└── README.md


/README.md:
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  1 | # Download ERA data with python
  2 | 
  3 | Since the ECMWF currently advice user to migrate from ERA-interim to ERA5 ([due ERA Interim is being phased out](https://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/)) and also to [migrate from ECMWF Web API to CDS API](https://confluence.ecmwf.int/display/CKB/How+to+migrate+from+ECMWF+Web+API+to+CDS+API), in this tutorial I will teach you how to download ERA5 data with python using CDS API.
  4 | 
  5 | ## Instalation
  6 | 
  7 | The CDS API can be installed with Conda or Pip, and it is recommended to install it within a python environment.
  8 | 
  9 | Installation using conda:
 10 | ```
 11 | conda config --add channels conda-forge
 12 | conda install cdsapi
 13 | ```
 14 | 
 15 | Installation using pip:
 16 | ```
 17 | pip install cdsapi
 18 | ```
 19 | 
 20 | ## Creates an account
 21 | 
 22 | Creates a CDS account [here](https://cds.climate.copernicus.eu/user/register).
 23 | 
 24 | ## Install the CDS API key
 25 | 
 26 | - You need to login to continue, login [here](https://cds.climate.copernicus.eu/user/login?destination=%2F%23!%2Fhome).
 27 | - After login, click [here](https://cds.climate.copernicus.eu/user).
 28 | - Scroll down in the pageweb until the API key section and copy the **UID** and **API Key** codes.
 29 | - Creates .cdsapirc file
 30 | 
 31 |   **For Linux**:
 32 |       creates the file $HOME/.cdsapirc
 33 | 
 34 |   **For Windows**:
 35 |       creates the file at %USERPROFILE%\\.cdsapirc
 36 | 
 37 |                More information for windows [here](https://confluence.ecmwf.int/display/CKB/How+to+install+and+use+CDS+API+on+Windows) and [here](https://confluence.ecmwf.int/pages/viewpage.action?pageId=139068264).
 38 | <br>
 39 | - Copy the next code within .cdsapirc
 40 | 
 41 | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;url: https://cds.climate.copernicus.eu/api/v2 <br>
 42 | &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;key: {**uid**}:{**api-key**}
 43 | 
 44 | 
 45 | For more detail see [here](https://cds.climate.copernicus.eu/api-how-to).
 46 | 
 47 | ## Accept data licence and generate a basic CDS API script using the CDS web interface
 48 | - Go to the C3S [climate data store (CDS)](https://cds.climate.copernicus.eu/#!/home)
 49 | - On the top menu bar, click on **Datasets**.
 50 | - On the left-hand side menu, expand **Product type** and select product type of interest (e.g. **Seasonal forecasts** to get all seasonal forecasts data listed, **Reanalysis** for ERA5 datasets)
 51 | - Follow the dataset title link of interest to the full dataset record
 52 | - Accept dataset licence and generate basic CDS API script
 53 | 
 54 | In my case, I selected **Reanalysis** in **Product type**, and I selected 
 55 | **ERA5 hourly data on pressure levels from 1979 to present** as a dataset. Then, selected the variables that I want to download and I did click on **Show API request** to see the python script.
 56 | 
 57 | 
 58 | ```python
 59 | import cdsapi
 60 | 
 61 | c = cdsapi.Client()
 62 | 
 63 | c.retrieve(
 64 |     'reanalysis-era5-pressure-levels',
 65 |     {
 66 |         'product_type': 'reanalysis',
 67 |         'format': 'netcdf',
 68 |         'variable': [
 69 |             'geopotential', 'potential_vorticity', 'temperature',
 70 |             'u_component_of_wind', 'v_component_of_wind',
 71 |         ],
 72 |         'pressure_level': [
 73 |             '100', '125', '150',
 74 |             '175', '200', '225',
 75 |             '250', '300', '350',
 76 |             '400', '450', '500',
 77 |             '550', '600', '650',
 78 |             '700', '750', '775',
 79 |             '800', '825', '850',
 80 |             '875', '900', '925',
 81 |             '950', '975', '1000',
 82 |         ],
 83 |         'year': '1979',
 84 |         'month': '01',
 85 |         'day': [
 86 |             '01', '02', '03',
 87 |             '04', '05', '06',
 88 |             '07', '08', '09',
 89 |             '10', '11', '12',
 90 |             '13', '14', '15',
 91 |             '16', '17', '18',
 92 |             '19', '20', '21',
 93 |             '22', '23', '24',
 94 |             '25', '26', '27',
 95 |             '28', '29', '30',
 96 |             '31',
 97 |         ],
 98 |         'time': [
 99 |             '00:00', '01:00', '02:00',
100 |             '03:00', '04:00', '05:00',
101 |             '06:00', '07:00', '08:00',
102 |             '09:00', '10:00', '11:00',
103 |             '12:00', '13:00', '14:00',
104 |             '15:00', '16:00', '17:00',
105 |             '18:00', '19:00', '20:00',
106 |             '21:00', '22:00', '23:00',
107 |         ],
108 |         'area': [
109 |             10, -120, -60,
110 |             -20,
111 |         ],
112 |     },
113 |     'download.nc')
114 | ```
115 | 
116 | Finally, I did run the python code from python environment where was installed CDS API, and I downloaded the ERA5 data.
117 | 


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