问题描述
我正在尝试下载一堆GOES-16辐射度数据，并在xarray中一起打开它们，以使用xr.open_mfdataset()函数进行分析。这些netcdf文件的坐标为t，这是我试图用作连接的时间戳，但是当我尝试执行此操作时却出现了错误ValueError: Could not find any dimension coordinates to use to order the datasets for concatenation。这是我的代码，以及下载两个示例.nc文件的链接。
使用以下命令下载两个文件：
wget https://noaa-goes16.s3.amazonaws.com/ABI-L1b-RadF/2019/141/02/OR_ABI-L1b-RadF-M6C14_G16_s20191410240370_e20191410250078_c20191410250143.nc
wget https://noaa-goes16.s3.amazonaws.com/ABI-L1b-RadF/2019/141/03/OR_ABI-L1b-RadF-M6C14_G16_s20191410310370_e20191410320078_c20191410320142.nc
和代码：
import xarray as xr
ds_sst = xr.open_mfdataset("OR_ABI-L1b-RadF*nc",concat_dim='t',combine='by_coords')
我能做些什么使我可以同时打开几个文件吗？
解决方法
改为使用combine='nested'。
从Xarray documentation开始，按座标组合：
尝试通过使用以下方法自动将给定的数据集神奇地合并为一个 尺寸坐标。
't'不是尺寸坐标，因此xarray魔术在这种情况下不起作用，因为xarray的combine_by_coords在导入的netcdfs之间寻找匹配的尺寸坐标。
在这种情况下，您需要更具体：使用combine = 'nested'并用concat_dim='t'指定新的尺寸名称。由于已经存在一个名为“ t”的坐标，xarray会自动将其提升为尺寸坐标。
ds_sst = xr.open_mfdataset("OR_ABI-L1b-RadF*nc",concat_dim='t',combine='nested')
结果数据集如下所示。
<xarray.Dataset>
Dimensions: (band: 1,num_star_looks: 24,number_of_image_bounds: 2,number_of_time_bounds: 2,t: 2,x: 5424,y: 5424)
Coordinates:
band_wavelength_star_look (num_star_looks) float32 dask.array<chunksize=(24,),meta=np.ndarray>
x_image float32 0.0
y_image float32 0.0
band_wavelength (band) float32 dask.array<chunksize=(1,meta=np.ndarray>
band_id (band) int8 dask.array<chunksize=(1,meta=np.ndarray>
t_star_look (num_star_looks) datetime64[ns] dask.array<chunksize=(24,meta=np.ndarray>
* y (y) float32 0.151844 ... -0.151844
* x (x) float32 -0.151844 ... 0.151844
* t (t) datetime64[ns] 2019-05-21T02:45:22.400760064 2019-05-21T03:15:22.406056960
Dimensions without coordinates: band,num_star_looks,number_of_image_bounds,number_of_time_bounds
Data variables:
Rad (t,y,x) float32 dask.array<chunksize=(1,5424,5424),meta=np.ndarray>
DQF (t,meta=np.ndarray>
time_bounds (t,number_of_time_bounds) datetime64[ns] dask.array<chunksize=(1,2),meta=np.ndarray>
goes_imager_projection (t) int32 -2147483647 -2147483647
y_image_bounds (t,number_of_image_bounds) float32 dask.array<chunksize=(1,meta=np.ndarray>
x_image_bounds (t,meta=np.ndarray>
nominal_satellite_subpoint_lat (t) float64 0.0 0.0
nominal_satellite_subpoint_lon (t) float64 -75.2 -75.2
nominal_satellite_height (t) float64 3.579e+04 3.579e+04
geospatial_lat_lon_extent (t) float32 9.96921e+36 9.96921e+36
yaw_flip_flag (t) float64 0.0 0.0
esun (t) float64 nan nan
kappa0 (t) float64 nan nan
planck_fk1 (t) float64 8.51e+03 8.51e+03
planck_fk2 (t) float64 1.286e+03 1.286e+03
planck_bc1 (t) float64 0.2252 0.2252
planck_bc2 (t) float64 0.9992 0.9992
valid_pixel_count (t) float64 2.305e+07 2.305e+07
missing_pixel_count (t) float64 268.0 290.0
saturated_pixel_count (t) float64 0.0 0.0
undersaturated_pixel_count (t) float64 0.0 0.0
focal_plane_temperature_threshold_exceeded_count (t) float64 0.0 0.0
min_radiance_value_of_valid_pixels (t) float64 8.217 8.472
max_radiance_value_of_valid_pixels (t) float64 125.5 123.2
mean_radiance_value_of_valid_pixels (t) float64 82.01 81.96
std_dev_radiance_value_of_valid_pixels (t) float64 24.64 24.53
maximum_focal_plane_temperature (t) float64 62.12 62.12
focal_plane_temperature_threshold_increasing (t) float64 81.0 81.0
focal_plane_temperature_threshold_decreasing (t) float64 81.0 81.0
percent_uncorrectable_L0_errors (t) float64 0.0 0.0
earth_sun_distance_anomaly_in_AU (t) float64 1.012 1.012
algorithm_dynamic_input_data_container (t) int32 -2147483647 -2147483647
processing_parm_version_container (t) int32 -2147483647 -2147483647
algorithm_product_version_container (t) int32 -2147483647 -2147483647
star_id (t,num_star_looks) float32 dask.array<chunksize=(1,24),meta=np.ndarray>
Attributes:
naming_authority: gov.nesdis.noaa
Conventions: CF-1.7
Metadata_Conventions: Unidata Dataset Discovery v1.0
standard_name_vocabulary: CF Standard Name Table (v35,20 July 2016)
institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...
project: GOES
production_site: WCDAS
production_environment: OE
spatial_resolution: 2km at nadir
orbital_slot: GOES-East
platform_ID: G16
instrument_type: GOES R Series Advanced Baseline Imager
scene_id: Full Disk
instrument_ID: FM1
title: ABI L1b Radiances
summary: Single emissive band ABI L1b Radiance Products...
keywords: SPECTRAL/ENGINEERING > INFRARED WAVELENGTHS > ...
keywords_vocabulary: NASA Global Change Master Directory (GCMD) Ear...
iso_series_metadata_id: a70be540-c38b-11e0-962b-0800200c9a66
license: Unclassified data. Access is restricted to ap...
processing_level: National Aeronautics and Space Administration ...
cdm_data_type: Image
dataset_name: OR_ABI-L1b-RadF-M6C14_G16_s20191410240370_e201...
production_data_source: Realtime
timeline_id: ABI Mode 6
date_created: 2019-05-21T02:50:14.3Z
time_coverage_start: 2019-05-21T02:40:37.0Z
time_coverage_end: 2019-05-21T02:50:07.8Z
id: abb3657a-03c0-47a9-a1ba-f3196c07c5a9
或者，您可以定义一个将坐标“ t”提升为尺寸坐标并将其传递给preprocess中的open_mfdataset自变量的函数。在将每个导入的NetCDF与其他导入的NetCDF连接之前，将应用此功能。
def preprocessing(ds):
return ds.expand_dims(dim='t')
ds_sst = xr.open_mfdataset("OR_ABI-L1b-RadF*nc",combine='by_coords',preprocess = preprocessing)
结果与上面相同。