Entity

Time filter

Source Type

Toulouse, France

Remy S.,CNRM GAME | Bergot T.,CNRM GAME
Monthly Weather Review | Year: 2010

Because poor visibility conditions have a considerable influence on airport traffic, a need exists for accurate and updated fog and low-cloud forecasts. Couche Brouillard Eau Liquide (COBEL)-Interactions between Soil, Biosphere, and Atmosphere (ISBA), a boundary layer 1D numerical model, has been developed for the very short-term forecast of fog and low clouds. This forecast system assimilates local observations to produce initial profiles of temperature and specific humidity. The initial conditions have a great impact on the skill of the forecast. In this work, the authors first estimated the background error statistics; they varied greatly with time, and cross correlations between temperature and humidity in the background were significant. This led to the implementation of an ensemble Kalman filter (EnKF) within COBEL-ISBA. The new assimilation system was evaluated with temperature and specific humidity scores, as well as in terms of its impact on the quality of fog forecasts. Simulated observations were used and focused on the modeling of the atmosphere before fog formation and also on the simulation of the life cycle of fog and low clouds. For both situations, the EnKF brought a significant improvement in the initial conditions and the forecasts. The forecast of the onset and burn-off times of fogs was also improved. The EnKF was also tested with real observations and gave good results. The size of the ensemble did not have much impact when simulated observations were used, thanks to an adaptive covariance inflation algorithm, but the impact was greater when real observations were used. © 2010 American Meteorological Society. Source


Dabas A.,CNRM GAME | Remy S.,Meteo - France | Bergot T.,CNRM GAME
Pure and Applied Geophysics | Year: 2012

A sodar was deployed at Roissy-Charles de Gaulle airport near Paris, France, in 2008 with the aim of improving the forecast of low visibility conditions there. During the winter of 2008-2009, an experiment was conducted that showed that the sodar can effectively detect and locate the top of fog layers which is signaled by a strong peak of acoustic reflectivity. The peak is generated by turbulence activity in the inversion layer that contrasts sharply with the low reflectivity recorded in the fog layer below. A specific version of the 1D-forecast model deployed at Roissy for low visibility conditions (COBEL-ISBA) was developed in which fogs' thicknesses are initialized by the sodar measurements rather than the information derived from the down-welling IR fluxes observed on the site. It was tested on data archived during the winters of 2008-2009 and 2009-2010 and compared to the version of the model presently operational. The results show a significant improvement-dissipation times of fogs are better predicted. © 2011 Springer Basel AG. Source


Roehrig R.,CNRM GAME | Bouniol D.,CNRM GAME | Guichard F.,CNRM GAME | Hourdin F.,LMD | Redelsperger J.C.,LPO
Journal of Climate | Year: 2013

The present assessment of the West African monsoon in the models of the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) indicates little evolution since the third phase of CMIP (CMIP3) in terms of both biases in present-day climate and climate projections. The outlook for precipitation in twenty-first-century coupled simulations exhibits opposite responses between the westernmost and eastern Sahel. The spread in the trend amplitude, however, remains large in both regions. Besides, although all models predict a spring and summer warming of the Sahel that is 10%-50% larger than the global warming, their temperature response ranges from 0 to 7 K. CMIP5 coupled models underestimate the monsoon decadal variability, but SST-imposed simulations succeed in capturing the recent partial recovery of monsoon rainfall. Coupled models still display major SST biases in the equatorial Atlantic, inducing a systematic southward shift of the monsoon. Because of these strong biases, the monsoon is further evaluated in SST-imposed simulations along the 108W-108E African Monsoon Multidisciplinary Analysis(AMMA)transect, across a range of time scales ranging from seasonal to intraseasonal and diurnal fluctuations. The comprehensive set of observational data now available allows an in-depth evaluation of the monsoon across those scales, especially through the use of high-frequency outputs provided by some CMIP5models at selected sites along the AMMA transect. Most models capture many features of the African monsoon with varying degrees of accuracy. In particular, the simulation of the top-of-atmosphere and surface energy balances, in relation with the cloud cover, and the intermittence and diurnal cycle of precipitation demand further work to achieve a reasonable realism. © 2013 American Meteorological Society. Source


Joetzjer E.,CNRM GAME | Douville H.,CNRM GAME | Delire C.,CNRM GAME | Ciais P.,Laboratory of Climate science | And 2 more authors.
Hydrology and Earth System Sciences | Year: 2013

Widely used metrics of drought are still derived solely from analyses of meteorological variables such as precipitation and temperature. While drought is generally a consequence of atmospheric anomalies, the impacts to society are more directly related to hydrologic conditions. The present study uses a standardized runoff index (SRI) as a proxy for river discharge and as a benchmark for various meteorological drought indices (scPDSI, SPI, SPEI-th, and SPEI-hg respectively). Only 12-month duration droughts are considered in order to allow a direct (no river routing) comparison between meteorological anomalies and their hydrological counterpart. The analysis is conducted over the Mississippi and Amazon river basins, which provide two contrasted test beds for evaluating drought indices at both interannual (using detrended data) and climate change (using raw data) timescales. Looking first at observations over the second half of the 20th century, the simple SPI based solely on precipitation is no less suitable than more sophisticated meteorological drought indices at detecting interannual SRI variations. Using the detrended runoff and meteorological outputs of a five-member single model ensemble of historical and 21th century climate simulations leads to the same conclusion. Looking at the 21st century projections, the response of the areal fraction in drought to global warming is shown to be strongly metric dependent and potentially overestimated by the drought indices which account for temperature variations. These results suggest that empirical meteorological drought indices should be considered with great caution in a warming climate and that more physical water balance models are needed to account for the impact of the anthropogenic radiative forcings on hydrological droughts. © 2013 Author(s). Source


Ribes A.,CNRM GAME | Azais J.-M.,Toulouse 1 University Capitole | Planton S.,CNRM GAME
Climate Dynamics | Year: 2010

This paper introduces an original method for climate change detection, called temporal optimal detection method. The method consists in searching for a smooth temporal pattern in the observations. This pattern can be either the response of the climate system to a specific forcing or to a combination of forcings. Many characteristics of this new method are different from those of the classical "optimal fingerprint" method. It allows to infer the spatial distribution of the detected signal, without providing any spatial guess pattern. The spatial properties of the internal climate variability doesn't need to be estimated either. The estimation of such quantities being very challenging at regional scale, the proposed method is particularly well-suited for such scale. The efficiency of the method is illustrated by applying it on real homogenized datasets of temperatures and precipitation over France. A multimodel detection is performed in both cases, using an ensemble of atmosphere-ocean general circulation models for estimating the temporal patterns. Regarding temperatures, new results are highlighted, especially by showing that a change is detected even after removing the uniform part of the warming. The sensitivity of the method is discussed in this case, relatively to the computation of the temporal patterns and to the choice of the model. The method also allows to detect a climate change signal in precipitation. This change impacts the spatial distribution of the precipitation more than the mean over the domain. The ability of the method to provide an estimate of the spatial distribution of the change following the prescribed temporal patterns is also illustrated. © 2009 Springer-Verlag. Source

Discover hidden collaborations