enes – prace board of directors march 20th, 2013 brussels · enes – prace board of directors...
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ENES – PRACE Board of Directors March 20th, 2013
Brussels
Outline
1. ENES and European Climate models 2. ENES infrastructure strategy 2012-2022 & HPC needs
3. Collaboration with PRACE and ENES
§
ENES European Network for Earth System modelling
http://enes.org
A network of European groups in climate/Earth system modeling
Launched in 2001 (MOU)
Ca 50 groups from academic, public and industrial world
Main focus : discuss strategy
to accelerate progress in climate/Earth system
modelling and understanding
Several EU projects
Collaboration with PRACE
IS-ENES Infrastructure for ENES
European projects
2009-2013; 2013-2017
Infrastructure Models & their environment
Model data (ESGF) Interface with HPC ecosystem
Users :
Climate modelling community Impact studies
State of the art in climate modelling CMIP5 experiments
7 in Europe
1 Canada
6 USA
1 Russia
5 China / 1 Korea
4 Japan
2 Australia
27 modelling groups 58 models
Modelling the Earth’s climate system
each ESM > 1000 man years: strong legacy
Basic physical laws Based on Navier-Stokes
Conservation of: energy,
mass (air, water, carbon) &
Parameterisations clouds, radiation,
subgrid-scale processes
IPCC (1990) IPCC (1995) IPCC (2001) IPCC (2007)
ESMs
Key science questions Q1. How predictable is climate on a range of timescales ?
Q2. What is the sensitivity of climate and how can we reduce uncertainties ? Q3. What is needed to provide reliable predictions of regional climate changes ?
Q4. Can we model and understand glacial-interglacial cycles ? Q5. Can we attribute observed signals to understand processes ?
Drivers : Science & Society From understanding to development of “Climate Services”
Infrastructure Strategy for the European Earth System Modelling Community
2012-2022
Writing team: J. Mitchell, R. Budich, S. Joussaume, B. Lawrence & J. Marotzke
52 contributors from BE, CZ, DE, DK, FI, FR, IT, NO, SE, SP, UK
Q1. How predictable is climate at different time scales ?
Multi-model decadal predictions 5 European models, 10 yr simulations at every 5 years
With ocean initial conditions
COMBINE EU Project, courtesy of
A. Bellucci (CMCC)
HPC Data assimilation
Large ensemble runs Resolution
Observations
Multi model
1960 2015
Surface air temperature
Q2. What is the sensitivity of climate and can we reduce uncertainties ? Feedbacks (eg. clouds, carbon cycle), nonlinear behaviours
Temperature change to 2 x CO2
Uncertainty to cloud feedbacks
Dufresne & Bony J. Climate, 2008
HPC Ensemble experiments
(eg. process studies)
CMIP3 (AR4)
2 to 4.5 °C mean 3°C
Multi-model mean Inter-model
Clouds
Q3. What is needed to provide reliable predictions/projections
of regional climate changes ?
Summer precipitation 2005 Simulations
global climate model HADGEM3 Resolutions 135km à 12km PRACE UPSCALE project
Courtesy of PL Vidale (NCAS) & M. Roberts (MO/HC)
HPC: Spatial Resolution
Ensemble runs (internal variability, parameterisations)
135 km 60 km 40 km
25 km 17 km 12 km
Observations
Q4. Can we model and understand glacial-interglacial cycles and better constrain model sensitivity using the past ?
N20
CO2
CH4
T
ice
In thousand of years
Source : EPICA community members, Nature 2004
Last Glacial Maximum (21 000 years BP) Simulations (PMIP2)
HPC Duration
(1000 to 100 000 simulated years) Complexity
IPCC (2007) Braconnot et al. (Clim Past 2007)
Observed past 600 000 years
Q5. Can we attribute observed signals to understand processes ? Globally ? Extreme events ?
observations
Simulations Natural forcings
Simulations Natural & anthropogenic forcings
HPC Large ensemble runs
For extreme events: Spatial resolution
Fast availability of computing power
IPCC (2007)
Infrastructure Strategy Roadmap
Res
olut
ion!
Computing!Resources!
Complexity!
EO, !Data Assim.!
Needs for HPC
And data storage
From Jim Kinter, the World Modelling Summit, 2008
ensemble: x 10
x 5-10
x 3 ≈ x 27 x 100 ≈ x 106
duration: x 10-100
Challenge: towards 1 km scale global climate models
Infrastructure Strategy Roadmap
« CORDEX »
« CMIP5 »
NASA
Infrastructure strategy for ENES for the next 10 years
Recommandations:
1) Access to world-class HPC for climate
at least «tailored » for climate up to « dedicated »
2) Develop the next generation of climate models
3) Set up data infrastructure (global and regional models) for large range of users from impact community
4) Improve physical network (e.g. link national archives)
5) Strengthen European expertise and networking
Input to IS-ENES2
ENES Towards an European Climate Infrastructure Initiative :
a sustainable virtual laboratory
§ Collaboration in PRACE IPs:
§ PRACE 1IP, WP7: SARA (John Donners): collaboration on EC-EARTH high-resolution Benchmarks: very limited interaction with scientific community
§ PRACE 2IP WP8 :
ENES priorities: coupler, I/O, dynamical cores, fault tolerance only partially followed & limited interactions
§ PRACE 3IP: none yet
§ Projects on Tier0 machines: UPSCALE & PULSATION HIRESCLIM & SPRUCE
§ Involvment in PRACE organisation: Members of SSC: Sylvie Joussaume, Jose Baldasano/Antonio Navarra Member of PRACE User Forum: Pier Luigi Vidale
ENES & PRACE
§ Projects on Tier0 machines: - UPSCALE Pier Luigi Vidale (UK) Hermit - PULSATION Sébastien Masson (FR) Curie - HIRESCLIM Colin Jones (SE) MareNostrum3 - SPRUCE Eric Maisonnave (FR) Curie
Feedbacks from PRACE projects
§ Preparatory access phase: too short (several components, tests, workflow) (0.5-1 yr)
§ Even if code ready on similar machine: time needed to adapt on Tier 0 (e.g. different environment, availability of tools, test experiments)
“CPU hours must be used regularly during the one year long project”: impossible
§ Need for IO, data storage and some data analysis easily accessible from Tier0 and petascale data storage in the network neighbourhood
§ Trained man power is key
§ Very difficult and limited with 1-year access
§ Need some long-term planning of machines and use
Key requirements (ENES Strategy and EOI for programme access)
§ Data intensive science : high- performance data IO and storage
e.g. Upscale : 500 TB § Need multi-year access
time to scientifically develop and validate the model configuration used (not just porting)
§ Recognise specificities: § Need of both capability and capacity : several runs in parallel: need to be recognised as massively parallel § Several codes coupled § Environment: support multi-executables, mix MPI/openPM § Workflow: queue system match, long initialisations, large number
of files …
World-class HPC for climate
« Tailored for climate »
Scalability issue
Scalability tests at resolution 25-30 km for the atmosphere
[E-W processors] x [N-S processors] x [openMP threads]
P.L. Vidale (NCAS) M. Roberts (MO/HC)
Joint Weather and Climate Research Programme A partnership in climate research
HadGEM3 – CRAY XE6 Hector
G. Riley et al., IS-ENES
IPSL Atmosphere
EC-Earth AOGCM
ARPEGE + simplified ocean
≈ 12 K cores
CPUs/1000
Scalability issue
Revisit dynamical cores And numerics
Parallel coupling Parallel I/O
Issue: develop Computing /climate
collaboration
§ Next international experiments : CMIP6/CORDEX6, still under definition
§ Most experiments to be performed at national level
§ Some « high-end » experiments to be performed on PRACE ? High international visibility, coordinated European experiments
Additional requirements:
§ Commitment known in advance
§ Prepare simulations in advance and then no change of machine
Typically : validation phase (2 years) & production phase (2 years)
§ Strict deadlines for submission of results
Contribution of PRACE to international experiments ?
« The mission of PRACE is to enable high impact scientific discovery and engineering research and development across all disciplines to enhance European competitiveness for the benefit of society. PRACE seeks to realize this mission by offering world class computing and data management resources and services through a peer review process. »
Conclusions
From climate community:
q Increasing demand from society: more reliable predictions of climate change for adaptation
q Strong needs for HPC:
Scalability: Increased resolution, Number of experiments, complexity Duration of experiments remains a problem
q HPC facilities tailored to our needs : IO, Data storage, physical network
Stability of computing environment: development/evaluation/ production runs
Strong expectations that PRACE can serve our needs