the adm-aeolus mission
DESCRIPTION
Representing the ADM-Aeolus Mission Advisory Group, and the L2B/L2C development Team. The ADM-Aeolus mission. Geneva, 19-21 May 2008. ADM-Aeolus: Wind profile measurements from space. UV lidar (355 nm) with two receivers - Mie (aerosol), Rayleigh (molecules) - PowerPoint PPT PresentationTRANSCRIPT
ECMWFWMO Workshop19-21 May 2008: ECMWF OSEs Slide 1
The ADM-Aeolus mission
Geneva, 19-21 May 2008
Representing the ADM-AeolusMission Advisory Group, and the
L2B/L2C development Team
ECMWFWMO Workshop19-21 May 2008: ECMWF OSEs Slide 2
ADM-Aeolus: Wind profile measurements from space UV lidar (355 nm) with two receivers
- Mie (aerosol), Rayleigh (molecules)
- both use direct detection
Wind profiles from surface to 27 km with resolution varying from 0.5 to 2 km
- vertical bins configurable in flight
- HLOS component only
- direction 7º from zonal at equator
- 6 hour coverage shown
ECMWFWMO Workshop19-21 May 2008: ECMWF OSEs Slide 3
90% of molecular returns
give wind accuracy better
than 2 m/s
Complemented by good
returns from
cloud-tops/cirrus (5 to
10%) and aerosol returns
at lower levels
ADM-Aeolus helps fill data
gaps in tropics & over
oceans
Data simulations for ADM-AeolusYield of good-quality data, at 5 and 1 km
ADM simulator developed by Stoffelen and Marseille (KNMI)
ECMWFWMO Workshop19-21 May 2008: ECMWF OSEs Slide 4
ADM-Aeolus data impact DA ensemble experiments (Tan et al. 2007, QJ)
“Control”(2004 observing system
including TOVS & AIRS)
“NoSondes”(TEMPs & PILOTs
withheld)
“ADM”(Control + simulated ADM)
Radiosonde impact
Impact = Spread(Ensemble-1) – Spread(Ensemble-2)
A reduction in spread (negative values) should indicate data
benefits
ADM impact
ADM + Sondes
ECMWFWMO Workshop19-21 May 2008: ECMWF OSEs Slide 5
Data impact on ensemble analyses - zonal wind spread at 200 hPa
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
NoSondes EnsembleECMWF Analysis VT:Thursday 16 January 2003 12UTC 200hPa **u-velocity
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
NoSondes
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
Control EnsembleECMWF Analysis VT:Thursday 16 January 2003 12UTC 200hPa **u-velocity
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
Control
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
DWL EnsembleECMWF Analysis VT:Thursday 16 January 2003 12UTC 200hPa **u-velocity
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
ADM-Aeolus
Radiosondes and wind profilers over N.Amer, Japan, Europe, Australia
DWL over oceans and tropics
ECMWFWMO Workshop19-21 May 2008: ECMWF OSEs Slide 6
Profiles of 12-hour FC impact, Tropics
Spread in zonal wind (U, m/s)
Scaling factor ~ 2 for wind error
Tropics, N. & S. Hem all similar
Simulated ADM adds value at all altitudes and in longer-range forecasts (T+48,T+96) and analyses
Differences significant (T-test)
Supported by information content diagnostics
Tropics
0.0 0.5 1.0 1.5 2.0 2.51000
100
ADM-Aeolus
NoSondes
Pre
ssur
e (h
Pa)
Zonal wind (m/s)
p<0.0007
ECMWFWMO Workshop19-21 May 2008: ECMWF OSEs Slide 7
The ADM-Aeolus Mission Advisory Group (ESA)Preparatory studies on use and impact in NWP
DLR: During A-TReC in autumn 2003, the airborne DWL of DLR observed wind in sensitive regions. For the first time DWL data were assimilated in a global model at ECMWF. Positive impact reported. (QJ 2007)
Meteo-France: Impact of line shape on wind measurements and correction methods (T and p). (Tellus 2008)
ECMWF + partners: Development of the L2B/L2C wind retrieval algorithms and processing facility (Tellus 2008). Codes available.
KNMI: Wind observation requirements for the definition of an operational network of Doppler Wind Lidars (DWL) in the post-ADM era, using the new SOSE technique (Tellus 2008)
Munich Uni: The potential of ALADIN to measure the optical properties of aerosol and clouds investigated based on simulation studies
KNMI: Optimization of the ADM Spatial and Temporal Sampling Strategy
EUMETSAT: Doppler Wind Lidar Sampling Scenarios in the Tropics (MWR, 2008)
About ~15 responses to ESA’s call for CAL/VAL studies
ECMWFWMO Workshop19-21 May 2008: ECMWF OSEs Slide 8
Tandem Aeolus Scenario
Same dawn-dusk orbit and instrument, but phase difference 180 degrees (45 minutes)
Minimum of observation coverage redundancy; great heritage (low
cost)
Twice as many LOS wind profiles as Aeolus
+
6-hours of sampling Courtesy N. Žagar
ECMWFWMO Workshop19-21 May 2008: ECMWF OSEs Slide 9
ADM-Aeolus, more than a demonstrator?
• Aeolus is expected to provide unique data of great value to the meteorological community.
• As a demonstration mission Aeolus is expected to deliver all data within 2 hrs and some within 30 min.
An additional ground station, specifically Troll, could reduce latency to 70 minutes for 10 out of 15 orbits per day
• DWL data is recognized by EUMETSAT as a high priority for post-EPS
• There is no present, funded, programme to provide wind profile data between the end of life of Aeolus and the post-EPS era
• An affordable gap-filler option has been sketched by ESA, and been presented to the EUMETSAT STG. Has support from several NWP centres.