将投影添加到Python中的Rioxarray数据集
我已经从气候数据存储下载了NETCDF，并想为其写下CR，因此我可以将其夹住以作为shapefile。但是，分配CRS时会出现错误。 在我的脚本下方以及正在打印的内容。尝试写CRS后，我会收到此错误：
MissingsPatialDimensionError：找不到Y尺寸（LAT）。数据变量：lon_bnds
# load netcdf with xarray
dset = xr.open_dataset(netcdf_fn)
print(dset)
# add projection system to nc
dset = dset.rio.write_crs("EPSG:4326", inplace=True)
# mask CMIP6 data with shapefile
dset_shp = dset.rio.clip(shp.geometry.apply(mapping), shp.crs)
dset
Out[44]:
<xarray.Dataset>
Dimensions: (time: 1825, bnds: 2, lat: 2, lon: 1)
Coordinates:
* time (time) object 2021-01-01 12:00:00 ... 2025-12-31 12:00:00
* lat (lat) float64 0.4712 1.414
* lon (lon) float64 31.25
spatial_ref int32 0
Dimensions without coordinates: bnds
Data variables:
time_bnds (time, bnds) object ...
lat_bnds (lat, bnds) float64 0.0 0.9424 0.9424 1.885
lon_bnds (lon, bnds) float64 ...
pr (time, lat, lon) float32 ...
Attributes: (12/48)
Conventions: CF-1.7 CMIP-6.2
activity_id: ScenarioMIP
branch_method: standard
branch_time_in_child: 60225.0
branch_time_in_parent: 60225.0
comment: none
...
title: CMCC-ESM2 output prepared for CMIP6
variable_id: pr
variant_label: r1i1p1f1
license: CMIP6 model data produced by CMCC is licensed und...
cmor_version: 3.6.0
tracking_id: hdl:21.14100/0c6732f7-2cdd-4296-99a0-7952b7ca911e
I've downloaded a netcdf from the Climate Data Store and would like to write a CRS to it, so I can clip it for a shapefile. However, I get an error when assigning a CRS.
Below my script and what is being printed. I receive this error after trying to write a crs:
MissingSpatialDimensionError: y dimension (lat) not found. Data variable: lon_bnds
# load netcdf with xarray
dset = xr.open_dataset(netcdf_fn)
print(dset)
# add projection system to nc
dset = dset.rio.write_crs("EPSG:4326", inplace=True)
# mask CMIP6 data with shapefile
dset_shp = dset.rio.clip(shp.geometry.apply(mapping), shp.crs)
dset
Out[44]:
<xarray.Dataset>
Dimensions: (time: 1825, bnds: 2, lat: 2, lon: 1)
Coordinates:
* time (time) object 2021-01-01 12:00:00 ... 2025-12-31 12:00:00
* lat (lat) float64 0.4712 1.414
* lon (lon) float64 31.25
spatial_ref int32 0
Dimensions without coordinates: bnds
Data variables:
time_bnds (time, bnds) object ...
lat_bnds (lat, bnds) float64 0.0 0.9424 0.9424 1.885
lon_bnds (lon, bnds) float64 ...
pr (time, lat, lon) float32 ...
Attributes: (12/48)
Conventions: CF-1.7 CMIP-6.2
activity_id: ScenarioMIP
branch_method: standard
branch_time_in_child: 60225.0
branch_time_in_parent: 60225.0
comment: none
...
title: CMCC-ESM2 output prepared for CMIP6
variable_id: pr
variant_label: r1i1p1f1
license: CMIP6 model data produced by CMCC is licensed und...
cmor_version: 3.6.0
tracking_id: hdl:21.14100/0c6732f7-2cdd-4296-99a0-7952b7ca911e
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当您致电rioxarray登录时
因此，您遇到的问题是RioXarray看到数据集中的四个变量：
其中，
lat_bnds，lon_bnds和pr都有x或y尺寸可以剪切。 Rioxarray并没有为在这种情况下做什么做出一些任意选择，而是通过消息MissingsPatialDimensionError：y Dimension（LAT）提出了错误。数据变量：lon_bnds。这表明在处理变量lon_bnds时，不确定该怎么做，因为它可以找到x维度，而不是ydimension。为了解决这个问题，您有两个选择。首先是在
pr数组上调用clip。这可能是正确的呼叫 - 通常，我建议尽可能只使用数组（不是数据集）进行数据处理，除非您真正的知道您要在数据集中的所有变量上绘制一个操作。在pr上调用剪辑看起来像这样：或者，您可以解决真正应该是坐标的data_variables的问题。您可以使用方法 /a>重新分类非data
data_variables为non-Dimension坐标。在这种情况下：我不确定这是否会完全解决您的问题 - Rioxarray可能在处理坐标时仍会引起此错误。您总是可以放下界限。但是，仅在单个变量上调用此方法的第一种方法将起作用。
When you call the rioxarray accessor
ds.rio.clipusing axr.Datasetrather than axr.DataArray, rioxarray needs to guess which variables in the dataset should be clipped. The method docstring gives the following warning:So the issue you're running into is that rioxarray sees four variables in your dataset:
Of these,
lat_bnds,lon_bnds, andprall havexorydimensions which could conceivably be clipped. Rather than making some arbitrary choice about what to do in this situation, rioxarray is raising an error with the messageMissingSpatialDimensionError: y dimension (lat) not found. Data variable: lon_bnds. This indicates that when processing the variablelon_bnds, it's not sure what to do, because it can find anxdimension but not aydimension.To address this, you have two options. The first is to call
clipon theprarray only. This is probably the right call - generally I'd recommend only doing data processing with Arrays (not Datasets) whenever possible unless you really know you want to map an operation across all variables in the dataset. Calling clip onprwould look like this:Alternatively, you could resolve the issue of having data_variables that really should be coordinates. You can use the method
set_coordsto reclassify the non-datadata_variablesas non-dimensioncoordinates. In this case:I'm not sure if this will completely resolve your issue - it's possible that rioxarray will still raise this error when processing coordinates. You could always drop the bounds, too. But the first method of only calling this on a single variable will work.