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1. Download 2m temperature from the Copernicus Climate Change Service (C3S)'s Climate Data Store (CDS) and save the data as file t2m_20000801.grib. In this example, selections are set as below:
   1. Dataset: ERA5 hourly data on single levels from 2000 to 2017 (you may see different years as new data is released)
   2. Parameter    : 2m temperature
   3. Product type: Reanalysis
   4. Year                  : 2000
   5. Month              : August
   6. Day                    : 01
   7. Time                 : 06:00, 12:00 and 18:00
   8. Format             : GRIB

2. Check the GRIB file by issuing command grib_ls -P time t2m_20000801.grib, you should see three GRIB messages in the file at three different times: 600, 1200, 1800 as shown below. Remember three time values were selected in step 1. Option -P time shows key "time", typing grib_ls for help.

   Code Block
   language bashtext
   t2m_20000801.grib time edition centre typeOfLevel level dataDate stepRange dataType shortName packingType gridType 600 1 ecmf surface 0 20000801 0 an 2t grid_simple regular_ll 1200 1 ecmf surface 0 20000801 0 an 2t grid_simple regular_ll 1800 1 ecmf surface 0 20000801 0 an 2t grid_simple regular_ll 3 of 3 messages in t2m_20000801.grib 3 of 3 total messages in 1 files

   
   

3. Say I want to extract lat, lon, 2t (2m temperature) at time = 12:00 from the GRIB file. Run command grib_get_data -w time=1200 t2m_20000801.grib > temp.csv and you will get a file containing data like below. Option -w time=1200 filters data for time = 12:00 only, typing grib_get_data for help.

   Code Block
   language bashtext
   Latitude, Longitude, Value 90.000 0.000 2.7346786499e+02 90.000 0.250 2.7346786499e+02 90.000 0.500 2.7346786499e+02 90.000 0.750 2.7346786499e+02 ...

   
   

4. Format the CSV file. You may use script below.

   Code Block
   language bashpy
   #!/usr/bin/env python """ Save as format.py, then run "python format.py". Input file : temp.csv Output file: t2m_20000801.csv """ with open('temp.csv', 'r') as f_in, open('t2m_20000801.csv', 'w') as f_out: f_out.write(next(f_in)) [f_out.write(','.join(line.split()) + '\n') for line in f_in]

   
   

5. You have a CSV file t2m_20000801.csv, which is ready to be imported in Excel. Notice there are over 1 million records in the file! You may now want to extract data for time=600 and 1800.

   Code Block
   language bash
   Latitude, Longitude, Value 90.000,0.000,2.7346786499e+02 90.000,0.250,2.7346786499e+02 90.000,0.500,2.7346786499e+02 90.000,0.750,2.7346786499e+02 ...

   
   

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