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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,

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Presentation on theme: "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,"— Presentation transcript:

1 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, and the L2B/L2C development Team

2 ECMWF WMO 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

3 ECMWF WMO 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-Aeolus Yield of good-quality data, at 5 and 1 km ADM simulator developed by Stoffelen and Marseille (KNMI)

4 ECMWF WMO 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

5 ECMWF WMO Workshop19-21 May 2008: ECMWF OSEs Slide 5 Data impact on ensemble analyses - zonal wind spread at 200 hPa NoSondesControl ADM-Aeolus  Radiosondes and wind profilers over N.Amer, Japan, Europe, Australia  DWL over oceans and tropics

6 ECMWF WMO 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 ADM-Aeolus NoSondes Pressure (hPa) Zonal wind (m/s) p<0.0007

7 ECMWF WMO 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

8 ECMWF WMO 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

9 ECMWF WMO 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.


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