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Add "env" folder" and update README
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‎.gitignore

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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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# env/
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# venv/
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# ENV/
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env.bak/
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venv.bak/
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‎README.md

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# EFAS_skill
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# EFAS skill assessment
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Analysis of the skill of [EFAS (Europen Flood Awareness System)](https://www.efas.eu/en) formal flood notifications since the deployment of EFAS v4 (October 2020).
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## Structure of the repository
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The repository contains six folders:
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* [conf](https://github.com/casadoj/EFAS_skill/tree/cleaning/conf) contains the configuration file (_config.yml_) used by all notebooks.
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* [data](https://github.com/casadoj/EFAS_skill/tree/cleaning/data) contains the original data used in the analysis (whenever the size is suitable to be stored in GitHub).
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* [docs](https://github.com/casadoj/EFAS_skill/tree/cleaning/docs) contains several documents associated to the development of the repository: the EGU documents, presentations in meetings...
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* [notbook](https://github.com/casadoj/EFAS_skill/tree/cleaning/notebook) contains the notebooks used to develop the analysis.
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* [py](https://github.com/casadoj/EFAS_skill/tree/cleaning/py) contains Python files with functions created during the analysis.
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* [results](https://github.com/casadoj/EFAS_skill/tree/cleaning/results) is used to save datasets and plots produced by running the notebooks.
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## Data
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The analysis is limited to the [EFAS fixed reporting points](https://github.com/casadoj/EFAS_skill/blob/cleaning/data/reporting_points/Station-2022-10-27v12.csv) with a catchment area larger than 500 km² (2357 points).
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The original datasets used for the study are:
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* EFAS v4 discharge reanalysis (_water balance_). This discharge data was downloaded from the [Copernicus Climate Data Store](https://cds.climate.copernicus.eu/#!/home) (CDS) for the complete EFAS domain, and then the time series specific to each reporting point was extracted and saved as NetCDF files in the [_data/discharge/reanalysis/_](https://github.com/casadoj/EFAS_skill/tree/cleaning/data/discharge/reanalysis) folder. Due to file size limitations in GitHub, the original files downloaded from the CDS are not in the repository.
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* EFAS v4 discharge forecast. This data was extracted by Corentin from the Meteorological Archival and Retrival System (MARS) and provided as NetCDF files for each forecast date and model (COSMO, ECMWF-HRES, ECMWF-ENS, DWD). Due to the size of these files, the original files are not included in the repository.
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* The [discharge return periods](https://github.com/casadoj/EFAS_skill/blob/cleaning/data/thresholds/return_levels.nc) associated to each reporting point. Even though the data set contains several return periods (1.5, 2, 5, 10, 20 years, ...), the analysis only uses the 5-year return period.
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Assessment of the skill of [EFAS (Europen Flood Awareness System)](https://www.efas.eu/en) formal flood notifications.

‎conf/config.yml

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exceedance:
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reanalysis: ../results/exceedance/reanalysis/
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forecast: ../results/exceedance/forecast/
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hits: ../results/hits/new/
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hits: ../results/hits/
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skill: ../results/skill/
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skill_analysis:

‎env/environment.yml

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name: xr
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channels:
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- anaconda
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- defaults
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- conda-forge
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dependencies:
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- anyio=3.6.2=pyhd8ed1ab_0
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- argon2-cffi=21.3.0=pyhd8ed1ab_0
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- arrow-cpp=10.0.1=h9752425_4_cpu
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- asttokens=2.1.0=pyhd8ed1ab_0
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- attrs=22.1.0=pyh71513ae_1
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- aws-c-auth=0.6.21=h0fd8c68_3
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- babel=2.11.0=pyhd8ed1ab_0
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- backports=1.0=py_2
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279+
- tbb=2021.6.0=h59b6b97_0
280+
- tblib=1.7.0=pyhd8ed1ab_0
281+
- terminado=0.17.0=pyh08f2357_0
282+
- threadpoolctl=2.2.0=pyh0d69192_0
283+
- tiledb=2.11.3=h5689973_1
284+
- tinycss2=1.2.1=pyhd8ed1ab_0
285+
- tk=8.6.12=h2bbff1b_0
286+
- toml=0.10.2=pyhd3eb1b0_0
287+
- tomli=2.0.1=pyhd8ed1ab_0
288+
- toolz=0.12.0=pyhd8ed1ab_0
289+
- tornado=6.2=py39h2bbff1b_0
290+
- tqdm=4.65.0=pyhd8ed1ab_1
291+
- traitlets=5.5.0=pyhd8ed1ab_0
292+
- typing-extensions=4.1.1=hd3eb1b0_0
293+
- typing_extensions=4.1.1=pyh06a4308_0
294+
- tzdata=2022f=h04d1e81_0
295+
- ucrt=10.0.22621.0=h57928b3_0
296+
- urllib3=1.26.11=pyhd8ed1ab_0
297+
- vc=14.2=h21ff451_1
298+
- vs2015_runtime=14.32.31332=h1d6e394_9
299+
- wcwidth=0.2.5=pyh9f0ad1d_2
300+
- webencodings=0.5.1=py_1
301+
- websocket-client=1.4.2=pyhd8ed1ab_0
302+
- wheel=0.37.1=pyhd3eb1b0_0
303+
- widgetsnbextension=4.0.5=pyhd8ed1ab_0
304+
- win_inet_pton=1.1.0=pyhd8ed1ab_6
305+
- wincertstore=0.2=py39haa95532_2
306+
- winpty=0.4.3=4
307+
- xarray=0.20.1=pyhd3eb1b0_1
308+
- xerces-c=3.2.4=h63175ca_1
309+
- xyzservices=2022.9.0=pyhd8ed1ab_0
310+
- xz=5.2.6=h8cc25b3_0
311+
- yaml=0.2.5=h8ffe710_2
312+
- zeromq=4.3.4=h0e60522_1
313+
- zict=2.2.0=pyhd8ed1ab_0
314+
- zipp=3.10.0=pyhd8ed1ab_0
315+
- zlib=1.2.13=hcfcfb64_4
316+
- zstd=1.5.2=h19a0ad4_0
317+
- pip:
318+
- hydroeval==0.1.0
319+
prefix: C:\DEV\Anaconda3\envs\xr

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