Components of the climate system, interactions, and changes

(Source: IPCC AR4 WG1 Ch.1, FAQ 1.2, Figure 1)

Veronika Eyring, ESA CCI project integration meeting, March 2011

Atmospheric reanalysis: ERA-Interim

ECMWF forecasts: 1980 – 2010

Changes in skill are due to:

• improvements in modellingand data assimilation

• evolution of the observing system• atmospheric predictability

ERA-Interim: 1979 – 2010• uses a 2006 forecast system• ERA-40 used a 2001 system

• re-forecasts more uniform quality• improvements in modelling and data assimilation outweigh improvements in the observing system

CCI project integration meeting Reanalysis

PCMDI

Modelers, PCMDI, JPL/NASA, CommunityWho does what?

Produce Simulations &

Projections(HUGE job;

focus on model development – not analysis or observations)

Model output archived in a

uniform fashion to facilitate access and

analysis. (Far from trivial – see

below)

0 2 4 6 8 10 12 14 16 18 20 22 24 26

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

Number of Models

Sophisticated development

and application of model

diagnostics for evaluation

(Observations needed here,

but which ones?)

Identify and deliver/archive observations in form useful for model analysis

(Requires model, obs and

IT expertise)

Develop global observations relevant to

climate change research (Focus

on hardware, retrievals, delivery)

PCMDINASA

& JPLModelin

g

Centers

Weak

Link

Enormous Model Output/Complexity To quantify and reduce uncertainty, this chain has to work.

Wal

ise

r e

t al.

200

9,

Clim

atic

Ch

ang

e,

Su

bm

itte

d.

PCMDINASA Recommended Datasets for CMIP5

Match up of available NASA

datasets to PCMDI

priority list

4

Model Dataset Time Period

Comments

Atm Temperature (200,850hPa)

AIRS (≥ 300 hPa) MLS ( < 300 hPa)

9/02 – 8/04 -

AIRS +MLS needed to cover all pressure levels

Zonal and meridional wind (200,850 hPa)

No obvious match Reanalysis is the best product

Specific humidity (200, 850 hPa)

AIRS (≥ 300 hPa) MLS ( < 300 hPa)

9/02 – 8/04 -

AIRS +MLS needed to cover all pressure levels

Sea level pressure No obvious match Reanalysis is probably the best product 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

GPCP is an analysis product

Cloud cover MODIS 2/00 -

Precipitable water SSM/I 7/87 -

Sea surface height TOPEX/JASON series

10/92 - Project scientist recommends converting the AVISO product

Sea ice NSIDC 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 11 Southampton climatology 5

EANET 9 TRANSCOM 4 HALOE 4 CALIPSO 6 NCEP-NCAR 1 ISCCP-FD 4 SMD94 4

AERONET 9 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 1 ERA-40 2

MODIS 3 2 MOPITT 2 BOMEX 3 ERA-Interim 1 NCEP-NCAR 1 HOAPS 2

3 CARBOOCEAN 2 SHADOZ 2 ARM 3 AMMA 1 1 OAFLUX 2

CASTNET 2 2 Logan 2 2 ISCCP-D 1 BSRN 2

U of Miami 1 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 1 ERA-40 2 AIRS 1 ARM 1

SEAREX 1 1 UKMO analysis 2 TES 1

VGPM 1 NIWA 1 SCIAMACHY 1

EMDI 1 WOUDC 1

1 NOAA ESRL GMD 1

IGBP 1 EMEP 1

GEOLAND 1 CASTNET 1

1 IMPROVE 1

1 NDEP 1

1 EANET 1

AVHRR/NOAA 1 AIRS 1

GPCP 1

Fluxnet

SMD94 (da Silva)

Takahashi DB

Amsterdam Island & Cape Grim

NOAA Interpolated OLR

Zinke et al. CloudSat

Olson et al.

SeaWifs

ClimPP

Norby et al.

Sabine et al.,2004

Carr et al. 2006

Kettle et al. 1999

Veronika Eyring, ESA CCI project integration meeting, March 2011

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 , correlation for each variable

Quantitative Performance Metrics

Gleckler et al., JGR, 2008

Performance Metrics

Single Model Index

Weighting

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. GCOS, GSICS (Jan/Feb 2011)2. EUMETSAT CAF/CMSAF and SCOPE-CM3. NOAA-NASA initiatives (e.g. JPL CMIP5)4. WCRP Observation and Assimilation Panel (Apr 11)5. Reanalyses (ERACLIM, JRA-55, EURO4M) 6. 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 projectsAction: 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 PSDsAction: CCI

• Review terminology for error characteristics CMUG+CCI

• Slides from this meeting on CMUG web site Action: CMUG