9
ECMWF orkshop19-21 May 2008: ECMWF OSEs Slide 1 The ADM-Aeolus mission Geneva, 19-21 May 2008 Representing the ADM-Aeolus Mission Advisory Group, and the L2B/L2C development Team

ECMWF WMO Workshop19-21 May 2008: ECMWF OSEs Slide 1 The ADM-Aeolus mission Geneva, 19-21 May 2008 Representing the ADM-Aeolus Mission Advisory Group,

Embed Size (px)

Citation preview

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.