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Regional climate modelling activities at CSIRO
Second AIACC Asia and the Pacific Regional Workshop
2-5 November, Manila
John McGregor and Kim Nguyen
CSIRO Atmospheric Research
AcknowledgementsMartin Dix, Jack Katzfey and Eva Kowalczyk
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Outline
DARLAM limited-area model features of C-CAM simulations of present-day Australian climate simulations of Australian climate change an artificially-flooded inland lake simulations over Asia diurnal rainfall behaviour new activities
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DARLAM simulations of tropical cyclones
Observed tropical cyclone formation, Jan-March, 1967-1996
a b
30-year simulated TC formation, Jan-March
DARLAM domains: inner 30-km resolution; outer, 125-km resolution; nested in CSIRO Mark2 CGCM
Occurrence of TCs, in cyclone-daysWalsh, Nguyen and McGregor
(2004), Clim. Dyn.
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January 1982 rainfall from DARLAM 44 km resolution simulation over SARCS region
• performed in 1999, downscaled from NCEP (and Mk 3)• fairly good climatology, but see some spurious lateral boundary effects, due to one-way nesting
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Conformal-cubic grid Devised by Rancic et al., QJRMS 1996
Grid shows location of mass variables in CSIRO C-CAM model
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Conformal-cubic C48 grid used for AMIP simulations
Resolution is about 220 km
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· 2-time-level semi-implicit hydrostatic (recently, has non-hydrostatic option)
· semi-Lagrangian horizontal advection with bi-cubic spatial interpolation
· total variation diminishing (TVD) or semi-Lagrangian vertical advection
· unstaggered grid, with winds transformed to/from ·C-staggered positions before/after gravity wave calculations using reversible interpolation
· minimal horizontal diffusion needed:·Smagorinsky style; zero is fine
· weak off-centering (in time) used to avoid semi-Lagrangian "mountain resonances"
· careful treatment of surface pressure and pressure-gradient terms near terrain
· a posteriori conservation of mass and moisture
· grid is isotropic
Conformal-cubic model features
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· cumulus convection: -new CSIRO mass-flux scheme, including downdrafts
· includes advection of liquid and ice cloud-water
· interactive cloud distributions · derived prognostically from liquid water
· GFDL parameterization for long and short wave radiation
· gravity-wave drag scheme
· stability-dependent boundary layer and vertical mixing with non-local option
· vegetation/canopy scheme
· 6 layers for soil temperatures
· 6 layers for soil moisture (Richard's equation)
· option for cumulus mixing of trace gases
· diurnally varying skin temperatures for SSTs
Physical Parameterizations
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Observed 1979-95 DJF rainfall Observed 1979-95 JJA rainfall
CCAM 1979-95 DJF rainfall CCAM 1979-95 JJA rainfall
AMIP simulation with quasi-uniform 220 km grid
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Conformal-cubic C48 grid used for Australian simulations, Schmidt = 0.3
Resolution over Australia is about 60 km
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Full nudging of far-field winds in the free atmosphere, with e-folding time ~24 h
Partial nudging
No nudging
(only SSTs)
Far-field nudging
Model uses NCEP/GCM winds only outside the inner red boundary
Model uses NCEP/GCM winds (or other fields) at all points.
Global nudging
Full nudging of fields in the free atmosphere , with e-folding time ~48 h
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C-CAM/NCEP 1961-1990 IPCC
C-CAM/Mk3 “1975-2005”
30-year average annual rainfall total (mm/day)
GCM Mk3 “1975-2005”
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C-CAM/Mk3 “1975-2005”
IPCC
GCM Mk3 “1975-2005”
Annual average maximum daily screen temperature C-CAM/NCEP 1961-1990
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C-CAM/Mk3 “1975-2005”
IPCC C-CAM/NCEP 1961-1990
GCM Mk3 “1975-2005”
Annual average minimum daily screen temperature
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The monthly SST biases are corrected for the latest downscaled C-CAM simulations (using 12 monthly data sets).
Mk 3 GCM annual average SST error (degrees C)
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Mk3AOGCM
C-CAMXie-Arkin observed
DJF rainfall from 30-yCCAM (latest run) driven by Mk3
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Mk3AOGCM
C-CAMXie-Arkin observed
MAM rainfall from 30-yCCAM (latest run) driven by Mk3
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Change in annual precipitation (mm/day) for 2xCO2-1xCO2 from the Mk3 OAGCM simulation.
Change in annual precipitation (mm/day) for 2xCO2-1xCO2 from the C-CAM simulation, with forcing from the Mk3 OAGCM.
For present-day SST distributions, C-CAM produces more accurate simulations of the rainfall patterns. Reasonable to expect that this also applies for the climate-change SST distributions.
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Regional Model Intercomparison Project
RMIP_1: March 1997 - August 1998
RMIP_2: July 1988 - December 1998 on a large Asian domain including India, Indochina, China,
Japan, Siberia 60 km resolution ~10 limited-area models, 1 stretched global model lateral boundary conditions provided by 6-hourly NCEP
reanalyses organised by Congbin Fu (IAP) with sponsorship from APN
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Conformal-cubic C63 grid used for RMIP simulations, Schmidt = 0.37
Approx. 60 km resolution
Weights used for nudging with far-field winds
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Xie-Arkin Precip for JJA Xie-Arkin Precip for SON
10-y C-CAM/RMIP2 Precip for JJA 10-y C-CAM/RMIP2 Precip for SON
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Xie-Arkin Precip for DJF Xie-Arkin Precip for MAM
10-y C-CAM/RMIP2 Precip for DJF 10-y C-CAM/RMIP2 Precip for MAM
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Xie-Arkin Precip for JJA
10-y C-CAM/RMIP2 Precip for JJA
10-y C-CAM/Mekong Precip for JJAwith forcing from Mk3 GCM(instead of NCEP reanalysis)
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Malaysia Calcutta
Obs
C-CAM
Diurnal rainfall behaviour from 10-y RMIP run
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Andaman Sea Bay of Bengal
Obs
C-CAM
Diurnal rainfall behaviour from 10-y RMIP run
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8 km trial simulation over Fiji
C48 grid Model orography
For these fine-resolution simulations, “global nudging” from the broad-scale fields is the preferred strategy.
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In Fiji, Nadi (western division) has a marked seasonality in rainfall as compared to Suva which has year round rainfall under the influence of trade winds (resulting in more number of wet days). The marked differences in rainfall seasonality at these two locations in Fiji has been reproduced in the model.
Observed 1975 rainfallSuva May-October ~10 mm/dayNovember-April ~ 12 mm/day
Nadi May-October ~3 mm/dayNovember-April ~ 8 mm/day
Modelled amounts (next 2 slides) appear similar, but detailed comparison still to be carried out.
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Fiji rainfall – first 6 monthsJanuary
February
April
May
March June
IPCC climatology vs 1975 C-CAM
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Fiji rainfall – next 6 monthsJuly
August
October
November
September December
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Concluding comments Variable-resolution global models are well-suited
to perform the simulations “traditionally” performed by limited-area RCMs, whilst avoiding the usual lateral boundary problems.
The variable-resolution global model C-CAM reproduces well many features of the Australian and East Asian climates
Modelling advances and greater computing power are allowing regional climate simulations down to around 8 km resolution.