Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control
<p>Climate change intensifies weather-related disasters, necessitating novel mitigation strategies beyond conventional weather prediction methods. The control simulation experiment (CSE) framework proposes altering weather systems through small perturbations, but its effectiveness relative to...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2025-08-01
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| Series: | Nonlinear Processes in Geophysics |
| Online Access: | https://npg.copernicus.org/articles/32/281/2025/npg-32-281-2025.pdf |
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| _version_ | 1849390469122883584 |
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| author | R. Nagai Y. Bai M. Ogura M. Ogura S. Kotsuki S. Kotsuki N. Wakamiya |
| author_facet | R. Nagai Y. Bai M. Ogura M. Ogura S. Kotsuki S. Kotsuki N. Wakamiya |
| author_sort | R. Nagai |
| collection | DOAJ |
| description | <p>Climate change intensifies weather-related disasters, necessitating novel mitigation strategies beyond conventional weather prediction methods. The control simulation experiment (CSE) framework proposes altering weather systems through small perturbations, but its effectiveness relative to other control methods remains uncertain. This study evaluates CSE's efficacy against model predictive control (MPC), a well-established method in control engineering. We specifically develop an MPC algorithm tailored for the Lorenz-63 model, incorporating temporal deep unfolding to address challenges in controlling chaotic systems. Simulations show that MPC achieves higher success rates with less control effort under certain conditions, particularly with shorter prediction horizons. This work bridges control theory and atmospheric science, advancing the understanding of atmospheric controllability and informing future research efforts to mitigate extreme weather events.</p> |
| format | Article |
| id | doaj-art-891731dd59824435bb3ed446e971618b |
| institution | Kabale University |
| issn | 1023-5809 1607-7946 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Nonlinear Processes in Geophysics |
| spelling | doaj-art-891731dd59824435bb3ed446e971618b2025-08-20T03:41:39ZengCopernicus PublicationsNonlinear Processes in Geophysics1023-58091607-79462025-08-013228129210.5194/npg-32-281-2025Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive controlR. Nagai0Y. Bai1M. Ogura2M. Ogura3S. Kotsuki4S. Kotsuki5N. Wakamiya6Graduate School of Information Science and Technology, Osaka University, Osaka, JapanGraduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima, JapanGraduate School of Information Science and Technology, Osaka University, Osaka, JapanGraduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima, JapanInstitute for Advanced Academic Research, Chiba University, Chiba, JapanCenter for Environmental Remote Sensing, Chiba University, Chiba, JapanGraduate School of Information Science and Technology, Osaka University, Osaka, Japan<p>Climate change intensifies weather-related disasters, necessitating novel mitigation strategies beyond conventional weather prediction methods. The control simulation experiment (CSE) framework proposes altering weather systems through small perturbations, but its effectiveness relative to other control methods remains uncertain. This study evaluates CSE's efficacy against model predictive control (MPC), a well-established method in control engineering. We specifically develop an MPC algorithm tailored for the Lorenz-63 model, incorporating temporal deep unfolding to address challenges in controlling chaotic systems. Simulations show that MPC achieves higher success rates with less control effort under certain conditions, particularly with shorter prediction horizons. This work bridges control theory and atmospheric science, advancing the understanding of atmospheric controllability and informing future research efforts to mitigate extreme weather events.</p>https://npg.copernicus.org/articles/32/281/2025/npg-32-281-2025.pdf |
| spellingShingle | R. Nagai Y. Bai M. Ogura M. Ogura S. Kotsuki S. Kotsuki N. Wakamiya Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control Nonlinear Processes in Geophysics |
| title | Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control |
| title_full | Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control |
| title_fullStr | Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control |
| title_full_unstemmed | Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control |
| title_short | Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control |
| title_sort | evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control |
| url | https://npg.copernicus.org/articles/32/281/2025/npg-32-281-2025.pdf |
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