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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)
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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) - 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
Data simulations for ADM-AeolusYield of good-quality data, at 5 and 1 km • 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 ADM simulator developed by Stoffelen and Marseille (KNMI)
ADM-Aeolus data impact DA ensemble experiments (Tan et al. 2007, QJ) • Impact = Spread(Ensemble-1) – Spread(Ensemble-2) • A reduction in spread (negative values) should indicate data benefits “ADM” (Control + simulated ADM) ADM impact “Control” (2004 observing system including TOVS & AIRS) ADM + Sondes Radiosonde impact “NoSondes” (TEMPs & PILOTs withheld)
Control NoSondes ADM-Aeolus Data impact on ensemble analyses - zonal wind spread at 200 hPa • Radiosondes and wind profilers over N.Amer, Japan, Europe, Australia • DWL over oceans and tropics
ADM-Aeolus p<0.0007 Pressure (hPa) NoSondes Zonal wind (m/s) 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
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
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 ofsampling Courtesy N. Žagar
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.