Climate Research Activities on Garuda-NKN Platform S. K. Dash S. - - PowerPoint PPT Presentation

Climate Research Activities

• n Garuda-NKN Platform
• S. K. Dash
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• S. K. Dash

Points to Discuss

• Importance of Indian summer

monsoon & need of regional models

• RegCM3 simulations at IIT Delhi
• RegCM implemented on Garuda

GRID

• RegCM4 simulations
• Efforts for integrating RegCM4 on

ICTP computer using EU GRID

Importance of Monsoon in India

• Indian summer monsoon during June

September is very important for Indian agriculture and water sources

• Monsoon is scientifically challenging
• Monsoon is scientifically challenging
• Monsoon features are difficult to be

simulated by GCMs primarily because of large temporal and spatial variations

• There is a need for high resolution

Regional Models

Regional aspects of Indian surface features

Large spatial variations in monsoon rainfall in five homogeneous zones of India. The numbers inside the zones indicate mean monsoon rainfall (mm), standard deviation (mm) and coefficient of variation (%) from top to bottom respectively

1) ICTP RegCM3 simulations at IIT Delhi showing the impact of variations in Tibetan snow on summer monsoon rainfall rainfall 2) Two experiments (i) with 10cm of snow And (ii) no snow in the extreme case of global warming

Model domain used in RegCM3 and the five homogeneous zones of India such as North West India (NWI), West Central India (WCI), Central Northeast India (CNI), North East India (NEI) and South Peninsular India (SPI) (Parthasarathy et al., 1995)

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Central Lat and Lon- 20

• N, 80
• E

101 X 115 Points along XY direction Domain covers 55

• E to 105
• E and 5
• S to 45
• N

with Grid distance- 55 Km

Region over which 10cm of snow has been introduced uniformly in the snow experiment

20 40 60 80 100 120 1993 1994 1995 1996 average no-snow snow AI 10 20 30 40 50 60 1993 1994 1995 1996 average no-snow snow NWI 10 20 30 40 50 60 1993 1994 1995 1996 average no-snow snow NEI 40 50 60 no-snow snow WCI 40 50 60 no-snow snow SPI 40 50 60 no-snow snow CNI

• &
• 10

20 30 1993 1994 1995 1996 average 10 20 30 1993 1994 1995 1996 average 10 20 30 1993 1994 1995 1996 average

Comparison of JJAS mean rainfall (cm) over All India and its five homogeneous zones as simulated by RegCM3 in no-snow and snow experiments

Decrease of rainfall 30% for AI 20% for WCI 25% for CNI

23% for NWI 15% for SPI

Initial Conditions: 25th April to 3rd May up to 30th September, 9-member Horizontal grid distance: 55 Km Domain chosen: 51OE to 109OE and 3OS to 43ON

Simulation of Monsoons 1982-2009

Using ICTP RegCM3

• USGS Global 30 Arc-Sec. elevation datasets at 30’ resolution to create terrain

USGS Global GLCC dataset at 30’ resolution to create vegetation or landuse file Weekly analysis OISST available from NOAA for integration NCEP Reanalysis (NNRP1) are used for setting the initial and boundary conditions

• Variations in rainfall, temperature and winds

at time scales of intra-seasonal, seasonal and inter-annual examined in detail and compared with observations. compared with observations.

• Special emphasis given on contrasting

monsoon years such as 1982-1983, 1987- 1988, 2002-2003 etc to validate RegCM.

NKN TOPOLOGY

Source: http://www.cdacb.in/html/nkn.aspx

Clusters on Garuda (being used)

Garuda Head Node (gridfs)

Begabung Cluster Head Node (IITD) GG-BLR (Linux Xeon machine Bangalore) GG-HYD (Linux Xeon at Hyderabad)

Garuda Access Methods

Garuda allows submission of both sequential and parallel jobs. It provides two methods for job submission.

• 1. Access Portal – It provides graphical user interface

to the user through internet hiding the complexity of to the user through internet hiding the complexity of using the grid.

• 2. Command-line Interface - GARUDA users require

login at GARUDA head node for their job submission and the executable runs in the batch mode.

Resources used

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Time Evaluation

Seasonal Runs with RegCM3

#processors Execution Time(gg-blr) Execution Time(Ajaymeru) Gain on the grid 12 processors 1:35:40 2:35:42 1:00:02 24 processors 1: 10:49 2:02:54 0:52:05 30 processors 0:54:12 1:49:23 0:55:11 40 processors 0:46:36 1:20:26 0:33:50 60 processors 0:41:02 1:05:47 0:24:45

Execution Timings of RegCM4.1

• No. of

processors GARUDA AJAYMERU 4 3hr 31m 3hr 26m 8 2hr 33m 2hr 28m 16 1hr 26m 1hr 16m

One Month Simulations

16 1hr 26m 1hr 16m 32 0hr 42m 0hr 52m

• No. of processors

GARUDA AJAYMERU 4 16h 37m 16hr 6m 8 11hr 41m 11hr 18m 16 6hr 20m 5hr 40m 32 3hr 34m 4hr 5m

Seasonal Simulations

Architecture Infrastructure CPU Type Network Ajaymeru HPC Xeon Gigabit Switch Garuda(gg-blr) Grid Harpertown 3.16GHz Infiniband 20Gbps Full Duplex

Resources Used on European Grid

Argo HPC Nehalem 2.4 GHz Infiniband DDR EU-India Briareo (Trieste) Ce-01 (Trieste) Legnaro(Padova) Grid AMD 2.4GHz AMD 2.4GHz AMD 2.21GHz SDR SDR SDR

• RegCM4.1 Performance on the HPC and

Grid Infrastructure

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Performance Scalability Graph

The RegCM4.1 code is grid enabled and is ported on both Garuda and EUIndia Grid Infrastructure. The ec)

Ajaymeru Garuda Argo CE-01 Briareo 20000 16000

Infrastructure. The performance

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the code is comparable on various infrastructures considering the number of CPU Type and the CPU cores available. Time (sec Number of processors

8 16 32

12000 8000 4000

APHRODITE CRU

Climate of JJAS precipitation (cm) in RegCM3 and observations

RegCM3 IMD RegCM3 CMAP GPCP

RegCM3-IMD RegCM3-CRU RegCM3-APHRODITE

Percentage differences in JJAS precipitation in RegCM3 and Observations

RegCM3-GPCP RegCM3-CMAP

June July August September JJAS Correlation Coefficients between RegCM3 and IMD observed ensemble mean monsoon rainfall for the period 1982-2009 spanning 28 years. The contours are obtained with 9 point smoothing to the gridded result.

RegCM4 simulations in contrasting monsoon years monsoon years 1994-1998 and 2002-2003

2002 Precipitation

2003 Precipitation

Current efforts

• Climate runs under the international effort

called CORDEX for a century or so encounter difficulties in IIT Delhi due to computing limitations. limitations.

• Subsequent to the Dec workshop at IIT Delhi

efforts are in progress to integrate RegCM4

• n ICTP computing facilities using EU GRID.

Coordinated Regional Downscaling Experiment (CORDEX) is a program developed by the Task Force

• n Regional Climate Downscaling of World Climate

Research Programme (WCRP). The framework includes regional climate models (RCMs) and statistical downscaling, with an aim of (RCMs) and statistical downscaling, with an aim of evaluating the strengths and weaknesses

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downscaled climate information.

Schematic depiction of the primary uncertainties in regional climate change projection

Schematic depiction of the first phase CORDEX experiment set-up

12 11 2 3 4 6 7 8

Regional domains planned for the CORDEX experiments (some still under discussion); also indicated are existing projects that make use

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the corresponding domain

10 1 5 9