[1] A three-dimensional oceanic state is estimated for the period 1992-1997 as it results from combining large-scale ocean data sets with a general circulation model. At the cost of increased computational load, the estimation (assimilation) method is chosen specifically so that the resulting state estimate is consistent with the model equations, having no artificial sources or sinks. To bring the model into close agreement with observations, its initial temperature and salinity conditions are permitted to change, as are the time-dependent surface fluxes of momentum, heat and freshwater. Resulting changes of these ''control vectors'' are largely consistent with accepted uncertainties in the hydrographic climatology and meteorological analyses. The assimilation procedure is able to correct for many of the traditional shortcomings of the flow field by changing the surface boundary conditions. Changes in the resulting flow field are predominantly on the gyre scale and affect many features that are often poorly simulated in traditional numerical simulations, such as the strengths of the Gulf Stream and its extension, the Azores Current and the anticyclonic circulation associated with the Labrador Sea. Tests of the results and their consistency with prior error assumptions show that the constrained model has moved considerably closer to the observations imposed as constraints, but has also moved closer to independent data from the World Ocean Circulation Experiment not used in the assimilation procedure. In some regions where the comparisons remain indeterminate, not enough ocean observations are available, and it is difficult to ascribe the residuals to either the model or the observations. Although problems remain, a useful first solution to the global time-dependent ocean state estimation problem has been found. The estimates will continue to improve through the evolution of numerical models, computer power increases, more data, and more efficient estimation methods.

The dominant variability modes in the Tropics are investigated and contrasted with the anomalous situation observed during the last few years. The prime quantity analyzed is anomalous sea surface temperature (SST) in the region 30S-60N. Additionally, observed tropical surface wind stress fields were investigated. Further tropical atmospheric information was derived from a multidecadal run with an atmospheric general circulation model that was forced by the same SSTs. The tropical SST variability can be characterized by three modes: an interannual mode [the El Niño-Southern Oscillation (ENSO)], a decadal mode, and a trend or unresolved ultra-low-frequency variability. The dominant mode of SST variability is the ENSO mode. It is strongest in the eastern equatorial Pacific, but influences also the SSTs in other regions through atmospheric teleconnections, such as the Indian and North Pacific Oceans. The ENSO mode was strong during the 1980s, but it existed with very weak amplitude and short period after 1991. The second most energetic mode is characterized by considerable decadal variability. This decadal mode is connected with SST anomalies of the same sign in all three tropical oceans. The tropical Pacific signature of the decadal mode resembles closely that observed during the last few years and can be characterized by a horseshoe pattern, with strongest SST anomalies in the western equatorial Pacific, extending to the northeast and southeast into the subtropics. It is distinct from the ENSO mode, since it is not connected with any significant SST anomalies in the eastern equatorial Pacific, which is the ENSO key region. However, the impact of the decadal mode on the tropical climate resembles in many respects that of ENSO. In particular, the decadal mode is strongly linked to decadal rainfall fluctuations over northeastern Australia in the observations. It is shown that the anomalous 1990s were dominated by the decadal mode. Considerable SST variability can be attributed also to a linear trend or unresolved ultra-low-frequency variability. This trend that might be related to greenhouse warming is rather strong and positive in the Indian Ocean and western equatorial Pacific where it accounts for up to 30% of the total SST variability. Consistent with the increase of SST in the warm pool region, the trends over the tropical Pacific derived from both the observations and the model indicate a strengthening of the trade winds. This is inconsistent with the conditions observed during the 1990s. If the wind trends reflect greenhouse warming, it must be concluded that the anomalous 1990s are not caused by greenhouse warming. Finally, hybrid coupled ocean-atmosphere model experiments were conducted in order to investigate the sensistivity of ENSO to the low-frequency changes induced by the decadal mode and the trend. The results indicate that ENSO is rather sensitive to these changes in the background conditions.

The El Niño-Southern Oscillation (ENSO) phenomenon is modeled as a stochastically driven dynamical system. This was accomplished by adding to a Hybrid Coupled Model (HCM) of the tropical Pacific oceanatmosphere system a stochastic wind stress anomaly field that was derived from observations. The model exhibits irregular interannual fluctuations, whose space-time characteristics resemble those of the observed interannual climate variability in this region. To investigate the predictability of the model, the authors performed ensemble integrations with different realizations of the stochastic wind stress forcing. The ensembles were initialized at various phases of the model's ENSO cycle simulated in a 120-yr integration with a particular noise realization. The numerical experiments indicate that the ENSO predictability is severely limited by the stochastic wind stress forcing. Linear stochastic processes were fitted to the restart ensembles in a reduced state space. A predictability measure based on a comparison of the stationary and the time-dependent probability distributions of the fitted linear models reveals an ENSO predictability limit of considerably less than an average cycle length.

Climatic stresses limit plant growth and productivity. In the past decade, tree improvement programs were mainly focused on yield but it is obvious that enhanced stress resistance is also required. In this review we highlight important drought avoidance and tolerance mechanisms in forest trees. Genomes of economically important trees species with divergent resistance mechanisms can now be exploited to uncover the mechanistic basis of long-term drought adaptation at the whole plant level. Molecular tree physiology indicates that osmotic adjustment, antioxidative defense and increased water use efficiency are important targets for enhanced drought tolerance at the cellular and tissue level. Recent biotechnological approaches focused on overexpression of genes involved in stress sensing and signaling, such as the abscisic acid core pathway, and down-stream transcription factors. By this strategy, a suite of defense systems was recruited, generally enhancing drought and salt stress tolerance under laboratory conditions. However, field studies are still scarce. Under field conditions trees are exposed to combinations of stresses that vary in duration and magnitude. Variable stresses may overrule the positive effect achieved by engineering an individual defense pathway. To assess the usability of distinct modifications, large-scale experimental field studies in different environments are necessary. To optimize the balance between growth and defense, the use of stress-inducible promoters may be useful. Future improvement programs for drought resistance will benefit from a better understanding of the intricate networks that ameliorate molecular and ecological traits of forest trees.