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AWI Climate Model in CMIP6 simulations

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Page 1: Awi cmip peru_nomv

AWI Climate Model in CMIP6 simulations

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Outline

• Motivation and background• FESOM/ECHAM6 (AWI-CM) description

and validation• CMIP6 and HighResMIP• FESOM setup for CMIP6• Conclusions and outlook

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Motivation Models: describe climate state in space and time! Classical approach employs regular meshes:

cheapdynamics is poor

rich dynamicsexpensive

coarse fine

cheapboundary exchange

downscaling

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Local refinement

MPIOM setups focused on different regions (Sein et al., 2015)

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9 km resolution in the Arctic, 25 to 100 km elsewhere

Allows for multi-decadal global integrations with well-resolved Arctic

With the same number of nodes regular grids allow 60-70 km resolution

Advantageslocal refinement(s) in a global model realistic representation of small-scale features, e.g.

• narrow straits, polynias and overflows• topography

Unstructured mesh approach

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Finite Element Sea Ice Ocean Model (FESOM)

Solves:hydrostatic primitive equationssea ice equations

Uses Finite Element method: continuous linear basis functionstriangles in horizontaltetrahedra (or prisms) in vertical

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Influence of local refinement in the Arctic

9 km

25 km

kinetic energy temperature at 300m

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90,000 surface nodesT63

ECHAM6 FESOM

1990 constant radiative conditions

Coupling with ECHAM6 (AWI CM)

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Coupling with ECHAM6

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Model validation: 2m Temperature

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Model validation: Total precipitation

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90,000 surface nodes 130,000 surface nodes

ocean resolution! WORKS !

ECHAM6–FESOM: role of resolution

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1990 constant radiative conditionsbias in potential density at 1000m depth

! the deep bias is reduced !

before after

ECHAM6–FESOM: role of resolution

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Summary 1

• Same biases as in CMIP5 models• What is the source of the bias?• Local refinement helps• Key regions to focus on?

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CMIP6: Overarching questions

– How does the Earth system respond to forcing?– What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios?

Eyring et al., 2016 (GMD)

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CMIP6

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CMIP6: Organization

A handful of common experiments are the entry card to CMIP6:

DECK (Diagnostic, Evaluation and Characterization of Klima)CMIP historical simulations (1850 to 2014)

Common forcing and data standards, coordination, documentation, infrastructure

Eyring et al., 2016 (GMD)

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CMIP6: Organization• Ensemble of CMIP-Endorsed Model

Intercomparison Projects (MIPs)• Depending on scientific interest modelling groups may or

may not take part in some or all of them

• AWI:• ScenarioMIP• OMIP (Ocean)• PMIP (Paleo climate)• HighResMIP (High Resolution)• CORDEX (Coordinated Regional Climate Downscaling

Experiment) – only diagnostic• SIMIP (Sea Ice) – only diagnostic

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CMIP6: Entry card experiments• DECK

• AMIP: 1979-2014 with observed SST and SIC (Sea Ice Concentration) and observed forcings (anthropogenic including greenhouse gases and aerosols, volcanic, solar) MPI

• Control: 500 years 1850 forcing (after spin-up)• Abrupt 4*CO2 (150 years)• 1% CO2 increase / year (150 years)

• CMIP6 historical• Observed forcings 1850-2014

Entry card for CMIP6

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CMIP6: ScenarioMIP• RCP‘s 2.6, 4.5, 6.0, and 8.5 • 2015 to 2100

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CMIP6: HighResMIP• Short spin-up from EN4 climatology

(averaged over 1950 to 1954): ≈ 50 years with constant 1950 forcing

• 100 years with constant 1950 forcing as a reference

• 100 years with observed forcing up to 2014 and RCP8.5 forcing up to 2050

CMIP6 standard resolution and high resIn PRIMAVERA extra high res

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HighResMIP

• 17 international modelling groups• Atmospheric resolution: T127 (~100km), T255 (~50

km), T359(~35 km), T511(~25km), T799 (~16km)• Ocean resolution from 1º to 0.25º. Except for

FESOM• Two coupled simulations for 1950-2050 (control and

transient)

º

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CMIP6: HighResMIP• Short spin-up from EN4 climatology

(averaged over 1950 to 1954): ≈ 50 years with constant 1950 forcing

• 100 years with constant 1950 forcing as a reference

• 100 years with observed forcing up to 2014 and RCP8.5 forcing up to 2050

CMIP6 standard resolution and high resIn PRIMAVERA extra high res

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• The flexible layout of AWI-CM (Sidorenko et al. 2015, Rackow et al. 2016) allows to use eddy-resolving resolutions in key ocean areas. We exploit this capability in the North Atlantic (NA) in order to reduce long-standing biases, specifically the deep (~1000m) biases

Hierarchy of ocean model grids

reso

lutio

n

[km

]

REF87KCORE

AGUV

GLOB

top: Hierarchy of different ocean model grids. REF87K and CORE use ~1° resolution and moderate refinementto about 25km in the tropics and in the Arctic. AGUV and GLOB focus on the Agulhasand North Atlantic current region, with different weighting between those regions.

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Improvements in NA deep-ocean hydrography

REF87K

CORE

AGUV

GLOB

REF87K

CORE

AGUV

GLOB

right: Difference of potential temperature and salinity at 1000m to the WOA2005 climatologybelow: Global profiles of potential temperature and salinity, difference to the WOA2005 climatology

T127-GLOB

T127-AGUV

T127-CORE2

T63-REF87K

temperature

salinity

pot. temperature salinity

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What are the ocean key regions?

• Oceanic fronts • Regions of eddies activity• Deep water production• Polar regions (sea ice)• Straits• ???

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Fronts. Observed (AVISO) SSH

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Eddies activity: SSH variance (AVISO)

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FESOM mesh resolution

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FESOM HR local examples (Europe)

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FESOM HR local examples (GoM)

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SSH variance. Agulhas system

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North Atlantic Ocean deep bias

Temperature (K)

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Outlook. Frontier meshRossby radius (Hallberg, 2013)

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Conclusions• AWI-CM with T63 (~200km) atmospheric resolution

shows results similar to most of the CMIP5 climate models

• The model development for the CMIP6 simulations requires farther validation with T127 (~100km) and T255 (~50 km) atmosphere (ECHAM6)

• The ocean model resolution can play a crucial role in reduction of model biases

• The flexibility of FESOM (in the sense of horizontal resolution) could answer the question where and how to choose the ocean resolution in climate models.

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Thank you!