The example below is only based on Variable and the cf encode/decode variable functions.

```python import xarray as xr import numpy as np

create DataArray

times = [np.datetime64("2000-01-01", "ns"), np.datetime64("NaT")] da = xr.DataArray(times, dims=["time"], name="foo") da.encoding["dtype"] = np.float64 da.encoding["_FillValue"] = 20.0

extract Variable

source_var = da.variable print("---------- source_var ------------------") print(source_var) print(source_var.encoding)

encode Variable

encoded_var = xr.conventions.encode_cf_variable(source_var) print("\n---------- encoded_var ------------------") print(encoded_var)

decode Variable

decoded_var = xr.conventions.decode_cf_variable("foo", encoded_var) print("\n---------- decoded_var ------------------") print(decoded_var.load()) ```

```python /home/kai/miniconda/envs/xarray_311/lib/python3.11/site-packages/xarray/coding/times.py:618: RuntimeWarning: invalid value encountered in cast int_num = np.asarray(num, dtype=np.int64) /home/kai/miniconda/envs/xarray_311/lib/python3.11/site-packages/xarray/coding/times.py:254: RuntimeWarning: invalid value encountered in cast flat_num_dates_ns_int = (flat_num_dates * _NS_PER_TIME_DELTA[delta]).astype( /home/kai/miniconda/envs/xarray_311/lib/python3.11/site-packages/xarray/coding/times.py:254: RuntimeWarning: invalid value encountered in cast flat_num_dates_ns_int = (flat_num_dates * _NS_PER_TIME_DELTA[delta]).astype(

---------- source_var ------------------ <xarray.Variable (time: 2)> array(['2000-01-01T00:00:00.000000000', 'NaT'], dtype='datetime64[ns]') {'dtype': <class 'numpy.float64'>, '_FillValue': 20.0} dtype num float64

---------- encoded_var ------------------ <xarray.Variable (time: 2)> array([ 0., 20.]) Attributes: units: days since 2000-01-01 00:00:00 calendar: proleptic_gregorian _FillValue: 20.0

---------- decoded_var ------------------ <xarray.Variable (time: 2)> array(['2000-01-01T00:00:00.000000000', 'NaT'], dtype='datetime64[ns]') {'_FillValue': 20.0, 'units': 'days since 2000-01-01 00:00:00', 'calendar': 'proleptic_gregorian', 'dtype': dtype('float64')} ```

@spencerkclark With current master I get the following RuntimeWarning running your code example:

• on encoding (calling to_netcdf()):

python /home/kai/miniconda/envs/xarray_311/lib/python3.11/site-packages/xarray/coding/times.py:618: RuntimeWarning: invalid value encountered in cast int_num = np.asarray(num, dtype=np.int64)

• on decoding (calling open_dataset()):

python /home/kai/miniconda/envs/xarray_311/lib/python3.11/site-packages/xarray/coding/times.py:254: RuntimeWarning: invalid value encountered in cast flat_num_dates_ns_int = (flat_num_dates * _NS_PER_TIME_DELTA[delta]).astype( /home/kai/miniconda/envs/xarray_311/lib/python3.11/site-packages/xarray/coding/times.py:254: RuntimeWarning: invalid value encountered in cast flat_num_dates_ns_int = (flat_num_dates * _NS_PER_TIME_DELTA[delta]).astype(

The latter was discussed in #7098 (casting float64 to int64), the former was aimed to be resolved with this PR.

I'll try to create a test case using Variable and the respective encoding/decoding functions without involving IO (per your suggestion @spencerkclark).

Thanks @spencerkclark for taking the time. NaN has been written to disk (as you assumed). Let's have another try next week.

@dcherian You were right from the beginning, changing order for decoding and handling _FillValue in CFDatetimeCoder seems to be one working solution with minimal code changes.

If the CI is happy I'll add tests to cover for the nanosecond issues in #7817.

Thanks for the heads-up, @spencerkclark. No worries, I need to apply some changes anyway as it turns out.

All tests have passed. Rebased now on latest main. The issue described in #7817 is resolved. Ready for first reviews.

I've reset the order of coders to the initial behaviour. Instead the times are special cased in the CFMaskCoder. Locally it works, but I'll only trust the CI.

@spencerkclark I'd appreciate if you could have a look here. All but one test pass, but I can't immediately see what that test is doing. Looks like mismatched dtypes on the attributes. If you have any suggestions how to possibly improve, please let me know. I've not added tests here, yet.