Software title Description Download Links Reference
Hydrologic deep learning PyTorch code used in published, Fang et al., 2017, Fang et al., 2018, and papers under review gitHub link  

Process-based Adaptive Wateshed Simulator + Community Land Model




PRISM repo

PAWS repo

Integrated generic data package (gd) and Matlab I/O interface matTable


Geoscientific models manage myriad and increasingly complex data structures as trans-disciplinary models are integrated. They often incur significant redundancy with cross-cutting tasks. Reflection, the ability of a program to inspect and modify its structure and behavior at runtime, is known as a powerful tool to improve code reusability, abstraction, and separation of concerns. Reflection is rarely adopted in high-performance Geoscientific models, especially with Fortran, where it was previously deemed implausible. Practical constraints of language and legacy often limit us to feather-weight, native-language solutions. We demonstrate the usefulness of a structural-reflection-emulating, dynamically-linked metaObjects, gd. We show real-world examples including data structure self-assembly, effortless save/restart and upgrade to parallel I/O, recursive actions and batch operations. We share gd and a derived module that reproduces MATLAB-like structure in Fortran and C++. We suggest that both a gd representation and a Fortran-native representation are maintained to access the data, each for separate purposes . Embracing emulated reflection allows generically-written codes that are highly re-usable across projects.


page for gd