Transcript - CCCR - Indian Institute of Tropical Meteorology

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
Model
Experiment
Resolution
Driving
Model
Driving
Experiment
IITM
WRF3.1.1
BMJ Cu
Scheme
50 km;
Mercator
ERA-Interim
Global 0.75o
IITM
RegCM3.0
Grell Cu
Scheme
50 km;
Mercator
ERA-Interim
Global 1.5o
IITM
LMDZ AGCM
Emanuel Cu
Scheme
35 km;
Variable
ERA-Interim
Nudged with
ERA-Interim
IITM
LMDZ AGCM
Tiedtke Cu
Scheme
35 km;
Variable
ERA-Interim
Nudged with
ERA-Interim
•
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
Network Common Data Form
• NetCDF is a set of software libraries and self-describing machineindependent 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)
• 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
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
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
•
Select JJAS months
cdo
cdo
•
Compute JJAS mean & set relative time axis
cdo
cdo
•
-selmon,6,7,8,9 $DATADIR/OBS/CRU_precip_mon_1989-2005-WA.nc CRU_precip_jjas.nc
-selmon,6,7,8,9 $DATADIR/LMDZ/LMDZ1_precip_mon_1989-2005-WA.nc LMDZ1_precip_jjas.nc
-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
•
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.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]