1. Rocketsondes/lidars by P. Keckhut et al. Talk given by Chantal CLAUD, LMD, Palaiseau, France + some other considerations ( EUROSPICE, SOLICE projects )

2. This study: « Temperature trends in the middle atmosphere of the mid-latitude as seen by systematic rocket launches above Volgograd Agnès Kubicki 1, Philippe Keckhut 1 *, Marie-Lise Chanin 1, Alain Hauchecorne 1, Evgeny Lysenko 2, Georgy Golitsyn 2

3. Instrumental changes on US Rocket

4. Instrumental changes on soviet rocket Volgograd sensor changes Estimated from the time serie analyses Estimated from the aerothermic calculations Raw data Corrected data Kubicki et al., submitted toJASTP, 2004.

5. Tidal interferences They induce large interferences in data comparisons, trends and satellite validations 6K Keckhut et al., J. Geophys. Res., p10299, 1996 Keckhut et al., J. Geophys. Res., p447, 1999

6. Tidal interferences Volgograd Time of launch Averaged temperature 45-55 km 2:00 10:00 15:00 Kubicki et al., submitted toJASTP, 2004.

7. Temperature trends Rockets 8°S-34°N Lidar OHP 44°N Significant trends 1-3 K/decade Homogeneous from 8°s to 44°N Keckhut et al., J. Geophys. Res., p447, 1999 Beig et al, Rev. Geoph., 2003

8. Trends as a function of latitude Volgograd OHP, _ _ Wallops, --- Riory, …. US tropical °°°° US tropical Wallops OHP Volgograd Riory Summer Winter Kubicki et al., submitted toJASTP, 2004. US tropical: 8°S-34°N Wallops Island: 37,5°N Ryori, Japan: 39°N OHP, France 44°N Volgograd 49°N

9. Les données Les trois bases de données considérées au meme temps offrent une description détaillée de la stratosphère au cours de 20 dernières années

10. The multi-parameter regressions (AMOUNTS) ( Hauchecorne et al., 1991; Keckhut et al., 1995) To evaluate temperature trends and variability (for data and model outputs): It is necessary to parametrize the variability: T(t) = m + St + ATrend + BSolar + CQBO + DENSO + EAO + Nt The A, B, C, D, E terms represent the amplitude of trends / factors of variability; (! Volcanic eruptions) The residuals (AR(1)) include all the variability not considered in the parametrization. The analysis of the residual terms : model inadequacies the degree of confidence of the analysis

11. Solaire SOI QBO (B. Naujokat) Indice AO: Thompson and Wallace, 1998 Les facteurs de variabilité de la température stratosphérique

12. Datasets US Rocketsondes 1969-90s LIDAR in France 1970-2001 SSU 1979-2001

13. Response to solar changes: 11-year time scale US Rocket sites Tropic Subtropic Midlatitude

14. Response to solar changes: 11-year time scale Lidar 44°N SummerWinter

15. Response to solar changes: 11-year time scale ±60° SSU at 6 hPa

16. Response to solar changes Photochemical response at low latitude Negative response at high latitude Strong seasonal response Role of the dynamics?

17. Mecanistic simulations of the atmospheric solar response Responses depend on PW activity Responses are highly non- linear Clim*1.5 Clim*1.8 Clim*2.2 3D Rose/Reprobus model at SA

18. Conclusions Equatorial response close to the photochemical response (1-2 K) Negative response at mid and high latitude with a strong seasonal effect The solar response is strongly related to wave activity Numerical simulations show a similar response with a specific planetary wave level

19. AO regressions Seasonal regressions at 100 hPa Vertical structures of annual regressions Winter

20. CONTRIBUTION OF THE ARCTIC OSCILLATION TO OBSERVED TRENDS AT 50 HPA (IN K/DECADE) FUB 1979-1998

21. Trends of T D-M Weakening of the mean residual circulation (1980 – 1999) 50 hPa 30 hPa 100 hPa 2 sigma at 100 hPa Trend in the T D-M [K/season/year]

22. The UM model: –64 vertical levels ( 1000 hPa - 0.01 hPa) –Horizontal resolution = 2.5° x 3.75° –Non-orographic gravity wave drag scheme (Scaife et al., 2002) –Methane oxydation scheme as a source for water vapour Transient simulations (1980-1999): –Trend imposed on the WMGHG following the IPCC IS92a scenario (Houghton et al., 1996) –Sea Ice and SST fields specified with data from the AMIP (Gates, 1992) Ensembles: – UM - control : ensemble of 5 simulations including AMIP-II ozone climatology (seasonal cycle in ozone) -> representing conditions prior to ozone depletion – UM - ozone : ensemble of 5 simulations including a linear trend in ozone varying with latitude and height. Ozone trends are calculated from TOMS 1979-1997, SAGEI/II (Langemtaz, 2000) The UM simulations

23. UM-control UM-ozone

24. The ozone contribution: Changes in the MRC Tendance de T D-M [K/saison/année] UM-O3 30 hPa UM-O3 100 hPa UM-Contrôle 100 hPa

25. Fz trends (Jan- Feb- March) Ozone changes responsible for reduction in wave activity in high latitudes during late winter? Proposed mechanism: (Hu et Tung, 2003) UM-ozone UM-control

26. Concerning the future… Russian rockets data continue after 1995, negociations to acquire them also… Lidar data from TMF (Table Mountain Facility, California) which cover the period 1988-present might be useful. Other lidars data begin after 1995, so that the record might be too short. At SA, Agnes Kubicki will work on Heiss (82°N), Molodesnaya (67°S), and Thumba (8°N) records. From May 2005 on, Serge Guillas will work on non-linear methods to determine trends (bootstrap). At LMD, work will continue on trend determination (FUB). At SA and LMD, a 20 years run from LMDz-Reprobus is available.