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 Institut e Model Experiment Resolutio n
Driving Model Driving Experime nt 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 ERAInterim IITM LMDZ AGCM Tiedtke Cu Scheme 35 km; Variable ERA-Interim Nudged with ERAInterim
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 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 Users 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
-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 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
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]
Near Death of a District: The 'Perfect Storm' ... Cool Waters of the mid 1990s The intensity of the storm was calmed by cool waters in the mid 1990s as enrollments continued to increase. Rising enrollments masked the monster of...
Identifying a commonalities in predicate-argument structures: Agent diagnosing [Dr.Z] diagnosed [Jack's bronchitis] Person diagnosed Disease [Jack] was diagnosed [with bronchitis] [by Dr.Z] [Dr. Z's] diagnosis [of Jack's bronchitis] allowed her to treat him with the proper antibiotics.
Migration and Identity. Canada's identity is influenced by the movement of people. Whenever someone moves from one country to another, or from region to region they take ideas and ways of living with them.
The CMA is the certification that can deliver a tangible return on your investment. Professionals with a CMA can earn much more in average total compensation annually than noncertified peers. 4. Convenient. The CMA exam is offered at hundreds of...
Garfield Gini-Newman, Roland Case. Leading Educational Change for a 21st Century World , The Critical Thinking Consortium 2015. Small Teaching by James M. Lang. Bain, K. (2004). What The Best College Teachers Do. Harvard University Press: Cambridge, MA.
using a range of cohesive devices*, including adverbials, within and across sentences and paragraphs. using passive and modal verbs mostly appropriately. using inverted commas, commas for clarity, and punctuation for parenthesis mostly correctly, and making somecorrect use of semi-colons, dashes,...
eNodeB's are bottle-neck devices over mobile network, and "buffer bloat" is the main reason for TCP performance degradation. Reducing maximum RWND on UEs to avoid "buffer bloat" is not practical. Large buffer inside eNodeB is a double-edged sword to performance,...
Ready to download the document? Go ahead and hit continue!