CCMVal Status and Overview

1
Chemistry-Climate Model Validation Activity for
SPARC (CCMVal)Status and Workshop Goals
Veronika Eyring (DLR), Ted Shepherd (Univ.
Toronto), Darryn Waugh (JHU), Andrew Gettelman
(NCAR), and Steven Pawson (NASA)
CCMVal Workshop 2009 Toronto, 1-5 June 2009
2
Motivation
CCMVal-1 simulations
3
CCMVal approach to CCM Evaluation and analysis
CCMVal Evaluation Table
Eyring et al., BAMS, 2005
4
Example CCMVal Diagnostic Table For Transport
Process Diagnostic Variables Data
Subtropical and polar mixing barriers PDFs of long-lived tracers N2O, CH4, CFC-11, etc. Potential Vorticity (PV) Satellite and in situ (aircraft, balloons) chemical measurements and Meteorological Analyses
Subtropical and polar mixing barriers Latitudinal gradients of long-lived tracers N2O, CH4, CFC-11, etc. Potential Vorticity (PV) Satellite and in situ (aircraft, balloons) chemical measurements and Meteorological Analyses
Subtropical and polar mixing barriers Correlations of long-lived tracers N2O, CH4, CFC-11, etc. Potential Vorticity (PV) Satellite and in situ (aircraft, balloons) chemical measurements and Meteorological Analyses
Subtropical and polar mixing barriers Phase and amplitude of tropical CO2 or H2O annual cycle in lower stratosphere (tape recorder) CO2, H2O or idealized annually repeating tracer Satellite and in situ measurements
Meridional circulation Mean age Conserved tracer with linearly increasing concentration, SF6 or CO2 in situ measurements
Meridional circulation Correlation of interannual anomalies of total ozone and Planetary wave flux Total ozone and heat flux at 100 hPa, zonal and monthly means Satellite measurements,Meteorological Analyses
Entire CCMVal Evaluation table
http//www.pa.op.dlr.de/CCMVal/CCMVal_EvaluationTa
ble.html will be updated as part of the SPARC
CCMVal Report
Eyring et al., BAMS, 2005
5
CCMVal-1 (in support of WMO/UNEP 2007 and AR4)

• 13 CCMs participated in the first round of CCMVal
  (CCMVal-1).
• Output collected in the central CCMVal database
  at the British Atmospheric Data Centre (BADC).
• Evaluation diagnostics obtained from various
  observational datasets.
• Results have been used to support the 2006
  WMO/UNEP Scientific Assessment of Ozone Depletion
  and IPCC AR4.
• Currently around 60 CCMVal Collaborators working
  with CCMVal output
• Several CCMVal-1 papers published,
• submitted or in preparation.
• Multi-model evaluation focusing mainly on
• transport dynamics has been performed
• (e.g. large differences in inorganic chlorine).
• Demonstrated the advantage of a
• multi-model evaluation strategy.

6
CCMVal-1 Model Assessment (13 CCMs)mainly
focused on transport and polar dynamics
diagnostics
Inorganic Chlorine
Temperature Bias
Mean Age
Water Vapor
Eyring et al., JGR, 2006
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CCMVal-1 Ozone Projections
There are substantial differences in the date at
which Cly returns to 1980 values varying from
before 2030 to after 2050. (Primarily transport
related.) There is a similar large variation in
the timing of recovery of Antarctic spring-time
column ozone back to 1980 values.
Value of Process-oriented evaluation of CCMs
Eyring et al., JGR, 2007
8
Unsatisfying from an assessment point of view ...
WMO, 2007 TWENTY QUESTIONS AND ANSWERS ABOUT THE
OZONE LAYER 2006 UPDATE Lead Author D.W. Fahey
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Quantitative Performance Metrics Inorganic
Chlorine Cly
Grades
Waugh Eyring, ACP, 2008
good
bad
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CCMVal-1 developedperformance metrics

• Potential benefits
• Allow visualization of performance for multiple
  aspects of the simulations.
• Allow identification of incompletely modeled
  processes.
• Enable quantitative assessment of model
  improvements for different versions of individual
  CCMs and for different generations (e.g. CCMVal-1
  vs CCMVal-2).
• Make it possible to explore the value of
  weighting the projections.
• Potential improvements
• Explore other metrics.
• Consider other diagnostics (radiation
  chemistry).
• Better consider uncertainty in observations by
  using observations from multiple platforms and
  instruments.
• Metrics for seasonal and interannual variability
  and trends.
• Statistically more robust grading.

1
0
Waugh and Eyring, ACP, 2008
11
Weighting Ozone Projections
For diagnostics and ozone projections considered
there is, generally, only small differences
between weighted and unweighted multi-model mean
projections.
12
IPCC, WGNE and WGCM

• The missing set of metrics that might be used to
  narrow the range of plausible climate projections
  through a comparison of model simulations with
  observations is one of the current principal
  source of uncertainty in model evaluation IPCC,
  AR4, WG1, 2007.
• WGNE/WGCM metrics panel established (Members
  Karl Taylor, Beth Ebert, Veronika Eyring, Peter
  Gleckler, Robert Pincus, Richard Wood)
• IPCC Expert meeting on "Metrics" and "Assessing
  and Combining Multi-model Climate Projections",
  January 2010, NCAR, Boulder, USA

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CCMVal Diagnostic Tool (requires NCL Python
installed)

• Andrew Gettelman (NCAR), Veronika Eyring (DLR),
  Greg Bodeker (NIWA), Irene Cionni (DLR), Chris
  Fischer (NCAR), Mike Neish (Univ. Toronto),
  Hamish Struthers (NIWA), Ted Shepherd (Univ.
  Toronto), Hisako Shiona (NIWA) Charlotte Pascoe
  (BADC)
• Facilitate the model evaluation for CCMVal, e.g.
• Allow quick looks at standard diagnostic plots
  output diagnostic variables
• Produce climatology files from CCMVal
  CF-compliant model output.
• Include the diagnostics of the previous round of
  CCMVal evaluation so that we don't have to start
  from scratch each time
• ensures progress
• allows to assess quickly where we stand with the
  new CCMVal simulations
• helps to increase the standard for CCM evaluation
• Expandable and extensible
• Useful for multiple model groups those
  analyzing models
• SPARC CCMVal report can extend tool (i.e. provide
  diagnostics once report is finalized)
• Extend with tropospheric diagnostics (in
  collaboration with Jean-Francois Lamarque)

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E06FIG01.ncl Figure1 of Eyring et al., JGR, 2006

• ./var_att/ta_att.ncl
• info_at_fig01_lat_max (/90.,90.,-60.,-60./)
• info_at_fig01_lat_min (/60.,60.,-90.,-90./)
• info_at_fig01_season (/"DJF","MAM","JJA","SON"/)
• info_at_fig01_refModel (/"ERA-40"/)
• info_at_fig01_climObs (/"NCEP","UKMO"/)
  Climatological Observation file
• info_at_fig01_climObs_file (/"input_data/OBS/CCMVal
  1_1980_2000_NCEP_Obs_T2Mz_ta.nc","input_data/OBS/C
  CMVal2_1992-2001_UKMO_Obs_C2Mz_ta.nc"/) C2Mz file

Climatological mean temperature biases for
latitudes between info_at_fig01_lat_max and
info_at_fig01_lat_min for the info_at_fig01_season
seasons. Biases are calculated relative to
info_at_fig01_refModel. The grey area shows
info_at_fig01_refModel plus and minus 1 standard
deviation about the climatological mean. The
climatological means info_at_fig01_climObs are
included.
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CCMVal-2 (in support of WMO/UNEP 2010 and AR5)

• 18 CCMs participate in the 2nd round of CCMVal
  (CCMVal-2).
• CCMVal-2 reference and sensitivity simulations
  defined (Eyring et al., 2008)
• CCMVal-2 simulations of the future begin in 1960,
  and most continue to 2100.
• Earlier starting date allows a more accurate
  determination of the milestone when total ozone
  returns to pre-1980 levels
• Extended simulations allow multi-model ozone
  projections and an analysis of the causes of
  these projected changes throughout the 21st
  century.
• CCMVal-2 data request output is collected in
  Climate and Forecast (CF) standard compliant
  NetCDF format at BADC.
• Allows automatic software to work on the output
  (e.g. CCMVal diagnostic tool and netCDF
  operators).
• Same format as for CMIP5 simulations.
• Base output for core diagnostics 3D (lat, lon, p)
  monthly mean fields. In addition, instantaneous
  output for a subset of diagnostics is collected
  (e.g. UTLS).
• CCMVal Data Policy
• To release the model data to the SPARC CCMVal
  author teams at an early stage, a PHASE 0 has
  been added to the existing Phase 1 and 2 of the
  CCMVal data policy.
• In PHASE 0 CCMVal-2 data are only accessible for
  the authors and models PIs.

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CCMVal-2 Models
Model Group and Location Horiz. resolution Vert. Layers / Upper Boundary
1 AMTRAC3 GFDL, USA 2 (lat) x 2.5(lon) 48 L / 0.002 hPa
2 CAM3.5 NCAR, USA 1.9(lat)x2.5(lon) 26 L / 2.2 hPa
3 CCSRNIES NIES, University of Tokyo, Japan T42 34 L / 0.012 hPa
4 CMAM MSC, Univ. of Toronto, York Univ., Canada T31 71 L / 0.000637 hPa
5 CNRM-ACM Meteo-France, France T42(GCM), T21(CHEM) 60L / 0.07 hPa
6 E39CA DLR, Germany T30 39 L / 10 hPa
7 EMAC MPI Mainz, Germany T42 90 L/ 0.01hPa
8 GEOSCCM NASA/GSFC, USA 2 x 2.5 72 L / 0.01hPa
9 LMDZrepro IPSL, France 2.5 x 3.75 50 L / 0.07 hPa
10 MRI MRI, Japan T42 68 L / 0.01 hPa
11 NIWA-SOCOL NIWA, NZ T30 39 L / 0.01 hPa
12 SOCOL PMOD/WRC and IAC ETHZ, Switzerland T30 39 L / 0.01 hPa
13 ULAQ University of L'Aquila, Italy 10 x 22.5 (CHEM) 26 L / 0.04 hPa
14 UMETRAC NIWA, NZ 2.5 x 3.75 64 L / 0.01 hPa
15 UMSLIMCAT University of Leeds, UK 2.5 x 3.75 64 L / 0.01 hPa
16 UMUKCA-METO MetOffice, UK 2.5 x 3.75 64 L / 84 km
17 UMUKCA-UCAM University of Cambridge, UK 2.5 x 3.75 64 L / 84 km
18 WACCM (v.3) NCAR, USA 4 x 5 66 L / 4.5 x 10-6 hPa
17
InorganicChlorineCCMVal-1CCMVal-2
Documentation of Model Improvements
18
SPARC CCMVal Report on Evaluation of CCMs 18
CCMs in support of WMO/UNEP 2010 and IPCC AR5

• In the past there has been insufficient time to
  evaluate CCM performance thoroughly while
  preparing the Ozone Assessments.
• The goal of the SPARC CCMVal report is to provide
  useful and timely information for the WMO/UNEP
  2010 IPCC AR5 and an up-to-date evaluation of
  CCMs, a reassessment of the projections of ozone
  and UV radiation through the 21st century, and
  the impact of stratospheric changes on climate.
• Structure and Authors (around 100 authors are
  analyzing the CCMVal-2 data)
• Executive Summary Eyring, Shepherd, Waugh plus
  chapter Lead Authors
• Chapter 1 Introduction Eyring, Shepherd,
  Waugh
• Part A Chapter 2 Chemistry Climate Models and
  Scenarios Morgenstern, Giorgetta, Shibata
• Part B Process evaluation
• Chapter 3 Radiation Fomichev, Forster
• Chapter 4 Dynamics Butchart, Charlton
• Chapter 5 Transport Neu, Strahan
• Chapter 6 Chemistry and microphysics
  Chipperfield, Kinnison
• Chapter 7 UTLS Gettelman, Hegglin
• Part C Chemistry-Climate Coupling
• Chapter 8 Natural Variability Manzini, Matthes
• Chapter 9 Long-term Projection of Stratospheric
  Ozone Austin, Scinocca
• Chapter 10 Effect of the Stratosphere on Climate
  Baldwin, Gillett
• Timelines Currently under final external review,
  published Jan-March 2010 JGR Special Issue

19
Chapter 7 The UTLS in chemistry-climate
models Michaela I. Hegglin Andrew
Gettelman Seok-Woo Son, Masatomo Fujiwara,
Simone Tilmes, Laura Pan, Peter Hoor, Huikyo Lee,
Gloria Manney, Thomas Birner, Gabriele Stiller,
Markus Rex, Stefanie Kremser, Don Wuebbles

• CCMVal-2 included for the first time the
  comprehensive validation of CCM performance in
  the tropical and extra-tropical UTLS.
• Major efforts were needed in order to
• find and process suitable observations for
  comparison
• establish robust diagnostics for the CCMs (which
  operate in a free-running mode and are
  multi-dimensional)
• turn the diagnostic into a quantitative grade
• Trend analyses for tropopause measures and
  chemical species were also included.

20
The global UTLS
21
Seasonal cycle in H2O
The right representation of the water vapour is
critical for both the radiative and chemical
properties of the UTLS (and the stratosphere in
general), and should be mainly determined by the
seasonal cycle in the tropical cold point
temperatures.

• The models show major difficulties in reproducing
  the H2O seasonal cycle.
• Model means, phase, and amplitude of the seasonal
  cycle exhibit a wide range.
• At lower altitudes, the models indicate too
  strong mixing across the tropopause.

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GLOBAL UTLS METRICS TABLE
23
KEY FINDINGS

• Despite their relatively low horizontal
  resolution, the CCMs perform reasonably well in
  resolving the complex processes and structures in
  the UTLS. Models with semi- Lagrangian transport
  schemes tend to be overly diffusive and perform
  worst.
• The models perform least in representing the
  amplitude and phase in water vapour, both in the
  tropics and the extra-tropics. This seems
  particularly worrisome in the light of the
  expected feedback role of water vapour.

KEY ISSUES AND RECOMMENDATIONS

• The UTLS is still relatively sparsely sampled by
  observations. This limits our confidence in the
  quantitative evaluation of model performance in
  the UTLS. New observations are needed especially
  for O3 and H2O with a vertical resolution better
  than 1 km and a horizontal resolution better than
  100 km, especially in the SH and the tropics.
• In this round of CCMVal, our main focus was on
  evaluating the representation of dynamics, and
  transport and mixing in the UTLS.
• However, testing chemistry should be part of
  future model validation efforts, including
  tropospheric CCMs used for the IPCC. Future model
  development is needed that brings together
  tropospheric and stratospheric chemistry climate
  models.

24
SPARC CCMVal Report Chapter 8 Natural
Variability of Stratospheric Ozone Lead
Authors Elisa Manzini and Katja
Matthes Co-Authors Christian Blume, Greg
Bodeker, Chiara Cagnazzo, Natalia Calvo, Andrew
Charlton-Perrez, Anne Douglass, Pier Giuseppe
Fogli, Lesley Gray, Junsu Kim, Kuni Kodera,
Markus Kunze, Cristina Pena Ortiz, Bill Randel,
Thomas Reichler, Gera Stenchikov, Claudia
Timmreck, Matt Toohey, and Shigeo Yoden
25
Motivation Stratospheric ozone is known to vary
in response to a number of natural factors, such
as the seasonal and the 11-year cycles in solar
irradiance, the QBO, ENSO, variations in
transport associated with large-scale
circulations (i.e., Brewer Dobson circulation)
and dynamical variability associated with the
annular modes. Aerosols from volcanic eruptions
can also affect stratospheric ozone, although
their effects depend on the background
atmospheric composition. Ozone observations have
demonstrated variations on a large number of
spatial and temporal scales. Objective The
goal of this Chapter is to evaluate how well CCMs
simulate natural stratospheric ozone variability,
based on our current knowledge about links
between ozone variations and natural forcings.
26
Tropical variability measure Detrended,
deseasonalized and filtered
(9-48 months) time series. Monthly zonal mean
standard deviation (5oS-5oN).
Zonal wind (m/s)
Ozone density (DU/km)
TOP PANELS The QBO (via nudging of the zonal
winds or vorticity) is assimilated in the
chemistry climate models (8 models out of 17
models)
CCMVal-2 simulations in color, ERA40 (left) and
SAGE (right) black.
27

• QBO, key results
• The modeling of the QBO in the CCMVal-2 models is
  judged to be still at a primitive stage. A very
  few models are capable to spontaneously simulate
  the salient features of QBO ozone variations.
• Some AGCM in recent years have been able to
  simulate a quite realistic QBO in zonal winds and
  related dynamical quantities, but it does not
  seem that this expertise has passed to the CCMs,
  possibly also because of the computational and/or
  developmental constrain of the additional
  chemical modelling.
• The nudging of the QBO induces substantial errors
  in QBO ozone variations, notably in the amplitude
  of the column ozone.
• RECOMMENDATIONS
• Advance the development of the modeling of the
  QBO is called for. This modeling problem is
  outstanding. It is an open issue that cannot be
  tackled by assimilating selected properties of
  the observed QBO in the CCMs.

28
SPARC CCMVal Report Chapter 9 Long-term
projections of stratospheric ozone Lead
Authors John Austin and John Scinocca Co-Author
s Trevor Bailey, Luke Oman, David Plummer,
David Stephenson, and Hamish Struthers
29
Ozone Changes in CCMVal-2

• Vertical profile results of the MLR analysis for
  the CCMVal-2 models in the latitude band
  10S-10N.
• (a) Ozone in the year 2000
• (b) Ozone change from 2000 to 2100
• (c) EESC change from 2000 to 2100,
• (d) Contribution of the EESC change to the ozone
  change.
• (e) and (f) are the same as (c) and (d), except
  for temperature.
• From Chapter 9, Figure 9.4 of SPARC CCMVal
  (2010).

30
Ozone Changes in CCMVal-2

• 1980 baseline-adjusted multi-model trend (MMT)
  estimates of annually averaged total ozone for
  the latitude range 60-90S (heavy dark grey line)
  (upper panels).
• The baseline-adjusted IMT estimates, and
  unadjusted fit to the observations are
  additionally plotted.
• The lower panel shows the same analysis of
  CCMVal-2 data but for a baseline adjustment
  employing a 1960 reference date
• From Chapter 9, Figure 9.11 of SPARC CCMVal
  (2010).

31
Ozone Changes in CCMVal-2

• Date of return to 1960 (left) and 1980 (right)
  values for the annual average (tropical and
  midlatitude) and spring (polar) total ozone
  column derived from the IMT (colored symbols) and
  MMT (large black triangles) estimates for
  CCMVal-2 (left and right respectively in each
  latitude band).
• From Chapter 9, Figure 9.21 of SPARC CCMVal
  (2010).

32
SPARC CCMVal Report Chapter 10 Effects of the
stratosphere on the troposphere Lead Authors
Mark Baldwin Nathan Gillett Co-Authors
Piers Forster, Ed Gerber, Michaela Hegglin,
Alexey Karpechko, Junsu Kim, Paul Kushner, Olaf
Morgenstern, Thomas Reichler, Seok-Woo Son,
Kleareti Tourpali
33
Effect of ozone hole depletion/recovery on climate

• y-axis is SH
• polar cap 50 hPa ozone
• x-axis is
• (a) SH polar cap 100 hPa temperature
• (b) TP pressure poleward of 50S
• (c) latitude of 850 hPa zonal wind maximum
• (d) SH Hadley cell boundary at 500 hPa

34
Effect of climate change on clear-sky UV radiation

• High northern latitudes will see a long-term
  reduction in UV
• Tropics will see a long-term increase

35
Effect of ozone depletion/recovery and climate
change on stratosphere-to-troposphere ozone flux

• Effect of ozone depletion/recovery evident in SH
• Strengthening Brewer-Dobson circulation will
  increase ozone flux
• CCMVal models on the high side of AR4 range, also
  of the observational estimates

36
AR5 WG1 draft outline

• Ch.1 Introduction
• Ch.2 Observations Atmosphere and Surface
• Ch.3 Observations Ocean
• Ch.4 Cryosphere
• Ch.5 Information from climate archives
• Ch.6 Carbon and other biogeochemical cycles
• Ch.7 Clouds and aerosols
• Ch.8 Anthropogenic and natural radiative forcing
• Ch.9 Evaluation of climate models
• Ch.10 Detection and attribution of climate
  change from global to regional
• Ch.11 Near-term climate change projections and
  predictability
• Ch.12 Long-term climate change projections,
  commitments, reversibility
• Ch.13 Sea-level change
• Ch.14 Climate phenomena and their relevant for
  future regional climate change

37
SPARC and IGAC possible points of entry

• Ch.2 Observations Atmosphere and Surface
• Changes in atmospheric circulation
• Spatial-temporal patterns of climate variability
• Ch.7 Clouds and aerosols
• Aerosol types, including black carbon
• Geoengineering involving aerosols
• Ch.8 Anthropogenic and natural radiative forcing
• Radiative forcing changes solar and volcanic
• Effects of atmospheric chemistry and composition,
  incl. GHGs
• Radiative forcing due to emissions from aviation
  and shipping
• Ch.9 Evaluation of climate models
• Performance metrics, ensembles and their use
• New model components and coupling
• Representation of processes and feedbacks in
  climate models
• Simulation of recent and longer-term records
• Simulation of regional patterns, variability and
  extremes

38

• Ch.10 Detection and attribution of climate
  change from global to regional
• Atmospheric and surface changes
• Ch.11 Near-term climate change projections and
  predictability
• Climate change projections for the next few
  decades
• Predictability of decadal climate variations and
  change
• Regional climate change, variability and extremes
• Atmospheric composition and air quality
• Possible effects of geoengineering
• Ch.12 Long-term climate change projections,
  commitments, reversibility
• Projections for the 21st century
• Ch.14 Climate phenomena and their relevant for
  future regional climate change
• Patterns of variability
• Monsoons
• Interconnections among phenomena

39
AR5 WG2 draft outline (30 chapters!)
SPARC and IGAC point of entry

• Ch.11 Human health
• Air quality and human health with WG1 authors on
  air quality
• I asked Chris Field (WG2 co-chair) about
  climate/ozone/UV aspects, and he said that
  climate/ozone/health issues would be part of this
  section. He said there are considering a
  separately identified group of atmospheric
  chemistry authors.