Spaceborne Doppler Wind Lidars - Scientific motivation and impact studies for ADM/Aeolus
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Transcript of Spaceborne Doppler Wind Lidars - Scientific motivation and impact studies for ADM/Aeolus
Slide 1
Wind Lidar working group February 2010 Slide 1
Spaceborne Doppler Wind Lidars-
Scientific motivation and impact studies for ADM/Aeolus
Erland Källén
with help from
David Tan, Carla Cardinali, Paul Berrisford
ECMWF
Slide 2
Wind Lidar working group February 2010 Slide 2
OutlineADM/Aeolus
Scientific motivation Present observing system
Forecast error Sensitivity to Observations
Re-analysis uncertainties
ADM/Aeolus impact study
Conclusions
Slide 3
Wind Lidar working group February 2010 Slide 3
Atmospheric Dynamics Mission ADM/Aeolus
Slide 4
Wind Lidar working group February 2010 Slide 4
[H]LOS
ADM-Aeolus
•Doppler Lidar
•Aerosol and molecular scattering
•Intermittent pulses
•Only one wind component
•Dawn-dusk polar orbit
•Measurement error < 2 m/s
Slide 5
Wind Lidar working group February 2010 Slide 5
ADM/Aeolus
Slide 6
Wind Lidar working group February 2010 Slide 6
Main scientific objectives of ADM/Aeolus
Improve representation of wind field
in atmospheric analyses Tropics: Wind field governs dynamics Mid-latitudes: Intense storm developments
and meso-scale circulation systems
Numerical weather prediction
Climate sensitivity
Slide 7
Wind Lidar working group February 2010 Slide 7
Additional objectives
Aerosol information
Cloud properties
Slide 8
Wind Lidar working group February 2010 Slide 8
Outline
ADM/Aeolus
Scientific motivation Present observing system
Forecast error Sensitivity to Observations
Re-analysis uncertainties
ADM/Aeolus impact study
Conclusions
Slide 9
Wind Lidar working group February 2010 Slide 9
Present observing system
Radiosondes
Pilot balloons and profilers
Buoys
Satellites
Aircraft data
Slide 10
Wind Lidar working group February 2010 Slide 10
Radiosondes1 Nov 2004, ECMWF Total: 590
Slide 11
Wind Lidar working group February 2010 Slide 11
Satellite polar orbiting1 Nov 2004, ECMWF Total: 247309
Slide 12
Wind Lidar working group February 2010 Slide 12
Aircraft data1 Nov 2004, ECMWF Total 26219
Slide 13
Wind Lidar working group February 2010 Slide 13
Outline
ADM/Aeolus
Scientific motivation Present observing system
Forecast error Sensitivity to Observations
Re-analysis uncertainties
ADM/Aeolus impact study
Conclusions
Slide 14
Wind Lidar working group February 2010 Slide 14
Forecast error Sensitivity to Observations
a b bx = x + K(y - Hx )Analysis solution:
a
a
J J
x
y y x
Forecast error sensitivity to the analysis xa:
a
Jx
, ( )b
J JFEC J
y y Hxy y
1
a
J J
R HA
y x
Rabier F, et al. 1996.
Compute the δJ:
Forecast error J (“dry energy norm” ps, T, u, v)
1Ta
x
K R HAy
The tool provides the
Forecast Error Contribution
for each assimilated observation, which can be accumulated by observation type, subtype, variable or level
→ (y: observations)
→
Slide 15
Wind Lidar working group February 2010 Slide 15
24 H Forecast Error Contribution of GOS
Slide 16
Wind Lidar working group February 2010 Slide 16
Mass versus Wind contributions
0
10
20
30
40
50
60
70
Conventional-wind Conventional-mass Satellite-wind Satellite-mass
FC
E %
Total per OBS
Slide 17
Wind Lidar working group February 2010 Slide 17
Outline
ADM/Aeolus
Scientific motivation Present observing system
Forecast error Sensitivity to Observations
Re-analysis uncertainties
ADM/Aeolus impact study
Conclusions
Slide 18
Wind Lidar working group February 2010 Slide 18
Re-analyses of zonal winds
Kistler et al., 2001
NCEP ERA-15
Difference
NCEP/ERA-15
Slide 19
Wind Lidar working group February 2010 Slide 19
ERA-InterimZonal mean wind 1989-2001
m/s
>15
>30
30>25
<-10
Slide 20
Wind Lidar working group February 2010 Slide 20
Difference ERA-Interim vs. ERA-40 Zonal mean wind 1989-2001
m/s
>2
<-4
Slide 21
Wind Lidar working group February 2010 Slide 21
Outline
ADM/Aeolus
Scientific motivation Present observing system
Forecast error Sensitivity to Observations
Re-analysis uncertainties
ADM/Aeolus impact study
Conclusions
Slide 22
Wind Lidar working group February 2010 Slide 22
Assimilation study for ADM/Aeolus
Assimilation ensembles for data impact assessment
Use ensemble spread as proxy for short-range forecast errors (background errors)
By extension, good data reduce ensemble spread
DWL impact
Radiosonde/profiler impact - provides calibration
Tan et al., QJRMS 133:381-390 (2007)
Slide 23
Wind Lidar working group February 2010 Slide 23
Reference ResultVerificationNWP-SystemObservations
Reference ResultAn & FcDiagnostics
NWP-SystemEnsembleObservations
OSEOSE
Assimilation EnsembleAssimilation Ensemble
Real atmosphere
Assimilation/ forecast
Assimilation/ forecast
Compare to reference
Compare to reference
Impact assessment
Ref. run
Assimilation/ forecast
Assimilation/ forecast
Ensemble spread
Ensemble spread
Assimilation/ forecast Ensemble spread
Calibrate
Impact assessment
Slide 24
Wind Lidar working group February 2010 Slide 24
-0.1
0.1 0.1
0.1
80 S 80 S
60 S60 S
40 S 40 S
20 S20 S
0 0
20 N20 N
40 N 40 N
60 N60 N
80 N 80 N
120 W
120 W 60 W
60 W 0
0 60 E
60 E 120 E
120 E
Thursday 16 January 2003 12UTC ECMWF Forecast t+12 VT: Friday 17 January 2003 00UTC 500hPa **u-velocity
-2.6
-2.2
-1
-0.4
-0.3
-0.2
-0.1
0.1
0.2
0.3
0.4
1
2.2
2.6
-0.1
-0.1
0.1
80 S 80 S
60 S60 S
40 S 40 S
20 S20 S
0 0
20 N20 N
40 N 40 N
60 N60 N
80 N 80 N
120 W
120 W 60 W
60 W 0
0 60 E
60 E 120 E
120 E
Thursday 16 January 2003 12UTC ECMWF Forecast t+12 VT: Friday 17 January 2003 00UTC 500hPa **u-velocity
-2.6
-2.2
-1
-0.4
-0.3
-0.2
-0.1
0.1
0.2
0.3
0.4
1
2.2
2.6
-0.1
0.1 0.1
0.1
80 S 80 S
60 S60 S
40 S 40 S
20 S20 S
0 0
20 N20 N
40 N 40 N
60 N60 N
80 N 80 N
120 W
120 W 60 W
60 W 0
0 60 E
60 E 120 E
120 E
Thursday 16 January 2003 12UTC ECMWF Forecast t+12 VT: Friday 17 January 2003 00UTC 500hPa **u-velocity
-2.6
-2.2
-1
-0.4
-0.3
-0.2
-0.1
0.1
0.2
0.3
0.4
1
2.2
2.6
-0.1
-0.1
0.1
80 S 80 S
60 S60 S
40 S 40 S
20 S20 S
0 0
20 N20 N
40 N 40 N
60 N60 N
80 N 80 N
120 W
120 W 60 W
60 W 0
0 60 E
60 E 120 E
120 E
Thursday 16 January 2003 12UTC ECMWF Forecast t+12 VT: Friday 17 January 2003 00UTC 500hPa **u-velocity
-2.6
-2.2
-1
-0.4
-0.3
-0.2
-0.1
0.1
0.2
0.3
0.4
1
2.2
2.6
Data impact on ensemble forecasts - zonal wind spread at 500 hPa
Sondes
60°S60°S
30°S 30°S
0°0°
30°N 30°N
60°N60°N
150°W
150°W 120°W
120°W 90°W
90°W 60°W
60°W 30°W
30°W 0°
0° 30°E
30°E 60°E
60°E 90°E
90°E 120°E
120°E 150°E
150°E
Thursday 16 January 2003 12UTC ECMWF Forecast t+12 VT: Friday 17 January 2003 00UTC 500hPa **u-velocity
0.75
0.9
1.05
1.2
1.35
1.5
1.65
1.8
1.95
2.1
2.25
Control
ADM-Aeolus
Radiosondes and wind
profilers over Japan,
Australia, N.Amer, Europe
DWL over oceans & tropics
Slide 25
Wind Lidar working group February 2010 Slide 25
60°S60°S
30°S 30°S
0°0°
30°N 30°N
60°N60°N
150°W
150°W 120°W
120°W 90°W
90°W 60°W
60°W 30°W
30°W 0°
0° 30°E
30°E 60°E
60°E 90°E
90°E 120°E
120°E 150°E
150°E
NH=-0.03 SH= -0.04 Trop= -0.17 Eur=-0.02 NAmer= 0.02 NAtl= -0.02 NPac= -0.04Lev=200, Par=u, FcDate=20030116-20030228 12Z, Step=12
RMS of Ensemble fcspread: RMS(fcspread_emi1_emi2_emi3_emi4) - RMS(fcspread_em9l_em9m_em9n_em9o)
-1
-0.8
-0.6
-0.4
-0.2
-0.1
-0.040.04
0.1
0.2
0.4
0.6
0.8
1
60°S60°S
30°S 30°S
0°0°
30°N 30°N
60°N60°N
150°W
150°W 120°W
120°W 90°W
90°W 60°W
60°W 30°W
30°W 0°
0° 30°E
30°E 60°E
60°E 90°E
90°E 120°E
120°E 150°E
150°E
NH=-0.03 SH= -0.05 Trop= -0.09 Eur=-0.06 NAmer= -0.03 NAtl= 0 NPac= -0.04Lev=200, Par=u, FcDate=20030116-20030228 12Z, Step=12
RMS of Ensemble fcspread: RMS(fcspread_em9l_em9m_em9n_em9o) - RMS(fcspread_embd_embe_embf_embg)
-1
-0.8
-0.6
-0.4
-0.2
-0.1
-0.040.04
0.1
0.2
0.4
0.6
0.8
1
Data impact on ensemble forecasts - zonal wind spread at 200 hPa
Sondes
60°S60°S
30°S 30°S
0°0°
30°N 30°N
60°N60°N
150°W
150°W 120°W
120°W 90°W
90°W 60°W
60°W 30°W
30°W 0°
0° 30°E
30°E 60°E
60°E 90°E
90°E 120°E
120°E 150°E
150°E
Thursday 16 January 2003 12UTC ECMWF Forecast t+12 VT: Friday 17 January 2003 00UTC 200hPa **u-velocity
0.75
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
2.6
2.8
Control
ADM-Aeolus
Radiosondes and wind
profilers over Japan,
Australia, N.Amer, Europe
DWL over oceans and
tropics
Slide 26
Wind Lidar working group February 2010 Slide 26
Conclusions
Wind data is lacking in present global
observing system Tropical analyses suffer
Climate system re-analyses uncertain in tropics, polar areas and stratosphere
ADM/Aeolus will provide vertical wind
profiles with global coverage
Slide 27
Wind Lidar working group February 2010 Slide 27
Thank you for your attention– questions?