Multi-model operational seasonal forecasts for SADC
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Transcript of Multi-model operational seasonal forecasts for SADC
Multi-model operational Multi-model operational seasonal forecasts for seasonal forecasts for SADCSADC
Willem A. Willem A. LandmanLandmanAsmerom BerakiAsmerom BerakiCobus OlivierCobus OlivierFrancois Francois EngelbrechtEngelbrecht
Conformal-Cubic Conformal-Cubic Atmospheric Model Atmospheric Model (CCAM)(CCAM)
Runs performed on a computer cluster at the Runs performed on a computer cluster at the University of PretoriaUniversity of Pretoria
Climatological ensemble runs - 12hr LAF (5 Climatological ensemble runs - 12hr LAF (5 members)members)
Atmospheric initial conditions for climatological Atmospheric initial conditions for climatological runs obtained from NCEP reanalysis dataruns obtained from NCEP reanalysis data
Climatological simulations performed for the Climatological simulations performed for the period: 1979-2003. Lower boundary forcing from period: 1979-2003. Lower boundary forcing from AMIP SST and sea-iceAMIP SST and sea-ice
ECHAM4.5 at the SAWSECHAM4.5 at the SAWS
All runs performed on NEC SX-8All runs performed on NEC SX-8 Climatological (6 members) and operational ensemble Climatological (6 members) and operational ensemble
runs - 24hr LAFruns - 24hr LAF Atmospheric initial conditions from ECMWF (1979 to Atmospheric initial conditions from ECMWF (1979 to
1996) analysis1996) analysis Climatological dataset (1979-2003) constructed using Climatological dataset (1979-2003) constructed using
AMIP physics; model constrained by lower boundary AMIP physics; model constrained by lower boundary conditions generated from a high resolution AMIP2 conditions generated from a high resolution AMIP2 dataset for SST and sea-icedataset for SST and sea-ice
Operational set-up: persisted and forecast SSTs obtained Operational set-up: persisted and forecast SSTs obtained from a high resolution observed SST (optimum from a high resolution observed SST (optimum interpolation v-2) and IRI (mean) respectively (6 members interpolation v-2) and IRI (mean) respectively (6 members each)each)
12-member ensemble operational runs on 1812-member ensemble operational runs on 18 thth of each of each month for 6 consecutive months (i.e., 0-5 months lead-month for 6 consecutive months (i.e., 0-5 months lead-time)time)
First objective multi-model forecast
Old subjective consensus forecast
Combining algorithm:1. CPT downscaling2. Equal weights
Multi-model ensemble
Ensemble 1
(ECHAM4.5 at SAWS)
12 members
Ensemble 2
(CCAM at UP)
5 members
Ensemble 3
(CCM3.6 at IRI)
24 members
Ensemble 4
(CFS at CPC)
40 members
The current long-range forecast multi-model ensemble system of the South African Weather Service
New forecasting New forecasting systemsystem
UEA CRU data (0.5UEA CRU data (0.5° resolution)° resolution)– PrecipitationPrecipitation– Minimum temperaturesMinimum temperatures– Maximum temperatures Maximum temperatures
MOS using 850 hPa MOS using 850 hPa geopotential height fieldsgeopotential height fields– Domain: 10N-50S; 0-70EDomain: 10N-50S; 0-70E
Production date: from July 2008
DJF rainfall simulation DJF rainfall simulation skillskill
DJF 1999/2000 precip & DJF 1999/2000 precip & max temp PROBABILITY max temp PROBABILITY forecastsforecasts
Pre
cip M
ax T
A typical example of the format of the forecasts
Rainfall forecast issued in DecemberRainfall forecast issued in December
DMC and VACSDMC and VACS
DMCDMC– SAWS to compile draft document on SAWS to compile draft document on
modernizing the SARCOF processmodernizing the SARCOF process– DMC has been receiving MM forecasts DMC has been receiving MM forecasts
from SAWS since August 2008from SAWS since August 2008 MM work to be linked with VACSMM work to be linked with VACS
– Workshop in 2009 (will introduce Workshop in 2009 (will introduce product)product)
ENSO forecastENSO forecast
CCA (antecedent CCA (antecedent SST)SST)
ECHAM4.5-MOM3 ECHAM4.5-MOM3 (from Dave DeWitt)(from Dave DeWitt)
CFS (NCEP)CFS (NCEP)
Combining algorithm:1. CPT downscaling2. Equal weights
Multi-model ensemble(& verification statistics)
Ensemble 1
(ECHAM4.5 at SAWS)
12 members
Ensemble 2
(CCAM at UP)
5 members
Ensemble 3
(CCM3.6 at IRI)
24 members
Ensemble 4
(CFS at CPC)
40 members
The planned long-range forecast multi-model ensemble system of the South African Weather Service
Ensemble 5+6 (+7)
(GloSea4 at UKMO
and
CPTEC/COLA at INPE
(ECMWF?))