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Modernizing the open-source community Noah-MP land surface model (version 5.0) with enhanced modularity, interoperability, and applicability.

Authors :
He, Cenlin
Valayamkunnath, Prasanth
Barlage, Michael
Chen, Fei
Gochis, David
Cabell, Ryan
Schneider, Tim
Rasmussen, Roy
Niu, Guo-Yue
Yang, Zong-Liang
Niyogi, Dev
Ek, Michael
Source :
EGUsphere; 4/12/2023, p1-31, 31p
Publication Year :
2023

Abstract

The widely-used open-source community Noah-MP land surface model (LSM) is designed for applications ranging from uncoupled land-surface and ecohydrological process studies to coupled numerical weather prediction and decadal global/regional climate simulations. It has been used in many coupled community weather/climate/hydrology models. In this study, we modernize/refactor the Noah-MP LSM by adopting modern Fortran code and data structures and standards, which substantially enhances the model modularity, interoperability, and applicability. The modernized Noah-MP is released as the version 5.0 (v5.0), which has five key features: (1) enhanced modularization and interoperability by re-organizing model physics into individual process-level Fortran module files, (2) enhanced data structure with new hierarchical data types and optimized variable declaration and initialization structures, (3) enhanced code structure and calling workflow by leveraging the new data structure and modularization, (4) enhanced (descriptive and self-explanatory) model variable naming standard, and (5) enhanced driver and interface structures to couple with host weather/climate/hydrology models. In addition, we create a comprehensive technical documentation of the Noah-MP v5.0 and a set of model benchmark and reference datasets. The Noah-MP v5.0 will be coupled to various weather/climate/hydrology models in the future. Overall, the modernized Noah-MP will allow a more efficient and convenient process for future model developments and applications. [ABSTRACT FROM AUTHOR]

Details

Language :
English
Database :
Complementary Index
Journal :
EGUsphere
Publication Type :
Academic Journal
Accession number :
163037293
Full Text :
https://doi.org/10.5194/egusphere-2023-675