Climatology of Paranal. Prepared by M. Sarazin, ESO

Transcription

1 Climatology of Paranal Prepared by M. Sarazin, ESO 1

2 Climatology of Paranal The Main Climate Actors The Main Parameters And their Climatology 2

3 Main Climate Actors Bolivian High El Nino Southern Oscillation South American Monsoon Pacific Decadal Oscillation (?) Global Warming (no) 3

4 Main Climate Actors 1-The Bolivian High The Bolivian high is characterized by a warm core below about 150 mb, capped above by a cold top. The warm temperatures extend from the surface and maximize at around 300 mb. M. Beniston, P. Casals & M. Sarazin; Perturbations to astronomical observations at the European Southern Observatory's very large telescope site in Paranal, Chile: analyses of climatological causes; Theoretical and Applied Meteorology, Volume 73 Issue 3-4 (2002) pp

5 Main Climate Actors 2-South American Monsoon System (SAMS) also called Bolivian Winter Over 60% of the annual precipitation of the Andes is concentrated in the austral summer (DJF) in the form of intensive convective rainstorms along the plateau, when easterly flow prevails over the central Andes allowing moisture transport from the interior of the continent up to the Altiplano. 5

6 Main Climate Actors 3- El Niño/Southern Oscillation (ENSO): El Niño/Southern Oscillation (ENSO): The term for the coupled oceanatmosphere interactions in the tropical Pacific characterized by episodes of anomalous high sea surface temperatures in the equatorial and tropical eastern Pacific; associated with large scale swings in surface air pressure between the western and eastern tropical Pacific. These episodes recur at irregularly spaced intervals (2-7 years) and may persist for as long as 2 years (Niño=warmer water, Niña=colder water). 6

7 Main Climate Actors 4- Pacific Decadal Oscillation (PDO): The "Pacific Decadal Oscillation" (PDO) is a long-lived El Niño-like pattern of Pacific climate variability. While the two climate oscillations have similar spatial climate fingerprints, they have very different behavior in time. Two main characteristics distinguish PDO from El Niño/Southern Oscillation (ENSO): first, 20th century PDO "events" persisted for 20-to-30 years, while typical ENSO events persisted for 6 to 18 months 7

8 Main Parameters Seeing Coherence Time Precipitable Water Vapor Cloudiness: Observatory night reports 8

9 Main Parameters The Seeing The seeing is measured by dedicated Instruments: DIMM since 1988 MASS since

10 Main Parameters The Seeing The seeing is measured by dedicated Instruments: DIMM since 1988 MASS since

11 Main Parameters The Seeing The seeing measured by DIMM compares well with UT4 active optics spot size 11

12 Main Parameters The Seeing Comparison with FORS Image Quality Because its diameter is comparable to the finite outer scale of the turbulence, the site is better for a VLT than predicted by DIMM by about 10% in the visible FORS data, Roberto Mignani, ESO 12

13 Main Parameters The Seeing Comparison with ISAAC image quality for a VLT, the site is better than predicted by DIMM by up to 30% in the IR ISAAC data, Wolfgang Hummel, ESO 13

14 Main Parameter The turbulence Coherence Time, Tau0 (adaptive optics, VLTI fringe tracker) First light of Sinfoni Bonnet et al, The Messenger 117 Tau0=0.31 r0/ V0 The wavefront velocity is estimated from 200mb and ground wind velocity V0fit= Max(Vground, 0.4 V200mb ) (systematic trend observed during Paranal and Gemini balloon campaigns) 14

15 Main Parameters CLOUDS and RECIPITABLE WATER VAPOR (Andre Erasmus, SAAO, South-Africa) Infra-red Window Channel and Water Vapour Channel at 11:45UT on October 25, 2000 Infra-Red Window (10.7µm) Water Vapor (6.7µm) GOES Meteorological Satellites 15

16 Main Parameters CLOUDS and PRECIPITABLE WATER VAPOR km 9 *Site 1 5 4km 62 o Schematic showing a 9-pixel area centred on a potential site in plan view (left) and cross-section (right). At left, each square represents a pixel in the satellite image. At right, assuming a site altitude of 4km and a pixel resolution of ~10km, at Tropopause level (~12km), the sky encompassed by the 9-pixels corresponds approximately to an area of observation within 62 o of zenith. 16

17 Main Parameters PRECIPITABLE WATER VAPOR PWV (mm) statistics for Paranal (January - August 1998) and Chajnantor (January - September 1999) for satellite and groundbased site monitor measurements of PWV Site Sensor Satellite Paranal Site Monitor Satellite Chajnantor Site Monitor Period Day Night Day 24 hrs 10 th percentile st Quartile Median rd Quartile Conclusion: The satellite-derived PWV for daytime hours gives a reliable and accurate absolute humidity measurement that is representative of daytime and nighttime moisture conditions 17

18 Main Parameters PRECIPITABLE WATER VAPOR Precipitable water vapor content of the atmosphere (ppwh2o) multiplied by the airmass of the standard star observation versus sensitivity. Data are shown whenever available during TIMMI2 operations in year: R. Siebenmorgen, ESO 18

19 Climatology of Cloud Cover ( ) Seeing ( ) Turbulence Coherence Time Precipitable Water Vapor Boundary Layer Flow 19

20 Climatology of The Cloud Cover Paranal photometric night monthly fraction Long term degradation? Coupling with El Nino? 20

21 Climatology of The Cloud Cover Paranal photometric night monthly fraction Long term degradation (Bolivian High moving South) Coupling with El Nino 21

22 Climatology of The Cloud Cover La Silla photometric night monthly fraction Long term improvement (Polar low moving South) Coupling with El Nino 22

23 Climatology of The Cloud Cover Paranal photometric night monthly fraction Long term degradation (Bolivian High moving South) Coupling with El Nino 23

24 Climatology of The Cloud Cover Paranal-La Silla differential photometric night monthly fraction 24

25 Climatology of The Seeing Paranal & La Silla seeing Long term degradation? Coupling with El Nino? 25

26 Climatology of The Seeing Paranal seeing during the VLT life Monthly Average 0.91 Monthly Median 0.81 (0.66) 5 percentile 0.47 (0.38) 26

27 Climatology of The Seeing Paranal seeing Long term degradation + Coupling with El Nino 27

28 Climatology of The Seeing Paranal & La Silla seeing Long term degradation + Coupling with El Nino 28

29 Climatology of The turbulence Coherence Time, Tau0 Tau0=0.31 r0/ V0 Paranal Wind at 200mb No long term climatic trend 29

30 Climatology of The turbulence Coherence Time, Tau0 Tau0=0.31 r0/ V0 Paranal Wind at 200mb No long term climatic trend No coupling with el-nino 30

31 Climatology of The turbulence Coherence Time, Tau0 Tau0=0.31 r0/ V0 Paranal yearly wind vertical profile The strong seasonal trends of Tau0 are due to Jet Stream variability 31

32 Climatology of The turbulence Coherence Time, Tau0 Tau0=0.31 r0/ V0 Paranal Median tau0 reaches 5ms in summer, below 3ms the rest of the year 80% of the dark time larger than 3ms in J-FM, only 40% in J-J-A-S 32

33 Climatology of Precipitable Water Vapor Paranal & La Silla 3-hourly PWV 33

34 Climatology of Precipitable Water Vapor Paranal & La Silla 3-hourly PWV Winter is two times dryer than Summer 34

35 Looking for long term trends The mechanism of the degradation of the seeing at Paranal is not global but selective: the superb seeing conditions from the sea breeze (N-Westerly wind) are progressively replaced by turbulent boundary layer flow from the land (N-Easterly wind) This effect is amplified by the presence of other summits upwind Study Boundary Layer Climatology 35

36 Climatology of Boundary Layer Flow A Mesoscale Model can reproduce regional patterns MM5 analysis of the wind trajectories during bad seeing conditions at Paranal (source: Dept. of Meteorology, Univ. of Munich) 36

37 Climatology of Boundary Layer Flow A Mesoscale Model can reproduce regional patterns MM5 vertical cut along the NE wind flow during bad seeing conditions at Paranal (source: Dept. of Meteorology, Univ. of Munich) 37

38 Climatology of Boundary Layer Flow (NCAR-NCEP re-analysis)

39 Climatology of Boundary Layer Flow Paranal Wind Velocity at 700mb Long term trend El-Nino anticoupling? 39

40 Climatology of Paranal Two lines of sight which make all the difference 40