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: [email protected]

CORDEX-South Asia Evaluation Runs available for Hands On Analyses & Visualization

Institute IITM IITM IITM IITM Model Experiment WRF3.1.1

RegCM3.0

LMDZ AGCM LMDZ AGCM BMJ Cu Scheme Grell Cu Scheme Emanuel Cu Scheme Tiedtke Cu Scheme Resolution 50 km; Mercator 50 km; Mercator 35 km; Variable 35 km; Variable Driving Model Driving Experiment ERA-Interim ERA-Interim ERA-Interim ERA-Interim Global 0.75

o Global 1.5

o Nudged with ERA-Interim Nudged with ERA-Interim

• • All RCM outputs regridded on a common region and 0.5

o lat./lon. Grid in NetCDF Monthly/Daily mean Precipitation for the period 1989-2005

•

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

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

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)

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GrADS has been implemented worldwide on a variety of commonly used operating systems and is freely distributed over the Internet

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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

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

$cd plot[ 1-5 ]

(Climate Data Analysis Module-1) (Change to each sub-module directory) Thanks to Sandip & Sabin

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, Jayashree Revadekar, Rajiv Chaturvedi, Milind Mujumdar and Vimal Mishra)

• • 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)

• 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

Comparison of RCMs simulated mean precipitation spatial patterns during Summer monsoon (JJAS) season File: CDA1/plot2/mul-mod-seasonal-mean.cdo

• cdo Select JJAS months -selmon,6,7,8,9 $DATADIR/OBS/CRU_precip_mon_1989-2005-WA.nc CRU_precip_jjas.nc

cdo -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 cdo -r -settaxis,2000-07-15,00:00,1mon -timmean CRU_precip_jjas.nc CRU_precip_jjas-mean.nc

-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…..nc RegCM…...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

Area averaged mean monthly annual cycle of precipitation File: CDA1/plot3/annual-cycle.cdo

• cdo cdo Compute monthly mean climatology -ymonmean $DATADIR/OBS/CRU_precip_mon_1989-2005-WA.nc CRU_precip_mon_CLIM.nc -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.nc

cdo -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

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 cdo -yearmean -selmon,6/9 $DATADIR/OBS/CRU_precip_mon_1989-2005-WA.nc CRU_precip_jjas.nc

-yearmean -selmon,6/9 $DATADIR/LMDZ/LMDZ1_precip_mon_1989-2005-WA.nc LMDZ1_precip_jjas.nc

• Compute standard deviation of JJAS mean cdo cdo -timstd CRU_precip_jjas.nc CRU_precip_jjas-timstd.nc

-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

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 cdo -selmon,6,7,8,9 $DATADIR/CRU_precip_mon_1989-2008-WA.nc CRU_precip_jjas.nc

-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.nc

cdo -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.nc

cdo -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.nc

cdo -div CRU_precip_jjas-mean-IND-anom.nc CRU_precip_jjas-mean-IND-fldmean-std.nc CRU_precip_jjas-mean-IND-std-fldmean.nc

cdo -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

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

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.nc

cdo -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

Many Thanks to: • • My Team members Sabin & Sandip

Thanks for your attention

Email: [email protected]