Atanas Trayanov

Design and Implementation of Components in the Earth System Modeling Framework

The Earth System Modeling Framework is a component-based architecture for developing and assembling climate and related models. A virtual machine underlies the component-level constructs in ESMF, providing both a foundation for performance portability and mechanisms for resource allocation and component sequencing.

Implementing applications with the earth system modeling framework

The Earth System Modeling Framework (ESMF) project is developing a standard software platform for Earth system models. The standard defines a component architecture superstructure and a support infrastructure. The superstructure allows earth scientists to develop complex software models with numerous components in a coordinated fashion. The infrastructure allows models to run efficiently on high performance computers. It offers capabilities that are commonly needed in Earth Science applications, for example, support for a broad range of discrete grids, regridding functions, and a distributed grid class which represents the data decomposition. We illustrate these features through a simplified finite-volume atmospheric model, and report the parallel performance of the underlying ESMF components.

MAPL: a high-level programming paradigm to support more rapid and robust encoding of hierarchical trees of interacting high-performance components

We describe the design, and deployment in several large scale Earth system codes, of an innovative programming library, MAPL. MAPL is a layer of software that is built on top of the Earth System Modeling Framework (ESMF) component library. It provides mechanisms for automating and managing key aspects of the interconnection and control of deep, hierarchical trees of interacting components. Examples of the use of the MAPL library, in both an illustrative five component coupled system and with state-of-the-art large scale Earth system models, are used to highlight MAPLs role in automating key aspects of the creation of sophisticated, scalable component based systems.

Cross‐organization interoperability experiments of weather and climate models with the Earth System Modeling Framework

Typical weather and climate models need a software tool to couple sub‐scale model components. The high‐performance computing requirements and a variety of model interfaces make the development of such a coupling tool very challenging. In this paper, we describe the approach of the Earth System Modeling Framework, in particular its component and coupling mechanism, and present the results of three cross‐organization model interoperability experiments. Copyright

GEOS-Chem High Performance (GCHP): A next-generation implementation of the GEOS-Chem chemical transport model for massively parallel applications

Global modeling of atmospheric chemistry is a grand computational challenge because of the need to simulate large coupled systems of ∼ 100–1000 chemical species interacting with transport on all scales. Offline chemical transport models (CTMs), where the chemical continuity equations are solved using meteorological data as input, have usability advantages and are important vehicles for developing atmospheric chemistry knowledge that can then be transferred to Earth system models. However, they have generally not been designed to take advantage of massively parallel computing architectures. Here, we develop such a highperformance capability for GEOS-Chem (GCHP), a CTM driven by meteorological data from the NASA Goddard Earth Observation System (GEOS) and used by hundreds of research groups worldwide. GCHP is a grid-independent implementation of GEOS-Chem using the Earth System Modeling Framework (ESMF) that permits the same standard model to operate in a distributed-memory framework for massive parallelization. GCHP also allows GEOS-Chem to take advantage of the native GEOS cubed-sphere grid for greater accuracy and computational efficiency in simulating transport. GCHP enables GEOS-Chem simulations to be conducted with high computational scalability up to at least 500 cores, so that global simulations of stratosphere– troposphere oxidant–aerosol chemistry at C180 spatial resolution (∼ 0.5× 0.625) or finer become routinely feasible.