CCAM simulations for CORDEX South Asia John Mc

CCAM simulations for CORDEX South Asia John Mc. Gregor, Vidya Veldore, Marcus Thatcher, Peter Hoffmann, Jack Katzfey and Kim Nguyen CSIRO Marine and Atmospheric Research Aspendale, Melbourne CORDEX Workshop Kathmandu 28 August 2013 CSIRO Marine and Atmospheric Research 1

Outline • • • Introduction to the downscaling approach GCM selection SST bias correction CCAM model features Behaviour of the simulations CSIRO Marine and Atmospheric Research

Downscaling with CCAM Bias correction CCAM (~50 km) GCM (~200 km) CCAM (~14 km) GCM SST/Sea-ice CSIRO Marine and Atmospheric Research

CCAM downscaling methodology • Coupled GCMs have coarse resolution, but also possess Sea Surface Temperature (SST) biases such as the equatorial “cold tongue” • We first run a quasi-uniform 50 km global CCAM run driven by the bias-corrected SSTs • • The 50 km run is then downscaled to 10 km by running CCAM with a stretched grid, but applying a digital filter every 6 h to preserve large-scale patterns of the 50 km run A separate 100 km global CCAM run is also used to drive Reg. CM 4. 2 at its boundaries for 20 km RCM runs Quasi-uniform C 192 CCAM grid with resolution about 50 km, showing every 4 th grid point Stretched C 96 grid with resolution about 14 km over Nepal, showing every 2 nd grid point CSIRO Marine and Atmospheric Research

Some previous CCAM downscaling projects Indonesia 14 km Pacific Islands 60 km and 8 km South Africa Australia Tasmania 20 km – 60 km 8 km – 14 km CSIRO Marine and Atmospheric Research

GCM Selection | Peter Hoffmann CSIRO Marine and Atmospheric Research

GCM Selection Requirements • Good performance in present climate • Simulation of rainfall, air temperature etc. • Reproduce observed trends • Good SSTs • ENSO pattern/frequency • SST distribution • Good spread of climate change signals GCM Selection | Pete Hoffmann CSIRO Marine and Atmospheric Research

GCM Selection Evaluation studies • 24 CMIP 5 models • > 20 evaluation studies • 6 publications with rankings + evaluation used within the Vietnam project • Peer-reviewed or submitted ACCESS 1. 0 ACCESS 1. 3 Can. ESM 2 CCSM 4 CNRM-CMS CSIRO-Mk 3 -6 -0 FGOALS-g 2 FGOALS-s 2 GFDL-CM 3 GFDL-ESM 2 M GISS-E 2 -H Had. CM 3 Had. GEM 2 -CC Had. GEM 2 -ES inmcm 4 IPSL-CM 5 A-LR IPSL-CM 5 A-MR MIROC 4 h MIROC 5 MIROC-ESM-CHEM MPI-ESM-LR MRI-CGCM 3 Nor. ESM 1 -M GCM Selection | Peter Hoffmann CSIRO Marine and Atmospheric Research

GCM Selection Example: performance in current climate over Indochina Evaluation region Results annual rainfall GCM Selection | Peter Hoffmann CSIRO Marine and Atmospheric Research

GCM Selection - Rankings GCMs Bhend (pers. Watterson communication) Suppiah (2012, HRD VN) et al. (Aust) et al. (Kont) Grose et al. (2012, submitted) Kim and Yu (2012, GRL) Z-score Temp RMSE Cor EP ENSO Cor CP ENSO trend Temp Prec PC Prec M-Score No. ENSO N 3. 4 Corr N 3. 4 Std N 3. 4 EOF 1 ACCESS 1. 0 4 8 19 20 3 2 7 1 2 7 ACCESS 1. 3 Can. ESM 2 CCSM 4 1 17 22 6 11 3 22 7 1 21 11 1 8 12 7 7 12 5 2 7 6 11 5 20 5 2 5 8 11 13 Kug et al. (2012, ERL) Cor N 3 N 4 12 3 2 5 1 18 2 CNRM-CMS 21 17 2 2 2 1 8 8 2 9 3 2 1 CSIRO-Mk 3 -6 -0 10 10 14 4 15 16 6 14 11 1 11 8 6 FGOALS-g 2 12 23 9 10 14 13 2 4 3 4 FGOALS-s 2 23 16 10 12 19 20 9 21 4 14 GFDL-CM 3 9 22 6 6 5 9 9 19 5 12 GFDL-ESM 2 M GISS-E 2 -H Had. CM 3 2 20 15 15 12 13 11 24 23 9 24 19 11 20 14 17 4 9 3 22 7 1 12 4 1 15 10 3 5 9 7 1 3 9 15 18 6 6 2 13 9 4 7 3 7 Had. GEM 2 -CC 13 4 Had. GEM 2 -ES Inmcm 4 14 8 4 24 18 13 16 17 4 13 4 15 6 4 10 16 6 8 2 11 6 10 7 4 15 5 IPSL-CM 5 A-LR 16 21 17 15 22 22 1 6 3 4 4 4 16 IPSL-CM 5 A-MR MIROC 4 h MIROC 5 7 18 5 5 2 7 16 8 3 14 13 7 21 21 4 5 5 2 5 15 3 9 10 9 3 23 2 16 5 2 8 6 5 10 MIROC-ESM 19 19 20 22 18 19 3 17 10 14 MIROC-ESM-CHEM 3 20 21 23 17 18 3 15 7 13 MPI-ESM-LR 11 1 5 5 1 3 7 18 7 6 1 4 17 MRI-CGCM 3 Nor. ESM 1 -M 13 6 14 18 12 4 3 8 10 9 11 8 9 5 12 2 3 4 11 6 6 8 6 1 11 8 14 CSIRO Marine and Atmospheric Research

GCM Selection Final ranking The rankings of the 6 individual studies are averaged to yield a final ranking of the models. Rank GCM Average Score 1 CNRM-CM 5 0. 31 2 CCSM 4 0. 34 3 ACCESS 1. 3 0. 35 4 Nor. ESM 1 -M 0. 35 5 ACCESS 1. 0 0. 39 6 MPI-ESM-LR 0. 41 7 GFDL-CM 3 0. 42 8 Had. GEM 2 -CC 0. 44 9 MIROC 4 h 0. 46 10 MIROC 5 0. 47 11 GFDL-ESM 2 M 0. 48 12 MRI-CGCM 3 0. 51 13 Had. CM 3 0. 53 14 IPSL-CM 5 A-MR 0. 53 15 Had. GEM 2 -ES 0. 54 16 FGOALS-g 2 0. 57 17 CSIRO-Mk 3. 6. 0 0. 57 18 inmcm 4 0. 61 19 Can. ESM 2 0. 61 20 MIROC-ESM-CHEM 0. 69 21 GISS-ES-H 0. 70 22 IPSL-CM 5 A-LR 0. 71 23 FGOALS-s 2 0. 80 24 MIROC-ESM 0. 84 GCM Selection | Peter Hoffmann CSIRO Marine and Atmospheric Research

GCM Selection Climate change signal JJA - good spread X X X CSIRO Marine and Atmospheric Research

SST correction CSIRO Marine and Atmospheric Research

• Observations • daily optimum interpolation SST & SIC (Reynolds et al. , 2007) • 1/4° resolution for 1982 -2011 • Method OBS GCM adjust mean frequency adjust variance SST CSIRO Marine and Atmospheric Research

SST bias correction Results: SST BIAS ACCESS 1. 0 JAN JUL original after correction (K) CSIRO Marine and Atmospheric Research

Results: SST variance ACCESS 1. 0 (January) ACCESS 1. 0 Observed Bias & Variance corrected Mean SSTs SST Stdev CSIRO Marine and Atmospheric Research

The conformal-cubic atmospheric model • CCAM is formulated on the conformal-cubic grid • Orthogonal • Isotropic Example of quasi-uniform C 48 grid with resolution about 200 km CSIRO Marine and Atmospheric Research

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 - it preserves the orthogonality and isotropy of the grid - same primitive equations, but with modified values of map factor C 48 grid (with resolution about 20 km over Vietnam CSIRO Marine and Atmospheric Research

CCAM dynamics • • • atmospheric GCM with variable resolution (using the Schmidt transformation) 2 -time level semi-Lagrangian, semi-implicit total-variation-diminishing vertical advection reversible staggering - produces good dispersion properties a posteriori conservation of mass and moisture CSIRO Marine and Atmospheric Research

CCAM physics • Cumulus convection: scheme for simulating rainfall processes • Detailed modelling of water vapour, liquid and ice to determine cloud patterns CSIRO Marine and Atmospheric Research

CCAM physics • Cumulus convection: scheme for simulating rainfall processes • Detailed modelling of water vapour, liquid and ice to determine cloud patterns • Parameterization of turbulent boundary layer (near Earth’s surface) CSIRO Marine and Atmospheric Research

CCAM physics • Cumulus convection: scheme for simulating rainfall processes • Detailed modelling of water vapour, liquid and ice to determine cloud patterns • Parameterization of turbulent boundary layer (near Earth’s surface) • Modelling of vegetation and using 6 layers for soil temperatures and moisture • CABLE canopy scheme CSIRO Marine and Atmospheric Research

CCAM physics • Cumulus convection: scheme for simulating rainfall processes • Detailed modelling of water vapour, liquid and ice to determine cloud patterns • Parameterization of turbulent boundary layer (near Earth’s surface) • Modelling of vegetation and using 6 layers for soil temperatures and moisture. 3 layers for snow • CABLE canopy scheme • GFDL parameterization of radiation (incoming from sun, outgoing from surface and the atmosphere) CSIRO Marine and Atmospheric Research

Cumulus parameterization • • • In each convecting grid square there is an upward mass flux within a saturated aggregated plume There is compensating subsidence of environmental air in each grid square As for Arakawa schemes, the formulation is in terms of the dry static energy sk = cp. Tk + gzk and the moist static energy hk = sk + Lqk CSIRO Marine and Atmospheric Research

Above cloud base subsidence plume detrainment downdraft CSIRO Marine and Atmospheric Research

Enhancements for Maritime Continent The Maritime Continent has many islands with land or sea breeze effects, and extra SST variability a) enhance sub-grid cloud-base moisture if diurnal increase of SSTs, or b) enhance sub-grid cloud-base moisture if upwards vertical motion Both (a) and (b) are beneficial over Indonesia, Australia, Vietnam, China – (b) slightly better (b) seems less suitable over India (a) still fine over India CSIRO Marine and Atmospheric Research

Cloud microphysics scheme (Rotstayn) CCAM carries and advects mixing ratios of water vapour (qg), cloud liquid water (ql) and cloud ice water (qi) CSIRO Marine and Atmospheric Research

Latest GFDL radiation scheme • Provides direct and diffuse components • Interactive cloud distributions are determined by the liquid- and icewater scheme of Rotstayn (1997). The simulations also include the scheme of Rotstayn and Lohmann (2002) for the direct and indirect effects of sulphate aerosol • Short wave (has H 2 O, CO 2, O 3, O 2, aerosols, clouds, fewer bands) • Long wave (H 2 O, CO 2, O 3, N 2 O, CH 4, halocarbons, aerosols, clouds) CSIRO Marine and Atmospheric Research

A recent AMIP run 1979 -1989 DJF JJA Obs CCAM 100 km Tuning/selecting physics options: • • In CCAM, usually done with 100 km or 200 km AMIP runs, especially paying attention to Australian monsoon, Asian monsoon, Amazon region No special tuning for stretched runs CSIRO Marine and Atmospheric Research 29

CORDEX runs using CCAM • We are performing global runs at 50 km, providing outputs for 4 CORDEX domains: Africa, Australia, SE Asia, S Asia. • RCP 4. 5 and 8. 5 emissions scenarios • So far have downscaled 6 of the CMIP 5 GCMs at 50 km/ L 27 resolution (as part of large Vietnam project). Output now available. • Doing more runs, and more at 100 km. • Performing the runs at CSIRO, CSIR_South_Africa, and Queensland_CCCE CSIRO Marine and Atmospheric Research

TRMM JJAS GPCP JJAS a 100 km a 14 km a 50 km ERA-I b 50 km – ACCESS Others quite similar CSIRO Marine and Atmospheric Research

Rainfall change by 2080 (mm/d) JJAS RCP 8. 5 CCAM_MPI CCAM_CNRM CCAM_GFDL CCAM_ACCESS CSIRO Marine and Atmospheric Research 32

% rainfall change by 2080 (mm/d) JJAS RCP 8. 5 CCAM_MPI CCAM_GFDL CCAM_CNRM CCAM_ACCESS CSIRO Marine and Atmospheric Research 33

TRMM-3 B 43 GPCP CCAM-100 km CCAM-14 km CCAM-Coupled CCAM-BVC_SST Over land sea TRMM 100 & 14 km coupled GPCP 50 km runs Convection in 50 km runs included vertical velocity enhancement (b) CSIRO Marine and Atmospheric Research

DJF JJA Obs CCAM 100 km CCAM 14 km over N India stretched 35 CSIRO Marine and Atmospheric Research

100 km AMIP runs vs CMAP CCAM DJF CCAM JJA MAM CMAP SON 1979 -1989 C 96 100 km AMIP run Generally good rainfall. Fresh 50 km CORDEX runs are underway. Research CSIRO Marine and Atmospheric

14 km runs vs Aphrodite DJF JJA CCAM Aphrodite MAM SON CSIRO Marine and Atmospheric Research

14 km runs vs IMD obs CSIRO Marine and Atmospheric Research

JJAS present-day rainfall over NEPAL DHM obs CCAM 14 km CSIRO Marine and Atmospheric Research

CCAM coupled model - 14 km over Asia Quite acceptable rainfall CSIRO Marine and Atmospheric Research

14 km coupled runs – 3 days MSLP, wind vectors, mixed layer depth > 50 m CSIRO Marine and Atmospheric Research 41

14 km coupled runs – 3 days SSTs CSIRO Marine and Atmospheric Research 42