Time filter

Source Type

Legras B.,CNRS Dynamic Meteorology Laboratory | Mestre O.,National School of Meteorological Studies | Bard E.,College de France | Yiou P.,CEA Saclay Nuclear Research Center
Climate of the Past | Year: 2010

A key issue of climate change is to identify the forcings and their relative contributions. The solar-climate relationship is currently the matter of a fierce debate. We address here the need for high quality observations and an adequate statistical approach. A recent work by Le Mouël et al. (2010) and its companion paper by Kossobokov et al. (2010) show spectacular correlations between solar activity and temperature series from three European weather stations over the last two centuries. We question both the data and the method used in these works. We stress (1) that correlation with solar forcing alone is meaningless unless other forcings are properly accounted for and that sunspot counting is a poor indicator of solar irradiance, (2) that long temperature series require homogenization to remove historical artefacts that affect long term variability, (3) that incorrect application of statistical tests leads to interpret as significant a signal which arises from pure random fluctuations. As a consequence, we reject the results and the conclusions of Le Mouël et al. (2010) and Kossobokov et al. (2010). We believe that our contribution bears some general interest in removing confusion from the scientific debate.© Author(s) 2010. Source

Lemaire V.E.P.,INERIS | Colette A.,INERIS | Menut L.,CNRS Dynamic Meteorology Laboratory
Atmospheric Chemistry and Physics | Year: 2016

Because of its sensitivity to unfavorable weather patterns, air pollution is sensitive to climate change so that, in the future, a climate penalty could jeopardize the expected efficiency of air pollution mitigation measures. A common method to assess the impact of climate on air quality consists in implementing chemistry-transport models forced by climate projections. However, the computing cost of such methods requires optimizing ensemble exploration techniques. By using a training data set from a deterministic projection of climate and air quality over Europe, we identified the main meteorological drivers of air quality for eight regions in Europe and developed statistical models that could be used to predict air pollutant concentrations. The evolution of the key climate variables driving either particulate or gaseous pollution allows selecting the members of the EuroCordex ensemble of regional climate projections that should be used in priority for future air quality projections (CanESM2/RCA4; CNRM-CM5-LR/RCA4 and CSIRO-Mk3-6-0/RCA4 and MPI-ESM-LR/CCLM following the EuroCordex terminology). After having tested the validity of the statistical model in predictive mode, we can provide ranges of uncertainty attributed to the spread of the regional climate projection ensemble by the end of the century (2071-2100) for the RCP8.5. In the three regions where the statistical model of the impact of climate change on PM2.5 offers satisfactory performances, we find a climate benefit (a decrease of PM2.5 concentrations under future climate) of -1.08 (±0.21), -1.03 (±0.32), -0.83 (±0.14) μg m-3, for respectively Eastern Europe, Mid-Europe and Northern Italy. In the British-Irish Isles, Scandinavia, France, the Iberian Peninsula and the Mediterranean, the statistical model is not considered skillful enough to draw any conclusion for PM2.5. In Eastern Europe, France, the Iberian Peninsula, Mid-Europe and Northern Italy, the statistical model of the impact of climate change on ozone was considered satisfactory and it confirms the climate penalty bearing upon ozone of 10.51 (±3.06), 11.70 (±3.63), 11.53 (±1.55), 9.86 (±4.41), 4.82 (±1.79) μg m-3, respectively. In the British-Irish Isles, Scandinavia and the Mediterranean, the skill of the statistical model was not considered robust enough to draw any conclusion for ozone pollution. © Author(s) 2016. Source

Angot G.,University of Versailles | Keckhut P.,University of Versailles | Hauchecorne A.,University of Versailles | Claud C.,CNRS Dynamic Meteorology Laboratory
Journal of Geophysical Research: Atmospheres | Year: 2012

This study describes a method to calculate long-term temperature trends, as an alternative to the ones based on monthly mean temperatures, which are highly impacted by the high winter variability partially due to wave-mean flow interactions like Sudden Stratospheric Warmings (SSW). This method avoids the strong influence of SSWs and provides "background" temperature trend estimates which are in better agreement with expected direct radiative effects. The data set used results from lidar measurements - performed above southern France continuously since late 1978 - combined with radiosonde profiles. With this new methodology, the long-term trends during winter at 40 km shows a larger cooling per decade (-2 0.4 K) than when the mean temperature is used (-0.4 0.4 K). The background temperature trend is closer to the summer trend estimates which are similar whatever the temperature proxy used, due to the absence of SSWs (-2.9 0.3 K per decade with the mean-based method and -3.4 0.3 K per decade with the background-based calculation). Based on this background temperature, composite evolutions of winter anomalies for both vortex-displacement and vortex-splitting major SSWs have been displayed: in both cases the largest warming occurs at the time of the SSW in the upper stratosphere, with mean amplitudes of more than 10 K. A warm signal in the upper mesosphere could suggest a potential precursory role of gravity waves. Displacement-type events present an 18-day periodicity, which is a clear sign of the wave number one Rossby wave. Colder tropospheric temperatures are noticed before and during the SSW, and warmer ones after the event, with a stronger signal for split-type events. © 2012. American Geophysical Union. All Rights Reserved. Source

Mailler S.,CNRS Dynamic Meteorology Laboratory | Lott F.,Ecole Nationale des Ponts et Chaussees
Monthly Weather Review | Year: 2015

The dynamical relations between equatorial atmospheric angular momentum (EAAM), equatorialmountain torques, and cold surges are analyzed in a general circulation model (GCM). First, the authors show that the global EAAM budget is well closed in the GCM, much better than in the NCEP-NCAR reanalysis. They then confirm that the equatorial torques due to the Tibetan Plateau, the Rockies, and the Andes are well related to the cold surges developing over East Asia, North America, and South America, respectively. For all these mountains, a peak in the equatorial mountain torque components precedes by few days the development of a cold surge, confirming that the cold surge's "preconditioning" is dynamically driven by large-scale mountains. The authors also analyze the contribution of the subgrid-scale orography (SSO) parameterizations and find that they contribute substantially to the torques. In experiments where these parameterizations are almost entirely reduced over a given massif, the authors find that the explicit pressure torques produced by that massif largely compensate the reduction in the parameterized torques. On the one hand, this proves that the explicitly resolved equatorial mountain torques are effective dynamical drivers of the flow dynamics, since they are enhanced when a parameterized torque is reduced. On the other hand, this shows that the cold surges can be captured in GCMs, provided that the synoptic conditions prior to their onset are realistic. The compensation between torques is nevertheless not complete and some weakening of the cold surges is found when the parameterized mountain torques are reduced. © 2015 American Meteorological Society. Source

Jouve L.,French National Center for Scientific Research | Brun A.S.,University Paris Diderot | Talagrand O.,CNRS Dynamic Meteorology Laboratory
Astrophysical Journal | Year: 2011

We have developed a variational data assimilation technique for the Sun using a toy αΩ dynamo model. The purpose of this work is to apply modern data assimilation techniques to solar data using a physically based model. This work represents the first step toward a complete variational model of solar magnetism. We derive the adjoint αΩ dynamo code and use a minimization procedure to invert the spatial dependence of key physical ingredients of the model. We find that the variational technique is very powerful and leads to encouraging results that will be applied to a more realistic model of the solar dynamo. © 2011. The American Astronomical Society. All rights reserved.. Source

Discover hidden collaborations