Climate Change and Assessment Working Group

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

History CSM1 and PCM1 u Built for vector computers u Atmosphere: CCM3 u Ocean component: NCAR ocean model u Sea ice simplified dynamics and thermodynamics u Built for parallel computers u Atmosphere: CCM3 u Ocean component: Parallel Ocean Program (POP) u Sea ice Model -Naval Postgraduate School model:VP, thermodynamics

Merging of CSM and PCM u Agreement to use the same model components u 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 u Full merger occurs when the new atmospheric model is available with the new flux coupler u Merged model - same basic atmosphere,ocean, sea ice, RTM, and LSM u NSF and DOE efforts may use different resolutions u Merged model called “CCSM”; PCM, CSM and PCTM will continue to be analyzed in the meantime

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

PCM Data Users (in addition to CSM users) F F Bill Anderson,NCAR F F Jeffrey Annis, Scripps F F Julie Arblaster, NCAR F F Raymond Arritt, Iowa State Univ. F F Tim Barnett, Scripps F F Cecilia Bitz, U. Washington F F Marcia Branstetter, U. Texas F F Curtis Covey, LLNL F F Ulrich Cubasch, DKRZ F F Aiguo Dai, NCAR F F Clara Deser, NCAR F F Irene Fischer-Burn, DKRZ F F John Gregory,IPCC F F James Hack, NCAR F F Charles Hakkarinen, EPRI F F Chick Keller, LANL F F Jeff Kiehl, NCAR F F Hans Luthardt, DKRZ F F Bob Malone, LANL F F Gerald Meehl, NCAR F F Sylvia Murphy, NCAR F F David Pierce, Scripps F F Dennis Shea, NCAR F F Scott Smith, LANL F F John Taylor, Argonne F F Tony Tubbs, Scripps F F Warren Washington, NCAR F F John Weatherly, CRREL F F Michael Wehner, LLNL F F Dean Williams, LLNL F F Kao J. Chin Yue, LANL

CSM Climate Change Simulations u 1% CO 2 increase (80 years) u Historical 1870 to 1999 (GHG) u Historical 1870 to 1999 (GHG+sulfate) u Ensemble (4) Historical 1870 to 1999 (GHG+sulfate+solar) u 21st Century Business as Usual (BAU), and stabilization u IPCC SRES A1(5), A2, and B2

PCM Historical and Future Simulations u CSM greenhouse gas and sulfate aerosol forcing u 1870 control simulation (300 years) u 1995 control simulation (300 years) u 1870 to 1999 GHG+sulfate (ensemble of 10) u 1870 to1999 GHG+sulfate+solar (ensemble of 4) u 1870 to 1999 solar (one) u “Business as Usual” (ensemble of 5) u “stabilization” (ensemble of 5) u Business as Usual (one) u IPCC SRES A2 and B (one each)

PCM 1% CO2 Increase/Year and Stabilization Experiments u 1995 Control simulation--300 years u Ensemble of 5 capped at 2X CO 2 u One simulation of 100 years with constant 2X CO 2 u One simulation capped at 4X CO 2 u One run for 100 years with constant 4XCO 2 u One simulation with 0.5% per year capped at 2X CO 2

PCM and CSM Presence in the International Climate Modeling Community Both 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, CMIP2+ Access to CSM: via NCAR (CSM web page) Access to PCM: runs archived at PCMDI (contact Mike Wehner:

ACPI Demonstration Project u End to End test of climate prediction…from 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 u Several (6) special PCM1 simulations with 6 hour output for regional models for 2000 to 2050

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

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

Estimated 1998 urban extent in the eastern US Source: LandScan 1998; Dobson et al, 2000

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

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.

Source: LandScan 1998; Dobson et al, 2000 Estimated 1998 urban extent in western Europe

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)

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).

Estimated soil degradation severity ( )

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 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

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

Examples of Climate Change Experiments u Greenhouse gases u Sulfate aerosols (direct effect) u Stratospheric ozone u Land surface changes u Volcanic forcing u Solar change forcing u Biomass burning u Various energy/emissions use strategies

Change of Extremes u Heat waves, cold snaps u Floods, droughts u First freeze dates, hard freeze frequency u Precipitation intensity u Diurnal temperature

DOE Climate Change Prediction Program (CCPP) u Develop climate modeling capability that takes advantage of new generation parallel architecture supercomputers u Build on the previous DOE CHAMMP modeling developments u Develop model components and coupled models that can be used for energy policy, IPCC, and the National Assessments