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Operational ground-based remote sensing of wind

Operational ground-based remote sensing of wind Experiences from the European wind profiler network CWINDE. V. Lehmann 1 , A. Haefele 2 , S. Klink 4 , G. Martucci 2 , M. Hervo 2 , M. Turp 3 , Eileen Päschke 1 , R. Leinweber 1 1 - Deutscher Wetterdienst 2 - MeteoSwiss

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Operational ground-based remote sensing of wind

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  1. Operational ground-based remote sensingof wind Experiencesfromthe European wind profilernetwork CWINDE V. Lehmann1, A. Haefele2, S. Klink4, G. Martucci2, M. Hervo2, M. Turp3, Eileen Päschke1, R. Leinweber1 1 - Deutscher Wetterdienst 2 - MeteoSwiss 3 - UK MetOffice 4 - EUMETNET Observations Programme

  2. Outline of talk • Radar Wind Profilersandtheir operational use in the EUMETNET E-PROFILE Programme – CWINDE • Benefits: RWP dataimpact in NumericalWeatherPrediction • Challenges: Currentandfuturetasksfor E-PROFILE

  3. Radar Wind Profilersandtheir operational use in the EUMETNET E-PROFILE Programme – CWINDE • Benefits: RWP dataimpact in NumericalWeatherPrediction • Challenges: Currentandfuturetasksfor E-PROFILE

  4. WMO Statement of Guidance for high resolution NWP (May 2012): „The critical atmospheric variables that are not adequately measured by current or planned systems are (in order of priority)“ • Wind profiles at all levels (u,v) • Temperature and humidity profiles of adequate vertical resolution in cloudy and rainy areas • Precipitation • Snow equivalent water content • Soil moisture http://www.wmo.int/pages/prog/www/OSY/GOS-RRR.html

  5. Radar wind profiler (L-Band to VHF) • „Clear air“ Doppler radars – wavelenghts 0.2 – 6 m •  Horizontal wind vector (u,v), virtualtemperatureTv • 1.) Maturetechnology: • - First demonstration in early 1970‘ies • - Operationallyusedsincemid 1990‘ies • - (Most) operationally relevant problemssolved • 2.) All-weather 24/7 operation • data in bothclearandcloudyatmosphere (!) • 3.) Availability • - Commercial vendorsexisting • 4.) Practicality • - RF Spectrumassignedby WRC • - Interferenceissues must beconsidered

  6. EUMETNET E-PROFILE Coordinated WIND profiler network in Europe (CWINDE) http://www.metoffice.gov.uk/science/specialist/cwinde/profiler/

  7. EUMETNET E-PROFILE – some facts A networkfor operational profilingof wind andaerosol • Runs under EUMETNET, a grouping of 31 European NMS’s: 1.1. 2013 - 31.12. 2017 • 19 (out of 31) members - responsible: MeteoSwiss • Co-operative network, nocentralfundingforsites • Wind profilingnetwork - CWINDE (operational) • 42 RWP : • VHF: 16 (including11 O-Q networkradars in Canada) • UHF: 4 (Germany, 482 MHz) • L-Band: 22 (including La Reunionand Samoa) • 107 „weatherradars“ (mostly C-Band): VAD, VVP wind data • Aerosol profilingnetwork(underdevelopment) www.eumetnet.eu/e-profile

  8. Automatic Laser Ceilometer (ALC) network Extended remit of E-PROFILE: Inclusion of laser ceilometers 1. New capabilities (instruments) recentceilometergeneration backscattercontainsinformation on aerosolsandclouds 2. Suitability for network operation Low costs Unattended 24/7 operation Most instruments already deployed  Network integration and data harmonization needed Future E-PROFILE ceilometernetwork

  9. CWINDE Performance targets 1. Data availability • ≥ 85 % (≥ 95 %internalgoal) 2. Message timeliness • Observation time + 30 minutes: ≥ 95 % 3. Measurement accuracy(estimatedfrom ECMWF IFS): • integral RMS vectordifference: ≤ 5.0 m/s

  10. Monitoring: Quality (against NWP) Vertically averaged statistics: VD – vector difference, WS - wind speed, (U,V)T – horizontal wind vector

  11. Monitoring: Availability & Timeliness AVL: Availability, Δ30: Timeliness (t + 30 min), Δ60: Timeliness (t + 60 min)

  12. Radar Wind Profilersandtheir operational use in the EUMETNET E-PROFILE Programme – CWINDE • Benefits: RWP dataimpact in NumericalWeatherPrediction • Challenges: Currentandfuturetasksfor E-PROFILE

  13. Cost/benefitconsiderationsfor RWP FSA NOAA report from May 2004: “The NOAA profiler network provides the best overall wind profile performance since no alternative provides equal or higher performance at lower costs” However, OSE impact studies performed by various NWP Centres had so far given quite mixed results: “overall weakly positive or neutral impact” Probable reasons: • Small total number of RWP • “Good and bad” lumped together http://www.nws.noaa.gov/ost/coea/COEA_May26_final.pdf

  14. Estimationof RWP observationimpact in NWP – Adjointsensitivityestimates (FSO) FSA Model state vector, dimension O(108) Norm of the state vector – „energy measure“: Forecast error of two forecasts starting at t-6 h and t=0. The difference of the two forecast errors at t +24 h is approximately only due to the new observations ingested at t = 0 „Innovation x Observation sensitivity“: involves only observation space quantities Allows partitioning of forecast error reduction for each observation „Observation sensitivitycalculationrequires: • Adjointofforecastmodel (TL) • Adjointofdataassimilationsystem Langland and Baker (2004) „Estimation of observation impact using the NRL variational data assimilation system“, Tellus 56A, 189-201

  15. ECMWF FSO estimateofobservationimpact Mean FEC (normalized by # of observations) Total FEC. Observation contribution to the global forecast error reduction (FEC) in the ECMWF IFS, grouped by observation type in percent, for September and October 2011. Courtesy of C. Cardinali, ECMWF.

  16. UK MetOffice FSO estimateof RWP impact Deutscher Wetterdienst Reductionofforcasterrormeasuredby global moistenergy norm (u,v,T,p,q) 4 German TEMPs vs. 4 German RWP (482 MHz) First resultsfrom UK MetO FSO-tool fortheperiod Aug 22 – Sep 29, 2010 Courtesy: Richard Marriott Catherine Gaffard Ronny Leinweber Lindenberg RWP impactis 5 timesbiggerthantheimpactoftheco-located Radiosonde !

  17. Radar Wind Profilersandtheir operational use in the EUMETNET E-PROFILE Programme – CWINDE • Benefits: RWP dataimpact in NumericalWeatherPrediction • Challenges: Currentandfuturetasksfor E-PROFILE

  18. Challengesfor E-PROFILE (and RWP) Deutscher • Protection of frequencies: Need bands without interfering RF signals • Qualified staffcrucial – maintain existing knowledge through training and workshops • Enforce strict quality control at the sites – “no data is better than bad data” • Clutter filtering – many algorithms are existing, bub not always implemented • Detection of non-homogeneous wind field conditions – convection, gravity waves,… • Hardware and software maintenance: • Radars operate over 10+ years – need for renovation or replacement • Continuous evolution of operating systems – IT security • Development and automation of monitoring • System failures must be identified quickly • Standardization of RWP “raw data” formats (moments, spectra, I/Q) • NWP monitoring statistics – development of unified graphics (results from different models) • Exploit potential of new IR Doppler lidars for Boundary-Layer wind profiling • Implementation of new WMO BUFR template for wind observations in 2015

  19. Lidar wind profiler (IR) •  Horizontal wind vector (u,v) • 1.) Maturity: • - First demonstration in mid 1960‘ies (CO2 laser) • - Wind shearwarningsystemssincemid 2000 • - Testing in operational settingunderway • 2.) All-weather 24/7 operation: Yes, limited availability • - in andaboveopticallythickclouds • - in particle-freeatmosphere (notargets) • 3.) Availability • - Commercial vendorsexisting • - Market currentlyveryactive (mainly wind energy) • 4.) Practicality • - Easy todeploy, fullyautonomousoperation • - All-fiber optics: Mechanicallyverystable • - Eye safe (Laser class 1M) Radial wind data from a 24 beam VAD-scan, Oct 03, 2012 08:20 -09:20 UTC

  20. Data availability: Radar vs. Lidar wind profiler (quality controlled data only) 482 MHz RWP, 1 µs pulse, “Low mode” 1. 5 µm Lidar, 160 ns pulse Oct. 02, 2012 – Oct. 02, 2013 max # : 17568

  21. 482 MHz radar vs 1.5 µm lidar: 1-year intercomparison statistics

  22. Summary • More wind profile observations are needed for high resolution NWP • Radar wind profiling is an existing and proven technology that can provide such data with good quality and high temporal resolution. • A clear positive impact of RWP data has been demonstrated using the new (adjoint based) sensitivity estimation method. • The EUMETNET E-PROFILE Programm continues to operate the CWINDE profiler network in a cooperative manner. The biggest challenge is the sustainability of CWINDE network profilers over 10+ years. • New IR-Doppler lidars can be used to complement the radar measurements in the Boundary Layer. • RWP (networks) will be a valuable reference for future space based sensors, like ESA‘s ADM Aeolus.

  23. Thank you ! Lindenberg, Sep 03, 2011: Aerial view of 482 MHz RWP Meteorologisches Observatorium Lindenberg – Richard-Aßmann-Observatorium (2011) Meteorologisches Observatorium Lindenberg – Richard-Aßmann-Observatorium (2011) Meteorologisches Observatorium Lindenberg – Richard-Aßmann-Observatorium (2011)

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