Abstract. The Tropical Ocean-Global Atmosphere (TOGA) program sought to determine the predictability of the coupled ocean-atmosphere system. The World Climate Research Programme's (WCRP) Global Ocean-Atmosphere-Land System (GOALS) program seeks to explore predictability of the global climate system through investigation of the major planetary heat sources and sinks, and interactions between them. The Asian-Australian monsoon system, which undergoes aperiodic and high amplitude variations on intraseasonal, annual, biennial and interannual timescales is a major focus of GOALS. Empirical seasonal forecasts of the monsoon have been made with moderate success for over 100 years. More recent modeling efforts have not been successful. Even simulation of the mean structure of the Asian monsoon has proven elusive and the observed ENSO-monsoon relationships has been difficult to replicate. Divergence in simulation skill occurs between integrations by different models or between members of ensembles of the same model. This degree of spread is surprising given the relative success of empirical forecast techniques. Two possible explanations are presented: difficulty in modeling the monsoon regions and nonlinear error growth due to regional hydrodynamical instabilities. It is argued that the reconciliation of these explanations is imperative for prediction of the monsoon to be improved. To this end, a thorough description of observed monsoon variability and the physical processes that are thought to be important is presented. Prospects of improving prediction and some strategies that may help achieve improvement are discussed. IntroductionThe annual cycle of the monsoon systems has led the inhabitants of monsoon regions to divide their lives, customs, and economies into two distinct phases: the "wet" and the "dry." The wet phase refers to the rainy season during which warm, moist, and very disturbed winds blow inland from the warm tropical oceans. The dry phase refers to the other half of the year when winds bring cool and dry air from the winter continents. This distinct variation of the annual cycle occurs over Asia, Australia, west Africa, and in the Americas. In some locations (e.g., in the Asia-Australia sector) the dry winter air flows across the equa- Agricultural practices have traditionally been tied strictly to the annual cycle. Whereas the regularity of the warm and moist and cool and dry phases of the monsoon would seem to be ideal for agricultural societies, their very regularity makes agriculture susceptible to small changes in the annual cycle. Small variations in the timing and quantity of rainfall have the potential for significant societal consequences. A weak monsoon year (i.e., significantly less total rainfall than normal) generally corresponds to low crop yields. A strong monsoon usually produces abundant crops, although too much rainfall may produce devastating floods. In addition to the importance of the strength of the overall monsoon in a particular year, forecasting the onset of the subseasonal vari...

SUMMARYThe European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) is described. In addition to an unperturbed (control) forecast, each ensemble comprises 32 10-day forecasts starting from initial conditions in which dynamically defined perturbations have been added to the operational analysis. The perturbations are constructed from singular vectors of a time-evolution operator linearized around the short-rangeforecast trajectory. These singular vectors approximately determine the most unstable phase-space directions in the early part of the forecast period, and are estimated using a forward and adjoint linear version of the ECMWF numerical weather-prediction model. An appropriate norm is chosen, and relationships between the structures of these singular vectors at initial time and patterns showing the sensitivity of short-range forecast error to changes in the analysis are discussed. A methodology to perform a phase-space rotation of the singular vectors is described, which generates hemispheric-wide perturbations and renormalizes them according to analysis-error estimates from the data-assimilation system.The validation of the ensembles is given firstly in terms of scatter diagrams and contingency tables of ensemble spread and control-forecast skill. The contingency tables are compared with those from a perfect-model ensemble system; no significant differences are found in some cases. Brier scores for the probability of European flow clusters are presented, which indicate predictive skill up to forecast-day 8 with respect to climatological probabilities. The dependence of these scores on flow-dependent model errors is also discussed. Finally, ensemble-member skillscore distributions are presented, which confirm the overall satisfactory performance of the EPS, particularly in summer and autumn 1993. In winter, cases of poor performance over Europe were associated with the Occurrence of a split westerly flow with a blocking high and/or a cut-off low in the verifying analysis.' h o cases are studied in detail, one having large ensemble dispersion, the other corresponding to a more predictable situation. The case studies are used to illustrate the range of ensemble products routinely disseminated to ECMWF Member States. These products include clusters of flow types, and probability fields of weather elements.

A stochastic representation of random error associated with parametrized physical processes (‘stochastic physics’) is described, and its impact in the European Centre for Medium‐Range Weather Forecasts Ensemble Prediction System (ECMWF EPS) is discussed. Model random errors associated with physical parametrizations are simulated by multiplying the total parametrized tendencies by a random number sampled from a uniform distribution between 0.5 and 1.5. A number of diagnostics are described and a choice of parameters is made. It is shown how the scheme increases the spread of the ensemble, and improves the skill of the probabilistic prediction of weather parameters such as precipitation. A choice of stochastic parameters is made for operational implementation. the scheme was implemented successfully in the operational ECMWF EPS on 21 October 1998.

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S u MMARYConventional parametrization schemes in weather and climate prediction models describe the effects of subgrid-scale processes by deterministic bulk formulae which depend on local resolved-scale variables and a number of adjustable parameters. Despite the unquestionable success of such models for weather and climate prediction, it is impossible to justify the use of such formulae from first principles. Using low-order dynamicalsystems models, and elementary results from dynamical-systems and turbulence theory, it is shown that even if unresolved scales only describe a small fraction of the total variance of the system, neglecting their variability can, in some circumstances, lead to gross errors in the climatology of the dominant scales. It is suggested that some of the remaining errors in weather and climate prediction models may have their origin in the neglect of subgrid-scale variability, and that such variability should be parametrized by non-local dynamically based stochastic parametrization schemes. Results from existing schemes are described, and mechanisms which might account for the impact of random parametrization error on planetary-scale motions are discussed. Proposals for the development of non-local stochastic-dynamic parametrization schemes are outlined, based on potential-vorticity diagnosis, singular-vector analysis and a simple stochastic cellular automaton model.