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M. Déqué and J. Servain

Abstract

Connections between departures from the seasonal cycle of sea surface temperature (SST) in the tropical Atlantic and 50 kPa height over the midlatitude North Atlantic are studied for the period 1964–86. The teleconnections in both time and space are studied using canonical correlation analyses performed on the observed fields filtered by their first empirical orthogonal functions. By shifting the atmospheric time series relative to the oceanic one, the method yields estimates of the best correlation patterns. Two modes of teleconnection emerge, and both involve the midlatitude atmosphere leading the tropical ocean. The first linkage, being almost in phase, seems to be controlled by a direct mechanism. The second one, with a two season time lag, involves the global ocean-atmosphere circulation and is weakly correlated with a Southern Oscillation index. Both phenomena have strong seasonality. Like the midlatitude oceans, therefore, the tropical Atlantic seems to be led by the atmosphere and there is no evidence, unlike the tropical Pacific, of surface temperature anomalies inducing a midlatitude atmospheric response.

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M. Déqué and J. F. Royer

Abstract

The global T42 version of the French numerical weather prediction model has been used to produce monthly mean forecasts. A study based on 21 cases of 44-day forecasts (for winter months from 1983 to 1990) is presented. Nine forecasts in this database may be directly compared with ECMWF 30-day forecasts. Some skill of 15-day running means exist for both models beyond day 15, and it is better with the ECMWF model. Beyond day 30, the predictive skill does not completely vanish: after systematic error correction, the 50-kPa height anomaly correlation over the Northern Hemisphere is 0.27 for day 15–44 avenges; 3 out of 21 values are negative, and 4 values exceed 0.50. The amplitude of the forecast anomaly explains a small part of this case-to-case skill variability. Similar results are found for the other atmospheric field. However, such a marginal skill could be useful only in association with other predictors in a statistical postprocessing.

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P. Bernardet, A. Butet, M. Déqué, M. Ghil, and R. L. Pfeffer

Abstract

Experiments were performed in a rotating, differentially heated annulus, with and without bottom topography of azimuthal wavenumber 2. Both water and a viscous glycerol-water mixture were used as a working fluid. In one series of experiments, measurements of azimuthal velocity u were carded out by Doppler-laser velocimetry at midradius and at ⅓ and ⅔ depth. In the other, temperature measurements were made by a set of thermistors at three different heights and three different radii. Results were analyzed by Fourier transformation, separately in space and in time, and in terms of complex empirical orthogonal functions (CEOFs).

In the experiments with topography, a standing wave 2 is generated, with larger amplitude at the upper level and a tilted wave structure. The two leading CEOFs contain a very large fraction of the variance, and give an excellent picture of the spatial modulation of the traveling baroclinic waves. The dominant baroclinic wave has azimuthal wavenumber 4, 5 or 6, according to the nondimensional parameters of the given experiment, and pronounced sidebands due to the topography. The modulation of this wave is such that its largest amplitude occurs at the lower level upstream of the two topographic ridges. At the upper level, the modulation is weaker, with the maximum wave amplitude located downstream of the ridges. Partial decoupling of the two wave trains attached to the two ridges is evident in one experiment.

Low-frequency vacillation of the entire flow pattern is apparent; this vacillation has a period of about 50 annulus rotations in the viscous mixture. The possible relevance of this topographically induced vacillation to the extratropical 30–60 day oscillation is discussed.

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J-F. Mahfouf, A. O. Manzi, J. Noilhan, H. Giordani, and M. DéQué

Abstract

This paper describes recent developments in climate modeling at Météo-France related to land surface processes. The implementation of a simple land surface parameterization, Interactions between Soil Biosphere Atmosphere (ISBA), has gained from previous validations and calibrations at local scale against field datasets and from aggregation procedures devised to define effective land surface properties. Specific improvements for climate purposes are introduced: spatial variability of convective rainfall in canopy drainage estimation and subsurface gravitational percolation. The methodology used to derive climatological maps of land surface parameters at the grid-scale resolution of the model from existing database for soil and vegetation types at global scale is described. A 3-yr integration for the present day climate with a T42L30 version of the climate model has been performed. Results obtained compare favorably with available observed climatologies related to the various components of the continental surface energy and water budgets. Differences are due mostly to a poor simulation of the precipitation field. However, some differences suggest specific improvements in the surface scheme concerning representation of the bare soil albedo, the surface runoff, and the soil moisture initialization. As a first step prior to tropical deforestation experiments presented in Part II, regional analyses over the Amazon forest indicate that the modeled evaporation and net radiation are in good agreement with data collected during the Amazon Region Micrometeorological Experiment campaign.

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K. D. Williams, A. Bodas-Salcedo, M. Déqué, S. Fermepin, B. Medeiros, M. Watanabe, C. Jakob, S. A. Klein, C. A. Senior, and D. L. Williamson

Abstract

The Transpose-Atmospheric Model Intercomparison Project (AMIP) is an international model intercomparison project in which climate models are run in “weather forecast mode.” The Transpose-AMIP II experiment is run alongside phase 5 of the Coupled Model Intercomparison Project (CMIP5) and allows processes operating in climate models to be evaluated, and the origin of climatological biases to be explored, by examining the evolution of the model from a state in which the large-scale dynamics, temperature, and humidity structures are constrained through use of common analyses.

The Transpose-AMIP II experimental design is presented. The project requests participants to submit a comprehensive set of diagnostics to enable detailed investigation of the models to be performed. An example of the type of analysis that may be undertaken using these diagnostics is illustrated through a study of the development of cloud biases over the Southern Ocean, a region that is problematic for many models. Several models share a climatological bias for too little reflected shortwave radiation from cloud across the region. This is found to mainly occur behind cold fronts and/or on the leading side of transient ridges and to be associated with more stable lower-tropospheric profiles. Investigation of a case study that is typical of the bias and associated meteorological conditions reveals the models to typically simulate cloud that is too optically and physically thin with an inversion that is too low. The evolution of the models within the first few hours suggests that these conditions are particularly sensitive and a positive feedback can develop between the thinning of the cloud layer and boundary layer structure.

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K. R. Sperber, C. Brankovic, M. Déqué, C. S. Frederiksen, R. Graham, A. Kitoh, C. Kobayashi, T. Palmer, K. Puri, W. Tennant, and E. Volodin

Abstract

Ensembles of hindcasts from seven models are analyzed to evaluate dynamical seasonal predictability of 850-hPa wind and rainfall for the Asian summer monsoon (ASM) during 1987, 1988, and 1993. These integrations were performed using observed sea surface temperatures and from observed initial conditions. The experiments were designed by the Climate Variability and Predictability, Working Group on Seasonal to Interannual Prediction as part of the Seasonal Prediction Model Intercomparison Project. Integrations from the European Union Prediction of Climate Variations on Seasonal to Interannual Timescales experiment are also evaluated.

The National Centers for Environmental Prediction–National Center for Atmospheric Research and European Centre for Medium-Range Weather Forecasts reanalyses and observed pentad rainfall form the baseline against which the hindcasts are judged. Pattern correlations and root-mean-square differences indicate errors in the simulation of the time mean low-level flow and the rainfall exceed observational uncertainty. Most models simulate the subseasonal EOFs that are associated with the dominant variations of the 850-hPa flow during the ASM, but not with the fidelity exhibited by the reanalyses as determined using pattern correlations. Pattern correlations indicate that the first EOF, associated with the tropical convergence zone being located over the continental landmass, is best simulated. The higher-order EOFs are less well simulated, and errors in the magnitude and location of their associated precipitation anomalies compromise dynamical seasonal predictability and are related to errors of the mean state. In most instances the models fail to properly project the subseasonal EOFs/principal components onto the interannual variability with the result that hindcasts of the 850-hPa flow and rainfall are poor. In cases where the observed EOFs are known to be related to the boundary forcing, the failure of the models to properly project the EOFs onto the interannual variability indicates that the models are not setting up observed teleconnection patterns.

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T. N. Palmer, A. Alessandri, U. Andersen, P. Cantelaube, M. Davey, P. Délécluse, M. Déqué, E. Díez, F. J. Doblas-Reyes, H. Feddersen, R. Graham, S. Gualdi, J.-F. Guérémy, R. Hagedorn, M. Hoshen, N. Keenlyside, M. Latif, A. Lazar, E. Maisonnave, V. Marletto, A. P. Morse, B. Orfila, P. Rogel, J.-M. Terres, and M. C. Thomson

A multi-model ensemble-based system for seasonal-to-interannual prediction has been developed in a joint European project known as DEMETER (Development of a European Multimodel Ensemble Prediction System for Seasonal to Interannual Prediction). The DEMETER system comprises seven global atmosphere–ocean coupled models, each running from an ensemble of initial conditions. Comprehensive hindcast evaluation demonstrates the enhanced reliability and skill of the multimodel ensemble over a more conventional single-model ensemble approach. In addition, innovative examples of the application of seasonal ensemble forecasts in malaria and crop yield prediction are discussed. The strategy followed in DEMETER deals with important problems such as communication across disciplines, downscaling of climate simulations, and use of probabilistic forecast information in the applications sector, illustrating the economic value of seasonal-to-interannual prediction for society as a whole.

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S. Gualdi, S. Somot, L. Li, V. Artale, M. Adani, A. Bellucci, A. Braun, S. Calmanti, A. Carillo, A. Dell'Aquila, M. Déqué, C. Dubois, A. Elizalde, A. Harzallah, D. Jacob, B. L'Hévéder, W. May, P. Oddo, P. Ruti, A. Sanna, G. Sannino, E. Scoccimarro, F. Sevault, and A. Navarra

In this article, the authors describe an innovative multimodel system developed within the Climate Change and Impact Research: The Mediterranean Environment (CIRCE) European Union (EU) Sixth Framework Programme (FP6) project and used to produce simulations of the Mediterranean Sea regional climate. The models include high-resolution Mediterranean Sea components, which allow assessment of the role of the basin and in particular of the air–sea feedbacks in the climate of the region.

The models have been integrated from 1951 to 2050, using observed radiative forcings during the first half of the simulation period and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario during the second half.

The projections show a substantial warming (about 1.5°–2°C) and a significant decrease of precipitation (about 5%) in the region for the scenario period. However, locally the changes might be even larger. In the same period, the projected surface net heat loss decreases, leading to a weaker cooling of the Mediterranean Sea by the atmosphere, whereas the water budget appears to increase, leading the basin to lose more water through its surface than in the past. Overall, these results are consistent with the findings of previous scenario simulations, such as the Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects (PRUDENCE), Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES), and phase 3 of the Coupled Model Intercomparison Project (CMIP3). The agreement suggests that these findings are robust to substantial changes in the configuration of the models used to make the simulations.

Finally, the models produce a 2021–50 mean steric sea level rise that ranges between +7 and +12 cm, with respect to the period of reference.

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Adrian M. Tompkins, María Inés Ortiz De Zárate, Ramiro I. Saurral, Carolina Vera, Celeste Saulo, William J. Merryfield, Michael Sigmond, Woo-Sung Lee, Johanna Baehr, Alain Braun, Amy Butler, Michel Déqué, Francisco J. Doblas-Reyes, Margaret Gordon, Adam A. Scaife, Yukiko Imada, Masayoshi Ishii, Tomoaki Ose, Ben Kirtman, Arun Kumar, Wolfgang A. Müller, Anna Pirani, Tim Stockdale, Michel Rixen, and Tamaki Yasuda
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F. Vitart, C. Ardilouze, A. Bonet, A. Brookshaw, M. Chen, C. Codorean, M. Déqué, L. Ferranti, E. Fucile, M. Fuentes, H. Hendon, J. Hodgson, H.-S. Kang, A. Kumar, H. Lin, G. Liu, X. Liu, P. Malguzzi, I. Mallas, M. Manoussakis, D. Mastrangelo, C. MacLachlan, P. McLean, A. Minami, R. Mladek, T. Nakazawa, S. Najm, Y. Nie, M. Rixen, A. W. Robertson, P. Ruti, C. Sun, Y. Takaya, M. Tolstykh, F. Venuti, D. Waliser, S. Woolnough, T. Wu, D.-J. Won, H. Xiao, R. Zaripov, and L. Zhang

Abstract

Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the subseasonal to seasonal time range, the Subseasonal to Seasonal (S2S) Prediction research project has been established by the World Weather Research Programme/World Climate Research Programme. A main deliverable of this project is the establishment of an extensive database containing subseasonal (up to 60 days) forecasts, 3 weeks behind real time, and reforecasts from 11 operational centers, modeled in part on the The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database for medium-range forecasts (up to 15 days).

The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the subseasonal to seasonal time range that has been considered for a long time as a “desert of predictability.” In particular, this database will help identify common successes and shortcomings in the model simulation and prediction of sources of subseasonal to seasonal predictability. For instance, a preliminary study suggests that the S2S models significantly underestimate the amplitude of the Madden–Julian oscillation (MJO) teleconnections over the Euro-Atlantic sector. The S2S database also represents an important tool for case studies of extreme events. For instance, a multimodel combination of S2S models displays higher probability of a landfall over the islands of Vanuatu 2–3 weeks before Tropical Cyclone Pam devastated the islands in March 2015.

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