Transcript Impact of AMDAR/RS Modelling at the SAWS Warren Tennant Weather Forecast Modelling at the SAWS • UK Met Office Unified Modelling system running operationally at.

Impact of AMDAR/RS
Modelling at the SAWS
Warren Tennant
Weather Forecast Modelling at
the SAWS
• UK Met Office Unified Modelling system running
operationally at the SAWS since September 2006
• Installed under an operational licence with Met
Office that includes:
– using the model for operational forecasting
responsibilities
– Includes limited commercial use of model output
– Real-time feed of model input data (initial conditions
and observations) from Met Office
– Software support and upgrades
– Scientist exchange and visits
SAWS National Responsibility
SAWS is responsible to the public of South
Africa to provide:
national forecasts of basic weather conditions up to
three days ahead
advisories of high-impact weather conditions up to
48-hours ahead and longer where possible, and
warnings of imminent severe weather, to
 safeguard lives and property and mitigate the
impact of weather on South Africans
SAWS SADC Responsibility
SAWS serves as a WMO Regional Specialised
Meteorological Centre (RSMC) for the
Southern Africa Development Community
(SADC)
Plays a backup role in the event of national
disasters, e.g. Tropical Cyclone in Mozambique
Provides NWP guidance products to SADC as part
of the WMO/CBS Severe Weather Forecasting
Demonstration Project (SWFDP)
Process to role-out UM SA12 forecasts (images and
data) to SADC countries has been started
SA12 Regional Model
(based on Met Office NAE model)
1.
2.
3.
Reconfigure
global input for
48hr fcst at 00Z
3DVAR at 06
& 12Z from
above => 48hr
fcst at 12Z
Continuous
3DVAR 6hourly cycle =>
48hr fcst at 00Z
Observations in southern Africa
• SAWS has a
moderate upperair network
– 8 GPS stations
– 2 Island stations
• QC and
availability good
• Rest of southern
Africa is a
rawindsonde void
Global AMDAR Availability 00Z
Global AMDAR Availability 06Z
Global AMDAR Availability 12Z
Global AMDAR Availability 18Z
SAA-AMDAR Coverage
OSE Experiment Design
Continuous 3dVAR 6-hourly cycle
Control: All observations
Experiment: No AMDAR or Rawindsondes
Independent: Interpolated global model 4dVAR
initial conditions (no LAM DA)
Winter case: 1 May to 8 Jul 2007
Summer case: 24 Oct 2006 to 18 Jan 2007
Verification:~2000 rainfall stations and ~10
rawindsonde stations in South Africa
Wind-speed verified against
Rawindsondes
Wind Speed T-Corr vs RadioSondes (May-Jun-Jul)
1
0.95
0.9
Correlation Coefficient
• Obvious impact on
analyses
• Significant impact
at 24 hours
• Little impact at 48
hours (slight
degradation at
250hPa)
• Forecast without
DA better scores!
0.85
0.8
Control
0.75
Exp
Global Interp
0.7
0.65
0.6
0.55
0.5
850
Anal
500
250
850
24hr
500
250
850
48hr
500
250
Spatial ACC of wind-speed :: MJJ
• Impact of AMDAR/RS
on wind speed is
positive throughout
• True even if using
global 4dVAR analysis
as verification standard
• Run with no-DA
sometimes better than
DA run – especially
after 48 hours
Spatial ACC :: Wind Speed (May-Jun-Jul 2007)
1
0.95
0.9
Control
0.85
Exp
Global Interp
0.8
0.75
0.7
850
Anal
500
250
850
24hr
500
250
850
48hr
500
250
Spatial ACC :: Wind Speed (May-Jun-Jul 2007)
(Using Global 4dvar Analysis)
1
0.95
0.9
Control
0.85
Exp
0.8
Global Interp
0.75
0.7
850
Anal
500
250
850
24hr
500
250
850
48hr
500
250
Temperature temporal correlation to
Radiosondes
• Mostly positive impact
• Some cases where noDA works better
1
Correlation Coefficient
– possibly because
4dVAR initial
conditions from global
model better
– Inconsistency at LBCs
from LAM DA initial
conditions
Tem perature T-Corr vs RadioSondes :: NDJ
0.95
0.9
Control
0.85
Exp
Global Interp
0.8
0.75
0.7
850 500
Anal
250
850
24hr
500
250
Forecast Hour
850
48hr
500
250
Spatial ACC of temperature
forecasts
• Similar to wind
speed results
• Positive impact
throughout
• Less dependency of
impact on forecast
lead-time
Spatial ACC NDJ :: Tem perature (Control Analysis)
1
0.99
0.98
0.97
0.96
0.95
0.94
0.93
0.92
0.91
0.9
Control
Exp
Global Interp
850
Anal
500
250
850
24hr
500
250
850
48hr
500
250
Spatial ACC NDJ :: Tem perature (Global 4dvar Analysis)
1
0.99
0.98
0.97
0.96
0.95
0.94
0.93
0.92
0.91
0.9
Control
Exp
Global Interp
850
Anal
500
250
850
24hr
500
250
850
48hr
500
250
Rainfall forecast verification :: BIAS
Area Average Rainfall Bias (% of Observed)
:: Day 1 NDJ ::
250
• Bias expressed as a
percentage of the
observed rainfall
• Summer Case:
– No strong impact on
forecast day 1
– On day 2 more positive
impact, except very
light rain
200
150
ct l 1
exp 1
glb 1
100
50
0.2
1
2
5
10
20
50
0
C u t o f f T h r e sh o l d ( m m )
Area Average Rainfall Bias (% of Observed)
:: Day 2 NDJ :
250
200
150
ct l 2
exp 2
glb 2
100
50
0.2
1
2
5
10
0
C u t o f f T h r e sh o l d ( m m )
20
50
Rainfall forecast verification :: BIAS
Area Average Rainfall Bias (% of Observed)
:: Day 1 MJJ ::
250
• Winter Case:
– Bias similar on
forecast day 1
– Slight negative
impact for light rain
amounts on day 1
– On day 2 not a
positive impact as
with summer case
200
150
ct l 1
exp 1
glb 1
100
50
0.2
1
2
5
10
20
50
0
Area Average Rainfall Bias (% of Observed)
:: Day 2 MJJ :
250
200
150
ct l 1
exp 1
glb 1
100
50
0
0.2
1
2
5
10
20
50
Rainfall forecast verification :: RMSE
Rain RMSE (%)
:: Day 1 NDJ ::
• Summer Case:
– No strong impact
on forecast day 1
– On day 2 positive
impact for all
thresholds
– DA runs better than
no-DA run except
for heavy rain
140
120
100
Cont rol
80
No AM DAR/ RS
60
Global Int p
40
20
0
0.2
1
2
5
10
20
50
C u t o f f T r e sh o l d ( m m )
Rain RMSE (%)
:: Day 2 NDJ ::
160
140
120
100
Cont rol
80
No AM DAR/ RS
Global Int p
60
40
20
0
0.2
1
2
5
10
C u t o f f T r e sh o l d ( m m )
20
50
Summary and Conclusions
• AMDAR/RS have a definite positive impact on
regional model 3dVAR forecasts in southern
Africa
• Impact decreases with forecast lead-time :: signal
probably influenced by LBCs
• Best impact found with wind in mid-upper
troposphere in tropics
• Data assimilation plays an important role in
rainfall initialisation
• Impact on rainfall best seen in day 2 forecasts and
with heavy rainfall in winter