Task list for watershed/burn index projects

• First satpy tutorial and put before and after geotiffs into satpy xarray
• Satpy resample to resample both images on the same grid
• Qualitative/quantitative check on how good the burn ratio did.
• cloud masking
• compare two different channel

-[ ]Define which packages to take from CMIP6 catalogue for past and future precipitation figures
-[ ] Slice Vancouver and get raw numbers for precipitation values
-[ ] Contour Precipitation Values using Matplotlib

this only needs to be created once

gcs = gcsfs.GCSFileSystem(token='anon')

get the path to a specific zarr store (the first one from the dataframe above)

zstore = df_ta_ncar.zstore.values[-1]

create a mutable-mapping-style interface to the store

mapper = gcs.get_mapper(zstore)

open it using xarray and zarr

ds = xr.open_zarr(mapper, consolidated=True)
ds

OutOfBoundsDatetime Traceback (most recent call last)
c:\users\andersen\miniconda37\lib\site-packages\xarray\coding\times.py in decode_cf_datetime(num_dates, units, calendar, use_cftime)
156 try:
--> 157 dates = _decode_datetime_with_pandas(flat_num_dates, units, calendar)
158 except (OutOfBoundsDatetime, OverflowError):

c:\users\andersen\miniconda37\lib\site-packages\xarray\coding\times.py in _decode_datetime_with_pandas(flat_num_dates, units, calendar)
104 "Cannot decode times from a non-standard calendar, {!r}, using "
--> 105 "pandas.".format(calendar)
106 )

OutOfBoundsDatetime: Cannot decode times from a non-standard calendar, 'noleap', using pandas.

During handling of the above exception, another exception occurred:

ModuleNotFoundError Traceback (most recent call last)
c:\users\andersen\miniconda37\lib\site-packages\xarray\coding\times.py in _decode_cf_datetime_dtype(data, units, calendar, use_cftime)
76 try:
---> 77 result = decode_cf_datetime(example_value, units, calendar, use_cftime)
78 except Exception:

c:\users\andersen\miniconda37\lib\site-packages\xarray\coding\times.py in decode_cf_datetime(num_dates, units, calendar, use_cftime)
159 dates = _decode_datetime_with_cftime(
--> 160 flat_num_dates.astype(np.float), units, calendar
161 )

c:\users\andersen\miniconda37\lib\site-packages\xarray\coding\times.py in _decode_datetime_with_cftime(num_dates, units, calendar)
93 def _decode_datetime_with_cftime(num_dates, units, calendar):
---> 94 import cftime
95

ModuleNotFoundError: No module named 'cftime'

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last)
in
9
10 # open it using xarray and zarr
---> 11 ds = xr.open_zarr(mapper, consolidated=False)
12 ds

c:\users\andersen\miniconda37\lib\site-packages\xarray\backends\zarr.py in open_zarr(store, group, synchronizer, chunks, decode_cf, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, consolidated, overwrite_encoded_chunks, **kwargs)
596 consolidated=consolidated,
597 )
--> 598 ds = maybe_decode_store(zarr_store)
599
600 # auto chunking needs to be here and not in ZarrStore because variable

c:\users\andersen\miniconda37\lib\site-packages\xarray\backends\zarr.py in maybe_decode_store(store, lock)
579 concat_characters=concat_characters,
580 decode_coords=decode_coords,
--> 581 drop_variables=drop_variables,
582 )
583

c:\users\andersen\miniconda37\lib\site-packages\xarray\conventions.py in decode_cf(obj, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables, use_cftime)
583 decode_coords,
584 drop_variables=drop_variables,
--> 585 use_cftime=use_cftime,
586 )
587 ds = Dataset(vars, attrs=attrs)

c:\users\andersen\miniconda37\lib\site-packages\xarray\conventions.py in decode_cf_variables(variables, attributes, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables, use_cftime)
492 decode_times=decode_times,
493 stack_char_dim=stack_char_dim,
--> 494 use_cftime=use_cftime,
495 )
496 if decode_coords:

c:\users\andersen\miniconda37\lib\site-packages\xarray\conventions.py in decode_cf_variable(name, var, concat_characters, mask_and_scale, decode_times, decode_endianness, stack_char_dim, use_cftime)
334 times.CFDatetimeCoder(use_cftime=use_cftime),
335 ]:
--> 336 var = coder.decode(var, name=name)
337
338 dimensions, data, attributes, encoding = variables.unpack_for_decoding(var)

c:\users\andersen\miniconda37\lib\site-packages\xarray\coding\times.py in decode(self, variable, name)
424 units = pop_to(attrs, encoding, "units")
425 calendar = pop_to(attrs, encoding, "calendar")
--> 426 dtype = _decode_cf_datetime_dtype(data, units, calendar, self.use_cftime)
427 transform = partial(
428 decode_cf_datetime,

c:\users\andersen\miniconda37\lib\site-packages\xarray\coding\times.py in _decode_cf_datetime_dtype(data, units, calendar, use_cftime)
84 "opening your dataset with decode_times=False." % (units, calendar_msg)
85 )
---> 86 raise ValueError(msg)
87 else:
88 dtype = getattr(result, "dtype", np.dtype("object"))

ValueError: unable to decode time units 'hours since 1850-01-15 12:00:00.000000' with calendar 'noleap'. Try opening your dataset with decode_times=False.

https://jupyter.eoastest.xyz/user/phil/notebooks/data_share/jamie/shortwave-low-cloud-feedback-pha.ipynb

• tools:
  http://xarray.pydata.org/en/stable/
  https://github.com/mwouts/jupytext
  https://zarr.readthedocs.io/en/latest/?badge=latest
  https://xarray-contrib.github.io/xarray-tutorial/
  https://foundations.projectpythia.org/core/xarray/xarray.html

• cmip6 information

  • google dataset doc
  • cmip6 explainer

• scientific background

  • zelinka et al.: 2019
  • cloud feedback paper supplement

• find three journal articles
  https://aaqr.org/articles/aaqr-20-05-covid-0240.pdf

Data:

AIRS climcaps CO: https://disc.gsfc.nasa.gov/information/documents?title=AIRS%20Documentation

https://airs.jpl.nasa.gov/data/products/climcaps-L2-L3/

Aura: OMI SO2/NO2: https://disc.gsfc.nasa.gov/datasets?page=1&source=AURA%20OMI

https://disc.gsfc.nasa.gov/datasets?keywords=climcaps&page=1&source=Aqua%20AIRS

https://towardsdatascience.com/read-netcdf-data-with-python-901f7ff61648

• How to load a GeoTIFF into Xarray

this only needs to be created once

gcs = gcsfs.GCSFileSystem(token='anon')

get the path to a specific zarr store (the first one from the dataframe above)

zstore = df_ta_ncar.zstore.values[-1]

create a mutable-mapping-style interface to the store

mapper = gcs.get_mapper(zstore)

open it using xarray and zarr

ds = xr.open_zarr(mapper, consolidated=True)
ds

OutOfBoundsDatetime Traceback (most recent call last)
~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/coding/times.py in decode_cf_datetime(num_dates, units, calendar, use_cftime)
156 try:
--> 157 dates = _decode_datetime_with_pandas(flat_num_dates, units, calendar)
158 except (OutOfBoundsDatetime, OverflowError):

~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/coding/times.py in _decode_datetime_with_pandas(flat_num_dates, units, calendar)
104 "Cannot decode times from a non-standard calendar, {!r}, using "
--> 105 "pandas.".format(calendar)
106 )

OutOfBoundsDatetime: Cannot decode times from a non-standard calendar, 'noleap', using pandas.

During handling of the above exception, another exception occurred:

ModuleNotFoundError Traceback (most recent call last)
~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/coding/times.py in _decode_cf_datetime_dtype(data, units, calendar, use_cftime)
76 try:
---> 77 result = decode_cf_datetime(example_value, units, calendar, use_cftime)
78 except Exception:

~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/coding/times.py in decode_cf_datetime(num_dates, units, calendar, use_cftime)
159 dates = _decode_datetime_with_cftime(
--> 160 flat_num_dates.astype(np.float), units, calendar
161 )

~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/coding/times.py in _decode_datetime_with_cftime(num_dates, units, calendar)
93 def _decode_datetime_with_cftime(num_dates, units, calendar):
---> 94 import cftime
95

ModuleNotFoundError: No module named 'cftime'

During handling of the above exception, another exception occurred:

ValueError Traceback (most recent call last)
in
9
10 # open it using xarray and zarr
---> 11 ds = xr.open_zarr(mapper, consolidated=True)
12 ds

~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/backends/zarr.py in open_zarr(store, group, synchronizer, chunks, decode_cf, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, consolidated, overwrite_encoded_chunks, **kwargs)
596 consolidated=consolidated,
597 )
--> 598 ds = maybe_decode_store(zarr_store)
599
600 # auto chunking needs to be here and not in ZarrStore because variable

~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/backends/zarr.py in maybe_decode_store(store, lock)
579 concat_characters=concat_characters,
580 decode_coords=decode_coords,
--> 581 drop_variables=drop_variables,
582 )
583

~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/conventions.py in decode_cf(obj, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables, use_cftime)
583 decode_coords,
584 drop_variables=drop_variables,
--> 585 use_cftime=use_cftime,
586 )
587 ds = Dataset(vars, attrs=attrs)

~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/conventions.py in decode_cf_variables(variables, attributes, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables, use_cftime)
492 decode_times=decode_times,
493 stack_char_dim=stack_char_dim,
--> 494 use_cftime=use_cftime,
495 )
496 if decode_coords:

~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/conventions.py in decode_cf_variable(name, var, concat_characters, mask_and_scale, decode_times, decode_endianness, stack_char_dim, use_cftime)
334 times.CFDatetimeCoder(use_cftime=use_cftime),
335 ]:
--> 336 var = coder.decode(var, name=name)
337
338 dimensions, data, attributes, encoding = variables.unpack_for_decoding(var)

~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/coding/times.py in decode(self, variable, name)
424 units = pop_to(attrs, encoding, "units")
425 calendar = pop_to(attrs, encoding, "calendar")
--> 426 dtype = _decode_cf_datetime_dtype(data, units, calendar, self.use_cftime)
427 transform = partial(
428 decode_cf_datetime,

~/miniconda3/envs/a448/lib/python3.7/site-packages/xarray/coding/times.py in _decode_cf_datetime_dtype(data, units, calendar, use_cftime)
84 "opening your dataset with decode_times=False." % (units, calendar_msg)
85 )
---> 86 raise ValueError(msg)
87 else:
88 dtype = getattr(result, "dtype", np.dtype("object"))

ValueError: unable to decode time units 'hours since 1850-01-15 12:00:00.000000' with calendar 'noleap'. Try opening your dataset with decode_times=False.

Project todo list for Shuting

• Clone https://github.com/pangeo-data/pangeo-cmip6-examples
• go over the cmip6 tutorial
• fix issue #10 pangeo
• Check (ModuleNotFoundError: No module named 'dask_kubernetes')