[1] Two 1-month integrations were performed with the regional Eta model coupled with the Simplified Simple Biosphere model (SSiB) over South America. The goal of the present work is to validate the model and to investigate its biases and skill on the simulations of South American climate. This is an initial step on the use of this model for climate research. The Eta model was set up with 80-km horizontal resolution and 38 vertical layers over the South American continent and part of the adjacent oceans. Analyses from the National Centers for Environmental Prediction (NCEP) were used as initial and lateral boundary conditions. The selected months were August and November 1997, which are in opposite phases of the precipitation annual cycle observed in the central part of South America. The model was integrated continuously for each 1-month period. Monthly means and daily variations of simulated precipitation and surface temperature compare well with observations. The patterns of simulated outgoing longwave radiation are also similar to the observed ones. However, a positive bias is verified in the simulations. The model shows a positive bias in latent and sensible heat surface fluxes due to an excessive shortwave incoming radiation at the surface. Comparisons with a version of the Eta model coupled with the bucket model shows that the Eta/SSiB version improves the surface temperature and increases precipitation in the interior of the continent during wet months.

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The value of global (e.g. altimetry, satellite sea-surface temperature, Argo) and regional (e.g. radars, gliders, instrumented mammals, airborne profiles and biogeochemical) observation-types for monitoring the mesoscale ocean circulation and biogeochemistry is demonstrated using a suite of global and regional prediction systems and remotely-sensed data. A range of techniques is used to demonstrate the value of different observation-types to regional systems and the benefit of high-resolution and adaptive sampling for monitoring the mesoscale circulation. The techniques include Observing System Experiments, Observing System Simulation Experiments, adjoint sensitivities, representer matrix spectrum, observation footprints and spectral analysis. It is shown that local errors in global and basin-scale systems can be significantly reduced when assimilating observations from regional observing systems.

Amazonian rainfall plays a critical role in the global climate system and the hydrological cycle. It is thus important to quantify changes in the Amazonian rainfall and clarify its mechanism. Previous studies indicate that the interannual variability of Amazonian precipitation could be largely attributed to variabilities in the South American monsoon system and the El Niño Southern Oscillation. However, the trend of the wet season tropical Amazonian precipitation during recent decades is not very well investigated. In this study, by combining both satellite and in situ observations, it is revealed that tropical Amazonian precipitation has significantly increased by ∼180 to 600 mm (in different datasets) in the wet season during the satellite era from 1979 to 2015. We then use a state-of-the-art atmospheric model to simulate the impact of the tropical sea surface temperatures (SSTs) on the precipitation changes. Results show that the multidecadal warming of the tropical Atlantic has contributed more than half of this precipitation change over the past three decades, while the east Pacific cooling plays a secondary role. We finally combine the simulation results and the reanalysis data to investigate the mechanisms of this process, i.e. the SST variability dramatically increases the convergence of the moisture transport over the Amazon region. The precipitation changes over the Amazon region largely impact on the local hydrological cycle and the ecosystem, and have important impacts on the global climate system by mediating the teleconnection between the Pacific and the Atlantic oceans. Our results show that the long-term change in the wet season Amazonian precipitation is important and deserves further investigation and discussion.

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Operational oceanography can be described as the provision of routine oceanographic information needed for decision-making purposes. It is dependent upon sustained research and development through the end-to-end framework of an operational service, from observation collection to delivery mechanisms. The core components of operational oceanographic systems are a multi-platform observation network, a data management system, a data assimilative prediction system, and a dissemination/accessibility system. These are interdependent, necessitating communication and exchange between them, and together provide the mechanism through which a clear picture of ocean conditions, in the past, present, and future, can be seen. Ocean observations play a critical role in all aspects of operational oceanography, not only for assimilation but as part of the research cycle, and

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