Routine to calculate icclim [CLIP-C] indices using the icclim python module for EUR-44 domain.

• includes both bias corrected and non-bias corrected RCM data
• up to date with DRS ClipC metadata compliance v1.3 - July 2016
• calculate 15 climate extreme indices:
  • precipitation: PRCPTOT,R1MM,RX1DAY,R95P,R10MM,R20MM,CWD,CDD
  • tmax: ID,TX,SU
  • tmin: FD,TR,TN
  • tmean: HD17

Input files:

RMC bias corrected files used as input are provided by http://exporter.nsc.liu.se/e4ba1c00373c4b548b12c30b269a1c98/

Non-bias corrected files are on http://esgf.llnl.gov/

Step by step procedure of RCM variable tasmax (example for non-bias corrected)

• producing climate extreme indices ID (icing days), SU (summer days) and TX (mean of daily maximum temperature):

1. Calculate indices using .py script:

Beforehand install icclim module from https://github.com/cerfacs-globc/icclim

Then run:

* calc_indices_icclim_RCM_TMAX_EUR_44.py -for bias corrected RCM output

• prereq modules to run this script:

import netCDF4
import ctypes
import icclim
import datetime
import icclim.util.callback as callback

2. Filter out zeroes on sea points (sea mask):

   • sea_mask_tasmax.sh

3. Import RCM tracking_id as invar_tracking_id and create unique indice tracking_id:

   • get_put_invar_tracking_id_python_TMAX.py

4. Create metadata global entries fields and fill them in

   • meta_var_attr_tasmax.sh

5. Calculate ensemble statistics

   • calc_indicator_statistics_tasmax.sh

6. Append rlat,rlon as variables to statistics indices files produces in the previous step with:

   • append_rename_vars_nc_nco.sh

7. Change global metadata fields "title" and "summary" for ensemble indices:

   • titles_summaries_tasmax.sh

8. Rename tracking_id to invar_tracking_id and create unique tracking_id entry and value for ensemble indices files

   • rename_tracking_id2invar_tracking_id_and_gen_new_tracking_id_tasmax.sh