Contribution by Philippe Keckhut, Service d’Aéronomie/IPSL Chantal Claud, Laboratoire de Météorologie Dynamique/IPSL An updated analysis of stratospheric.

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Contribution by Philippe Keckhut, Service dAronomie/IPSL Chantal Claud, Laboratoire de Mtorologie Dynamique/IPSL An updated analysis of stratospheric temperature trends Slide 2 Overview - lidar stations - SSU characteristics - comparisons SSU/lidars - Solar effect Slide 3 Lidars StationLatitudeLongitudeOperating since Hohenpeissenberg47,80N11,02E1987 OHP: Obs de Haute-Provence 43,93N5,71E1979 Table Mountain Facility 34,04N117,70W1988 Hawa19,54N155,58W1993 La Runion21,80S55,5E1994 Table 1. List of lidar stations used in this study Slide 4 SSU weighting functions AMSU weighting functions Slide 5 Comparisons for OHP + Hohenpeissenberg channel 26 (6 hPa) Slide 6 ? Comparisons for OHP + Hohenpeissenberg - channel 47X (0,5 hPa) Slide 7 Comparison for TMF - channel 27 (2 hPa) Slide 8 Comparison for Mauna Loa - channel 47X (0,5 hPa) Slide 9 Oscillation at low altitude, not present at higher altitudes? Comparisons for La Runion - channels 26 (6 hPa) and 47X (0,5 hPa) Slide 10 TMF OHP Vertical trends Slide 11 TEMPERATURE CLIMATOLOGY AND TREND ESTIMATES OF THE UTLS REGION AS OBSERVED AT A SOUTHERN SUBTROPICAL SITE, DURBAN, SOUTH AFRICA H. Bencherif, et al., ACPD, 2006. 70 hPa Linear trend Slide 12 Temperature climatology above Dumont DUrville (Antarctica) Keckhut et al. Nov-AprilAug.-Oct. Occurrence of T < 190K ECMWF-RS at 100hPa for 1995-2000 Slide 13 47X 27 26 25 15X MSU4 Cagnazzo et al., 2006 79-2004 83-98 Slide 14 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 Slide 15 Solaire SOI QBO (B. Naujokat) Indice AO: Thompson and Wallace, 1998 Les facteurs de variabilit de la temprature stratosphrique Slide 16 Response to the 11-year solar cycle US Rocket sites Tropics Sub-tropics Mid-latitudes Kekchut et al., 2005 Slide 17 Response to the 11-year solar cycle Lidar 44N SummerWinter Keckhut et al., 2005 Slide 18 Response to the 11-year solar cycle 70 SSU at 6 hPa 1979-1998 Keckhut et al., 2005 Slide 19 Response to solar cycle at low latitudes, photochemical response at high and mid- latitudes, negative response with a strong seasonal dependence Role of the dynamics? Slide 20 Mechanistic simulations of the atmospheric solar response Response depends on Planetary Waves activity Response is highly non-linear Clim*1.5 Clim*1.8 Clim*2.2 3D Rose/Reprobus model at SA Hampson et al., 2005 Slide 21 Solar cycle/ conclusions Equatorial response close to the photochemical response (1-2 K) Negative response at mid and high latitudes with a strong seasonal effect The solar response is strongly related to wave activity Slide 22 Concerning the future - a new Phd student should work on trends from September 2006 on: methodology, temperature satellite retrievals, and trend updates. - Europeen project Geomon (IP, P.K. coordinator deputy): ground- satellite synergy for trend estimates (can be seen as a european contribution to SPARC). - work on solar influence on the low stratosphere: observations ( FUB, MSU4, SSU) + Rose-Reprobus simulations. - study of the solar influence using LMDz-Reprobus including an interactive chemistry (a 20 years run is available) + extension to the mesosphere.