yid,xid]
wind_area = wind[yid,xid]
if np.sum(wind>=IDval) > 0:
lon_area = np.where(qlv_area<IDval,-999.9,lon_area)
lat_area = np.where(qlv_area<IDval,-999.9,lat_area)
yid2, xid2 = seach_point(lon_area, lat_area, lon_point, lat_point)
```
最佳答案
看来你的数据已经在 numpy 中了。这是一个想法(没有你的 cdf,所以让我们假设第 3 列是风):
>>> y = np.zeros((4,4))
>>> data = np.zeros((4,4))
>>> data[:,3] = [1,12, 4, 9]
>>> data
array([[ 0., 0., 0., 1.],
[ 0., 0., 0., 12.],
[ 0., 0., 0., 4.],
[ 0., 0., 0., 9.]])
>>> data[ data[:,3] > 6]
array([[ 0., 0., 0., 12.],
[ 0., 0., 0., 9.]])
关于Python 删除所有特定变量的坐标 - netcdf,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/58122777/