Radiosonde stratospheric temperatures at Dumont d'Urville (Antarctica):  trends and link with polar stratospheric clouds

David, Christine; Keckhut, Philippe; Armetta, A.; Jumelet, Julien; Snels, M.; Marchand, Marion; Bekki, Slimane

doi:10.5194/acp-10-3813-2010

Cited by 15 publications

(17 citation statements)

References 62 publications

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“…However, this mechanism can only operate in the cold season when stratospheric temperatures are cold enough for these clouds to form. Furthermore, while a 3% decade −1 increase in the wintertime occurrence of polar stratospheric clouds has been reported at Dumont d'Urville since 1989 [ David et al , 2010], there remain insufficient observations (in space and time) to confirm or disprove the proposed trends in their abundance or depth [ Lachlan‐Cope et al , 2009; David et al , 2010].…”

Section: Discussionmentioning

confidence: 99%

Half‐century air temperature change above Antarctica: Observed trends and spatial reconstructions

Screen

Simmonds

2012

J. Geophys. Res.

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[1] This study provides a comprehensive analysis of observed 50-year (1961-2010) seasonal air temperature trends from radiosonde ascents above Antarctica. Comparisons between multiple radiosonde data sets (homogenized in different ways) at each of eight Antarctic stations reveals substantial differences in the upper-air temperature trend magnitudes and their statistical significance between data sets. However, when considering the average of these data sets at each station, or averaging across all stations, a robust vertical profile of half-century temperature change emerges, characterized by mid-tropospheric warming and stratospheric cooling. Statistically significant Multistation-mean 500 hPa warming (0.1 to 0.2 C decade À1 ) is found in all seasons, whereas the lower stratospheric cooling has been manifest primarily in austral spring and summer, but with larger magnitudes (À1.0 to À2.0 C decade À1 ). We undertake the first spatial reconstructions of pan-Antarctic upper-air temperature trends. They strongly suggest that both the year-round mid-tropospheric warming and spring and summer lower stratospheric cooling have occurred above the entire continent, although their magnitudes and significance vary regionally. The reconstructed 500 hPa warming trends in winter and spring are largest over West Antarctica, the Ross Ice shelf, Victoria Land and Oates Land, and show close resemblance to those found in previously published surface temperature trend reconstructions, suggesting coupling between the surface and trends aloft. We speculate that the winter and spring mid-tropospheric warming may, in part, be driven by tropical ocean warming, analogous to proposed mechanisms for the co-located surface warming. The spring and summer lower stratospheric cooling is entirely consistent with the temperature response to ozone depletion.Citation: Screen, J. A., and I. Simmonds (2012), Half-century air temperature change above Antarctica: Observed trends and spatial reconstructions,

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Section: Discussionmentioning

confidence: 99%

Half‐century air temperature change above Antarctica: Observed trends and spatial reconstructions

Screen

Simmonds

2012

J. Geophys. Res.

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“…Long-term observations of PSCs have been performed at McMurdo (Adriani et al, 1992(Adriani et al, , 1995(Adriani et al, , 2004Di Liberto et al, 2014) from 1989 until 2010, and at Dumont d'Urville (Santacesaria et al, 2001;David et al, 1998David et al, , 2010 from 1990 until now, both with polarization-sensitive lidars. Recently the McMurdo lidar has been transferred to Dome C and has been operating there since 2014 (Snels et al, 2018).…”

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confidence: 99%

Comparison of Antarctic polar stratospheric cloud observations by ground-based and space-borne lidar and relevance for chemistry–climate models

et al. 2019

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Abstract. A comparison of polar stratospheric cloud (PSC) occurrence from 2006 to 2010 is presented, as observed from the ground-based lidar station at McMurdo (Antarctica) and by the satellite-borne CALIOP lidar (Cloud-Aerosol Lidar with Orthogonal Polarization) measuring over McMurdo. McMurdo (Antarctica) is one of the primary lidar stations for aerosol measurements of the NDACC (Network for Detection of Atmospheric Climate Change). The ground-based observations have been classified with an algorithm derived from the recent v2 detection and classification scheme, used to classify PSCs observed by CALIOP. A statistical approach has been used to compare ground-based and satellite-based observations, since point-to-point comparison is often troublesome due to the intrinsic differences in the observation geometries and the imperfect overlap of the observed areas. A comparison of space-borne lidar observations and a selection of simulations obtained from chemistry–climate models (CCMs) has been made by using a series of quantitative diagnostics based on the statistical occurrence of different PSC types. The distribution of PSCs over Antarctica, calculated by several CCMVal-2 and CCMI chemistry–climate models has been compared with the PSC coverage observed by the satellite-borne CALIOP lidar. The use of several diagnostic tools, including the temperature dependence of the PSC occurrences, evidences the merits and flaws of the different models. The diagnostic methods have been defined to overcome (at least partially) the possible differences due to the resolution of the models and to identify differences due to microphysics (e.g., the dependence of PSC occurrence on T−TNAT). A significant temperature bias of most models has been observed, as well as a limited ability to reproduce the longitudinal variations in PSC occurrences observed by CALIOP. In particular, a strong temperature bias has been observed in CCMVal-2 models with a strong impact on PSC formation. The WACCM-CCMI (Whole Atmosphere Community Climate Model – Chemistry-Climate Model Initiative) model compares rather well with the CALIOP observations, although a temperature bias is still present.

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“…Since the optical signature of volcanic aerosol layers on lidar profiles is rather similar to the weak signal of optically small PSC, applying this method to the detection of volcanic layer appears straightforward (i.e. David et al, 1998 andDavid et al, 2010). In the same way, the detection of other clouds (cirrus or noctulescent clouds Von Cossart et al, 1996or Dubietis et al, 2010 should also be possible with this approach.…”

Section: Discussionmentioning

confidence: 99%

“…One of the most sensitive instrument to PSC layers is the lidar (LIght Detection And Ranging). Note however that, although there are several long lidar time series available, homogeneous times series of lidar-based PSCs detections remain scarce which is why there is a need for systematic, reliable and simple methods to extract PSC signals from lidar profiles time series (David et al, 2010). or WMO, 1999). Lidar measurements consist of very short pulses of focused light, illuminating the overhead atmospheric column, with a relatively small divergence.…”

Section: Introductionmentioning

confidence: 99%

Detection of particle layers in backscatter profiles: application to Antarctic lidar measurements

et al. 2012

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A detection method is proposed and studied to infer the presence of hidden signals in a statistical way. It is applied here to the detection of Polar Stratospheric Cloud (PSC) layers in lidar backscatter profiles measured over the Dumont D'Urville station (Antarctica). PSCs appear as layers with enhanced variance in non stationary, heteroscedastic signal profiles, between two unknown altitudes to be estimated. The method is based on a three step algorithm. The first step is the stationarization of the signal, the second performs the maximum likelihoods estimation of the signal (PSC altitude range and variance inside and outside the PSC layer). The last step uses a Fisher-Snédécor test to decide whether the detection of PSC layer is statistically significant. Performances and robustness of the method are tested on simulated data with given statistical properties. Bias and detection limit are estimated. The method is then applied to lidar backscatter profiles measured in 2008. No PSC are detected during seasons when PSCs are not expected to form. As expected, PSC layers are detected during the austral winter and early spring. The effect of time averaging of the profiles is investigated. The best compromise for detection of PSC layers in lidar backscatter profiles acquired at Dumont D'Urville is a time averaging window of 1 h typically

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Radiosonde stratospheric temperatures at Dumont d'Urville (Antarctica): trends and link with polar stratospheric clouds

Cited by 15 publications

References 62 publications

Half‐century air temperature change above Antarctica: Observed trends and spatial reconstructions

Half‐century air temperature change above Antarctica: Observed trends and spatial reconstructions

Comparison of Antarctic polar stratospheric cloud observations by ground-based and space-borne lidar and relevance for chemistry–climate models

Detection of particle layers in backscatter profiles: application to Antarctic lidar measurements

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