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License: MIT License
a collection of remote climate data accessed via intake cached to disk
License: MIT License
It is annoying to download obs4mip datasets. here, we could create a catalog with common observational data products. Example:
# atmos xco2 crdp: CO2 monthly satellite from 2003 to 2014
# httpServer after search on https://esgf-data.dkrz.de/search/obs4mips-dkrz/
url='https://esgf-data1.ceda.ac.uk/thredds/fileServer/esg_esacci/ghg/data/obs4mips/crdp_3/CO2/v100/xco2_ghgcci_l3_v100_200301_201412.nc'
import intake_xarray
intake_xarray.NetCDFSource('simplecache::'+url,storage_options=dict(simplecache={'same_names':True, 'cache_storage':'my_cache'})).to_dask()
# GPCP 1.3 GB
url='https://dpesgf03.nccs.nasa.gov/thredds/fileServer/obs4MIPs/observations/NASA-GSFC/Obs-GPCP/GPCP/1DD_v1.2/atmos/pr_GPCP-1DD_L3_v1.2_19961001-20110630.nc'
ds = intake_xarray.NetCDFSource('simplecache::'+url,storage_options=dict(simplecache={'same_names':True, 'cache_storage':'my_cache'})).to_dask()
How to:
Advantages compared to downloading yourself:
Open questions:
the access model is not very clear.
nc files via opendap works only without caching
nc files via other sources: from http(s), ftp only works with/because of caching
http can also work with #bytes
to do: explain better in readme
to_dask()
not lazy when simplecache
in url: intake/intake-xarray#73Why: allows to subselect data before downloading
Also for averaging/dods
currently only defaults are tested
cat.atmosphere.GISTEMP(t_res='ltm').describe()
'user_parameters': [{'name': 's_res',
'description': 'spatial resolution',
'type': 'str',
'allowed': ['1200km', '250km'],
'default': '1200km'},
{'name': 'realm',
'description': 'data region including or excluding ocean',
'type': 'str',
'allowed': ['landonly', 'combined'],
'default': 'combined'},```
After intake/intake-thredds#6 is resolved
as #83
showcase
explain differences
http and opendap changable via url parameter, but opendap no simplecache
https://www.psl.noaa.gov/forecasts/sstlim/
pd.read_csv('https://www.psl.noaa.gov/forecasts/sstlim/n4gl.frcstlead3',sep='\t',skiprows=3, names=['Verif Date','Pred-1sigma','Prediction','Pred+1sigma'])
and try with climpred
website seems down, firefox shows security issues
pattern= catalog : dataset name : url : comment
ocean: World Ocean Atlas: https://www.nodc.noaa.gov/OC5/woa18/ : different versions and variables via parameter #15
global carbon budget with https://github.com/edjdavid/intake-excel #22
land: precipitation: https://psl.noaa.gov/data/gridded/tables/precipitation.html:
Mauna Loa CO2 netcdf ftp://aftp.cmdl.noaa.gov/data/trace_gases/co2/in-situ/surface/mlo/ #19
climate indices: see http://iridl.ldeo.columbia.edu/SOURCES/.Indices
reanalysis #48
Resources:
with derived datasets https://github.com/intake/intake/blob/master/docs/source/transforms.rst
maybe via parameter cache: default simplecache::
description: |
text
Text
https://www.naturalearthdata.com/features/
Urban areas
http://www.pik-potsdam.de/~mmalte/rcps/
SSPs require login https://tntcat.iiasa.ac.at/RcpDb/dsd?Action=htmlpage&page=download
via intake-excel
rioxarray
to env
and use engine='rasterio'
add:
jupyter labextension install @jupyter-widgets/jupyterlab-manager
jupyter labextension install @pyviz/jupyterlab_pyviz
import hvplot.xarray
intake.gui.add('master.yaml')
postBuild
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