awi cmip peru_nomv
TRANSCRIPT
AWI Climate Model in CMIP6 simulations
Outline
• Motivation and background• FESOM/ECHAM6 (AWI-CM) description
and validation• CMIP6 and HighResMIP• FESOM setup for CMIP6• Conclusions and outlook
Motivation Models: describe climate state in space and time! Classical approach employs regular meshes:
cheapdynamics is poor
rich dynamicsexpensive
coarse fine
cheapboundary exchange
downscaling
Local refinement
MPIOM setups focused on different regions (Sein et al., 2015)
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
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
Influence of local refinement in the Arctic
9 km
25 km
kinetic energy temperature at 300m
90,000 surface nodesT63
ECHAM6 FESOM
1990 constant radiative conditions
Coupling with ECHAM6 (AWI CM)
Coupling with ECHAM6
Model validation: 2m Temperature
Model validation: Total precipitation
90,000 surface nodes 130,000 surface nodes
ocean resolution! WORKS !
ECHAM6–FESOM: role of resolution
1990 constant radiative conditionsbias in potential density at 1000m depth
! the deep bias is reduced !
before after
ECHAM6–FESOM: role of resolution
Summary 1
• Same biases as in CMIP5 models• What is the source of the bias?• Local refinement helps• Key regions to focus on?
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)
CMIP6
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)
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
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
CMIP6: ScenarioMIP• RCP‘s 2.6, 4.5, 6.0, and 8.5 • 2015 to 2100
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
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
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
• 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.
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
What are the ocean key regions?
• Oceanic fronts • Regions of eddies activity• Deep water production• Polar regions (sea ice)• Straits• ???
Fronts. Observed (AVISO) SSH
Eddies activity: SSH variance (AVISO)
FESOM mesh resolution
FESOM HR local examples (Europe)
FESOM HR local examples (GoM)
SSH variance. Agulhas system
North Atlantic Ocean deep bias
Temperature (K)
Outlook. Frontier meshRossby radius (Hallberg, 2013)
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.
Thank you!