Transcript Wrap up - Ensembles

Components of the climate system,
interactions, and changes
(Source: IPCC AR4 WG1 Ch.1, FAQ 1.2, Figure 1)
Atmospheric reanalysis: ERA-Interim
ECMWF forecasts:
2010
1980 –
Changes in skill are due to:
• improvements in modelling
and data assimilation
• evolution of the observing
system
• atmospheric predictability
ERA-Interim:
1979 – 2010
• uses a 2006 forecast system
• ERA-40 used a 2001 system
CCI project integration
meeting
• re-forecasts more uniform
quality
• improvements in modelling and
data assimilation outweigh
improvements in the
observing
system
Veronika Eyring, ESA CCI project integration meeting, March 2011
Reanalysis
Modelers, PCMDI, JPL/NASA, Community
Who does what?
Model output
archived in a
uniform fashion
to facilitate
access and
analysis. (Far
from trivial – see
below)
Sophisticated
Identify and
Develop global
development
deliver/archive
observations
and application
observations in
relevant to
of model
form useful for
climate change
diagnostics for
model analysis
research (Focus
evaluation
(Requires
on hardware,
(Observations
model, obs and
retrievals,
needed here,
IT expertise)
delivery)
but which
ones?)
To quantify and reduce uncertainty, this chain has to
work.
Enormous Model Output/Complexity
pre-industrial control
present-day control
climate of the 20th Century (20C3M)
committed climate change
SRES A2
720 ppm stabilization (SRES A1B)
550 ppm stabilization (SRES B1)
1%/year CO2 increase (to doubling)
1%/year CO2 increase (to quadrupling)
slab ocean control
2xCO2 equilibrium
AMIP
0
2
4
6
8
10
12
14
16
18
Number of Models
20
22
24
26
Waliser et al. 2009, Climatic Change, Submitted.
Produce
Simulations &
Projections
(HUGE job;
focus on model
development –
not analysis or
observations)
PCMDI
NASA Recommended Datasets for CMIP5
Model
Match up of
available
NASA
datasets to
PCMDI
priority list
4
Dataset
Time
Period
9/02 –
8/04 -
PCMDI
Comments
Atm Temperature
(200,850hPa)
AIRS (≥ 300 hPa)
MLS ( < 300 hPa)
Zonal and meridional wind
(200,850 hPa)
No obvious match
Specific humidity (200, 850
hPa)
AIRS (≥ 300 hPa)
MLS ( < 300 hPa)
Sea level pressure
No obvious match
Surface (10m) zonal and
meridional wind
QuikSCAT
CCMP
1999 – 2009
7/87 – 12/09
Oceans only. No land products. CCMP is a
multi-sensor variational analysis product
Ocean surface zonal and
meridional wind stress
QuikSCAT
CCMP
1999 – 2009
7/87 – 12/09
Oceans only. No land products. CCMP is a
multi-sensor variational analysis product
Sea surface temperature
AMSR-E
6/02 -
SST science team recommends multiple products
TOA reflected shortwave
radiation and OLR
CERES
3/00 -
TOA longwave and shortwave
TOA clear-sky fluxes
CERES
3/00 -
Total precipitation
TRMM
GPCP
1997 2/79 – 4/08
Cloud cover
MODIS
2/00 -
Precipitable water
SSM/I
7/87 -
Sea surface height
TOPEX/JASON
series
10/92 -
Sea ice
NSIDC
AIRS +MLS needed to cover all pressure levels
Reanalysis is the best product
9/02 –
8/04 -
AIRS +MLS needed to cover all pressure levels
Reanalysis is probably the best product match
GPCP is an analysis product
Project scientist recommends converting the
AVISO product
microwave product would be best. More
investigation is needed.
Evaluation Datasets
Aerosols
Carbon Cycle
Chemistry
Clouds
Precipitation
Radiation
Surface Fluxes
EMEP
11
GLODAP
8
MIPAS
12
ISCCP-D
9
GPCP
4
ERBE
13
NCEP-NCAR
6
IMPROVE
11
NOAA ESRL GMD
4
UARS
8
MODIS
7
CMAP
3
CERES
EANET
9
TRANSCOM
4
HALOE
4
CALIPSO
6
NCEP-NCAR
1
ISCCP-FD
4
SMD94
4
AERONET
9
Fluxnet
4
TOMS
3
MISR
3
GPCC
1
PARASOL
3
ISCCP-FD
4
GAW
4
EUROFLUX
3
MOZAIC
3
PARASOL
3
CRU
1
GEBA
2
ERBE
2
SKYNET
4
AMERIFLUX
3
SCIAMACHY
3
TOGA-COARE
3
HOAPS
1
BSRN
2
GEBA
2
AEROCE
3
NCEP/DOE AMIP-II
2
ODIN
3
AMMA
3
TRMM
1
MODIS
2
CMAP
2
MISR
3
ISLSCP
2
ILAS
3
SIRTA
3
NCEP/DOE AMIP-II
1
SMD94 (da Silva)
1
ERA-40
2
MODIS
3
Takahashi DB
2
MOPITT
2
BOMEX
3
ERA-Interim
1
NCEP-NCAR
1
HOAPS
2
Amsterdam Island &
Cape Grim
3
CARBOOCEAN
2
SHADOZ
2
ARM
3
AMMA
1
NOAA Interpolated
OLR
1
OAFLUX
2
CASTNET
2
Zinke et al.
2
Logan
2
CloudSat
2
ISCCP-D
1
BSRN
2
U of Miami
1
Olson et al.
2
TES
2
ERBE
1
SIRTA
1
GPCP
1
POLDER
1
MODIS
2
TRMM
2
NOAA Interpolated OLR
1
TOGA-COARE
1
MODIS
1
CALIPSO
1
SeaWifs
1
ERA-40
2
AIRS
1
ARM
1
SEAREX
1
ClimPP
1
UKMO analysis
2
TES
1
VGPM
1
NIWA
1
SCIAMACHY
1
EMDI
1
WOUDC
1
Norby et al.
1
NOAA ESRL GMD
1
IGBP
1
EMEP
1
GEOLAND
1
CASTNET
1
Sabine et al.,2004
1
IMPROVE
1
Carr et al. 2006
1
NDEP
1
Kettle et al. 1999
1
EANET
1
AVHRR/NOAA
1
AIRS
1
GPCP
1
11 Southampton climatology 5
Quantitative Performance Metrics


A performance metric is a statistical measure of agreement between a simulated
and observed field (or co-variability between fields) which can be used to assign a
quantitative measure of performance (“grade”) to individual models
Low-order statistical measures: RMS error, mean error (bias), ratio of s,
correlation for each variable
Performance
Metrics
Single Model
Index
Weighting
Gleckler et al., JGR, 2008
Veronika Eyring, ESA CCI project integration meeting, March 2011
Meeting Aims
•
Check ECV project URDs are consistent with the needs of
Climate Research Groups and GCOS requirements, including
source traceability
•
Allow ECV teams to explain how their projects address the
integrated perspective for consistency between the ECVs to
avoid gaps
•
Start review of product specifications but define what is in it.
•
Discuss how to deal with uncertainties in products
•
Finalise the ECV projects data needs for ECMWF reanalysis data
•
Start a discussion on ECV data set validation
•
Maintain oversight of the position within the international
framework in which CMUG/CCI is operating
Actions
• All ECVs who want ERA-Interim data to reply to David
• Ensure consistent use of level 1B data CCI+CMUG
• Interpolation should be co-ordinated within and
between projects (CDO tool) CCI
• Discussion on trial datasets and code to write
datasets in correct format. Data Standards WG
• Continue interaction with JPL NASA CMIP5 project,
NASA Measures?, EUMETSAT and GCOS All
• More presentations on use of satellite data in climate
models in next coloc meetings. CMUG
• Identify potential comparisons CCI+CMUG
• Need for ‘Golden Year’? (e.g. aerosol vs FIRE) CMUG
to complete table
Uncertainty from Coloc 1
• precision: a measurement which has a small random
uncertainty is said to have high precision
• accuracy: a measurement which has a small systematic
uncertainty is said to have high accuracy
Related Activities
1.
2.
3.
4.
5.
6.
GCOS, GSICS (Jan/Feb 2011)
EUMETSAT CAF/CMSAF and SCOPE-CM
NOAA-NASA initiatives (e.g. JPL CMIP5)
WCRP Observation and Assimilation Panel (Apr 11)
Reanalyses (ERACLIM, JRA-55, EURO4M)
Coupled Model Intercomparison Project and
follow-on activities (Exeter, June 11)
7. Inputs to IPCC AR-5/6 (interaction with authors)
8. EU IS-ENES, METAFOR, …
9. EU GMES (MACC, MyOcean, Climate, ….)
Outputs from meeting
• Meeting report of actions agreed by ECV projects
Action: CMUG
• Scientific report describing strategic position of the
CCI, in the international arena Action: CMUG+CCI
• Updates to URDs, DARDs based on discussions here
and CMUG review (D2.1) and release of PSDs
Action: CCI
• Review terminology for error characteristics
CMUG+CCI
• Slides from this meeting on CMUG web site Action:
CMUG