CRESCENDO and CMIP6

- MERGE Involvement

Paul Miller

Dept. of Physical Geography and Ecosystem Science

Lund University, Sweden

• LPJ-GUESS in EC-Earth – status report

• CMIP6 - commitments and plans

• EC-Earth configurations for CMIP6

• CRESCENDO – motivation and project structure

• MERGE involvement in CRESCENDO

• Further CRESCENDO items of interest: ESMValTool, Emerging

Constraints

MERGE, CMIP6 & CRESCENDO

• LPJ-GUESS (EC-Earth branch) currently included (along with TM5, new

coupling interface etc.) in an ESM development branch:

(branches/development/2014/r1902-merge-new-components)

• MPI enabled – allows us to run LPJ-GUESS using more replicate patches

than EC-Earth v2.4 (currently 25)

• OASIS-MCT enabled – One (root) process communicates with IFS

• Ready for T159 (PMIP) and T255 (C4MIP, LUMIPstandard, 80km approx.)

resolution

• H-TESSEL LAI updated daily, but we now update high cover type and

high/low cover fractions in IFS code too

• Currently preparing1850 spin-up using same climate forcing as PISCES

• Ready for communication with TM5 (CO2, isoprene + 2 * monoterpene

soon)

• Qiang Li & Qiong Zhang (Stockholm Univ.) testing new albedo

parameterisation based on cover type, cover fraction and snow cover

Status report

LPJ-GUESS Coupling to EC-Earth v3.2

LPJ-GUESS

Version 4

(vegetation &

BGC)

HTESSEL

(land surface)

NEMO/PISCES

/LIM3

Version 3.6

OASIS-MCT LAI, high &

low vegetation

tile fraction

& types

3 Crops

temperature

radiation

Precipitation

Soil state

NEE/CO2

[CO2]

IFS

(atmosphere)

TM5

(chemistry,

transport)

Implemented

CMIP6

EC-Earth & CMIP6

CO2

External Forcing &

Boundary Conditions:

LULCC

CO2 emissions

N deposition

PMIP inputs

runoff

WCRP Grand Challenges

• Clouds, Circulation and Climate Sensitivity

• Changes in Cryosphere

• Climate Extremes

• Regional Climate Information

• Regional Sea-level Rise

• Water Availability

and

• Biogeochemical forcings and feedbacks

Experimental design will address:

1. How does the Earth System respond to forcing?

2. What are the origins and consequences of systematic model biases?

3. How can we assess future climate changes given climate variability,

predictability and uncertainties in scenarios?

CMIP6 – Scientific Context and Research Questions

CMIP6 DECK & MIPS

CMIP6 Historical Simulation will serve as a benchmark for CMIP6-endorsed MIPs

fro

m E

yri

ng

et

al.

2015

CMIP7, 8, 9, …

DECK experiments should not evolve

but provide continuity, and be

part of the model development cycle

1. Pre-industrial concentration-driven (1850 LU & N deposition)

2. Pre-industrial emission-driven (1850 LU & N deposition)

3. 1% CO2 increase C-driven run until 4*CO2 - 140 years (1850 LU & N

deposition)

4. “CMIP6 Historical”: Emission-driven, 1850-2014. Historical CO2

emissions, LU + N deposition

5. “esm1pcbgc”: 1% CO2 increase C-driven run until 4*CO2 - 140 years.

Radiation code “sees” 1850 CO2 value

6. “esmssp5-85”: Emission-driven, 2015-2100. RCP8.5 LU + N deposition

• Some overlap with LUMIP runs, so close cooperation with KIT essential

• Full ESM estimated to require approx. 4 times resources than a standard

(GCM) EC-Earth run.

• Approved: a dedicated MERGE CMIP6 resource to carry out these runs,

including documentation, output post-processing and upload to ESGF

Our Planned C4MIP Runs C

4M

IP

DE

CK

Much CMIP6 Forcing Still in Preparation

• CMIP6 will strengthen our outreach profile

• EC-Earth can be the tool that further unites our Research Themes

• EC-Earth/CMIP6 will help us to strengthen ties with other research

environments (e.g. LUCCI) and SFOs (e.g. Bert Bolin Centre)

• Participation also likely in PMIP, AerChemMIP

Nevertheless, much work remains with regard to improving the process

realism of ESMs, evaluating processes and feedbacks, and producing

reliable, policy-relevant climate projections.

MERGE Stage 2, EC-Earth and CMIP6

• Coordinated Research in Earth Systems and Climate: Experiments,

kNowledge, Dissemination and Outreach

• Horizon 2020 call: SC5-01-2014 “Advanced Earth-system models”

• Project PI: Colin Jones (Univ. Leeds, UK)

• A budget of 15m euro, approx.

• Started 1 Nov. 2015 and will run for 5 years

• Kick-off meeting (with PRIMAVERA) Nov 24-26 at Exeter University and

UK Met Office. Paul Miller to attend and report back to MERGE.

• With 36 PMs, Lund Univ. is the 19th largest partner of 24

• Interviews of 4 postdoc candidates will take place on 16 Nov.

Aim: “Improve the process realism and future climate projection reliability of

European ESMs, while evaluating and documenting the performance

quality of these models…”

CRESCENDO

CRESCENDO

CRESCENDO Structure

Concept and Approach: “CRESCENDO combines an ensemble of ESMs and IAMs

with advanced analysis methods to improve key ESM process-parameterizations

while also producing, understanding, constraining and quantifying an ensemble of

ESM projections. These activities necessarily occur in parallel, with new projections

using mature ESMs in the 1st half of the project (e.g. CMIP6-standard models) and

process improvements being developed and implemented into these ESMs

throughout the project, resulting in an improved set of European ESMs at the

conclusion of both CRESCENDO and CMIP6.”

RT1: Improving ESM processes

Leads: Pierre Friedlingstein & Parv Suntharalingam

WP1.1 Terrestrial biogeochemical processes (ULUND 15 PMs)

T1.1.1 Carbon and nitrogen dynamics in vegetation and soils

Improved representation of N limitation influence on climate-carbon cycle feedbacks, N

mineralisation & deposition, plant N uptake, N2O & NOx

T1.1.2 Wetlands and permafrost systems and methane emissions

Improved representation of permafrost, its climate-carbon cycle feedbacks,

CH4 and wetland ecosystems

T1.1.3 Land use and land cover in ESMs

Coordinate LU representation in ESMs (for LUMIP), and improve the representation of

forest structure (species, age, height)

WP1.2 Marine biogeochemical processes

T1.2.1 Improved ocean dynamics (resolution) and impact on marine biogeochemistry

T1.2.2 Improved representation of organic matter cycling

T1.2.3 External input of nutrient and emission of trace gases

WP1.3 Natural aerosols and trace gases (ULUND 8 PMs)

T1.3.1 Emissions of terrestrial aerosols and trace gases (wildfires, BVOCs, mineral dust)

Couple fire and BVOC emissions to ESM chemistry-aerosol modules

T1.3.2 Emissions of marine aerosols and trace gases

T1.3.3 Atmospheric processing and deposition of aerosols and trace gases

Time varying NOy & NHx deposition, BVOC emissions and SOA schemes

LPJ-GUESS

Version 4.1

(vegetation &

BGC)

HTESSEL

(land surface)

NEMO/PISCES

/LIM3

Version 3.6

OASIS-MCT LAI, high &

low vegetation

tile fraction

& types

3 Crops

Soil Carbon

temperature

radiation

Precipitation

Soil state

NEE/CO2, CH4, N2O,

Soot/wildfire, BVOC,

NOx

IFS

(atmosphere)

TM5

(chemistry,

transport)

Implemented

CMIP6

CRESCENDO

EC-Earth in CRESCENDO

CO2

VOCs,

DMS, sea salt

External Forcing &

Boundary Conditions:

LULCC

CO2 emissions

[CO2]

runoff

• LPJ-GUESS has been updated (Smith et al. 2014) to account for plant and soil N

dynamics.

• Model performance has been improved in many respects

C-N Interactions in LPJ-GUESS

Smith et al. 2014

Biogeosciences

WETCHIMP demonstrated the wide spread of annual CH4 fluxes (1993-2004) – offline runs with the best models

Melton et al. (2013)

Permafrost Carbon in ESMs

Incubation experiments help us to parameterise potential

cumulative C release

• Cumulative, % C release after samples have been held at 5 ⁰C for > 1 year

• Vertical distribution of C often not incorporated, or even known

• Few models take either dynamic vegetation or N availability in permafrost soils into account

• This information will be incorporated in CRESCENDO models

Schuur et al., 2015

Aerobic

Summary of Latest Modelling Experiments to Estimate

Cumulative C Release from Permafrost

• Cumulative C release in 8 models of varying complexity, all following RCP8.5 approx.

• Average C release of 92 PgC by 2100

Schuur et al., 2015

BVOC

Annual cycle

Annual cycle of GPP,

isoprene and

monoterpene emissions

from LPJ-GUESS,

averaged for 1981-2000

Daily values will be sent

to TM5 in Task 1.3.1

Slide: Guy Schurgers

RT2: Process-level evaluation of ESM improvements

Lead: Chris Jones

WP2.1 Evaluating terrestrial processes in ESMs (ULUND 8 PMs)

T2.1.1 Carbon and nitrogen dynamics in vegetation and soils

New metrics to constrain global carbon storage and turnover in ESMs, and their climate

sensitivity. Evaluation of C & N responses to FACE experimental treatments

T2.1.2 Wetlands and permafrost systems and methane emissions

Evaluation of permafrost physics (CALM, borehole T, sensitivity to snow cover); sitewise

CH4 evaluations and meta-analysis of environmental sensitivity; global wetland area and

CH4 emissions

T2.1.3 Land use and land cover in ESMs

ESA CCI land cover data, global LAI datasets, observed albedo and FLUXNET datasets

WP2.2 Evaluating marine processes in ESMs

WP2.3 Evaluating natural aerosol and trace gas processes (ULUND 4 PMs)

T2.3.1 Evaluation of new ESM coupled aerosol processes (wildfires, BVOCs, mineral dust)

BVOC emissions evaluated using AMS (Spracklen et al.). GFED3 to evaluate global

burned area and fire intensity. Fire emissions using plume products etc,

T2.3.2 Evaluation of aerosol under pre-industrial-like natural conditions

T2.3.3 Evaluation of trace gases

Surface BVOC flux measurements. Evaluation of tropospheric O3 and CH4 lifetime

Observed environmental sensitivity of daily CH4 fluxes in permafrost zones

Olefeldt et al. (2013)

RT3: Benchmarking full ESMs. Constraining ESM projections. Quantifying ES feedbacks

and forcing

Leads: Reto Knutti & Veronika Eyring

WP3.1 Towards routine benchmarking of ESMs

T3.1.1 Enhanced platform for routine evaluation and benchmarking of ESMs: ESMValTool

WP3.2 Understanding and constraining model projections: emergent constraints

T3.3.3 Emergent constraints on land carbon cycle feedbacks

Other tasks will extend and develop the emergent constraint theory and methodology to other

ESM components and processes

WP3.3 Quantification of forcing and feedbacks

Quantifying effective radiative forcing and feedbacks in runs with interactive aerosols, chemistry,

land use etc.

RT4: New scenarios and projections (Scenario MIP)

Leads: Detlef van Vuuren & Jason Lowe

WP4.1 Novel climate scenarios and future projections: The CMIP6 ScenarioMIP

Matrix of new radiative forcing targets and socioeconomic pathways consistent with these

WP4.2 Assessing the robustness of ESM performance and scenario response to model resolution

WP4.3 Organising ESM simulations for CMIP6 ScenarioMIP

• ESMValTool is “a community diagnostic and performance metrics

tool for routine evaluation of ESMs in CMIP”

• Open source, operates on NetCDF model output

• Community tool, with a subversion (svn) repository

• Continuously in development, and easy to add new datasets and metrics

for ESM evaluation

• Compare ESMs with observations, with other ESMs, with previous

versions of the same ESM etc.

• Will run on the ESGF for routine analysis of CMIP6 output

• Extensive documentation and Wiki

• Can even use reproduce figures in papers and reports (e.g. IPCC AR5)

• Current variables: Sea ice, temperature, water vapour, radiation, O3,

monsoons and modes of variability (e.g. ENSO), clouds, soil water,

terrestrial and marine biogeochemistry, southern ocean biases etc.

ESMValTool (see Eyring et al. (2015) GMDD, 8)

ESMValTool – Comparing CMIP5 models

Worse than median

Better than median

Eyring et al. 2015

GMDD, Vol 8

ESMValTool – Carbon Cycle Biases and Aerosol Optical Depth

Land C uptake

Eyring et al. 2015

GMDD, Vol 8

Ocean C release

PM Cox et al. Nature (2013) doi:10.1038/nature11882

Emergent constraint on the sensitivity of tropical land carbon to

climate change

CO2 only

Fully coupled

PM Cox et al. (2013) doi:10.1038/nature11882

Emergent constraint on the sensitivity of tropical land carbon to

climate change