dorsal/arxiv
View SchemaSuper-Droplet Method for the Numerical Simulation of Clouds and Precipitation: a Particle-Based Microphysics Model Coupled with Non-hydrostatic Model
| Authors | Shin-ichiro Shima, Kanya Kusano, Akio Kawano, Tooru Sugiyama, Shintaro Kawahara |
|---|---|
| Categories | |
| ArXiv ID | physics/0701103 |
| URL | https://arxiv.org/abs/physics/0701103 |
| DOI | 10.1002/qj.441 |
| Journal | Quarterly Journal of the Royal Meteorological Society, 135 (2009) 1307--1320 |
| License | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
Abstract
A novel, particle based, probabilistic approach for the simulation of cloud microphysics is proposed, which is named the Super-Droplet Method (SDM). This method enables accurate simulation of cloud microphysics with less demanding cost in computation. SDM is applied to a warm-cloud system, which incorporates sedimentation, condensation/evaporation, and stochastic coalescence. The methodology to couple super-droplets and a non-hydrostatic model is also developed. It is confirmed that the result of our Monte Carlo scheme for the stochastic coalescence of super-droplets agrees fairly well with the solutions of the stochastic coalescence equation. The behavior of the model is evaluated using a simple test problem, that of a shallow maritime cumulus formation initiated by a warm bubble. Possible extensions of SDM are briefly discussed. A theoretical analysis suggests that the computational cost of SDM becomes lower than the spectral (bin) method when the number of attributes - the variables that identify the state of each super-droplet - becomes larger than some critical value, which we estimate to be in the range $2\sim4$.
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"abstract": "A novel, particle based, probabilistic approach for the simulation of cloud\nmicrophysics is proposed, which is named the Super-Droplet Method (SDM). This\nmethod enables accurate simulation of cloud microphysics with less demanding\ncost in computation. SDM is applied to a warm-cloud system, which incorporates\nsedimentation, condensation/evaporation, and stochastic coalescence. The\nmethodology to couple super-droplets and a non-hydrostatic model is also\ndeveloped. It is confirmed that the result of our Monte Carlo scheme for the\nstochastic coalescence of super-droplets agrees fairly well with the solutions\nof the stochastic coalescence equation. The behavior of the model is evaluated\nusing a simple test problem, that of a shallow maritime cumulus formation\ninitiated by a warm bubble. Possible extensions of SDM are briefly discussed. A\ntheoretical analysis suggests that the computational cost of SDM becomes lower\nthan the spectral (bin) method when the number of attributes - the variables\nthat identify the state of each super-droplet - becomes larger than some\ncritical value, which we estimate to be in the range $2\\sim4$.",
"arxiv_id": "physics/0701103",
"authors": [
"Shin-ichiro Shima",
"Kanya Kusano",
"Akio Kawano",
"Tooru Sugiyama",
"Shintaro Kawahara"
],
"categories": [
"physics.ao-ph",
"physics.flu-dyn"
],
"doi": "10.1002/qj.441",
"journal_ref": "Quarterly Journal of the Royal Meteorological Society, 135 (2009)\n 1307--1320",
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"title": "Super-Droplet Method for the Numerical Simulation of Clouds and Precipitation: a Particle-Based Microphysics Model Coupled with Non-hydrostatic Model",
"url": "https://arxiv.org/abs/physics/0701103"
},
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