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Hands-On Training in CORDEX South Asia Data Analysis Module-1

This module provides an introduction to hands-on training in data analysis for CORDEX South Asia. It covers evaluation runs, regridding data, using NetCDF and CDO utilities, and visualization with GrADS.

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Hands-On Training in CORDEX South Asia Data Analysis Module-1

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  1. Introduction to Hands On Training in CORDEX South Asia Data Analysis Module-1 J. Sanjay Centre for Climate Change Research (CCCR) Indian Institute of Tropical Meteorology (IITM), Pune (An Autonomous Institute of the Ministry of Earth Sciences, Govt. of India) Email: sanjay@tropmet.res.in

  2. CORDEX-South Asia Evaluation Runs available for Hands On Analyses & Visualization • All RCM outputs regridded on a common region and 0.5o lat./lon. Grid in NetCDF • Monthly/Daily mean Precipitation for the period 1989-2005

  3. Network Common Data Form • NetCDF is a set of software libraries and self-describing machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data • NetCDF Utilities • ncdump reads a netCDF dataset and prints a textual representation of the information in the dataset • ncdump –h file.nc prints the header information in a NetCDF file

  4. Climate Data Operators • CDO is a collection of command line Operators to manipulate and analyse Climate and NWP model Data(from MPIM https://code.zmaw.de/projects/cdo) • Supported data formats are GRIB 1/2, netCDF 3/4, SERVICE, EXTRA and IEG. There are more than 600 operators available • CDO has very small memory requirements and can process files larger than the physical memory • CDO is open source • Full documentation available as html or pdf from homepage (https://code.zmaw.de/projects/cdo) • CDO User’s Guide Version 1.6.1 • CDO Reference Card

  5. Grid Analysis and Display System • (from COLA http://www.iges.org/grads) • GrADS is an interactive desktop tool that is used for easy access, manipulation, and visualization of earth science data • GrADS has two data models for handling gridded and station data • GrADS supports many data file formats, including binary (stream or sequential), GRIB (version 1 and 2), NetCDF, HDF (version 4 and 5), and BUFR (for station data) • GrADS has been implemented worldwide on a variety of commonly used operating systems and is freely distributed over the Internet • Online documentation has become the new standard for GrADS. Documentation page (http://www.iges.org/grads/gadoc) has • User's Guide • Tutorial • useful Index for quick reference

  6. Structure of Files Start Virtual Box Fedora14 Login User : CORDEX Passwd: cordex123 Home Directory:/home/CORDEX/Desktop/Modules DATA Directories: OBS: Observation Data -Monthly RegCM/LMDZ/ARW: Model Data –Monthly (1989-2005) OBS/DAILY: Daily Files (1996-2005) What to do: CDO & GrADS Scripts $ cd scripts/CDA1 (Climate Data Analysis Module-1) $cd plot[1-5] (Change to each sub-module directory) Thanks to Sandip & Sabin

  7. Climate Data Analysis Module: CDA1 (CORDEX South Asia: Climate model outputs) – Mean & Variability • Day 4: Friday, 30 August 2013 • 09:00 – 11:00 Hands on training: 1 • (Trainers: J. Sanjay, JayashreeRevadekar, Rajiv Chaturvedi, MilindMujumdar and VimalMishra) • Precipitation Analyses and Visualization of: • Observed Mean spatial patterns during Summer monsoon (JJAS) and Winter (DJF) seasons • Comparison of RCMs simulated mean spatial patterns during Summer monsoon (JJAS) season • Area averaged mean monthly annual cycle • Comparison of RCMs simulated spatial patterns of interannual variability (standard deviation) during Summer monsoon (JJAS) season • Temporal evolution of area averaged interannual variability (summer monsoon season anomalies normalized with standard deviation) • Scripts provided: Analyses using CDO (Climate Data Operators) and visualization using GrADS (Graphical Analysis and Display System)

  8. Precipitation Observed Mean Spatial patterns during Summer monsoon (JJAS) and Winter (DJF) seasons • File: CDA1/plot1/seasonal-mean.cdo • Select months • cdo -selmon,6,7,8,9 $DATADIR/OBS/CRU_precip_mon_1989-2005-WA.nc CRU_precip_jjas.nc • Time average over season • cdo -timmean CRU_precip_jjas.nc CRU_precip_jjas_mean.nc • File: CDA1/plot1/seasonal-mean.gs • GrADS script to plot & prepare output in EPS format • File: CDA1/plot1/seasonal-mean.sh • Unix shell script for CDO analysis & GrADS output • Exercise: • Please bring out the differences in the two seasons

  9. Comparison of RCMs simulated mean precipitation spatial patterns during Summer monsoon (JJAS) season • File: CDA1/plot2/mul-mod-seasonal-mean.cdo • Select JJAS months • cdo -selmon,6,7,8,9 $DATADIR/OBS/CRU_precip_mon_1989-2005-WA.nc CRU_precip_jjas.nccdo -selmon,6,7,8,9 $DATADIR/LMDZ/LMDZ1_precip_mon_1989-2005-WA.nc LMDZ1_precip_jjas.nc • Compute JJAS mean & set relative time axis • cdo -r -settaxis,2000-07-15,00:00,1mon -timmean CRU_precip_jjas.nc CRU_precip_jjas-mean.nccdo -r -settaxis,2000-07-15,00:00,1mon -timmean LMDZ1_precip_jjas.nc LMDZ1_precip_jjas-mean.nc • Compute Ensemble JJAS mean • cdo -ensmean LMDZ1_precip_jjas-mean.nc LMDZ2…..ncRegCM…...nc ARW……..nc ENS_precip_jjas-mean.nc • File: CDA1/plot2/mul-mod-seasonal-mean.gs • GrADS script to plot & prepare output in EPS format • File: CDA1/plot2/mul-mod-seasonal-mean.sh • Unix shell script for CDO analysis & GrADS output • Exercise: • Please bring out the differences in the simulations

  10. Area averaged mean monthly annual cycle of precipitation • File: CDA1/plot3/annual-cycle.cdo • Compute monthly mean climatology • cdo -ymonmean $DATADIR/OBS/CRU_precip_mon_1989-2005-WA.nc CRU_precip_mon_CLIM.nc cdo -ymonmean $DATADIR/LMDZ/LMDZ1_precip_mon_1989-2005-WA.nc LMDZ1_precip_mon_CLIM.nc • Select region • cdo -sellonlatbox,70,90,10,25 CRU_precip_mon_CLIM.nc CRU_precip_mon_CLIM_IND.nccdo -sellonlatbox,70,90,10,25 LMDZ1_precip_mon_CLIM.nc LMDZ1_precip_mon_CLIM_IND.nc • Area average • cdo -fldmean CRU_precip_mon_CLIM_IND.nc CRU_precip_mon_CLIM_IND_fldmean.nc cdo -fldmean LMDZ1_precip_mon_CLIM_IND.nc LMDZ1_precip_mon_CLIM_IND_fldmean.nc • Set relative time axis • cdo -r -settaxis,2000-01-15,12:00,1mon CRU_precip_mon_CLIM_IND_fldmean.nc CRU_precip_mon_CLIM_IND_fldmean-n.nc cdo -r -settaxis,2000-01-15,12:00,1mon LMDZ1_precip_mon_CLIM_IND_fldmean.nc LMDZ1_precip_mon_CLIM_IND_fldmean-n.nc • File: CDA1/plot3/annual-cycle.gs • GrADS script to plot & prepare output in EPS format • File: CDA1/plot3/annual-cycle.sh • Unix shell script for CDO analysis & GrADS output • Exercise: • Please bring out the differences in the annual cycle • Analyse for a region of your choice

  11. Comparison of RCMs simulated spatial patterns of summer monsoon (JJAS) season precipitation interannual variability (standard deviation) • File: CDA1/plot4/mul-mod-seasonal-std.cdo • Select JJAS months & seasonal mean for each year • cdo -yearmean -selmon,6/9 $DATADIR/OBS/CRU_precip_mon_1989-2005-WA.nc CRU_precip_jjas.nccdo -yearmean -selmon,6/9 $DATADIR/LMDZ/LMDZ1_precip_mon_1989-2005-WA.nc LMDZ1_precip_jjas.nc • Compute standard deviation of JJAS mean • cdo -timstd CRU_precip_jjas.nc CRU_precip_jjas-timstd.nccdo -timstd LMDZ1_precip_jjas.nc LMDZ1_precip_jjas-timstd.nc • File: CDA1/plot4/mul-mod-seasonal-std.gs • GrADS script to plot & prepare output in EPS format • File: CDA1/plot4/mul-mod-seasonal-std.sh • Unix shell script for CDO analysis & GrADS output • Exercise: • Please bring out the differences in the simulations

  12. Temporal evolution of area averaged of summer monsoon (JJAS) season precipitation interannual variability (seasonal anomalies normalized with standard deviation) • File: CDA1/plot5/IAV.cdo • Compute JJAS mean for each year • cdo -selmon,6,7,8,9 $DATADIR/CRU_precip_mon_1989-2008-WA.nc CRU_precip_jjas.nc • cdo -yearmean CRU_precip_jjas.nc CRU_precip_jjas-mean.nc • Select region and area average • cdo -sellonlatbox,70,90,10,25 CRU_precip_jjas-mean.nc CRU_precip_jjas-mean-IND.nccdo -fldmean CRU_precip_jjas-mean-IND.nc CRU_precip_jjas-mean-IND-fldmean.nc • Compute area averaged seasonal anomalies • cdo -timmean CRU_precip_jjas-mean-IND-fldmean.nc CRU_precip_jjas-mean-IND-fldmean-timmean.nccdo -sub CRU_precip_jjas-mean-IND-fldmean.nc CRU_precip_jjas-mean-IND-fldmean-timmean.nc CRU_precip_jjas-mean-IND-anom.nc • Prepare the observed summer monsoon precipitation index • cdo -timstd CRU_precip_jjas-mean-IND-fldmean.nc CRU_precip_jjas-mean-IND-fldmean-std.nccdo -div CRU_precip_jjas-mean-IND-anom.nc CRU_precip_jjas-mean-IND-fldmean-std.nc CRU_precip_jjas-mean-IND-std-fldmean.nccdo -r -settaxis,1989-07-15,00:00,1year CRU_precip_jjas-mean-IND-std-fldmean.nc CRU_precip_jjas-mean-IND-std-fldmean-n.nc • File: CDA1/plot5/IAV.gs • GrADS script to plot & prepare output in EPS format • File: CDA1/plot5/IAV.sh • Unix shell script for CDO analysis & GrADS output • Exercise: • Please indicate the extreme monsoon years

  13. Comparison of RCMs simulated Summer monsoon (JJAS) season mean precipitation bias • File: CDA1/plot6/mul-mod-seas-mean-bias.cdo • Compute JJAS long-term mean bias cdo -sub ../plot2/LMDZ1_precip_jjas-mean.nc ../plot2/CRU_precip_jjas-mean.nc LMDZ1_precip_jjas-bias.nc • File: CDA1/plot6/mul-mod-seas-mean-bias.gs • GrADS script to plot & prepare output in EPS format • File: CDA1/plot6/mul-mod-seas-mean-bias.sh • Unix shell script for CDO analysis & GrADS output

  14. Comparison of RCMs simulated and Observed Summer monsoon (JJAS) season mean precipitation Coefficient of Variation (CV = Standard Deviation / Mean) • File: CDA1/plot7/mul-mod-seas-mean-cv.cdo • Compute JJAS mean CV cdo -mulc,100.0 -div ../plot4/CRU_precip_jjas-timstd.nc ../plot2/CRU_precip_jjas-mean.nc CRU_precip_jjas-cv.nccdo -mulc,100.0 -div ../plot4/LMDZ1_precip_jjas-timstd.nc ../plot2/LMDZ1_precip_jjas-mean.nc LMDZ1_precip_jjas-cv.nc • File: CDA1/plot7/mul-mod-seas-mean-cv.gs • GrADS script to plot & prepare output in EPS format • File: CDA1/plot7/mul-mod-seas-mean-cv.sh • Unix shell script for CDO analysis & GrADS output

  15. Many Thanks to: • My Team members • Sabin & Sandip Thanks for your attention Email: sanjay@tropmet.res.in

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