1. ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES GIANLUCA LOMBARDI Dept. of Astronomy Univ. of Bologna INAF  OABo Dept. of Astronomy Univ. of Padova SERGIO ORTOLANI VALENTINA ZITELLI INAF  OABo

2. ASTRONOMY AND METEOROLOGY: A SUMMARY GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 1 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 New giant telescopes will start operations about 10 years after the first seeing campaign and typically will operate in the next 20-30 years or more Trend of the astroclimate in a time scale of decades Predictions using existing models Quality of ground-based observations Local environment conditions Meteorological parameters are critical in order to optimize optical observations Short time scale astroclimate prediction (up to now several models are under development) LONG TIME SCALE ASTROCLIMATOLOGY SHORT TIME SCALE ASTROCLIMATOLOGY

3. WHICH PARAMETERS TO BE TAKEN INTO ACCOUNT? GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 2 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 LONG TIME SCALE ASTROCLIMATOLOGY AIR TEMPERATURE AIR PRESSURE RELATIVE HUMIDITY DEW POINT TEMPERATURE WIND DIRECTION WIND SPEED CLOUD COVERAGE TRENDS THROUGH DECADES SEASONAL EFFECTS CONNECTIONS WITH WIDE-SCALE PHENOMENONS (NAO, EL NIÑO, ETC.) SHORT TIME SCALE ASTROCLIMATOLOGY SURFACE LAYER SEEING SURFACE LAYER SEEING, τ 0 τ 0 EXTINCTION STABILITY INSTRUMENTS THERMALIZATION VERTICAL and HORIZONTAL TEMP. GRADIENT > LOCAL WIND DIRECTION and WIND SPEED> LOCAL WIND DIRECTION and WIND SPEED > VERTICAL WIND SPEED> VERTICAL WIND SPEED > PARTICLES POLLUTION> PARTICLES POLLUTION > PRECIPITABLE WATER VAPOUR, MOLECULES> PRECIPITABLE WATER VAPOUR, MOLECULES > PRESSURE and TEMPERATURE FLUCTUATIONS> PRESSURE and TEMPERATURE FLUCTUATIONS >

4. SITES UNDER INVESTIGATION GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 3 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 N E TNG NOT CAMC OBSERVATORIO DEL ROQUE DE LOS MUCHACHOS (ORM) LA PALMA, CANARIES Data from local ground-based Weather Stations

5. SITES UNDER INVESTIGATION GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 3 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 PARANAL OBSERVATORY ATACAMA COAST, CHILE Paranal Astronomical Site Monitor N E Data from local ground-based Weather Stations

6. SITES UNDER INVESTIGATION GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 3 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 ANTARCTIC SITES Dumont d’Urville Terra Nova Bay Dome C South Pole Data from local ground-based Weather Stations

7. AIR TEMPERATURE GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 4 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 LONG TIME SCALE ASTROCLIMATOLOGY ORM warming:  1.0 deg/10yr PARANAL warming:  0.4 deg/10yr ANTARCTIC sites are very stable

8. AIR TEMPERATURE GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 5 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 LONG TIME SCALE ASTROCLIMATOLOGY Warming has been detected at Antarctic Peninsula during 1 century data Non-homogeneous distribution of meteorological station (costal stations dominates) Is the warming dominated by Peninsula stations? Does a time lag exist in the T variation at Paranal and ORM? If YES, which is its temporal scale?

9. AIR TEMPERATURE GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 6 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 SHORT TIME SCALE ASTROCLIMATOLOGY Zago 1995, PhD Thesis Example of FWHM data from TNG (June 2008) (data from Ortolani’s observations in V band

10. AIR TEMPERATURE GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 7 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 SHORT TIME SCALE ASTROCLIMATOLOGY Remember paper RACINE et al. 1991, PASP, 103, 1020 and yesterday’s talk of same author! DT = T 2  T level M1 Image quality deteriorates when DT >  0.6 deg Example of data from TNG

11. AIR PRESSURE GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 8 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 LONG TIME SCALE ASTROCLIMATOLOGY Dispersion of monthly P at Paranal is decreasing. Standard deviation reduced of about 70% between 1990 and 2006. Monthly P at Paranal May be it is linked with wide-scale phenomenons? ORM There is NO evidence of the same effect at ORM.

12. WIDE-SCALE PHENOMENONS GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 9 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 SOUTHERN OSCILLATION INDEX SOI = Tahiti high  Darwin low Positive SOI corresponds to La Niña episodes (abnormally cold Pacific water) Negative SOI corresponds to El Niño episodes (abnormally warm Pacific water) Local minimums in the P annual trends at Paranal are linked to the presence of La Niña events while maximums with El Niño It is also known (Sarazin et al. 2005) that SOI is directly linked with the number of photometric nights at La Silla and Paranal Could be interesting to look for a link with bad weather downtime T and P at Paranal vs SOI

13. WIDE-SCALE PHENOMENONS GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 10 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 NORTH ATLANTIC OSCILLATION INDEX NAO Index = Azores high  Icelandic low Positive NAO: annual T and P are lower than their average among the decades Negative NAO: annual T and P stay above the average T and P at ORM vs NAO Index

14. AIR PRESSURE GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 11 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 SHORT TIME SCALE ASTROCLIMATOLOGY Changes in T (red) follow changes in P (blue) at ORM. P and T cross-correlation analysis at ORM and Paranal in 1998, 1999 and 2000. Typical delay is 2–3 hr. Correlation range: ORM = 50-90%Paranal = few % to 70% In both observatories the delay decreases in warm seasons. Is it possible to foresee the changes in temperature a few hours in advance? Pressure and Temperature correlation

15. WIND DIRECTION GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 12 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 Prevalent Wind Direction together with the orography of the site affect local seeing properties (presence of Surface Layers). Under peculiar conditions Paranal is strongly affected (remember talk of Melnick et al.!) Statistics of the nighttime Wind Direction at ORM in the period 1998-2004 Due to its complex orography, what happens to local Surface Layers at different locations at ORM?

16. WIND SPEED GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 13 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 Wind Speed limits affect the observations from the operational point of view. Image quality at TNG in different Wind Speed conditions. Figure shows that image quality is also linked to Wind Speed. Image quality at TNG is better when 3.3 m/s < w sp < 12 m/s

17. WHICH IS THE LESSON WE LEARNED? GIANLUCA LOMBARDI ASTROCLIMATOLOGICAL ANALYSIS OF GROUND-BASED OBSERVATORIES Dept. of Astronomy Univ. of Bologna Dept. of Astronomy Univ. of Padova INAF  OABo 14 of 14 OTaM08 – ALGHERO – SEPTEMBER 16 TH 2008 Long baseline data (decades) shows the past evolution of the climate. On the basis of long baseline data, is it possible to predict changes in the climate of analyzed regions in the future firsts decades? 1. We need models to predict short-term local environment conditions in order to improve in real time the performance of the instrumentations and the techniques of observation 3. Local environment conditions (temperature and pressure variations, wind direction, wind speed, thermal gradients, etc.) affect local observations 2.