scholarly journals Representation of heterogeneity effects in Earth system modeling: Experience from land surface modeling

1997 ◽  
Vol 35 (4) ◽  
pp. 413-437 ◽  
Author(s):  
Filippo Giorgi ◽  
Roni Avissar
Keyword(s):  
Land Surface ◽  
System Modeling ◽  
Surface Modeling ◽  
Earth System ◽  
Earth System Modeling ◽  
Land Surface Modeling ◽  
Heterogeneity Effects

Coupled earth system modeling on heterogeneous HPC architectures with ParFlow in the Terrestrial Systems Modeling Platform

2021 ◽  
Author(s):  
Jaro Hokkanen ◽  
Stefan Kollet ◽  
Jiri Kraus ◽  
Andreas Herten ◽  
Markus Hrywniak ◽  
...  
Keyword(s):  
Land Surface ◽  
Memory Management ◽  
High Performance ◽  
Data Exchange ◽  
System Modeling ◽  
Hydrologic Model ◽  
Earth System ◽  
Single Node ◽  
Earth System Modeling ◽  
Domain Specific

<p>Rapidly changing heterogeneous supercomputer architectures pose a great challenge to many scientific communities trying to leverage the latest technology in high-performance computing. Implementations that simultaneously result in a good performance and developer productivity while keeping the codebase adaptable and well maintainable in the long-term are of high importance. ParFlow, a widely used hydrologic model, achieves these attributes by hiding the architecture-dependent code in preprocessor macros (ParFlow embedded Domain Specific Language, eDSL) and leveraging NVIDIA's Unified Memory technology for memory management. The implementation results in very good weak scaling with up to 26x speedup when using four NVIDIA A100 GPUs per node compared to using the available 48 CPU cores. Good weak scaling is observed using hundreds of nodes on the new JUWELS Booster system at the Jülich Supercomputing Centre, Germany. Furthermore, it is possible to couple ParFlow with other earth system compartment models such as land surface and atmospheric models using the OASIS-MCT coupler library, which handles the data exchange between the different models. The ParFlow GPU implementation is fully compatible with the coupled implementation with little changes to the source code. Moreover, coupled simulations offer interesting load-balancing opportunities for optimal usage of the existing resources. For example, running ParFlow on GPU nodes, and another application component on CPU-only nodes, or efficiently distributing the CPU and GPU resources of a single node between the different application components may result in the best usage of heterogeneous architectures.</p>

scholarly journals Seasonal to multi-year soil moisture drought forecasting

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Musa Esit ◽  
Sanjiv Kumar ◽  
Ashutosh Pandey ◽  
David M. Lawrence ◽  
Imtiaz Rangwala ◽  
...  
Keyword(s):  
Soil Moisture ◽  
North America ◽  
Land Surface ◽  
System Modeling ◽  
Precipitation Variability ◽  
Surface Processes ◽  
Earth System ◽  
Drought Forecasting ◽  
Earth System Modeling ◽  
Order Of Magnitude

AbstractSoil moisture predictability on seasonal to decadal (S2D) continuum timescales over North America is examined from the Community Earth System Modeling (CESM) experiments. The effects of ocean and land initializations are disentangled using two large ensemble datasets—initialized and uninitialized experiments from the CESM. We find that soil moisture has significant predictability on S2D timescales despite limited predictability in precipitation. On sub-seasonal to seasonal timescales, precipitation variability is an order of magnitude greater than soil moisture, suggesting land surface processes, including soil moisture memory, reemergence, land–atmosphere interactions, transform a less predictable precipitation signal into a more predictable soil moisture signal.

scholarly journals Infiltration from the Pedon to Global Grid Scales: An Overview and Outlook for Land Surface Modeling

2019 ◽  
Vol 18 (1) ◽  
pp. 1-53 ◽  
Author(s):  
Harry Vereecken ◽  
Lutz Weihermüller ◽  
Shmuel Assouline ◽  
Jirka Šimůnek ◽  
Anne Verhoef ◽  
...  
Keyword(s):  
Land Surface ◽  
Surface Modeling ◽  
Land Surface Modeling ◽  
Global Grid
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