1. 1 Regional climate modelling using CCAM: background to the simulations John McGregor CSIRO Marine and Atmospheric Research Aspendale, Melbourne High-resolution Vietnam Climate Projections Workshop Melbourne 13 December 2012

2. 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 2 |

3. Advantages of variable-resolution GCMs for 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 3 |

4. 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 4 |

5. 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 5 |

6. Some quasi-uniform grids 6 Gnomonic-cubic grid Sadourny (MWR, 1972) Fibonacci grid (Swinbank and Purser, 1999) Icosahedral grid

7. 7 4 variable-resolution global models CCAM - Australia GEOS - USA ARPEGE - France GEM - Canada Conformal- cubic Spectral Latitude- longitude 38400 points 71868 points 64800 points 37518 points Latitude- longitude modest stretching time-slice

8. 8 Original Sadourny (1972) C20 grid Equi-angular C20 grid Alternative cubic grids Conformal-cubic C20 grid

9. 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 9

10. 10 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

11. 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 11 |

12. 12 Location of variables in grid cells All variables are located at the centres of quadrilateral grid 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 as spectral method (see McGregor, MWR, 2006), but avoids any problems of Gibbs’ phenomena. 2-grid waves preserved. Gives relatively lively winds, and good wind spectra.

13. 13 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 4 th 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 *

14. 14 Dispersion behaviour for linearized shallow-water equations Typical atmosphere case Typical ocean case N.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

15. 15 MPI implementation Remapping of off-processor neighbour indices to buffer region Indirect addressing is used extensively in CCAM - simplifies coding Original Remapped region 0

16. 16 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

17. 17 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 DJFJJA

18. 18 Variable-resolution conformal-cubic grid The C-C grid is moved to locate panel 1 over the region of interest The 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 factor Plot shows a C48 grid (Schmidt factor = 0.3) with resolution about 60 km over Australia

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

20. 20 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

21. 21 Downscaled forecasts 60 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.

22. 22 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

23. 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 JulyCorrected July 23 |

24. CCAM Downscaling for Viet Nam | Peter Hoffmann 24 | 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 km biases

25. 25 Mk 3.5 200 km CCAM 20 km CCAM 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

26. 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 26 |

27. Nusa Tenggara Region 112 o E-123 o E, 12 o S - 4 o S 14 km grid Makassar (south Sulawesi region) 27 |

28. 28 Bandung Denpasar Ampenan Jakarta 14 km simulations downscaled from NCEP reanalysis SSTs 28 |

29. 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 29 |

30. 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 30 |

31. 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 31 |

32. 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, s k = c p T k + gz k and the moist static energy h k = s k + Lq k 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

33. Above cloud base

34. Below cloud base Updraft Subsidence Downdraft MD M-D M 2.5 M 1.5 D 2.5 D 1.5 M 2.5 -D 2.5 kbkb 1 M 1.5 -D 1.5 I2I2 I kb I1I1 X kb X2X2 X1X1 [s b,q b ] [s D,q D ] Note that flux M=M 2.5 +I kb and flux D=D 2.5 +X kb etc

35. 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 35

36. 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

37. 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.

38. Thank you!