Preprints
https://doi.org/10.5194/egusphere-2023-1612
https://doi.org/10.5194/egusphere-2023-1612
24 Jul 2023
 | 24 Jul 2023

Parallel SnowModel (v1.0): a parallel implementation of a Distributed Snow-Evolution Modeling System (SnowModel)

Ross Mower, Ethan D. Gutmann, Jessica Lundquist, Glen E. Liston, and Soren Rasmussen

Abstract. SnowModel, a spatially distributed, snow-evolution modeling system, was parallelized using Coarray Fortran for high-performance computing architectures to allow high-resolution (1 m to 100’s of meters) simulations over large, regional to continental scale, domains. In the parallel algorithm, the model domain is split into smaller rectangular sub-domains that are distributed over multiple processor cores using one-dimensional decomposition. All of the memory allocations from the original code have been reduced to the size of the local sub-domains, allowing each core to perform fewer computations and requiring less memory for each process. A majority of the subroutines in SnowModel were simple to parallelize; however, there were certain physical processes, including blowing snow redistribution and components within the solar radiation and wind models, that required non-trivial parallelization using halo-exchange patterns. To validate the parallel algorithm and assess parallel scaling characteristics, high-resolution (100 m grid) simulations were performed over several western United States domains and over the contiguous United States (CONUS). The CONUS scaling experiment had approximately 71 % parallel efficiency; runtime decreased by a factor of 32 running on 2304 cores relative to 52 cores (the minimum number of cores that could be used to run such a large domain as a result of memory and time limitations). CONUS 100 m simulations were performed for 21 years (2000–2021) using 46,238 and 28,260 grid cells in the x and y dimensions, respectively. Each year was simulated using 1800 cores and took approximately 5 hours to run.

Ross Mower, Ethan D. Gutmann, Jessica Lundquist, Glen E. Liston, and Soren Rasmussen

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1612', Anonymous Referee #1, 26 Aug 2023
    • AC3: 'Reply on RC1', Ross Mower, 11 Nov 2023
  • RC2: 'Comment on egusphere-2023-1612', Chen Zhang, 03 Sep 2023
    • AC4: 'Reply on RC2', Ross Mower, 11 Nov 2023
  • AC1: 'Author Comments-2023-1612', Ross Mower, 17 Oct 2023
    • AC2: 'Reply on AC1', Ross Mower, 18 Oct 2023
Ross Mower, Ethan D. Gutmann, Jessica Lundquist, Glen E. Liston, and Soren Rasmussen

Data sets

Parallel-SnowModel-1.0 Ross Mower, Ethan Gutmann, and Glen Liston https://github.com/NCAR/Parallel-SnowModel-1.0

Model code and software

Parallel-SnowModel-1.0 Ross Mower, Ethan Gutmann, and Glen Liston https://github.com/NCAR/Parallel-SnowModel-1.0

Ross Mower, Ethan D. Gutmann, Jessica Lundquist, Glen E. Liston, and Soren Rasmussen

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Latest update: 21 Feb 2024
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Short summary
Higher resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a Distributed Snow-Evolution Modeling System (SnowModel) to allow it to leverage high performance computing resources. Continental simulations that were previously estimated to take 120 days, can now be performed in five hours.