hereinafter referred to as the ccsm consortium phil jones lanl on behalf of all the consorts
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COLLABORATIVE DESIGN AND DEVELOPMENT OF THE COMMUNITY CLIMATE SYSTEM MODEL FOR TERASCALE COMPUTING (CDDCCSMTC). Hereinafter referred to as the CCSM Consortium Phil Jones (LANL) On behalf of all the consorts.

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hereinafter referred to as the ccsm consortium phil jones lanl on behalf of all the consorts

COLLABORATIVE DESIGN AND DEVELOPMENT OF THE COMMUNITY CLIMATE SYSTEM MODEL FOR TERASCALE COMPUTING (CDDCCSMTC)

Hereinafter referred to as the CCSM Consortium

Phil Jones (LANL)

On behalf of all the consorts

slide2

The SciDAC CCSM Consortium consists of PI: R. Malone4, J. Drake5 , Site-Contacts: C. Ding2, S. Ghan6, D. Rotman3, J. Taylor1, J. Kiehl7, W. Washington7, S.-J. Lin8, Co-Is: J. Baumgardner4, T. Bettge7, L. Buja7, S. Chu4, T. Craig7, P. Duffy3, J. Dukowicz4, S. Elliot4, D. Erickson5, M. Ham5, Y. He2, F. Hoffman5, E. Hunke4, R. Jacob1, P. Jones4, J. Larson1, J. Lamarque7, W. Lipscomb4, M. Maltrud4, D. McKenna7, A. Mirin3, W. Putman8, W. Sawyer8, J. Schramm7, T. Shippert6, R. Smith4, P. Worley5, W. Yang2

1Argonne National Lab, 2Lawrence Berkeley National Lab, 3Lawrence Livermore National Lab, 4Los Alamos National Lab, 5Oak Ridge National Lab, 6Pacific Northwest National Lab, 7National Center for Atmospheric Research, 8NASA-Goddard Space Flight Center

science goals
Science Goals
  • Assessment and prediction
    • IPCC, national assessments (alarmist fearmongering)
    • Energy policy (Dick Cheney’s private sessions)
  • Regional climate prediction
    • High resolution, downscaling, water!
  • Atmospheric chemistry/ocean biogeochemistry
    • Carbon cycle
    • Aerosols
project goals
Project Goals
  • Software
    • Performance portability
    • Software engineering (repositories, standardized testing – No Code Left Behind initiative)
  • Model Development
    • Better algorithms
    • New physical processes (esp. chemistry, biogeochemistry)
community climate system model
Community Climate System Model

Land

LSM/CLM

Atmosphere

CAM

NSF/DOE

270 Participants

7 States

10 Fluxes

6 States

6 Fluxes

Once

hour

per

per

Flux Coupler

hour

Once

6 States

6 Fluxes

7 States

9 Fluxes

4 States

3 Fluxes

6 States

13 Fluxes

day

per

Once

per

Once

hour

6 Fluxes

11 States

10 Fluxes

Ocean

POP

Ice

CICE/CSIM

coupler architecture
Coupler Architecture
  • Issues:
  • sequencing
  • frequency
  • distribution
  • parallelism
  • single or multiple
  • executables
  • stand alone execution
  • MPH3 (multi-processor handshaking) library for coupling component models
  • CPL6 -- Implemented, Tested, Deployed
  • ESMF/CCA

Version 1.0 Released

November 2002

prediction and assessment
Prediction and Assessment

Many century-scale simulations (>2500yrs)

@~5yrs/day

Cycle vampires:

Many dedicated cycles at computer centers

performance portability
Performance Portability
  • Vectorization
    • POP easy (forefront of retro fashion)
    • CAM, CICE, CLM
  • Blocked/chunked decomposition
    • Sized for vector/cache
    • Load balanced distribution of blocks/chunks
    • Hybrid MPI/OpenMP
    • Land elimination
  • Performance modeling w/PERC
hypop
HYPOP
  • Arbitrary Lagrangian-Eulerian vertical coordinate
    • Keep Lagrangian in deep ocean
    • Remap to z-coordinate in mixed layer
    • CSU SciDAC
  • New time stepping/mode splitting
  • Progress
    • Model currently working in z-coord mode
    • Examining vertical grid generators
    • Testing
slide16
CICE
  • Incremental Remapping for Sea Ice and Ocean Transport
    • Incremental remapping scheme that proved to be three times faster than MPDATA, total model speedup of about 30% --added to CCSM/CSIM
    • CICE3.0 restructered for vector Community Sea Ice Model
  • Sensitivity analysis and parameter tuning test of the CICE code
    • Automatic Differentiation (AD)-generated derivative code
regional prediction
Regional Prediction

Kentucky

Mississipi State

Oklahoma State

Stanford

resolution and precipitation
Resolution and Precipitation

(DJF) precipitation in the California region in 5 simulations, plus observations. The 5 simulations are: CCM3 at T42 (300 km), CCM3 at T85 (150 km) , CCM3 at T170 (75 km), CCM3 at T239 (50 km), and CAM2 with FV dycore at 0.4 x 0.5 deg.

CCM3 extreme precipitation events depend on model resolution. Here we are using as a measure of extreme precipitation events the 99th percentile daily precipitation amount. Increasing resolution helps the CCM3 reproduce this measure of extreme daily precipitation events.

subgrid orography scheme
Subgrid Orography Scheme
  • Reproduces orographic signature without increasing dynamic resolution
  • Realisitic precipitation, snowcover, runoff
  • Month of March simulated with CCSM
eddy resolving ocean
Eddy-Resolving Ocean

Obs

2 deg

0.28 deg

0.1 deg

greenhouse gases
Greenhouse Gases
  • Energy production
  • Bovine flatulence
  • Presidential campaigning
  • Source-based scenarios
atmospheric chemistry
Atmospheric Chemistry
  • Gas-phase chemistry with emissions, deposition, transport and photo-chemical reactions for 89 species.
  • Experiments performed with 4x5 degree Fvcore – ozone concentration at 800hPa for selected stations (ppmv)
  • Mechanism development with IMPACT
    • A)    Small mechanism (TS4), using the ozone field it generates for photolysis rates.
    • B)     Small mechanism (TS4), using an ozone climatology for photolysis rates.
    • C)    Full mechanism (TS2), using the ozone field it generates for photolysis rates.

Zonal mean

Ozone, Ratio A/C

Zonal mean

Ozone, Ratio B/C

ocean biogeochemistry
Ocean Biogeochemistry
  • LANL Ecosystem Model
    • nutrients (nitrate, ammonium, iron, silicate)
    • phytoplankton (small, diatom, coccolithophores)
    • zooplankton
    • bacteria, dissolved organic material, detritus
    • dissolved inorganic carbon (DIC), alkalinity
    • trace gases (dimethyl sulfide, carbonyl sulfide, methyl halides and nonmethane hydrocarbons)
    • elemental cyclings (C,N,Fe,Si,S)
ocean biogeochemistry1
Ocean Biogeochemistry
  • Iron Enrichment in the Parallel Ocean Program
  • Surface chlorophyll distributions in POP
  • for 1996 La Niña and 1997 El Niño
global dms flux from the ocean using pop
Global DMS Flux from the Ocean using POP

The global flux of DMS from the ocean to the atmosphere is shown as an annual mean. The globally integrated flux of DMS from the ocean to the atmosphere is 23.8 Tg S yr-1 .

things not mentioned
Things not mentioned…
  • Software engineering
  • Other model improvements
    • fvcore work
    • land model (river transport, biogeochem, etc.)
  • Ocean grid/topography generator
  • Parallel I/O work
  • ESG
  • Now how much would you pay? You also get…
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