Lolli S.,Leosphere |
Conil S.,Andra Inc |
Dabas A.,MeteoFrance |
Donovan D.,KNMI |
And 7 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2010
Eyjafjallajökull volcano eruptions of ash plumes starting on April 2010 paralyzed completely air traffic in Europe for several days. During the crisis, Leosphere collected 24/7 real time measurements of the backscatter profiles, taken by ALS polarizations lidars spread from Denmark to South of France in order to provide quick looks of the sky at regular intervals for different met agencies and for the Volcanic Ash Advisory Centres (VAAC) coordinated by UK MetOffice. Moreover, Meteo France supported by other institutions such as CNRS (Centre National de la Recherche Scientifique), CEA (Commissariat à l'Energie Atomique), CNES (Centre National d'Études Spatiales) and Leosphere performed several test flights over France and North Atlantic with an airborne Lidar. These unique data allowed detection and identification of ash plume and provided a guidance regarding the decision-making chain. The ash mass concentration and its calculation were also discussed. © 2010 Copyright SPIE - The International Society for Optical Engineering.
Compo G.P.,University of Colorado at Boulder |
Compo G.P.,National Oceanic and Atmospheric Administration |
Whitaker J.S.,National Oceanic and Atmospheric Administration |
Sardeshmukh P.D.,University of Colorado at Boulder |
And 29 more authors.
Quarterly Journal of the Royal Meteorological Society | Year: 2011
The Twentieth Century Reanalysis (20CR) project is an international effort to produce a comprehensive global atmospheric circulation dataset spanning the twentieth century, assimilating only surface pressure reports and using observed monthly sea-surface temperature and sea-ice distributions as boundary conditions. It is chiefly motivated by a need to provide an observational dataset with quantified uncertainties for validations of climate model simulations of the twentieth century on all time-scales, with emphasis on the statistics of daily weather. It uses an Ensemble Kalman Filter data assimilation method with background 'first guess' fields supplied by an ensemble of forecasts from a global numerical weather prediction model. This directly yields a global analysis every 6 hours as the most likely state of the atmosphere, and also an uncertainty estimate of that analysis. The 20CR dataset provides the first estimates of global tropospheric variability, and of the dataset's time-varying quality, from 1871 to the present at 6-hourly temporal and 2° spatial resolutions. Intercomparisons with independent radiosonde data indicate that the reanalyses are generally of high quality. The quality in the extratropical Northern Hemisphere throughout the century is similar to that of current three-day operational NWP forecasts. Intercomparisons over the second half-century of these surface-based reanalyses with other reanalyses that also make use of upper-air and satellite data are equally encouraging. It is anticipated that the 20CR dataset will be a valuable resource to the climate research community for both model validations and diagnostic studies. Some surprising results are already evident. For instance, the long-term trends of indices representing the North Atlantic Oscillation, the tropical Pacific Walker Circulation, and the Pacific-North American pattern are weak or non-existent over the full period of record. The long-term trends of zonally averaged precipitation minus evaporation also differ in character from those in climate model simulations of the twentieth century. © 2011 Royal Meteorological Society and Crown Copyright.
Jorda G.,CSIC - Mediterranean Institute for Advanced Studies |
Gomis D.,CSIC - Mediterranean Institute for Advanced Studies |
Alvarez-Fanjul E.,Puertos del Estado |
Global and Planetary Change | Year: 2012
The contribution of atmospheric pressure and wind to the XXI century sea level variability in Southern Europe is explored under different climate change scenarios. The barotropic version of the HAMSOM model is forced with the output of the atmospheric ARPEGE model run under scenarios B1, A1B and A2. Additionally, a control simulation forced by observed SST, GHGs and aerosols concentrations for the period 1950-2000 and a hindcast forced by a dynamical downscalling of ERA40 for the period 1958-2001 are also run using the same models. The hindcast results have been validated against tide gauge observations showing good agreement with correlations around 0.8 and root mean square error of 3.2. cm. A careful comparison between the control simulation and the hindcast shows a reasonably good agreement between both runs in statistical terms, which points towards the reliability of the modelling system when it is forced only by GHG and aerosols concentrations. The results for the XXI century indicate a sea level decrease that would be especially strong in winter, with trends of up to - 0.8 ± 0.1. mm/year in the central Mediterranean under the A2 scenario. Trends in summer are small but positive (~. 0.05 ± 0.04. mm/yr), then leading to an increase in the amplitude of the seasonal cycle. The interannual variability also shows some changes, the most important being a widespread standard deviation increase of up to 40%. An increase in the frequency of positive phases of the NAO explains part of the winter negative trends. Also, an increase in the NAO variability would be responsible for the projected increase of the interannual variability of the atmospheric component of sea level. Conversely, the intra-annual variability (1-12. months excluding the seasonal cycle) does not show significant changes. © 2011 Elsevier B.V.
Galmarini S.,European Commission - Joint Research Center Ispra |
Bonnardot F.,MeteoFrance |
Jones A.,UK Met Office |
Potempski S.,European Commission - Joint Research Center Ispra |
And 3 more authors.
Atmospheric Environment | Year: 2010
Several techniques have been developed over the last decade for the ensemble treatment of atmospheric dispersion model predictions. Among them two have received most of the attention, the multi-model and the ensemble prediction system (EPS) modeling. The multi-model approach relies on model simulations produced by different atmospheric dispersion models using meteorological data from potentially different weather prediction systems. The EPS-based ensemble is generated by running a single atmospheric dispersion model with the ensemble weather prediction members. In the paper we compare both approaches with the help of statistical indicators, using the simulations performed for the ETEX-1 tracer experiment. Both ensembles are also evaluated against measurement data. Among the most relevant results is that the multi-model median and the mean of EPS-based ensemble produced the best results, hence we consider a combination of multi-model and EPS-based approaches as an interesting suggestion for further research. © 2010 Elsevier Ltd.