Observational needs for global carbon cycle modelling Chris Jones Met Office Hadley CentreESA CCI...

Observational needs for global carbon cycle modelling

Chris Jones

Met Office Hadley Centre ESA CCI CMUG Fourth Integration Meeting, Exeter, June 2014

© Crown copyright Met Office

• Importance of carbon cycle in climate models and projections

• Large Uncertainty

– Better evaluation needed

• Role of EO and ESA-CCI

• Requirements for CMIP6

Introduction


Motivation – why are carbon cycle projections important?• Carbon cycle key new element in CMIP5 modelling

• Makes projections more relevant and useful

• “TCRE” – critical new outcome of AR5• What emissions (reductions) required to achieve given pathway?

• But large uncertainty hinders usefulness

Warming link to cumulative emissionsAR5, WG1, SPM.10

compatible emissions pathways for the RCPs. Fig 6.25; Jones et al., 2013

But what are the key processes and uncertainties?• ANOVA decomposition of spread between models and scenarios

• Scenario differences dominate compatible fossil emissions

After mid-century emissions pathways separate almost completely by scenario

Hewitt et al., 2013 submitted

• ANOVA decomposition of spread between models and scenarios


• Similar for ocean uptake, but not for land

Land uncertainty

large in models

through 21st century


ocean spread largely due to

scenarios

“Low confidence on the magnitude of modelled future land carbon changes”

“very high confidence, ocean carbon uptake of anthropogenic CO2 emissions will continue”

But what are the key processes and uncertainties?

But what are the key processes and uncertainties?• ANOVA decomposition of spread between models and scenarios


• Similar for ocean uptake, but not for land

• Caveat – not true regionally for ocean…

Global ocean N. Atlantic

S. ocean


Missing processes in CMIP5 models?

●Permafrost carbon

●Permafrost thaw “virtually certain” [Ch. 12]

●“low confidence” on the magnitude of carbon losses

●N-cycle: “very likely, …, that nutrient shortage will limit ... future land carbon sinks”

●Wetlands: “ [CH4 emissions] likely to increase... low confidence in magnitude”

●Land-management●fire

Fig 6.36; O'Connor et al., 2013

Evaluation background• Model development has moved towards

greater complexity

• Carbon-cycle, chemistry, more interactive aerosols now common place in CMIP5-class models

• Evaluation not necessarily kept apace

Ocean Atmos

Ice Land

Ecosystems

Chemistry

Aerosol

AOIL well evaluated

ESMless well evaluated

Evaluation• Taken here in its widest sense

• Understanding the system and implementing improvements in the models

• Goes far beyond simple beauty context of comparing datasets side-by-side

• Top-down

• Need to look at whole-system outputs. “get the right answer…”

• Bottom-up

• Process understanding and evaluation. “…for the right reason”

• Emergent constraints

• A posterior constraint on outputs – determining which observations matter

CMIP5 Biogeochemistry Evaluation• Anav et al. (2013, J. Clim) began an

activity to systematically evaluate carbon cycle in CMIP5 models


Anav et al, 2013

Global soil and biomass carbon stores


N. Hemi model spread: factor 4 tropics model

spread: factor 2

Model spread in biomass540 ± 220 PgC


Anav et al, 2013



Anav et al, 2013

N. Hemi model spread: factor 10

tropics model spread: factor 5

Model spread in soil carbon1510 ± 790 PgC


EO requirements

• Long list– LAI/NDVI

• Phenology, seasonal cycle and trends– Land cover

• Especially for land-use/change– Biomass

• Evaluating/monitoring stock changes, land use emissions– Atmospheric Composition

• CO2, CH4– Soil moisture, fire

• Drivers of terrestrial carbon changes– Ocean colour

• Biological activity, location of nutrients

CCI example: Land-cover• ESA CCI land-cover project and new dataset coming out of this

• Being used to evaluate new PFTs map

• Example of working directly with EO community to influence format/quality of products

courtesy Anna Harper, Andy Hartley

Emergent Constraints

First coined in the context of climate projections by Allen & Ingram (2002) (?)

Emergent Constraint : a relationship between an Earth System sensitivity to anthropogenic forcing and an observable (or already observed) feature of the ES.

Emergent because it emerges from the ensemble of ESMs.

Constraint because it enables an observation to constrain the estimate of the ES sensitivity in the real world.

Fluctuation Dissipation Theorem – so we think we can trust links across timescales from variability to sensitivity...

Archetypal Example of an Emergent Constraint

Hall & Qu (2006)Slide courtesy Peter Cox

Relationship between CO2 Growth-rate and Tropical Temperature - Observations

Slide courtesy Peter Cox

Constrained distribution of tropical land carbon

Prior C4MIPPDF

After IAVConstraint

Slide courtesy Peter Cox


Emergent Constraints:caveats and potential

• Not a silver bullet

– Not intended to replace “traditional” evaluation

• But fine balance of carbon processes leads to high risk that model improvement won't narrow uncertainty...

– c.f. Cloud feedbacks and climate sensitivity

• EMCs provide a complimentary approach

– But Carbon IAV only uses 1 data point!

– Mauna Loa CO2 site

– Spatial information may allow regional constraints

– Also apply to CH4 IAV to assess future sensitivity


Future requirements of ESM Evaluation

• CMIP6

• Idea of satellite “MIP”s around a smaller core

• Each MIP to be responsible for own set of process experiments

• Must all have strong evaluation focus

courtesy Eyring & Stouffer


Requirements and priorities for CMIP6

• CMIP6 will devolve experiment design/evaluation activities back to component communities

• Crude history:– 2000-2009: “carbon cycle is important”– 2009-2014: “included in CMIP models. Large spread”– 2015-2020: “must improve”

• Not just make progress• But be able to demonstrate/quantify progress


C4MIPOCMIP LUMIP

GHGsOceancolour

Biomass

GHGs Landcover

MIP activities

CCI datasets

Future datasets


Conclusions

• Carbon cycle crucial in current / next-generation climate models

– But only if we can make demonstrable progress in evaluation and improvement

– Evaluation need to keep pace with added complexity

• Vision for CMIP6

• Leading role of MIPs in ensuring evaluation focus

• Multiple carbon-related MIP activities

• EO / CCI data will prove invaluable

Observational needs for global carbon cycle modelling Chris Jones Met Office Hadley CentreESA CCI...

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