id,node_id,number,title,user,state,locked,assignee,milestone,comments,created_at,updated_at,closed_at,author_association,active_lock_reason,draft,pull_request,body,reactions,performed_via_github_app,state_reason,repo,type
894497993,MDU6SXNzdWU4OTQ0OTc5OTM=,5331,AttributeError using map_blocks with dask 2021.05.0,9010180,closed,0,,,3,2021-05-18T15:18:53Z,2021-05-19T08:01:07Z,2021-05-19T08:01:07Z,NONE,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

Please be concise with code posted. See guidelines below on how to provide a good bug report:

- Craft Minimal Bug Reports: http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve

Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
-->

**What happened**:

In an environment with xarray 0.18.0 and dask 2021.05.0 installed, I saved a dataset using `to_zarr`, opened it again using `open_zarr`, and called `map_blocks` on one of its variables. I got the following traceback:

```
Traceback (most recent call last):
  File ""/home/pont/./dasktest2.py"", line 12, in <module>
    ds2.myvar.map_blocks(lambda block: block)
  File ""/home/pont/loc/envs/xcube-repos/lib/python3.9/site-packages/xarray/core/dataarray.py"", line 3770, in map_blocks
    return map_blocks(func, self, args, kwargs, template)
  File ""/home/pont/loc/envs/xcube-repos/lib/python3.9/site-packages/xarray/core/parallel.py"", line 565, in map_blocks
    data = dask.array.Array(
  File ""/home/pont/loc/envs/xcube-repos/lib/python3.9/site-packages/dask/array/core.py"", line 1159, in __new__
    if layer.collection_annotations is None:
AttributeError: 'dict' object has no attribute 'collection_annotations'
```

**What you expected to happen**:

I expected `map_blocks` to complete successfully.

**Minimal Complete Verifiable Example**:

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

ds1 = xr.Dataset({
    ""myvar"": ((""x""), np.zeros(10)),
    ""x"": (""x"", np.arange(10)),
})   
ds1.to_zarr(""test.zarr"", mode=""w"")
ds2 = xr.open_zarr(""test.zarr"")
ds2.myvar.map_blocks(lambda block: block)
```

**Anything else we need to know?**:

I wasn't sure whether to report this issue with dask or xcube. With dask 2021.04.1 the example runs without error, and it seems that [dask PR 7309](https://github.com/dask/dask/pull/7309) introduced the breaking change. But my understanding of xarray's `map_blocks` implementation isn't sufficient to figure out where exactly the bug lies.

**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>
INSTALLED VERSIONS
------------------
commit: None
python: 3.9.4 | packaged by conda-forge | (default, May 10 2021, 22:13:33) 
[GCC 9.3.0]
python-bits: 64
OS: Linux
OS-release: 5.8.0-53-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8
libhdf5: None
libnetcdf: None

xarray: 0.18.0
pandas: 1.2.4
numpy: 1.20.2
scipy: None
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: 2.8.1
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2021.05.0
distributed: 2021.05.0
matplotlib: None
cartopy: None
seaborn: None
numbagg: None
pint: None
setuptools: 49.6.0.post20210108
pip: 21.1.1
conda: None
pytest: None
IPython: None
sphinx: None
</details>
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844712857,MDU6SXNzdWU4NDQ3MTI4NTc=,5093,"open_dataset uses cftime, not datetime64, when calendar attribute is ""Gregorian""",9010180,closed,0,,,2,2021-03-30T15:12:09Z,2021-04-20T14:17:42Z,2021-04-18T10:17:08Z,NONE,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.

Please be concise with code posted. See guidelines below on how to provide a good bug report:

- Craft Minimal Bug Reports: http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve

Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
-->

**What happened**:

I used `xarray.open_dataset` to open a NetCDF file whose `time` coordinate had the `calendar` attribute set to `Gregorian`. All dates were within the Timestamp-valid range.

The resulting dataset represented the `time` co-ordinate as a
`cftime._cftime.DatetimeGregorian`.

**What you expected to happen**:

I expected the dataset to represent the `time` co-ordinate as a `datetime64[ns]`, as documented [here](http://xarray.pydata.org/en/stable/generated/xarray.open_dataset.html) and [here](http://xarray.pydata.org/en/stable/weather-climate.html#non-standard-calendars-and-dates-outside-the-timestamp-valid-range).

**Minimal Complete Verifiable Example**:

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

def print_time_type(dataset):
    print(dataset.time.dtype, type(dataset.time[0].item()))

da = xr.DataArray(
    data=[32, 16, 8],
    dims=[""time""],
    coords=dict(
        time=pd.date_range(""2014-09-06"", periods=3),
        reference_time=pd.Timestamp(""2014-09-05""),
    ),
)


# Create dataset and confirm type of time
ds1 = xr.Dataset({""myvar"": da})
print_time_type(ds1)  # prints ""datetime64[ns]"" <class 'int'>

# Manually set time attributes to ""Gregorian"" rather
# than default ""proleptic_gregorian"".
ds1.time.encoding[""calendar""] = ""Gregorian""
ds1.reference_time.encoding[""calendar""] = ""Gregorian""
ds1.to_netcdf(""test-capitalized.nc"")

ds2 = xr.open_dataset(""test-capitalized.nc"")
print_time_type(ds2)
# prints ""object <class 'cftime._cftime.DatetimeGregorian'>""

# Workaround: add ""Gregorian"" to list of standard calendars.
xr.coding.times._STANDARD_CALENDARS.add(""Gregorian"")
ds3 = xr.open_dataset(""test-capitalized.nc"")
print_time_type(ds3)  # prints ""datetime64[ns]"" <class 'int'>
```

**Anything else we need to know?**:

The [documentation for the `use_cftime` parameter of `open_dataset`](http://xarray.pydata.org/en/stable/generated/xarray.open_dataset.html) says:

> If None (default), attempt to decode times to `np.datetime64[ns]` objects; if this is not possible, decode times to `cftime.datetime` objects.

In practice, we are getting some `cftime.datetime`s even for times which are interpretable and representable as `np.datetime64[ns]`s. In particular, we have some NetCDF files in which the `time` variable has a `calendar` attribute with a value of `Gregorian` (with a capital ‘G’). CF conventions [allow this](http://cfconventions.org/Data/cf-conventions/cf-conventions-1.8/cf-conventions.html#_attributes):

> When this standard defines string attributes that may take various prescribed values, the possible values are generally given in lower case. However, applications programs should not be sensitive to case in these attributes.

However, xarray regards `Gregorian` as a non-standard calendar and falls back to `cftime.datetime`. If (as in the example) `Gregorian` is added to `xr.coding.times._STANDARD_CALENDARS`, the times are read as `np.datetime64[ns]`s.

Suggested fix: in [`xarray.coding.times._decode_datetime_with_pandas`](https://github.com/pydata/xarray/blob/45b4436bd5a82e7020357cf681b13067a8dd59e9/xarray/coding/times.py#L169), change ‘`if calendar not in _STANDARD_CALENDARS:`’ to ‘`if calendar.lower() not in _STANDARD_CALENDARS:`’.

**Environment**:

<details><summary>Output of <tt>xr.show_versions()</tt></summary>
INSTALLED VERSIONS
------------------
commit: None
python: 3.9.2 | packaged by conda-forge | (default, Feb 21 2021, 05:02:46) 
[GCC 9.3.0]
python-bits: 64
OS: Linux
OS-release: 5.8.0-48-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8
libhdf5: 1.10.6
libnetcdf: 4.7.4

xarray: 0.17.1.dev39+g45b4436b
pandas: 1.2.3
numpy: 1.20.2
scipy: None
netCDF4: 1.5.6
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.4.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: None
distributed: None
matplotlib: None
cartopy: None
seaborn: None
numbagg: None
pint: None
setuptools: 49.6.0.post20210108
pip: 21.0.1
conda: None
pytest: None
IPython: None
sphinx: None

<!-- Paste the output here xr.show_versions() here -->

</details>

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