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Regional climate modelling using CCAM: background to the

simulations

John McGregor

CSIRO Marine and Atmospheric ResearchAspendale, Melbourne

High-resolution Vietnam Climate Projections WorkshopMelbourne 13 December 2012

Need to downscale data • Coupled GCMs have a resolution of hundreds of kilometres• Details of orography, land use and coasts can greatly affect local

climate- these details cannot be resolved by GCMs

Dynamical downscaling

GCM (typically 200 km) 20 km CCAM

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Advantages of variable-resolution GCMsfor dynamical downscaling

CCAM: Conformal Cubic Atmospheric Model

• no problematic lateral boundaries

• avoid boundary reflections, which can produce spurious vertical velocities; expect better tropical behaviour

• smaller (or no) nesting data sets

• avoid difficulties should forcing model and driven model have different inherent cold or moist biases

• can enforce conservation in a proper manner

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Quasi-uniform C48 CCAM grid with resolution about 200 km

Stretched C48 grid with resolution about 20 km over Indochina

• We first run a quasi-uniform (e.g. 50 km), or modestly-stretched, CCAM run driven by the bias-corrected SSTs

• The 50 km run is then downscaled to 20 km or 10 km by running CCAM with a stretched grid, but applying a digital filter every 6 h to inherit the large-scale patterns of the 50 km run

Preferred CCAM downscaling methodology

• Coupled GCMs have coarse resolution, but also possess Sea Surface Temperature (SST) biases

• A common bias is the equatorial “cold tongue”• We mostly trust the changes from GCMs, rather than

their absolute values, especially SST changes July SST bias for Mk 3.6

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CCAM physics• cumulus convection:

- mass-flux scheme, including downdrafts, entrainment, detrainment

- up to 3 simultaneous plumes permitted

• includes advection of liquid and ice cloud-water

• - used to derive the interactive cloud distributions (Rotstayn 1997)

• Smagorinsky style horizontal diffusion based on deformation

• stability-dependent boundary layer with non-local vertical mixing

• vegetation/canopy scheme (Kowalczyk et al. TR32 1994)

- 6 layers for soil temperatures

- 6 layers for soil moisture (Richard's equation)

• enhanced vertical mixing of cloudy air

• GFDL parameterization for long and short wave radiation

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Some quasi-uniform grids

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Gnomonic-cubic grid Sadourny (MWR, 1972)

Fibonacci grid(Swinbank and Purser, 1999)

Icosahedral grid

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4 variable-resolution global modelsCCAM - Australia

GEOS - USAARPEGE - France

GEM - Canada

Conformal-cubic

Spectral

Latitude-longitude

38400 points71868 points

64800 points

37518 pointsLatitude-longitude

modest stretchingtime-slice

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OriginalSadourny (1972) C20 grid

Equi-angular C20 grid

Alternative cubic grids

Conformal-cubicC20 grid

A little history

• Cube grid proposed by Sadourny (1972)• Rediscovered in early 90’s by several people (Ronchi,

McGregor, Rancic)• Semi-Lagrangian advection experiments (McGregor,

1997) on gnomonic cube grid• Conformal-cubic grid invented by Rancic et al. (1996) • CCAM was the first atmospheric GCM on cube grid

(1998) - adopted physics and code framework of DARLAM- N.B. an existing suitable code framework makes task far quicker- reversible staggering version was produced a few years later

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The conformal-cubic atmospheric model

• CCAM is formulated on the conformal-cubic grid

• Orthogonal• Isotropic

Example of quasi-uniform C48 grid with resolution about 200 km

CCAM dynamics

• atmospheric GCM with variable resolution (using the Schmidt transformation)

• 2-time level semi-Lagrangian (bi-cubic), semi-implicit

- incorporating total-variation-diminishing (TVD) vertical advection

• reversible staggering• - produces good dispersion

properties• a posteriori conservation of mass and

moisture

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Location of variables in grid cells

All variables are located atthe centres of quadrilateralgrid cells.

However, during semi-implicit/gravity-wave calculations, u and v are transformed reversibly to the indicated C-grid locations.

Produces same excellent dispersion properties asspectral method (see McGregor, MWR, 2006), but avoids any problems of Gibbs’ phenomena.

2-grid waves preserved. Gives relatively lively winds, and good wind spectra.

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Reversible staggering

Where U is the unstaggered velocity component and u is the staggered value, define (Vandermonde formula)

• accurate at the pivot points for up to 4th order polynomials• solved iteratively, or by cyclic tridiagonal solver• excellent dispersion properties for gravity waves, as shown for the

linearized shallow-water equations (following Randall)

| X | X | X |m-1 m-1/2 m m+1/2 m+1 m+3/2 m+2 m+3/4

*

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Dispersion behaviour for linearized shallow-water equations

Typical atmosphere case Typical ocean caseN.B. the asymmetry of the R grid response disappears by alternating the reversing direction each time step,giving same response as Z (vorticity/divergence) grid

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MPI implementation

Remapping of off-processor neighbour indices to buffer region

Indirect addressing is used extensively in CCAM - simplifies coding

Original

Remapped region 0

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Typical MPI performance

Showing both Face-Centred and Uniform decomposition for global C192 50 km runs, for 1, 6, 12, 24, 48, 72, 96, 144, 192, 288 CPUs (strong scaling example)

VCAM (shown for 6 cores) is slightly slower, but is still to be fully optimised

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An AMIP run 1979-1995

CCAM

Obs

Tuning/selecting physics options:• In CCAM, regularly checked with 200 km AMIP runs, especially paying

attention to Australian monsoon, Asian monsoon, Amazon region• No special tuning for stretched runs

DJF JJA

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Variable-resolution conformal-cubic grid The C-C grid is moved to locate panel 1 over the region of interestThe Schmidt (1975) transformation is applied• this is a pole-symmetric dilatation, calculated using spherical polar

coordinates centred on panel 1• it preserves the orthogonality and isotropy of the grid• same primitive equations, but with modified values of map factorPlot shows a C48 grid (Schmidt factor = 0.3) with resolution about 60 km over Australia

C48 grid having 20 km resolution over Vietnam: long= 108, lat=15.5, Schmidt = 0.09

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C48 8 km grid over New Zealand

C48 1 km grid over New Zealand

Grid configurations used to support Alinghi in America’s Cup Also Olympic sailing for Beijing and Weymouth (200 m)

Schmidt transformation can be used to obtain very fine resolution

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Downscaled forecasts60 km

8 km

1 km

When running the 8 km simulation, a digital filter is used to diagnose large-scale and fine-scale fields. The large-scale fields are then inherited every 3 hours from the 60 km run.

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• Uses a sequence of 1D passes over all panels to efficiently evaluate broad-scale digitally-filtered host-model fields (Thatcher and McGregor, MWR, 2009). Very similar results to 2D collocation method.

• These periodically (e.g. 6-hourly or 12-hourly) replace the corresponding broad-scale CCAM fields

• Gaussian filter typically uses a length-scale approximately the width of finest panel

• Suitable for both NWP and regional climate• We have no plans for adaptive grids, but instead will continue to use

progressive downscaling via digital filter method

Digital-filter downscaling method

Comments on CCAM and downscaling• In early CCAM runs, we used far-field forcing from the host GCM

• - did not compensate for GCM biases• - can lead to some inconsistencies if also apply SST bias correction

• Subsequently we used nudging from upper-level GCM winds• We prefer our current approach, using sea-ice and bias-corrected

SSTs• We can now also correct the variances of SSTs

Uncorrected July Corrected July

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CCAM Downscaling for Viet Nam | Peter Hoffmann24 |24

Present-day rainfall from 20 km simulation downscaling 1961-2000

Obs

20 km

Produces good present-day rainfall with generally small biases

Also good max/min temperatures

(Downscaling from CSIRO Mk3.5)

20 kmbiases

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Mk 3.5

200 kmCCAM

20 kmCCAM

Produces similar broad-scale patterns of changes between 200 km and 20 km runs

Gives broadly similar rainfall changes to Mk 3.5, but less so in tropics in DJF

SEACI example of rainfall trends (mm/day) 1961-2100

DJF MAM JJA SON ANN

• Ensemble of 60 km C64 runs over Australia for Climate Futures Tasmania project, (1961-2100) – 140 years

- from 6 GCMs: Mk3.5, GFDL 2.1, GFDL 2.0, ECHAM5, HADCM3, MIROC-Med

- for A2, B1• Ensemble of 14 km C48 runs over Tasmania (1961-2100) – 140 years

downscaled from above 60 km CCAM runs• Ensemble of simulations over Indonesia (60 km) and NTB (14 km)• Ensemble of 20 km simulations over SE Queensland• PCCSP – ensemble of global 60 km runs from 1971-2100 (from 6

GCMs), then downscaled to around 8 km for 7 individual countries• Vietnam project: ensemble of 10 km runs driven by 50 km CCAM runs

for CORDEX

Recent CCAM ensemble climate simulations

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Nusa Tenggara Region 112oE-123oE, 12oS - 4oS

14 km grid

Makassar (south Sulawesi region)

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Obs CCAMBandung

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OBS CCAMDenpasar

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OBS CCAMAmpenan

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Obs CCAMJakarta

14 km simulations downscaled from NCEP reanalysis SSTs

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CORDEX runs using CCAM• Co-Ordinated Regional Dynamical

Experiment carried out by many groups over 7 different domains

• We are performing global runs at 50 km, providing outputs for 4 CORDEX domains: Africa, Australasia, SE Asia, S Asia

• RCP 4.5 and 8.5 emissions scenarios• Will downscale at least 6 of the CMIP5

GCMs at 50 km resolution; others at 100 km or 200 km

• Performing the runs at CSIRO, CSIR (South Africa), and QCCCE

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Many available model outputs

• 6-hourly data• Winds• Temperatures (incl. daily max/min)• Relative humidity• Cloud fractions (low, middle, high)• Soil moisture and temperature• Pressure patterns• Many more

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• CABLE: new land-use/canopy/carbon scheme included• aerosol scheme added• urban scheme added• TKE boundary scheme available• new GFDL radiation scheme available• improvemed convection scheme• new dynamics for VCAM• coupling to PCOM (parallel cubic ocean model) of Motohiko

Tsugawa from JAMSTEC - underway (3:way: CSIRO + JAMSTEC + CSIR_SouthAfrica)

CCAM developments

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Description of the cumulus parameterization• Arakawa-style mass-flux scheme.• In each convecting grid square there is an upward mass flux

within a saturated aggregated plume.• There is compensating subsidence of environmental air.• The scheme is formulated in terms of the dry static energy,

sk = cpTk + gzk

and the moist static energyhk = sk + Lqk

• Closure is that convection is allowed to continue until the modified environment no longer supports a cumulus plume having the current cloud-base and cloud-top levels. The closure is simply that the mass flux be the minimum flux for which this occurs.

• A convective time scale is imposed (20 - 60 mins) affecting runs with small time steps

Above cloud base

Below cloud baseUpdraft Subsidence Downdraft

M DM-D

M2.5

M1.5

D2.5

D1.5

M2.5-D2.5

kb

1

M1.5-D1.5

I2

Ikb

I1

Xkb

X2

X1

[sb,qb ] [sD,qD ]

Note that flux M=M2.5+Ikb and flux D=D2.5+Xkb etc

Recent improvements to convection scheme

• Now handles shallow convection by specifying increased detrainment for shallow clouds• - detrained liquid water is handled by the microphysics

scheme

• To better handle sub-grid variability, available cloud base moisture is enhanced under certain conditions for coarse resolution • - enhancement factor smoothly reduces to 1 as dx -> 0• - addresses “grey zone” issues

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• Nbase -12 defines cloud base as being at top of PBL• Mbase -19 for large vertical velocity takes moisture from lowest level, with

surface wetness factor included.• Methprec (controls detrainment profile)

-2 generalized triangular (older simpler triangular was 8)• Methdetr (control detrainment for shallow vs deep)• Detrain value for deep clouds – typically 0.25• Entrain (controls fraction mass entrained from environment)

0.15 (could alter between 0.05 and 0.4, say)• Nevapcc (option to controls auto entrain fraction depending on cloud depth

0 (but could use -6 through to 60)

Brief description of convection switches

• Convtime (convective time scale)0.33 (hours) or -1, -2 (longer for shallow tending to 0.33 for deep)

• Convfact (multiplies calc. mass flux to boost convergence )1.1 (but 1. or 1.05 very similar results)

• Fldown (downdraft mass flux factor)0.3 (but could use 0.2 to 0.6)

• Nuvconv controls convective mixing of momentum-3 (30% of possible full value); -2 also OK

• Alfsea, alfland (basic enhancement of moisture at cloud base)currently (1.1, 1.4) for 200 km, reducing to 1.0 as ds tends to 0

• Tied_con (trigger using upward vertical vels to enhance available PBL moisture) 10 for 200 km, increasing for smaller ds

Brief description of convection switches cont.

Thank you!