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J. Shukla, J. Anderson, D. Baumhefner, C. Brankovic, Y. Chang, E. Kalnay, L. Marx, T. Palmer, D. Paolino, J. Ploshay, S. Schubert, D. Straus, M. Suarez, and J. Tribbia

Dynamical Seasonal Prediction (DSP) is an informally coordinated multi-institution research project to investigate the predictability of seasonal mean atmospheric circulation and rainfall. The basic idea is to test the feasibility of extending the technology of routine numerical weather prediction beyond the inherent limit of deterministic predictability of weather to produce numerical climate predictions using state-of-the-art global atmospheric models. Atmospheric general circulation models (AGCMs) either forced by predicted sea surface temperature (SST) or as part of a coupled forecast system have shown in the past that certain regions of the extratropics, in particular, the Pacific–North America (PNA) region during Northern Hemisphere winter, can be predicted with significant skill especially during years of large tropical SST anomalies. However, there is still a great deal of uncertainty about how much the details of various AGCMs impact conclusions about extratropical seasonal prediction and predictability.

DSP is designed to compare seasonal simulation and prediction results from five state-of-the-art U.S. modeling groups (NCAR, COLA, GSFC, GFDL, NCEP) in order to assess which aspects of the results are robust and which are model dependent. The initial emphasis is on the predictability of seasonal anomalies over the PNA region. This paper also includes results from the ECMWF model, and historical forecast skill over both the PNA region and the European region is presented for all six models.

It is found that with specified SST boundary conditions, all models show that the winter season mean circulation anomalies over the Pacific–North American region are highly predictable during years of large tropical sea surface temperature anomalies. The influence of large anomalous boundary conditions is so strong and so reproducible that the seasonal mean forecasts can be given with a high degree of confidence. However, the degree of reproducibility is highly variable from one model to the other, and quantities such as the PNA region signal to noise ratio are found to vary significantly between the different AGCMs. It would not be possible to make reliable estimates of predictability of the seasonal mean atmosphere circulation unless causes for such large differences among models are understood.

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E.A. D'Asaro, P. G. Black, L. R. Centurioni, Y.-T. Chang, S. S. Chen, R. C. Foster, H. C. Graber, P. Harr, V. Hormann, R.-C. Lien, I.-I. Lin, T. B. Sanford, T.-Y. Tang, and C.-C. Wu

Tropical cyclones (TCs) change the ocean by mixing deeper water into the surface layers, by the direct air–sea exchange of moisture and heat from the sea surface, and by inducing currents, surface waves, and waves internal to the ocean. In turn, the changed ocean influences the intensity of the TC, primarily through the action of surface waves and of cooler surface temperatures that modify the air–sea fluxes. The Impact of Typhoons on the Ocean in the Pacific (ITOP) program made detailed measurements of three different TCs (i.e., typhoons) and their interaction with the ocean in the western Pacific. ITOP coordinated meteorological and oceanic observations from aircraft and satellites with deployments of autonomous oceanographic instruments from the aircraft and from ships. These platforms and instruments measured typhoon intensity and structure, the underlying ocean structure, and the long-term recovery of the ocean from the storms' effects with a particular emphasis on the cooling of the ocean beneath the storm and the resulting cold wake. Initial results show how different TCs create very different wakes, whose strength and properties depend most heavily on the nondimensional storm speed. The degree to which air–sea fluxes in the TC core were reduced by ocean cooling varied greatly. A warm layer formed over and capped the cold wakes within a few days, but a residual cold subsurface layer persisted for 10–30 days.

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