# Presentation: 561397

## Building the connections between ASP and the CTM and GCM modeling communities 

**Anjuli Bamzai**
**Program Manager**
**Climate Change Prediction Program**
**U.S. Department of Energy**
**	****	****Oct 31-Nov 2 ASP Science Team Mtg **
**                          ****Alexandria VA **
***     ***

## Aerosols & IPCC**

**** First IPCC:  Climate change considered to be driven by anthropogenic GHG.  Inadequate understanding of aerosol climate interactions. Subsequent IPCC reports documented studies on aerosol-climate interactions.  Recent studies (E.g. Indo-Ex, ABC, Menon et al.) have confounded the previously orderly world of IPCC of the 1990s****  **
** **

## Recent Climate-Aerosol Reports 

**Aug 2005 *****EPRI Technical Report #101269: Interactions of Climate Change and Air Quality: Research Priorities and New Direction*****   **
** ****Apr 2005 *****PNAS Atmospheric brown clouds: Impacts on South Asian climate and hydrological cycle***** V. Ramanathan, C. Chung, D. Kim, T. Bettge, L. Buja, J. T. Kiehl, W. M. Washington, Q. Fu, D. R. Sikka, and M. Wild**
-  **Dec 2004 *****NAS Study Radiative Forcing of Climate Change: Expanding the Concept and Addressing Uncertainties***

## Recent NAS report  Jacob et al. 

## Sources of Key Uncertainties in Climate Change

**Sources of Key Uncertainties in Climate Change**
**Assessments**

** ****Future emissions**
** ****Climate sensitivity***
** ****Heat flux into the ocean**
** ****Radiative forcing due to aerosols and clouds**
** ****Carbon Cycle/climate feedbacks**
** ****Changes in ocean circulation**
*** ****The climate sensitivity determines how much the climate will change for a given change in atmospheric composition. It is usually expressed as the eventual  global-mean warming for a doubling of the CO****2**** concentration, and lies in the range of 1.5-4.5****o**** C with 90% confidence**

## Climate Change Prediction Program(CCPP) and SciDAC Strategic Goals

**1.  Develop models**** based on definitive theoretical foundations**
**2.    Develop better representations of key climate processes**** (land surface processes, convective transport, ***etc***) on appropriate scales **
**3.  Develop diagnostic methods and tools to evaluate**** the ability of GCM-based climate models to accurately describe and predict global climate system behavior**
**4.   Increase accuracy/ throughput of computer model-based projections**** of future climate system response to increasing atmospheric concentrations of greenhouse gases by incorporating best practices in computing technology**
**5.   Test and apply climate models**** for climate change projections under various scenarios, ***e.g.*** IPCC runs **
**6.   Examine issue of Detection and Attribution ****of climate change**** **
**        **

**BER LT**** **
***BER Long term measure***
***‘******to deliver improved climate ***
***data and models  for policy ***
***makers to determine safe ***
***levels of greenhouse gases ***
***in the Earth’s atmosphere ***
***and to reduce differences ***
***between observed and model ***
***simulated temperatures at ***
***sub-continental scales, based ***
***on the use of several decades ***
***of recent data.’***

## Community Climate System Model(CCSM)

_**Scientific Objectives:**_
**Develop a comprehensive climate model to study the Earth’s Climate.**** **
**Investigate seasonal and interannual variability in the climate.**** **
**Explore the history of Earth’s climate.**** **
**Estimate the future of the environment for policy formulation.**** **
_**Recent Accomplishments:**_
**Release of a new version (CCSM-3) to the climate community in June 2004.**
**Studies linking SST fluctuations, droughts, and extratropical variability.**
**Simulations of last 1000 years, Holocene, and Last Glacial Maximum.**
**Creation of largest ensemble of simulations for the IPCC AR4.**

**http://www.ccsm.ucar.edu**

## Atmosphere:
New treatments of the condensed water and geometry of clouds; 
Improved treatments of cloud droplets and ice particles; 
Improved representation of the interactions among water vapor, solar radiation, and terrestrial thermal radiation; 
New treatment of the effects of aerosols on the reflection and absorption of solar radiation; and 
New dynamical frameworks suitable for modeling atmospheric chemistry;
Coupler: 
Improved performance and scalability on parallel supercomputers; 
Faster multi-way communication among the component models; and
New communications infrastructure 

- New treatments of the condensed water and geometry of clouds;
- Improved treatments of cloud droplets and ice particles;
- Improved representation of the interactions among water vapor, solar radiation, and terrestrial thermal radiation;
- New treatment of the effects of aerosols on the reflection and absorption of solar radiation; and
- New dynamical frameworks suitable for modeling atmospheric chemistry;
**Coupler: **
- Improved performance and scalability on parallel supercomputers;
- Faster multi-way communication among the component models; and
- New communications infrastructure

**Improvements in Community Climate System Model (CCSM3.0) released June 2004**

** **

## Land:
New methods to enable simulation of the terrestrial carbon cycle; 
New methods to enable simulation of dynamic vegetation; and 
Improvements in land-surface physics to reduce temperature biases 
Ocean:
Improvements to the representation of the ocean mixed layer; 
Inclusion of solar heating by chlorophyll; and 	
New infrastructure for studying vertical mixing in the ocean

 Sea-ice:
Improved schemes for horizontal advection of sea ice; 
More realistic treatments of snow and ice reflectivity; and 
Updated treatments for sea-ice thickness
Complete system:

New portability for vector and Linux supercomputers; 
New, easy-to-use methods to run IPCC climate-change experiments; and 
Flexibility to simulate climate over a wide range of spatial resolutions with greater fidelity. 

- New methods to enable simulation of the terrestrial carbon cycle;
- New methods to enable simulation of dynamic vegetation; and
- Improvements in land-surface physics to reduce temperature biases
**Ocean:**
- Improvements to the representation of the ocean mixed layer;
- Inclusion of solar heating by chlorophyll; and
- New infrastructure for studying vertical mixing in the ocean
-  **Sea-ice:**
- Improved schemes for horizontal advection of sea ice;
- More realistic treatments of snow and ice reflectivity; and
- Updated treatments for sea-ice thickness
**Complete system:**
- New portability for vector and Linux supercomputers;
- New, easy-to-use methods to run IPCC climate-change experiments; and
- Flexibility to simulate climate over a wide range of spatial resolutions with greater fidelity.

**Improvements in Community Climate System Model (CCSM3.0) released June 2004 (contd.)**

##                           CCSM3 Climate Change simulations

- T170 AMIP simulation
- T170 CCSM3 coupled simulation, 1950 - 2050
- T85 Historical simulation from 1870 to 2000 (GHGs + SA +SAI +SV+ V + O) (130 years) with sulfate aerosols (direct and indirect effect)
-  T85 Historical simulation from 1870 to 2000 (GHGs + SA +SV+ V+ O + CA) (130 years) with carbon aerosols varying in space and time
- T85  Historical simulation from 1870 to 2000 (GHGs + SA +SV+ V+ O + DA) (130 years) with dust aerosols
- T85  Historical simulation 1870 to 2000 with sulfate indirect only
-  T85 Historical simulation 1870 to 2000 with dust aerosols only
-  T85 Historical simulation 1870 to 2000 with carbon aerosols only

## Execution of IPCC runs on DOE machines was a major activity 

**DOE ORNL Supercomputer:**
-  IBM p690 (Cheetah)
-  684 Processors
-  Peak speed: 4.5 Teraflops

**Characteristics of the Community Climate**
**System Model (CCSM3):**
-   ~1 quadrillion operations/simulated year
-  IPCC ~10,800 years
-  Rate of simulation: 3.5 sim. years/day
-  Output: 10 GB/simulated year
-   Data volume for IPCC: ~110 TB   (~200,000 Data CDs)
**DOE Resources for IPCC runs (CCSM, PCM)**
-    ORNL 2.34M CPU hr on cheetah
-    NERSC 1.4M CPU hr on seaborg
**Substantial DOE prior developmental work:**
-   Ocean & Sea Ice model development at LANL
-   Atmosphere & Land model testing/tuning at ORNL
***  ***Distributions of all IPCC runs is coordinated
-    through PCMDI LLNL.

## CCPP,  SciDAC Contributions to CCSM3 Release

**Software engineering design, parallel algorithms**
**Coupler and toolkit libraries **
**Performance/ optimization / vectorization**
**Ocean code POP 1.4.3 from DOE LANL**
**Sea ice code CICE from DOE LANL**
**DOE computer resources for model development**
**DOE computer resources for IPCC runs at ORNL, NERSC LBL**

## Ensemble Simulations

**Ensemble Simulations**

***Agreement with observations in  simulations that include ***
***both natural and greenhouse gas forcing ***

## Current Atmospheric Chemistry Modeling under SciDAC

**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

## Potential areas where ASP-CCPP programmatic objectives intersect 

**Data**

**GCM**

**Climate change simulations**

**ARM site**

**ARM, ASP**
**Field campaigns**

## Climate change modeling challenge

***Climate change modeling challenge***

**Notes:**
Modeling the physical, chemical, and biological processes involves numerous non-linear feedbacks and interactions among the components of the climate system. 
Because of the large natural variability in the time averaged state of the climate system, very long numerical integrations are often required to establish statistical significance in climate sensitivity studies. The quality of the simulations is crucially dependent upon the physical parameterizations incorporated in the model. The importance of model resolution to the quality of the numerical simulation is also a consideration. Modest increases in model resolution, increases in the sophistication of model physics and incorporation of new capabilities (e.g interactive coupling with biogeochemistry, atmospheric chemistry) can increase the computational requirements by several orders of magnitude. 

The most comprehensive mathematical models of the atmosphere appeared with the advent of electronic computers. Culmination of these efforts appeared in the work of Smagorinsky(1965) with the first GCM simulation employing the complete form of the equations of motion and model physics
Early 1960s: 1-D radiative convective models for greenhouse climate studies
1970s, 1980s: 1-D energy balance models for feedback analysis
1990s: Coupled atmosphere-ocean climate models

## Ongoing/Potential Future climate modeling challenges

-   Tropical Bias in high-end climate models
-   High resolution climate modeling
-   Cloud-resolving models
-   Biogeochemistry and carbon cycle modeling
-     From climate to comprehensive  Earth    System   Models  including Atm Chem
-    Exactly a decade ago, Nobel Prize to Crutzen, Molina, Rowland for elucidating atm chem processes in ozone depletion. The first award ever for Atm. Chem. and global environmental studies. Hopefully not the last....