netcdf (.nc) 文件只有 -999 值？

Question

我正在尝试分析来自 https://imdpune.gov.in/Clim_Pred_LRF_New/Grided_Data_Download.html 的降雨数据，特别是“网格化降雨 (0.25 x 0.25) NetCDF”文件。

我使用netCDF4 加载数据，但我得到了这个奇怪的结果：

from netCDF4 import Dataset
import numpy as np 

path = '2013.nc' 
f = Dataset(path ,'r')
rain = np.array(f.variables['RAINFALL'][:,:,:])

print(rain[0][0])

输出：

[-999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999. -999.
 -999. -999. -999.]

注意：这个特定文件没有问题，因为我每年的数据都得到相同的结果。你可以自己试试看。

我在 python 中加载数据是否错误是我下载的数据有问题吗？ latitude 和 longitude 变量并没有给我这个问题

Answer 1

from pathlib import Path
import numpy as np
import matplotlib.pyplot as plt

# file import 
path = Path('../../Downloads/')
file = 'Clim_Pred_LRF_New_RF25_IMD0p252013.nc' 
f = Dataset(path / file, 'r')

# select variable "Rainfall"
rain = np.array(f.variables['RAINFALL'][:,:,:]) 
# assign NaN value
rain[rain==-999.] = np.nan  

# plot dataset for selected date (2013-01-18)    
plt.pcolormesh(rain[17])
plt.colorbar()

数据看起来不错。

但是看看雨的形状：

print(rain.shape)
(365, 129, 135) 
# --> (days, latitude, longitude).

使用rain[0][0]，您将选择第一个时间步长 (Jan-01) 和第一个纬度 (6.5)，这将返回一个包含 NaN 值的一维数组，因为所有像素都在印度之外。使用 0 选择第二维和第三维将始终仅返回带有 -999 的数组。你可以试试rain[17][100]！

print(rain[17][100]
array([        nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,  1.2962954 ,  0.99620295,  2.705826  ,
        9.772656  , 11.187045  ,  0.        ,  3.0871496 ,  5.298688  ,
       18.108587  , 34.280876  , 35.034836  , 41.41929   , 38.952507  ,
       63.49905   , 92.398125  , 92.92495   , 80.57031   , 63.660515  ,
       45.413662  ,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan,
               nan,         nan,         nan,         nan,         nan],
      dtype=float32)