Report of the 13th Session of the JSC/CLIVAR

Working Group on Coupled Modelling (WGCM)San Francisco, 28-30 September 2009

Veronika Eyring (DLR, Germany)

13th Session of the JSC/CLIVAR Working Group on Coupled Modelling (WGCM)

San Francisco, 28-30 September 2009

I. Background and goals of the WGCM meetingII. Status CMIP5

Participating Models

CMIP5 SimulationsIII. Forcings CMIP5 simulations

Historical non-CO2 emission

IPCC Representative Concentration Pathways (RCPs)

AC&C/SPARC Ozone Database for CMIP5 IV. Observations for CMIP5

WOAP

NASA initiativeV. Evaluation of models

WCRP survey

Process-oriented evaluation

OUTLINE

Background:

• WCRP Working Group on Coupled Modelling (WGCM) leads the development of coupled ocean/atmosphere/land models used for climate studies on longer time-scales.

• WGCM is also WCRP's link to the Earth system modelling in IGBP's Analysis, Integration and Modeling of the Earth System (AIMES) and to the Intergovernmental Panel on Climate Change (IPCC).

Members:

S. Bony and. J. Meehl (co-chairs)

P. Braconnot, V. Eyring (SPARC, AC&C), D. Karoly, A. Hirst, M. A. Giorgetta, M. Kimoto, B. Wang, F. Giorgi N. Nakicenovic, C. Senior

Goals of this years WGCM meeting:

1. Make progress with CMIP5

2. Model evaluation

3. 1- day jointly with AIMES

I. Background WGCM and Gaols of the Meeting

Primary Group

Country Primary Contact

NERSC Norway M. Bentsen, H. Drange

Hadley Centre U.K. M. Collins, C. Jones

GFDL U.S.A.T. Delworth, I. Held, L. Horowitz, R. Stouffer

IPSL & LMD France J-L. Dufresne, S. Bony

NIES & U. Tokyo,

JapanS. Emori, M.

Kawamiya, M. Kimoto,

CCCMA Canada G. Flato

MPI-HH Germany M. Giorgetta

INGV Italy S. Gualdi

EC-Earth consortium

Europe W. Hazeleger

CSIRO & BMRC

Australia T. Hirst, K. Puri

NASA GSFC U.S.A. M. Suarez

Primary Group

Country Primary Contact

CSIRO & QCCCE

AustraliaL. Rotstayn, J. Syktus, S.

Jeffrey

NCAR U.S.A. J. Hurrell, J. Meehl

MRI Japan M. Kimoto

METRI (with Hadley Centre)

Korea W-T. Kwon

LASG IAP China T. Zhou, B. Wang

NASA GISS U.S.A. G. Schmidt

BCC ChinaQ. Li, Y. You, Z. Wang, T.

Wu, Y. Xu,

INM Russia E. Volodin

CERFACS & CNRM

France L. Terray, D. Salas-Melia

U. Reading U.K. L. Shaffrey

II. Status CMIP5Participating Models

© Crown copyright Met Office

1. Near-Term (2005-2030) high resolution (perhaps 0.5°), no carbon cycle, some chemistry and aerosols, single scenarioScience question: e.g. regional extremes

1. Longer term (to 2100 and beyond) lower resolution (roughly 1.5°), carbon cycle, specified or simple chemistry and aerosols, benchmark stabilization concentration scenarios; Science question: e.g. feedbacks.

II. CMIP5 model simulationsTwo classes of models to address two time frames and two sets of science

questions

Long-term simulations

• Solar (based primarily on Lean but spectrally resolved, or not)

• Historical non-CO2 emissions

• RCP emissions (different IAMs used to produce each RCP)

• Land-use (U. of New Hampshire – Chini, Hurtt, Frolking)

• Ozone time-evolving 3D historical concentrations (AC&C/SPARC)

• AMIP SSTs and sea ice (PCMDI)

• CFMIP Aqua-planet and idealized future pattern of SST (Hadley Centre)

III. Forcings CMIP5 Forcing data available on CMIP website (or via

links)http://cmip-pcmdi.llnl.gov

IIIa. AC&C: Historical Emissions for CMIP5

International effort to provide improved emissions 1850-2300, consistent across 2000 for anthropogenic (including shipping and aircraft) and biomass burning of reactive gases (not ODSs) and aerosols

Historical (1850-2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application.Jean-François Lamarque, Claire Granier, Tami C. Bond, O. Cooper,.Veronika Eyring, Angelika Heil, Mikiko Kainuma, Z. Klimont, David Lee, Catherine Liousse, J. R. McConnell , Aude Mieville, S. Oltmans, Bethan Owen, D. Parrish. Keywan Riahi, Martin Schultz, Drew Shindell, Steven Smith, Elke Stehfest, Allison Thomson, John Van Aardenne, Detlef Van Vuuren

IIIb. Scenarios and Harmonization

Objective to provide consistent set of emissions, concentrations and land use data at grid level for 1700-2100 (2300 period)

Harmonized in 2000 with “databases” and smooth transition to historical trend and future scenario.

Integrated Assessment Models (IAMs) provide concentrations for well-mixed gases, and emissions for air pollutants. Emissions will be translated into concentrations by atmospheric chemistry.

Source: van Vuuren et al., 2009Source: van Vuuren et al., 2009

RCP6.0 (not yet available). Either keeping constant or ramping back to RCP4.5

RCP6.0 (not yet available). Either keeping constant or ramping back to RCP4.5

Source: van Vuuren et al., 2009

IIIb. RCPs

• Ozone hole has led to a strengthening of the summertime surface westerlies at SH high latitudes [Thompson and Solomon, 2002].

• Ozone recovery is predicted to reverse that trend, with implications for the circulation of the southern ocean [Son et al., 2008].

• Effects of O3 depletion/recovery also in many other climate indicators showing its global impact.

• CMIP3 models without any prescribed ozone changes (green), the past and future trends are the same; whereas models with prescribed ozone depletion and ozone recovery are different

=>Need accurate representation of ozone recovery in climate projections.

Son et al., GRL, 2009

IIIc. AC&C / SPARC Ozone Database for CMIP5Effect of stratospheric ozone on climate

Oct-Jan DJF DJFDJF

IIIc. AC&C / SPARC Ozone Database for CMIP5Original plan: Building a new global ozone

databaseOriginal goal: create a new ozone database that would be available in

time for the CMIP5 modellers to use for AR5.

• The NCAR databaseThe NCAR database ( (Randel & WuRandel & Wu))

• The NIWA databaseThe NIWA database ( (Bodeker & HasslerBodeker & Hassler))

• The NOAA databaseThe NOAA database ( (Rosenlof & GrayRosenlof & Gray))

• The GSFC databaseThe GSFC database ( (Stolarski and FrithStolarski and Frith))

• The The Environment Canada databaseEnvironment Canada database ( (Fioletov and McLindenFioletov and McLinden))

However, we couldn't reach a consensus approach among the individual database contributors. But this doesn’t mean that we have abandoned the consensus ozone database project. The need for a consensus database remains.

Different Tiers:

Tier 0: Raw zonal mean monthly mean data

Tier 1: Databases constructed using a regression model, no missing data, pole-to-pole coverage, tropopause to 50 km or higher

A. Historical Database (1850-2009): CF netCDF monthly-mean lon, lat, pressure, time:month

1. Stratospheric data (Zonal means): • Multiple linear regression analysis of SAGE I+II satellite observations and polar ozonesonde

measurements for the period 1979-2005 (Randel and Wu, JGR, 2007). • Regression includes terms representing equivalent effective stratospheric chlorine (EESC) and

11-year solar cycle variability.• Extended backwards to 1850 based on the regression fits combined with extended proxy times

series of EESC and solar variability.2. Tropospheric data (3D but decadal averages):

• Average from the Community Atmosphere Model (CAM) version 3.5 and the NASA-GISS PUCCINI model.

• Both models simulate tropospheric and stratospheric chemistry with feedback to the radiation and were driven by the recently available historical (1850-2000) emissions succintly described in Lamarque et al., IGAC Newsletter, May 2009.

3. Combined stratospheric / tropospheric data (3D but underlying zonal mean in stratosphere):• S and T are combined by merging the two data sets across the climatological tropopause, to

produce a smooth final data set.

FINAL VERSION RELEASED ON 22 SEP 2009 (see CMIP5 website, 16 files a 30 MB)

Goal: Provide a merged tropospheric / stratospheric ozone time series from 1850 to 2100 for use in CMIP5 simulations without interactive chemistry.

I. Cionni & V. Eyring (DLR), JF. Lamarque & B. Randel (NCAR)

IIIc. AC&C / SPARC Ozone Data Sets for CMIP5

IIIc. AC&C / SPARC Ozone Data Sets for CMIP5A. Historical Database (1850-2009)

see more plots at http://www.pa.op.dlr.de/CCMVal/AC&CSPARC_O3Database_CMIP5.html

Net Ozone Change 1979 to 2005 [%]

Cionni et al., in prep, 2009

500 hPa July Ozone

1900-1909

1950-1959 2000-2009

1850-1859

Total Ozone compared to

other observations

B. Future Database (2010-2099)

• Stratosphere: multi-model CCMVal-2 mean• Troposphere: Community Atmosphere Model (CAM) version

3.5• The data from the observational core and the model time

series are combined separately for each latitude band and pressure level using a linear regression model.

C. Combined Ozone Timeseries (1850 to 2100)

IIIc. AC&C / SPARC Ozone Data Sets for CMIP5

Cionni et al., in prep, 2009Austin, Scinocca et al., Chapter 9, SPARC CCMVal Report, 2009

IVa. ObservationsWOAP

Background

• WCRP Observation and Assimilation Panel (WOAP)• Karl Taylor was appointed to be WGCM’s representative on WOAP.• WOAP is a coordination Panel in WCRP • It attempts to coordinate WCRP’s interests in observation-related activities.• In particular, WOAP is WCRP’s preferred channel for interacting with GCOS (Global

Climate Observing System)• WOAP helps to coordinate GCOS panels (e.g., AOPC & OOPC) (Atmos. and Ocean

Observation Panels for Climate• WOAP has strong interest in• Improving reanalyses• Promoting better calibration of and especially the continuity of climate observations=> Make more use of the existence of WOAP within WGCM and SPARC (SPARC Data

Initiative; presentation at March 2010 workshop by Michaela or Susann?)

IVb. ObservationsNASA Initiative for CMIP5 (J. Teixeira et al.)

Objective

To provide the community of researchers that will access and analyze CMIP5 model results access to analogous sets of observational data.

Analogous sets in terms of periods, variables, temporal/spatial frequency

This activity will be carried out in close coordination with the corresponding CMIP5 modeling entities and activities

It will directly engage the observational (e.g. mission and instrument) science teams to facilitate production of the corresponding data sets.

V. Model Evaluation(a) WCRP Model Survey

Key deficiencies of climate simulations :- (double) ITCZ and monsoons - internal modes of variability of the tropical atmosphere (MJO, ISO, QBO, ENSO, etc)- (excessively strong) equatorial cold tongue ; - (warm) SST biases in the eastern ocean basins- troposphere-stratosphere interactions- regional climate change responses of precipitation and soil moisture- cloud-climate and carbon-climate feedbacks

Key deficiencies in the models' physics :- cloud and moist processes : atmospheric convection, precipitation, clouds in PBL, UTLS, polar..- land-surface processes; soil moisture – precipitation interactions - ocean-atmosphere coupling (resolution, high-wind regimes, etc)- oceanic eddies - non-orographic gravity-wave drag; upper boundary condition (lid)- atmospheric chemistry

General:- imbalance in visibility and efforts between the exploration of new, ‘hot’ territories and the work on key persistent unresolved problems; - the increase of models’ resolution reduces some problems, but creates new ones - efforts put in model evaluation very unequal (e.g. climate-carbon coupled models)- lack of inter-disciplinary interactions

V. Model Evaluation(a) WCRP Model Survey

(1) Promote the growth of the model development community :-> reaffirm the importance of improving basic atmospheric and oceanic components of models, ...

(2) Organize systematic and coordinated investigations (physical / statistical) of the link between model errors and prediction errors :

- > promote systematic investigations of the impact of resolution, strato/tropo coupling, eddies...(3) Reduce the gap between large-scale modeling/processes/observations communities :

-> encourage process-oriented evaluations/diagnostics of models (cf CFMIP, CCMVal)(4) Reduce the gap between climate/NWP/assimilation communities (5) Observations :

-> development of simulators for model-data comparisons -> maintain observing network for long time series (in-situ, satellite) ...

(6) Facilitate the sharing and the distribution of ressources (cf CMIP) :-> develop, collect and distribute diagnostics and codes (e.g. CLIVAR MJO WG)-> facilitate access to observations and meteorological analyses

(7) Adapt the configuration of international programmes :-> separation WCRP / IGBP : an anachronism ?-> facilitate interactions among a large range of communities and disciplines

The results of the WCRP Survey on Model Evaluation will be written up in a e.g. BAMS paper

V. Model Evaluation(b) Process-oriented evaluation of climate models &

ESMs

IPCC, AR4

Model Intercomparison Projects (MIPs)

CCMVal

C4MIP

ILAMBMAREMIP LUCID

AMIP CMIPCFMIP

AEROCOM

OCMIP

AOMIP SIMIP

Is it time to get a bit more coordinated ?

PILPS

Process-oriented ESM evaluationfollowing the CCMVal approach

Start with the evaluation of Essential Climate Variables (ECVs) from GCOS; in addition processes; Most EU-ESM groups on board, interest from PCMDI, Article to be submitted to BAMS

Climate Feedback

Process Diagnostic Variables Observations for ES M Evaluation

References

Physical climate feedbacks

Atmospheric Dynamics & Clouds

Water vapour/lapse rate feedback

Positive climate feedback by increased water vapour greenhouse effect

OLR, profiles of T, q, xl, xi, cloud fraction for 1xCO2 and 2xCO2 c limate simulations

Outgoing long-wave radiation (OLR)

CERES ES-4 Soden and Held [2006]

Land Surface physics

Land-cover status - energy balance feedback

Strength of soil moisture – temperature coupling

Correlation between summer evapotranspiration, temperature and soil moisture.

Total evapotranspiration, Sensible heat flux, Surface temperature, Total and surface soil moisture, FAPAR

FLUXNET ecosystem sites data, SeaWiFS & MERIS FAPAR

Fluxnet [2006]

Gobron et al. [1999, 2006]

Ocean Dynamics & Sea Ice

North Atlantic thermohaline circulat ion and climate feedbacks

Surface wind stress forcing, formation of intermediate and deep water masses

Anomalous poleward mass, heat and fresh water transport

Hydrography (temperature, salin ity); 3-D velocity; volume, heat and fresh water transports

National oceanographic data center (NODC); inflow and overflow transport over sills and through openings from literature

Hátún et al. [2005]

Østerhus et al. [2005]

Global carbon cycle feedbacks

Land Biogeochemistry

Feedback between climate change and Net Ecosystem Productivity

Gross Primary Productivity

Sensitivity to changes in CO2 and climate

GPP, surface/leaf temperature, precipitation

FLUXNET ecosystem sites data

NDVI satellite p roduct

FACE manipulat ive experiments

Fluxnet [2006]

Tucker et al. [2005]

Norby et al. [2005]

Marine Biogeochemistry

Feedbacks between climate change plus rising CO2 and the biological carbon pumps

Biological particle production at the sea surface and vertical particle fluxes throughout the water column

Sensitivity to changes in climate, ocean circulat ion, and rising CO2

POC primary production, POC export production, PIC production,

POC part icle fluxes,

CaCO3 part icle fluxes

Primary productivity derived from remotely sensed ocean colour (SeaWiFS)

Particle fluxes from JGOFS data base

Behrenfeld and Falkowski [1997a,b] Behrenfeld et al. [2005]

Atmospheric composition feedbacks

Aerosols

Aerosol –climate interactions and feedbacks

Oxidation, wet removal & vertical mixing in troposphere

Changes in precipitation rate, wet deposition rates, aerosol residence time, vertical part itioning

Speciated wet removal rates, precipitation, mixing ratios,

EMEP, IMPROVE, NADP, aircraft and lidar profiles (CALIOP)

Rae et al. [2007] Kirkevag et al. [2008]

Chemistry-Climate

Changes in RF due to tropospheric ozone and other oxidants

Biogenic precursor emissions (VOC and NOx)

Temperature - and climate-dependent changes in NOx and VOC emission rates

Mixing ratios of NOx and key VOCs (especially isoprene and products)

SCIAMACHY, GOME2 (CH2O as an indicator of VOCs); CMDL flask network; composites of fie ld campaign data

Yienger and Levy [1995]

Jaegle et al. [2005]

Guenther et al. [2006]

Land and ocean emissions & deposition

Soil – atmospheric chemistry feedbacks

Soil emissions; dry deposition

Climate-dependent changes in wind blown dust

Mass and size distributions of dust, surface wind speed, and soil characterization, soil moisture and vegetation cover

Satellite dust aerosol products, AERONET

Tegen et al. [2004]

Balkanski et al. [2004]

1

Concept of process- oriented ESM evaluation

Proposal for an ESM MIP

Aim : Facilitate/encourage/enforce process oriented evaluation of ESMs

- Coordinated diagnostic effort

- Build on previous MIPs experience

- Focus on processes and feedbacks relevant for climate projections

- Use of global 20th century observations

- Use of CMIP5 and related model simulations

- ESM perspective (eg. coupling issues)

- To be endorsed by WGCM and AIMES ?

E S MIP