Convex Optimization of Initial Perturbations toward Quantitative Weather Control
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918281796911104 |
|---|---|
| author | Ohtsuka, Toshiyuki Okazaki, Atsushi Ogura, Masaki Kotsuki, Shunji |
| author_facet | Ohtsuka, Toshiyuki Okazaki, Atsushi Ogura, Masaki Kotsuki, Shunji |
| contents | This study proposes introducing convex optimization to find initial perturbations of atmospheric states to realize specified changes in subsequent weather. In the proposed method, we formulate and solve an inverse problem to find effective perturbations in atmospheric variables so that controlled variables satisfy specified changes at a specified time. The proposed method first constructs a sensitivity matrix of controlled variables, such as accumulated precipitation, to the initial atmospheric variables, such as temperature and humidity, through sensitivity analysis using a numerical weather prediction (NWP) model. Then a convex optimization problem is formulated to achieve various control specifications involving not only quadratic functions but also absolute values and maximum values of the controlled variables and initial atmospheric variables in the cost function and constraints. The proposed method was validated through a benchmark warm bubble experiment using the NWP model. The experiments showed that the identified perturbations successfully realized specified spatial distributions of accumulated precipitation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_19546 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Convex Optimization of Initial Perturbations toward Quantitative Weather Control Ohtsuka, Toshiyuki Okazaki, Atsushi Ogura, Masaki Kotsuki, Shunji Atmospheric and Oceanic Physics Systems and Control Optimization and Control This study proposes introducing convex optimization to find initial perturbations of atmospheric states to realize specified changes in subsequent weather. In the proposed method, we formulate and solve an inverse problem to find effective perturbations in atmospheric variables so that controlled variables satisfy specified changes at a specified time. The proposed method first constructs a sensitivity matrix of controlled variables, such as accumulated precipitation, to the initial atmospheric variables, such as temperature and humidity, through sensitivity analysis using a numerical weather prediction (NWP) model. Then a convex optimization problem is formulated to achieve various control specifications involving not only quadratic functions but also absolute values and maximum values of the controlled variables and initial atmospheric variables in the cost function and constraints. The proposed method was validated through a benchmark warm bubble experiment using the NWP model. The experiments showed that the identified perturbations successfully realized specified spatial distributions of accumulated precipitation. |
| title | Convex Optimization of Initial Perturbations toward Quantitative Weather Control |
| topic | Atmospheric and Oceanic Physics Systems and Control Optimization and Control |
| url | https://arxiv.org/abs/2405.19546 |