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L. R. Ji and S. Tibaldi

Abstract

The North Atlantic blocking case of 17–30 December 1978 is briefly described synoptically and the results from several 10-day integrations of the ECMWF global numerical model are investigated to assess the role played in both onset and maintenance of the block by the global orography, the Rocky Mountains and the Tibetan Plateau separately; and by the surface exchange (land-sea contrast) and the model's physical parameterizations. While the influence of land-sea contrast is confined to partially controlling the initiation of the process, the dominating effects of global orography (and of the Rocky Mountains in particular) in conditioning both onset and maintenance of the block are confirmed once more for this case. Despite the limitations of a single case study, some efforts are made to bridge the gap between oversimplified numerical models and observational diagnostic studies. The relative success of the control run in simulating onset and early maintenance of the blocking occurrence lends some confidence to the process of exporting the results from the model to the real atmosphere.

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T. N. Palmer and S. Tibaldi

Abstract

Using 10-day forecast 500 mb height data from the last 7 yr, the potential to predict the skill of numerical weather forecasts is discussed. Four possible predictor sets are described. The first, giving the consistency between adjacent forecasts, is apparently more skillful if the anomaly correlation coefficient, rather than RMS difference, is used as measure of forecast spread and forecast skill. It is concluded that much of this enhanced skill results from the dependence of the anomaly correlation coefficient on the magnitude of the forecast anomaly. It is noted that the spread between “today's” and “yesterday's” forecast is a more reliable estimate of the skill of yesterday's forecast than today's, and the implications of this on lagged-average ensemble forecasts are discussed. The impact of temporal filtering of the data in spread/skill correlations are also described.

The second predictor set is derived from a regression analysis between RMS error skill scores and EOF coefficients of the forecast and/or initial 500 mb heights. The predictors themselves are large-scale anomaly patterns, some of which, towards the end of the forecast period, resemble low-frequency teleconnection patterns of the atmosphere. It is shown that forecast EOF coefficients are more skilful predictors than EOF coefficients of the initial conditions, and that when both sets of coefficients are used in the regression there is a danger of overfitting. The dependence of these patterns on the truncation of the EOF expansion and of temporal filtering is discussed. In particular, it is shown that when a severe EOF truncation is made, some of the forecast flow anomaly patterns become less geographically localized, indicating poorer predictive skill.

The third predictor is defined as the RMS skill of the day-1 forecast. Both upstream and local correlations are studied. It is shown that with day-1 forecast error leading day-3 RMS error by up to 3 days, there appears to be a propagating signal, in addition to a quasi-stationary one. In general, the latter appears to be dominant. The fourth predictor is defined as the RMS difference between the forecast 500 mb height, and the initial 500 mb height. Use of this latter predictor was motivated by diagnostic studies showing relationships between interannual variability of forecast scores and interannual variability of persistence errors. These studies are partly described here. It is shown that the use of forecast persistence as a predictor gives partial skill, at least towards the end of the forecast period.

The skill of the predictors are tested, and the regression coefficients derived, on data from six winters, for both regional and hemispheric skill scores. As an independent test, the predictors are also applied separately to the seventh winter period 1986/87. It is concluded that some aspects of the low-frequency component of forecast skill variability can be satisfactorily predicted, though significant high frequency variability remains unpredicted.

In discussing the physical mechanisms that underlie the use of these predictors, three important components of forecast skill variability are discussed: the quality of the initial analysis, the intrinsic instability of the flow, and the role of model systematic errors.

It is shown that results from the EOF predictor for the European region towards the end of the forecast period are strongly influenced by model systematic error. On the other hand, over the Pacific/North American region, growth of errors on flows with varying barotropic stability characteristics are an important component of medium-range forecast variability. This is discussed using a barotropic model with basic states defined from the results of the regression analyses for various regions. At shorter range it is suggested that growth of errors by baroclinic processes is probably dominant.

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S. Tibaldi, A. Buzzi, and P. Malguzzi

Abstract

Cyclogenesis induced by an isolated mountain chain in a baroclinic flow is simulated in a channel version of the HIBU (Mesinger-Janjić) primitive equation model. The main features characteristic of cyclogenesis in the Ice of the Alps am reproduced when the mountain interacts with a finite-amplitude baroclinic wave. The distribution of derived quantities like vertical velocity and potential vorticity compare well with those analyzed in case studies.

The intercomparison of the evolution of the various fields and the analysis of energetics in experiments with and without mountains highlights the nature of the physical processes involved.

A small-scale baroclinic process is responsible for an amplification of the initial disturbance produced by the mountain when the cold front, associated with the large-scale wave, moves over it. This process, though enhancing the local energy conversion, reduces the efficiency of the baroclinic conversion over the whole domain.

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S. Tibaldi, E. Tosi, A. Navarra, and L. Pedulli

Abstract

Seven years of analyses and forecasts from the operational archives of the European Centre for Medium-Range Weather Forecasts have been analyzed to assess the performance of the model in forecasting blocking events. This paper extends the previous work by Tibaldi and Molteni to the other seasons of the year and to the Southern Hemisphere. The dataset covers the period from 1 December 1980 to 30 November 1987 and consists of 5OO-hPa geopotential height daily analyses and the 120 corresponding forecasts verifying on the same day, a dataset commonly known as the “Lorenz files.” Local blocking and sector blocking have been defined as in Tibaldi and Molteni, using a modified version of the Lejenas and Økland objective blocking index.

The results broadly confirm the conclusions previously reached for the winter season alone, extending their validity to the rest of the year and, mutatis mutandis, to the other hemisphere. The main observational difference between blocking in the two hemispheres is in the number of preferred locations: Atlantic and Pacific blocking in the Northern Hemisphere, and only one broad region in the Southern Hemisphere, around 180° longitude. Forecasting the onset of blocking events is in general a task that the model finds difficult, whereas if the integration starts from an already blocked initial condition, the performance of the model is usually better. The poor observational data coverage in the Southern Hemisphere is likely to produce initial conditions affected by larger errors, making the correct forecast of the onset of a blocking event an even more difficult task than it is in the Northern Hemisphere. In the Northern Hemisphere, although the dynamical characteristics of Atlantic and Pacific blocks are inferred from the respective model errors to be different, their detrimental effects on forecast performance are similar in the two cases.

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T.N. Palmer, C. Brankovic, F. Molteni, S. Tibaldi, L. Ferranti, A. Hollingsworth, U. Cubasch, and E. Klinker

Results from a 3 1/2-yr experimental program of extended-range integrations of the European Centre for Medium-Range Weather Forecasts (ECMWF) numerical weather prediction model are summarized. The topics discussed include

Our results are broadly consistent with those from other major centers evaluating the feasibility of dynamical extended-range prediction. We believe that operational extended-range forecasting using the ECMWF model may be viable to day 20—and possibly beyond—following further research on techniques for Monte Carlo forecasting, and when model systematic error in the tropics has been reduced significantly.

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