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The hydrodynamics of the TagusROFI (Regions of Freshwater Influence) is affected by the coastal upwelling, the estuarine tidal flow, the thermohaline circulation that is modulated by the Tagus freshwater discharge, and by its complex bathymetry. The use of numerical models is the best way to explain the processes that characterize this region. These models are also crucial to answer important scientific and management questions. Nevertheless, the robustness of the products derived from models depend on their accuracy and therefore models must be validated to determine the uncertainty associated. Time and space variability of the driving forces and of bathymetry enhance flow complexity increasing validation difficulties, requiring continuous high-resolution data to describe flow and thermohaline horizontal and vertical variabilities. In the present work, to increase the precision and accuracy of the coastal processes simulations, the sub-systems coastal area and the Tagus estuary were integrated into a single domain, which considers higher resolution grids in both horizontal and vertical directions. The three-dimensiosal (3D)-MOHID Water model was validated for the TagusROFI by comparing statistically modelling results with in situ and satellite L4 data. Validation with a conductivity, temperature, and depth probe (CTD), an acoustic doppler current profiler (ADCP) and satellite data was performed for the first time. Validation against tidal gauges showed that the model is able to simulate tidal propagation inside the estuary with accuracy. A very good agreement between CTD data and surface sea water temperature (SST) and salinity simulations was observed. The validation of current direction and velocity from ADCP data also indicated a high model accuracy for these variables. Comparisons between model and satellite for SST also showed that the model produces realistic SSTs and upwelling events. Overall results showed that MOHID setup and parametrisations are well implemented for the TagusROFI domain. These results are even more important when a 3D model is used in simulations due to its complexity once it considers both horizontal and vertical discretization allowing a better representation of the heat and salinity fluxes in the water column. Moreover, the results achieved indicates that 3D-MOHID is robust enough to run in operational mode, including its forecast ability, fundamental to be used as a management tool.

Severity of drought in California (U.S.) varies from year-to-year and is highly influenced by precipitation in winter months, causing billion-dollar events in single drought years. Improved understanding of the variability of drought on decadal and longer timescales is essential to support regional water resources planning and management. This paper presents a soft-computing approach to forecast the Palmer Drought Severity Index (PDSI) in California. A time-series of yearly data covering more than two centuries (1801–2014) was used for the design of ensemble projections to understand and quantify the uncertainty associated with interannual-to-interdecadal predictability. With a predictable structure elaborated by exponential smoothing, the projections indicate for the horizon 2015–2054 a weak increase of drought, followed by almost the same pace as in previous decades, presenting remarkable wavelike variations with durations of more than one year. Results were compared with a linear transfer function model approach where Pacific Decadal Oscillation and El Niño Southern Oscillation indices were both used as input time series. The forecasted pattern shows that variations attributed to such internal climate modes may not provide more reliable predictions than the one provided by purely internal variability of drought persistence cycles, as present in the PDSI time series.

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The General Curvilinear Coastal Ocean Model (GCCOM) is a 3D curvilinear, structured-mesh, non-hydrostatic, large-eddy simulation model that is capable of running oceanic simulations. GCCOM is an inherently computationally expensive model: it uses an elliptic solver for the dynamic pressure; meter-scale simulations requiring memory footprints on the order of 10 12 cells and terabytes of output data. As a solution for parallel optimization, the Fortran-interfaced Portable–Extensible Toolkit for Scientific Computation (PETSc) library was chosen as a framework to help reduce the complexity of managing the 3D geometry, to improve parallel algorithm design, and to provide a parallelized linear system solver and preconditioner. GCCOM discretizations are based on an Arakawa-C staggered grid, and PETSc DMDA (Data Management for Distributed Arrays) objects were used to provide communication and domain ownership management of the resultant multi-dimensional arrays, while the fully curvilinear Laplacian system for pressure is solved by the PETSc linear solver routines. In this paper, the framework design and architecture are described in detail, and results are presented that demonstrate the multiscale capabilities of the model and the parallel framework to 240 cores over domains of order 10 7 total cells per variable, and the correctness and performance of the multiphysics aspects of the model for a baseline experiment stratified seamount.