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Elena MASCIADRI

[ Ref : Masciadri E., submitted , AJ]. Elena MASCIADRI. [ Ref : Masciadri E., Avila R., Sanchez L., submitted , A&A]. IA-UNAM - MEXICO D.F. Selection of the BEST site for the GST.  Near Ground Wind (NGW) simulations.  Meso-Nh calibration for the

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Elena MASCIADRI

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  1. [ Ref : Masciadri E., submitted, AJ] Elena MASCIADRI [ Ref : Masciadri E., Avila R., Sanchez L., submitted, A&A] IA-UNAM - MEXICO D.F. Selection of the BEST site for the GST Near Ground Wind (NGW) simulations  Meso-Nh calibration for the optical turbulence (OT) simulation

  2. Outline • NEAR GROUND WIND SIMULATIONS  Why to simuate the NGW with a meso-scale model  Numerical validation: methodology  Statistical results  Practical procedure for the site characterization • MESO-NH CALIBRATION  Why do we need a calibration  Calibration technique  Recent resultsstatistical reliability of Meso-Nh  FUTURE DEVELOPMENTS

  3. ELTs Near Ground Wind (NGW) WHY ? To limit the potential vibrations produced by the interaction windmechanical and optical structure of the telescope  Good image quality At the present time The only accessible and free of charge estimations of the NGW are analysis and forecast s provided by GCM horizontal resolution ~ 2° Meso-scale Models ? Site Altitude Site Latitude Sky Brightness Precipitable water vapour Cloud cover Optical extinction Optical turbulence (OT) Discriminatory Astroclimatic Parameters

  4. 120 km MAIDANAK (38.67 N, 66.88 E)  horizontal resolution: 1 km Wind Intensity (@ 5 m) 15 PARANAL (24.61 S, 70.40 W) (m/sec) 10 Paranal 5 Dv ~ 4 m/s Maidanak 0 1 2 4 3 5 6 9 7 8 10 12 11 months Can Meso-Nh select the site having the lowest near ground wind intensity ?  ESPAS(OWL - D = 100 m)

  5. MAIDANAK PARANAL 25 nights t = 3 hr 20 nights t = 3 hr 1 <v>sim=3.83 m/sec <v>sim=2.30 m/sec 0.8 <v>meas=6.36 m/sec <v>meas=2.33 m/sec 0.6 0.4 0.2 26.84 % 47.30 % 0 [Ref: Masciadri E., submitted, A&A] 20 nights t = 0 hr 25 nights MAIDANAK PARANAL t = 0 hr CDRE 1 1 <v0>sim=4.52 m/sec <v0>sim=1.67 m/sec 0.8 ECMWF <v>sim=3.83 m/sec <v>meas=2.33 m/sec <v>meas=6.36 m/sec <v>sim=2.30 m/sec 0.8 <v>meas=6.36 m/sec 0.6 <v>meas=2.33 m/sec 0.6 0.4 0.4 0.2 99.40 % 66.67 % 0.2 0 26.84 % 47.30 % 1 0.5 1.5 0.4 1 0 0.2 0 0.6 0.8 2 0 relative error relative error 19 % t = 3 hr t = 3 hr 73 % 1 <v0>sim=4.52 m/sec <v0>sim=1.67 m/sec 0.8 0.6 0.4 0.2 Meso-Nh 99.40 % 66.67 % 0 1 1 0 2 0.4 0.8 0.5 1.5 0.4 1.5 1 0.2 0 0.2 0.5 0 0.6 0.6 0.8 1 2 0 relative error relative error <v>meas=2.33 m/sec <v>meas=6.36 m/sec 1 ECMWF

  6. 1. Quality of the initialization data 2. Tendency of underestimating the strong wind shears in the first meters PARANAL 25 nights MAIDANAK 20 nights 10 15 8 10 4 simulated wind intensity simulated wind intensity 5 2 0 0 0 15 0 10 2 4 8 5 10 (m/s) (m/s) measured wind intensity measured wind intensity

  7. 17/7/1999: STRONG NGW wind intensity – temporal evolution wind intensity - east-west section 3000 5000 (m) (m) 2940 2880 4000 13 2820 2760 3000 14 * 2700 2640 2000 2580 2520 1000 2460 * 8 0 3 h (km) 2 h 4 8 20 0 12 16 wind intensity - east-west section wind intensity – vertical profil 3000 3000 (m) (m) 2740 2840 2480 2680 2220 2520 ~ 50 m 1960 2360 1700 4 10 8 0 15 0 12 20 (km) 16 5 (m/s)

  8. 8/5/1999: LOW NGW wind intensity – temporal evolution wind intensity - east-west section 5000 3000 (m) 2940 2880 4000 2820 2760 3000 * 2700 3 2000 2640 2580 1000 2520 2460 * 2.28 0 (km) 3 h 4 8 20 2 h 0 12 16 wind intensity – vertical profil wind intensity - east-west section 3000 3000 (m) (m) 2840 2740 2680 2480 2520 2220 ~ 50 m 2360 1960 1700 4 0 6 4 8 2 (m/s) 0 12 20 (km) 16

  9. [50 – 90] %

  10. <v> (m/sec) 6.36 ECMWF P h (m) 1. 4.52 M 2.33 1.67 ~ 200 m Maidanak Paranal 6.36 P 3.83 Meso-Nh 2. 2.30 10 m M 2.33 ground Maidanak Paranal 3. systematic simulations at 10 m selection of the site with the lowest NGW systematic simulations at ~250 m identification of sites with strong NGW CDRE [ 26- 47 ] %

  11. STUDY FEASIBILITY FUJITSU VPP5000 - ECMWF Project accepted at ECMWF 3000 SBUs 15 sites  630 h CPU (2300 SBUs)   3h  3047 sec CPU  Maidanak/Paranal 45 nights  42 h CPU  NCEP re-analysis (hor. resolution = 1.875°)  probable low reliability

  12. 1. 2. 3. 4. WHY A CALIBRATION ? Free parameter: Emin It was proven that Emin cannot be measured At least in the stable regions of the atmosphereEmin ÷ [CN2] 3/2 We can identify regions of the atmosphere (slabs of a few kms) characterized by different Emin values • Calculation of an optimized Emin ‘at posteriori’ fitting CN2 profiles (measured and simulated) Calibration = definition of theEmin with respect to the whole atmosphere (~ 20 km)

  13. boundary layer First time: calibration without off-set free atmosphere surface layer • dome seeing • • • E*min 1.2·10-3 20 (km) a5 15 a4 10 a3 5 a2 a1 0 2.5·10-3 5·10-4 10-3 1.5·10-3 2·10-3 (kg m2 t-2) Least Square Method

  14. Averaged estimation over 10 nights San Pedro Martir site testing campaign 5/2000 20 H (km) Bold line: GS 15 Thin line: Balloons Dotted line: Meso-Nh 10 5 eTOT= 0.93 ‘’ eTOT= 0.79 ‘’ eBL= 0.77 ‘’ eBL= 0.62 ‘’ 0 eFA=0.45 ‘’ eFA=0.42 ‘’ 10-17 10-15 10-18 10-16 CN2 (m-2/3) MNH - surf. GS - dome

  15. San Pedro Martir site testing campaign (5/2000) 19/5/2000 9/5/2000 22/5/2000 21/5/2000 Thin line: Meso-Nh Dotted line: Balloons Bold line: GS

  16. ? * DP = Pmeas - Psim DP = Pscidar - Pballoons SAN PEDRO MÁRTIR CAMPAIGN 2000 10nights De sci. - sim. ~ De *sci. – bal <30 % climatologic reliability reliability over the temporal scale of one night De sci. - sim. ~ De *sci. – bal <40 % [ Ref : Masciadri, Avila, Sanchez, submitted, A&A] FORECAST SCORE ….COMPARISON BETWEEN FORECASTS AND MEASUREMENTS [ Ref : Masciadri & Jabouille, A&A, 376,727, 2001]

  17. PRESENT • Simulations of C2N (z) profiles over 1 year (San Pedro Martir) seasonal variation of C2N (z) • seasonal variation of ALL the integrated parameters (e, qAO,tAO…..)  Comparison simulations-measurements over a real LONG campaign (months) over at least 2 sites FUTURE 1°GS/LBT Mt. Graham ? 2°

  18. viewed by Meso-Nh model 60 km horizontal resolution = 400 m Mt. Graham - LBT site Dan McKenna (Stewart Observatory) Mickey Reeds (ASU Meso Mod. Group) h = 3247 m ( 32.7013 N, 109.8919 W) 1°

  19.  Meso-scale simulations - resol: [400-500] m  Micro-scale simulations - resol: [10-20] m GST(Giant Segmented Telescope) NOAO/CTIO/Gemini Priorities (sites): Mauna Kea (Hawaii) North Chili South US North Mexico NUMERICAL MODELISATION Chajnantor - 400 m San Pedro Martir - 400 m Mauna Kea - 1 k m 60 km 150 km 14.4 km

  20. END

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