Institute Pierre Simon Laplace LOCEAN
Institute Pierre Simon Laplace LOCEAN
Fontaine B.,University of Burgundy |
Garcia-Serrano J.,Complutense University of Madrid |
Roucou P.,University of Burgundy |
Rodriguez-Fonseca B.,Complutense University of Madrid |
And 6 more authors.
Climate Dynamics | Year: 2010
Using both empirical and numerical ensemble approaches this study focuses on the Mediterranean/West African relationship in northern summer. Statistical analyses utilize skin temperature, sea surface temperature, in situ and satellite rainfall, outgoing longwave radiation (OLR) observations and reanalyzed data winds and specific humidity on isobaric surfaces. Numerical investigations are based on a large set of sensitivity experiments performed on four atmospheric general circulation models (AGCM): ARPEGE-Climat3, ECHAM4, LMDZ4 and UCLA7. 3. Model outputs are compared to observations, discussed model by model and with an ensemble (multi-model) approach. As in previous studies the anomalous Mediterranean warm events are associated with specific impacts over the African monsoon region, i. e., a more intense monsoon, enhanced flux convergence and ascendances around the ITCZ, a strengthening of low level moisture advection and a more northward location of ascending motion in West Africa. The results show also new features (1) thermal variability observed in the two Mediterranean basins has unalike impacts, i. e. the western Mediterranean covaries with convection in Gulf of Guinea, while the eastern Mediterranean can be interpreted as Sahelian thermal-forcing; (2) although observations show symmetry between warming and cooling, modelling evidences only support the eastern warming influence; (3) anomalous East warm situations are associated with a more northward migration of the monsoon system accompanied by enhanced southwertely flow and weakened northeasterly climatological wind; (4) the multi-model response shows that anomalous East warm surface temperatures generate an enhancement of the overturning circulation in low and high levels, an increase in TEJ (Tropical Eeasterly Jet) and a decrease in AEJ (African Eeasterly Jet). © 2009 The Author(s).
Persechino A.,University of Southampton |
Mignot J.,Institute Pierre Simon Laplace LOCEAN |
Swingedouw D.,CEA Saclay Nuclear Research Center |
Labetoulle S.,Institute Pierre Simon Laplace LOCEAN |
And 2 more authors.
Climate Dynamics | Year: 2013
This study explores the decadal potential predictability of the Atlantic Meridional Overturning Circulation (AMOC) as represented in the IPSL-CM5A-LR model, along with the predictability of associated oceanic and atmospheric fields. Using a 1000-year control run, we analyze the prognostic potential predictability (PPP) of the AMOC through ensembles of simulations with perturbed initial conditions. Based on a measure of the ensemble spread, the modelled AMOC has an average predictive skill of 8 years, with some degree of dependence on the AMOC initial state. Diagnostic potential predictability of surface temperature and precipitation is also identified in the control run and compared to the PPP. Both approaches clearly bring out the same regions exhibiting the highest predictive skill. Generally, surface temperature has the highest skill up to 2 decades in the far North Atlantic ocean. There are also weak signals over a few oceanic areas in the tropics and subtropics. Predictability over land is restricted to the coastal areas bordering oceanic predictable regions. Potential predictability at interannual and longer timescales is largely absent for precipitation in spite of weak signals identified mainly in the Nordic Seas. Regions of weak signals show some dependence on AMOC initial state. All the identified regions are closely linked to decadal AMOC fluctuations suggesting that the potential predictability of climate arises from the mechanisms controlling these fluctuations. Evidence for dependence on AMOC initial state also suggests that studying skills from case studies may prove more useful to understand predictability mechanisms than computing average skill from numerous start dates. © 2012 Springer-Verlag.