Climate Change and Assessment Working Group

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Climate Change and Assessment Working Group
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Outline

• Climate change and assessment simulations now
  available
• Merged CSM and PCM model (CCSM)
• Cooperation between NSF and DOE
• Future research plans

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HistoryCSM1 and PCM1

• Built for vector computers
• Atmosphere CCM3
• Ocean component NCAR ocean model
• Sea ice simplified dynamics and thermodynamics

• Built for parallel computers
• Atmosphere CCM3
• Ocean component Parallel Ocean Program (POP)
• Sea ice Model -Naval Postgraduate School
  modelVP, thermodynamics

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Merging of CSM and PCM

• Agreement to use the same model components
• CSM and PCM lab staff will develop a merged flux
  coupler that can use both sequential and parallel
  execution mode of components - ongoing team of
  NCAR and DOE laboratory involvement
• Full merger occurs when the new atmospheric model
  is available with the new flux coupler
• Merged model - same basic atmosphere,ocean, sea
  ice, RTM, and LSM
• NSF and DOE efforts may use different resolutions
• Merged model called CCSM PCM, CSM and PCTM
  will continue to be analyzed in the meantime

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Distributed Involvement

• DOE and NSF Supported Project with
• Los Alamos National Laboratory
• National Center for Atmospheric Research
• Naval Postgraduate School
• Oak Ridge National Laboratory
• University of Texas, Austin
• Scripps Oceanographic Institute
• DOE Program on Climate Diagnostics and
  Intercomparison
• U.S. Army Cold Regions Research and Engineering
  Laboratory
• National Energy Research Supercomputer Center
• Lawrence Berkeley National Laboratory

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PCM Data Users (in addition to CSM users)

• Bill Anderson, NCAR
• Jeffrey Annis, Scripps
• Julie Arblaster, NCAR
• Raymond Arritt, Iowa State Univ.
• Tim Barnett, Scripps
• Cecilia Bitz, U. Washington
• Marcia Branstetter, U. Texas
• Curtis Covey, LLNL
• Ulrich Cubasch, DKRZ
• Aiguo Dai, NCAR
• Clara Deser, NCAR
• Irene Fischer-Burn, DKRZ
• John Gregory, IPCC
• James Hack, NCAR
• Charles Hakkarinen, EPRI
• Chick Keller, LANL

• Jeff Kiehl, NCAR
• Hans Luthardt, DKRZ
• Bob Malone, LANL
• Gerald Meehl, NCAR
• Sylvia Murphy, NCAR
• David Pierce, Scripps
• Dennis Shea, NCAR
• Scott Smith, LANL
• John Taylor, Argonne
• Tony Tubbs, Scripps
• Warren Washington, NCAR
• John Weatherly, CRREL
• Michael Wehner, LLNL
• Dean Williams, LLNL
• Kao J. Chin Yue, LANL

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CSM Climate Change Simulations

• 1 CO2 increase (80 years)
• Historical 1870 to 1999 (GHG)
• Historical 1870 to 1999 (GHGsulfate)
• Ensemble (4) Historical 1870 to 1999
  (GHGsulfatesolar)
• 21st Century Business as Usual (BAU), and
  stabilization
• IPCC SRES A1(5), A2, and B2

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PCM Historical and Future Simulations

• CSM greenhouse gas and sulfate aerosol forcing
• 1870 control simulation (300 years)
• 1995 control simulation (300 years)
• 1870 to 1999 GHGsulfate (ensemble of 10)
• 1870 to1999 GHGsulfatesolar (ensemble of 4)
• 1870 to 1999 solar (one)
• Business as Usual 2000-2100 (ensemble of 5)
• stabilization 2000-2100 (ensemble of 5)
• Business as Usual 2100-2200 (one)
• IPCC SRES A2 and B2 2000-2100 (one each)

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PCM 1 CO2 Increase/Year and Stabilization
Experiments

• 1995 Control simulation--300 years
• Ensemble of 5 capped at 2X CO2
• One simulation of 100 years with constant 2X
  CO2
• One simulation capped at 4X CO2
• One run for 100 years with constant 4XCO2
• One simulation with 0.5 per year capped at
  2X CO2

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PCM and CSM Presence in the International Climate
Modeling CommunityBoth prominent in the IPCC
Third Assessment Report (2001)Both represented
in the IPCC Data Distribution Centre
(Hamburg)Both represented in the CLIVAR Coupled
Model Intercomparison Project (CMIP) CMIP1,
CMIP2, CMIP2Access to CSM via NCAR (CSM web
page)Access to PCM runs archived at PCMDI
(contact Mike Wehner mwehner_at_pcmdi.gov)
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ACPI Demonstration Project

• End to End test of climate predictionfrom ocean
  initialization to global prediction of climate
  change to regional modeling of climate change to
  special impacts models such as hydrological
  models of small regions
• Several (6) special PCM1 simulations with 6 hour
  output for regional models for 2000 to 2050

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Interim Model - PCM-CSM Transitional Model
(PCTM)

• POP with GM and KPP (LANL, NCAR, NPS), R.
  Smith grid modifications (LANL)
• C. Bitz sea ice multi-thickness (5) distribution
  thermodynamics and E. Hunke et al. elastic
  viscous plastic dynamics (U. of Washington, LANL,
  NCAR)
• River Transport, Branstetter and Famiglietti
  (U. Of Texas, Austin, NCAR)
• CCM3.2 and later possibly CCM3.6 with liquid
  water and sulfate aerosol chemistry - T42
• From July 1999 to June 2001 (2 years), total PCM
  years run 2200 total PCTM years run 1000
  total of 3200 simulated years

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Assessing the impacts of human induced surface
change on the global energy balance Johannes
Feddema University of Kansas

• Purpose
• Develop a set of scenarios to simulate the
  impacts of urbanization and human impacts
• on soil structure and land surface properties
  from 1750 to 2100. Scenarios will be
• based on assessments of soil degradation (GLASOD,
  Oldeman, 1988), human
• population density (LandScan Dobson et al, 2000
  and historical land-use data
• (Ramankutty and Foley 1999 Klein Goldewijk,
  2001).
• Specific Goals
• Determine the impacts on soil degradation and
  urbanization on
• Hydrologic cycle
• Energy balance
• Global temperature signals
• In addition
• Compare projected temperature changes to the
  existing temperature records
• Overlay GCM simulated impacts with existing
  temperature stations to assess
• the impacts of urbanization on the historical
  temperature record

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Estimated 1998 urban extent in the eastern US
Source LandScan 1998 Dobson et al, 2000
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Future Plans

• Simulations with black carbon distributions in
  PCM1
• Volcanicsolar ensemble in PCM1
• Ongoing analysis of CSM and PCM simulations
• Higher resolution atmosphere -T85
• Land use change simulations
• Improved archival and cataloging of large data
  sets - EARTHGRID/DOE/
• Simulations related to energy use impacts on the
  climate system - ACPI demonstration project
• Future climate simulation with interactive carbon
  cycle
• Future climate simulation with statistical solar
  and volcano data
• Time and space varying SO2 emissions, 20th
  century
• Simulations with PCTM and CCSM when ready

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• URBANIZATION Background
• Research question
• Does extensive urbanization have an impact on
  global climate change?
• Urbanization is known to be a significant factor
  in
• changing hydrology in local areas and
  contributes to urban heat islands
• (decreased infiltration and reduced water holding
  capacities).
• obtaining accurate global historical
  temperature signals.
• changing albedo values.
• Future considerations
• Urban areas are expected to increase
  significantly even in regions of low population
  increase due to rural-urban migration and urban
  sprawl. For the U.S. this is estimated to be a
  35 percent increase over the next 25 years.

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Estimated 1998 urban extent in western Europe
Source LandScan 1998 Dobson et al, 2000
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• URBANIZATION proposed methodology
• Scenario development
• Determine population densities that define urban
  zones from the Department of Defense population
  and landuse databases (LandScan Dobson et al,
  2000).
• Create maps of urban extent from 1750 to 2100
  based on past and future national population
  estimates.
• Create a number of urban landuse subclasses that
  translate to specific infiltration rates, soil
  water holding capacities and albedo values.
• Model development
• Create new urban landuse classes for LSM that
  will change model parameters related to
• Albedo
• Infiltration rates (increase runoff and water
  loss from environment)
• Soil water holding capacities (reduced moisture
  availability during dry periods)

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• SOIL DEGRADATION background
• Research Question
• What is the impact of human induced soil loss and
  soil structure change on climate?
• Soil loss and alteration is known to
• change soil moisture water holding capacities
• increase runoff and reduce moisture availability
  (dry periods)
• change short-term albedo values, mostly from
  vegetation change
• Soil alteration and desertification have been
  shown to have a significant impact on surface
  energy balances (Williams and Balling, 1996).
  Comparisons between degraded and natural
  ecosystems in the Arizona-Mexico border region
  suggest that about 3 days to a week after a rain
  event there are large changes in the Bowen ratio
  (Bryant et al., 1990). Models also suggest that
  changes in soil water holding capacities lead to
  significant changes in hydrology, mostly in wet
  and dry climate regions (Feddema, 1999).

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Estimated soil degradation severity (1950-1980)
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SOIL DEGRADATION proposed methodology Scenario
Development Use of the global soil degradation
data (Oldeman, 1988) to manipulate the soil water
holding capacity. Data is based on the 1950-80
period. Combine the population, slope and soil
degradation data to create past and future soil
degradation estimates. Translate soil degradation
estimates to alter water holding capacities and
soil depth by relative percentages. Model
Development Develop means to manipulate soil
depth and water holding capacities (by layer) in
LSM from input data. Use relative degradation
measures to reduce water holding capacity and
soil depth estimates in LSM
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Issues

• Need improved climate change forcing GHGs and
  sulfur cycle carbon cycle, land-surface changes
  (U. Of Kansas) volcanic
• Higher resolution for atmospheric component
• High performance is a very high imperative on DOE
  machines must compete for time
• Computational balance of various components
• Testing various forcing components
• Initial state of ocean and sea ice Levitus,
  Barnett
• Ensembles are an imperative

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Examples of Climate Change Experiments

• Greenhouse gases
• Sulfate aerosols (direct effect)
• Stratospheric ozone
• Land surface changes
• Volcanic forcing
• Solar change forcing
• Biomass burning
• Various energy/emissions use strategies

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Change of Extremes

• Heat waves, cold snaps
• Floods, droughts
• First freeze dates, hard freeze frequency
• Precipitation intensity
• Diurnal temperature

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DOE Climate Change Prediction Program (CCPP)

• Develop climate modeling capability that takes
  advantage of new generation parallel architecture
  supercomputers
• Build on the previous DOE CHAMMP modeling
  developments
• Develop model components and coupled models that
  can be used for energy policy, IPCC, and the
  National Assessments