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

Climate Research Activities on Garuda-NKN Platform S. K. Dash 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) o N, 80 o E Central Lat and Lon- 20 101 X 115 Points along XY direction o E to 105 o E and 5 o S to 45 o N Domain covers 55 with Grid distance- 55 Km ���� �� ��$� %""#� ������ ����� �������� � ������� ������ ! !%$

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

120 60 60 � � & AI no-snow snow no-snow snow no-snow snow NWI NEI 100 50 50 80 40 40 60 30 30 40 20 20 20 10 10 0 0 0 1993 1994 1995 1996 average 1993 1994 1995 1996 average 1993 1994 1995 1996 average 60 60 60 � � � no-snow snow no-snow snow no-snow snow WCI CNI 50 SPI 50 50 40 40 40 30 30 30 20 20 20 10 10 10 0 0 0 1993 1994 1995 1996 average 1993 1994 1995 1996 average 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

Simulation of Monsoons 1982-2009 Using ICTP RegCM3 Initial Conditions: 25 th April to 3 rd May up to 30 th September, 9-member Horizontal grid distance: 55 Km Domain chosen: 51 O E to 109 O E and 3 O S to 43 O N ���������� ���������� 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) GG-BLR Begabung GG-HYD (Linux Xeon Cluster (Linux Xeon machine Head Node at Bangalore) (IITD) 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 �������� '� �(��� )����� *�&� ����� ,����� ���� )���� +����� ��� �-������ 0���1%$ 12#3# 5%�67 !%2 ��� . ��������� / #$!2 4 !%2$ �� &��$��� 0���1%$ 12#3# !#�67 +7� %4" ��� . 6����� / #$!2 4 85$ &���&��� 0���1%$ 12#3# 4�67 +7� 5# �� . 6������ #$9 4 ��������� 4%$" ���� /

Time Evaluation Seasonal Runs with RegCM3 #processors Execution Execution Gain on the grid Time(gg-blr) Time(Ajaymeru) 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 One Month Simulations No. of GARUDA AJAYMERU processors 4 3hr 31m 3hr 26m 8 2hr 33m 2hr 28m 16 16 1hr 26m 1hr 26m 1hr 16m 1hr 16m 32 0hr 42m 0hr 52m Seasonal Simulations 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

Resources Used on European Grid Architecture Infrastructure CPU Type Network Ajaymeru HPC Xeon Gigabit Switch Garuda(gg-blr) Grid Harpertown Infiniband 3.16GHz 20Gbps Full Duplex Argo HPC Nehalem 2.4 GHz Infiniband DDR EU-India Briareo (Trieste) AMD 2.4GHz SDR Ce-01 (Trieste) Grid AMD 2.4GHz SDR Legnaro(Padova) AMD 2.21GHz SDR

RegCM4.1 Performance on the HPC and Grid Infrastructure ������������������� ���������������� �������������������� ������������ ��������� ��������� ���������� ����� ��� ���� � ������ ���������� ���������� ����� ����� �� �� �� �� ���� � ������ !��������� ������ ������ � ������ "������ Ce � 01 ��� ��� &������ � ������� ��#$% Ce � 01 �� ��� &������ Ce � 01 ��� �������� "������ � ������� ���� �����

Performance Scalability Graph 20000 Briareo CE-01 The RegCM4.1 code is Argo grid enabled and is Garuda 16000 Ajaymeru ported on both Garuda and EUIndia Grid ec) Infrastructure. Infrastructure. The The Time (sec 12000 performance of the code is comparable on various infrastructures 8000 considering the number of CPU Type and the CPU cores 4000 available. 8 16 32 Number of processors

Climate of JJAS precipitation (cm) in RegCM3 and observations CRU RegCM3 IMD APHRODITE RegCM3 GPCP CMAP

Percentage differences in JJAS precipitation in RegCM3 and Observations RegCM3-IMD RegCM3-CRU RegCM3-APHRODITE RegCM3-CMAP RegCM3-GPCP

July June 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 on ICTP computing facilities using EU GRID.

� Coordinated Regional Downscaling Experiment (CORDEX) is a program developed by the Task Force on 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 of downscaled climate information.

Schematic depiction of the primary uncertainties in regional climate change projection

Schematic depiction of the first phase CORDEX experiment set-up

11 4 3 8 12 7 2 6 5 1 9 10 Regional domains planned for the CORDEX experiments (some still under discussion); also indicated are existing projects that make use of the corresponding domain