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Improved hindcasts of Indian monsoon rainfall using a Tier 1.5 approach
Fred Kucharski, Annalisa Bracco1, Jürgen Kröger,Franco Molteni2, Jin Ho Yoo
Earth System Physics, the Abdus Salam International Centre for Theoretical Physics,
Trieste, Italy – [email protected]
1now at Georgia Tech, Atlanta, GA, USA2now at ECMWF, Reading, England
ENSO – Asian Summer Monsoon teleconnectionRegression of precipitation onto NINO3.4 (190-240E, 5S-5N) in JJAS
Kucharski et al. (2007)
IMR index
Lead-lag correlations between Indian rain and ENSO
NINO3 (150-90W, 5S-5N) and JJAS-IMR (70-95E, 10-30N) indices
Kucharski et al. (2007)
The ICTP coupled global climate model
Tier1.5: global atmosphere and local ocean
• ICTP atmospheric GCM “SPEEDY”• Spectral dynamical core (Held and Suarez 1994)• Resolution: T30L8 (~ 3.75 deg x 3.75 deg)• Simplified physical parameterizations (Molteni, 2003)
• MIAMI ocean GCM “MICOM” (v2.9; Bleck et al., 1992)• Indian Ocean configuration (30E - 135E, 30S – 30N)• 1 deg x 1 deg , 20 isopycnal layers• Sponge layer and initialization data from Levitus (1994)
• Prescribed SST outside ocean GCM domain!
The ICTP coupled global climate model
Experimental set-up: from Tier1 & Tier2 to Tier1.5
1Only the ECMWF, Meteofrance (METF), UK-Metoffice (UKMO) hindcasts (1959-1999) are considered
SST forcing Indian Ocean Ens. # Purpose
OBS-TIER1.5 HadISST coupled 10 Potential predictability
DEM-TIER1.5 DEMETER1 coupled 27 Actual predictability
OBS-TIER2 HadISST HadISST 25 Tier2 vs. Tier1.5
DEMETER seasonal hindcastspredicted (ECMWF) vs. observed SST
Indian summer monsoon rainfall (JJAS)IMR & NINO3.4 indices
La Nina (> 1 stdv)
El Nino (> 1 stdv)
Indian summer monsoon rainfallhindcasted IMR & NINO3.4 indices
La Nina (> 1 stdv)
El Nino (> 1 stdv)
IMR correlationsCorrelation skill (indiv. membrs.) and coefficient (CRU observ.)
Correlation skill Correlation coefficient
OBS-TIER1.5 0.68 0.62
DEMETER multi model 0.57 0.43
ECMWF only 0.54 0.24
METF only 0.46 0.39
UKMO only 0.71 0.39
DEM-TIER1.5 multi model 0.70 0.51
SSTs from ECMWF 0.66 0.43
SSTs from METF 0.66 0.44
SSTs from UKMO 0.78 0.49
DEMETER+DEM-TIER1.5 0.54
OBS-TIER2 0.68 0.31
ENSO – Asian Monsoon teleconnectionRegression of precipitation onto NINO3.4 in JJAS
DEMETER seasonal hindcastspredicted vs. observed SST
The Tier1.5 approach
considerably improves the DEMETER hindcasts
has great potential to aim as a tool for seasonal
predictions of IMR
confirms the importance of coupled air-sea feedbacks
in the Indian Ocean
JJAS mean SST bias in the DEMETER models
ICTP AGCM stand-alone model: GCM of intermediate complexity
Spectral dynamical core (Held and Suarez 1994)
Truncation currently at T30 (~3.75x3.75 degrees)
5, 7 or (recently) 8 vertical levels
Variables: Vor, Div, T, log(ps) and Q
Physical parameterizations of Convection (mass flux) Large-scale condensation (RH criterion) Clouds (diagnosed) Short-wave radiation (two spectral bands) Long-wave radiation (four spectral bands) Surface fluxes of momentum and energy (bulk formulas) Vertical diffusion Land-temperature calculated in simple model of 1-m soil layer
Mixed-layer option
Ingredients: SST from HadISST or DEMETER1 as “pacemaker”
Suite of experiments: OBS-TIER1.5: coupled GCM (Indic) + HadISST elsewhere
DEM-TIER1.5: coupled GCM (Indic) + DEMETER elsewhere
OBS-TIER2: atmospheric GCM + HadISST everywhere
The ICTP coupled global climate model
Experimental set-up: from Tier1 & Tier2 to Tier1.5
1Only the ECMWF, Meteofrance, UK-Metoffice Tier1 hindcasts are considered
