![]() Adaptor code defines the underlying numerical grid (structured or unstructured) and the associated multi-dimensional fields, using the Visualization Toolkit (VTK). In the new approach, an adaptor interacts with an ESMF driver, which synchronizes the model components, the data exchange and the spatial interpolation that occurs among the computational grids of the model components.įigure 1: A conventional simulation system shows the flow of simulation code through an adaptor to ParaView Catalyst. In addition, the approach couples existing Earth system models with the Earth System Modeling Framework (ESMF) library and the interface of the National Unified Operational Prediction Capability (NUOPC) Layer. The approach integrates in situ visualization. The new approach (Figure 2) aims to create a more generic and standardized co-processing environment for Earth system science. It transfers information from the simulation code to ParaView Catalyst. Custom adaptor code is developed in the C++ programming language. This adaptor acts as an abstraction layer or a wrapper layer. In a conventional simulation system (Figure 1), ParaView Catalyst integrates a visualization pipeline with simulation code through an adaptor. This work was presented in “Towards in situ visualization integrated model coupling framework for earth system science” at the Fourth Workshop on Coupling Technologies for Earth System Models. This article discusses in situ visualization and highlights work that tested its integration with RegESM. In addition, in situ visualization does not entail extensive code development and restructuring. ![]() When compared to the conventional approach, in situ visualization can analyze key information that multi-component Earth system models generate in a higher temporal resolution. In situ visualization has been used to overcome the limitations of the conventional approach. Thus, the systems require extensive resources for computation and storage.ĭue to the increased complexity of multi-component modeling systems, the conventional post-processing approach has become insufficient to analyze and understand in detail fast-moving processes and interactions among model components. The increased complexity of multi-component modeling systems results in extra overhead in disk input/output and network bandwidth. This data determines the resolution of the spatial grid, the length of the simulation and the number of represented model components. A typical application of RegESM can produce tens of terabytes of raw data. Fully coupled multi-component and multi-scale modeling systems such as Regional Earth System Model (RegESM) are used to represent and analyze complex interactions among physical processes.
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