Presentation on theme: "Rocketsondes/lidars by P. Keckhut et al. Talk given by Chantal CLAUD, LMD, Palaiseau, France + some other considerations ( EUROSPICE, SOLICE projects )"— Presentation transcript:
Rocketsondes/lidars by P. Keckhut et al. Talk given by Chantal CLAUD, LMD, Palaiseau, France + some other considerations ( EUROSPICE, SOLICE projects )
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
Instrumental changes on US Rocket
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.
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
Tidal interferences Volgograd Time of launch Averaged temperature km 2:00 10:00 15:00 Kubicki et al., submitted toJASTP, 2004.
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
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, US tropical: 8°S-34°N Wallops Island: 37,5°N Ryori, Japan: 39°N OHP, France 44°N Volgograd 49°N
Les données Les trois bases de données considérées au meme temps offrent une description détaillée de la stratosphère au cours de 20 dernières années
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
Solaire SOI QBO (B. Naujokat) Indice AO: Thompson and Wallace, 1998 Les facteurs de variabilité de la température stratosphérique
Datasets US Rocketsondes s LIDAR in France SSU
Response to solar changes: 11-year time scale US Rocket sites Tropic Subtropic Midlatitude
Response to solar changes: 11-year time scale Lidar 44°N SummerWinter
Response to solar changes: 11-year time scale ±60° SSU at 6 hPa
Response to solar changes Photochemical response at low latitude Negative response at high latitude Strong seasonal response Role of the dynamics?
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
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
AO regressions Seasonal regressions at 100 hPa Vertical structures of annual regressions Winter
CONTRIBUTION OF THE ARCTIC OSCILLATION TO OBSERVED TRENDS AT 50 HPA (IN K/DECADE) FUB
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]
The UM model: –64 vertical levels ( 1000 hPa 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 ( ): –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 , SAGEI/II (Langemtaz, 2000) The UM simulations
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
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
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.