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Metadata

Name
Pre-processed data of atlas in EUCP-WP2
Repository
ZENODO
Identifier
doi:10.5281/zenodo.5788529
Description
Outputs from the probabilistic projection methods developed or assessed in the European Climate Projection system (EUCP) Horizon2020 project. The data can be previewed through our interactive atlas.

For more information, see the atlas about page, or the corresponding storyboard.

&nbsp;

Preprocessed data of Atlas in EUCP-WP2

We provide some notebooks that check the original/raw data, fix/add the metadata using CF-conventions&nbsp;https://cfconventions.org/Data/cf-conventions/cf-conventions-1.9/cf-conventions.html&nbsp;and save data in a NetCDF format. See&nbsp;https://github.com/eucp-project/atlas/blob/main/python/README.md.

For two of the methods, REA and ClimWIP,&nbsp;pre-calculated weights have also been included. Note that these weights are only valid in the context of this specific model ensemble. Therefore, the original (pre-processed) model data is published together with the weights.

The pre-processed data follows the following standards:

coordinates


climatology_bounds (climatology_bounds) datetime64[ns] [&#39;2050-06-01&#39;, &#39;2050-09-01&#39;, &#39;2050-12-01&#39;, &#39;2051-03-01&#39;]
time (time) (datetime64[ns]) [2050-07-16 2051-01-16] # &quot;JJA&quot;, &quot;DJF&quot;
latitude (lat) (float64) [30, ..., 75]
longitude (lon) (float64) [-10, ..., 40]
percentile (percentile) (int64) [10, 25, 50, 75, 90]


variables


tas (time, latitude, longitude, percentile) (float64)
pr (time, latitude, longitude, percentile) (float64)


attributes

The attributes of variables and coordinates are defined as:


&quot;tas&quot;: {
&quot;description&quot;: &quot;Change in Air Temperature&quot;,
&quot;standard_name&quot;: &quot;Change in Air Temperature&quot;,
&quot;long_name&quot;: &quot;Change in Near-Surface Air Temperature&quot;,
&quot;units&quot;: &quot;K&quot;,
&quot;cell_methods&quot;: &quot;time: mean changes over 20 years 2041-2060 vs 1995-2014&quot;,
},
&quot;pr&quot;: {
&quot;description&quot;: &quot;Relative precipitation&quot;,
&quot;standard_name&quot;: &quot;Relative precipitation&quot;,
&quot;long_name&quot;: &quot;Relative precipitation&quot;,
&quot;units&quot;: &quot;%&quot;,
&quot;cell_methods&quot;: &quot;time: mean changes over 20 years 2041-2060 vs 1995-2014&quot;,
},
&quot;latitude&quot;: {&quot;units&quot;: &quot;degrees_north&quot;, &quot;long_name&quot;: &quot;latitude&quot;, &quot;axis&quot;: &quot;Y&quot;},
&quot;longitude&quot;: {&quot;units&quot;: &quot;degrees_east&quot;, &quot;long_name&quot;: &quot;longitude&quot;, &quot;axis&quot;: &quot;X&quot;},
&quot;time&quot;: {
&quot;climatology&quot;: &quot;climatology_bounds&quot;,
&quot;long_name&quot;: &quot;time&quot;,
&quot;axis&quot;: &quot;T&quot;,
&quot;climatology_bounds&quot;: [&quot;2050-6-1&quot;, &quot;2050-9-1&quot;, &quot;2050-12-1&quot;, &quot;2051-3-1&quot;],
&quot;description&quot;: &quot;mean changes over 20 years 2041-2060 vs 1995-2014. The mid point 2050 is chosen as the representative time.&quot;,
},
&quot;percentile&quot;: {&quot;units&quot;: &quot;%&quot;, &quot;long_name&quot;: &quot;percentile&quot;, &quot;axis&quot;: &quot;Z&quot;},


The attributes of the data is defined as:


&quot;description&quot;: &quot;Contains modified&nbsp;institute&nbsp;method&nbsp;data used for Atlas in EUCP project.&quot;,
&quot;history&quot;: &quot;original&nbsp;institute&nbsp;method&nbsp;data files ...&quot;,


output file names

output_file_name =&nbsp;prefix_activity_institution-id_source_method_sub-method_cmor-var

example: atlas_EUCP_CNRM_CMIP6_KCC_cons_tas.nc

Reference:

https://eucp-project.github.io/atlas/about
Data or Study Types
multiple
Source Organization
Unknown
Access Conditions
available
Year
2021
Access Hyperlink
https://doi.org/10.5281/zenodo.5788529

Distributions

  • Encoding Format: HTML ; URL: https://doi.org/10.5281/zenodo.5788529
This project was funded in part by grant U24AI117966 from the NIH National Institute of Allergy and Infectious Diseases as part of the Big Data to Knowledge program. We thank all members of the bioCADDIE community for their valuable input on the overall project.