Presentation Information
[O12-P12]Evaluation of 3D Cloud Displacement and Wind Velocity Using a Simplified Observation System
*Yuichiro Tsukahara1 (1. Kaijo Earth Science Club)
Keywords:
meteorology,disaster prevention,Low-cost system
1. Introduction
Currently, upper-air wind direction and speed are measured using pilot balloons (pibals), wind profilers (WPRs), and satellites. However, pibals entail high operational costs, and WPRs are limited to only 33 locations in Japan, resulting in spatial gaps in the observation network. Furthermore, while satellite observations excel at providing a wide-area overview, it is challenging to pinpoint and continuously track sudden atmospheric fluctuations in the lower troposphere.
There is a critical need to establish an inexpensive, high-density fixed-point observation method that overcomes these geographical and economic constraints. Localized meteorological phenomena, such as the severe wind gust damage that occurred in Saitama Prefecture in July 2024, often strike within the blind spots of existing observation networks. Therefore, constructing a low-cost, rapid-response observation network is of paramount importance for disaster prevention and mitigation.
This study proposes a novel upper-air wind speed measurement system utilizing a three-point ground observation network combined with a unique geometric calculation model. This method enables omnidirectional measurement across the entire sky and significantly improves estimation accuracy—a feat that has traditionally been difficult to achieve with simple equipment. This paper outlines the proposed observation method and discusses its practical potential.
2. Method
Three commercially available 3D cameras and transparent hemispheres with crosshairs (photo1)were combined and installed at three points (A, B, C). An arbitrary point (O) on the cloud body was targeted, and the angle change from each station was measured retrospectively. The target at time tn was defined as On, and its projection point onto the ground was defined as Hn(photo2).
The equation (1) for calculating the horizontal displacement x is as follows:
x = (1/SABC)*√[-Σ{a2*(SH1CA-SH2CA)*(SH1AB-SH2AB)}] (Σ is the cyclic sum)
On the other hand, equation (2), which requires fewer variables, is x=(a*sin∠H1CB*sin∠H1BH2)/(sin∠H1H2B*sin∠CH1B). In this study, equation (2) was adopted to suppress the accumulation of errors in angle measurement.
The vertical displacement (cloud base altitude) was calculated using equation (3) OnHn=(c*sin∠HnBA*tan∠OAHn)/sin(∠AHnB) (1), and the three-dimensional velocity was obtained by dividing the horizontal and vertical displacements by time.
3. Demonstration Experiment and Results
3.1 Horizontal Demonstration
Observations were conducted at three stations near Shinozaki Station (duration t=1500s). From equation (2), x = (290*sin70°*sin60°)/(sin57°*sin13°)≈1251[m].1251/1500≈0.834[m/s] suggests a horizontal wind of approximately 0.834[m/s] blowing southeast at an altitude of around 2000-7000m during the observation period of 11:25-11:40.
3.2 Vertical Demonstration
Observations were conducted at two stations in Tsukuba City, Ibaraki Prefecture (t=180s). From equation (3), we get O1H1=(1482*sin125° * tan5°)/sin8° = 763.1[m] and O2H2=(1482*sin155°*tan25°)/sin23°=747.5 [m]. The descent velocity is (763.1-747.5)/180≈0.087[m/s], suggesting a weak downdraft during the observed period from 10:17 to 10:20. These results demonstrate that it is possible to understand atmospheric dynamics in three dimensions using simple angle measurements.
4. Discussion and Future Prospects
This study proposes a simple method for estimating upper-air wind speed and demonstrates its effectiveness.
This method does not rely on expensive infrastructure, enables the understanding of atmospheric flow dynamics, and is useful in the following three ways: 1, It has low technical and cost barriers and is excellent for supplementing gaps in conventional observation networks. 2, It does not require consumables, allowing for continuous data collection. 3, It has a high probability of contributing to the construction of a prediction network for localized meteorological disasters. In the future, we aim to establish a permanent observation system, including the use of equation (1), by developing an automated analysis program.
5. references
(1) https://www.yoho.jp/member/interfrex/cloudobs5.htm
Currently, upper-air wind direction and speed are measured using pilot balloons (pibals), wind profilers (WPRs), and satellites. However, pibals entail high operational costs, and WPRs are limited to only 33 locations in Japan, resulting in spatial gaps in the observation network. Furthermore, while satellite observations excel at providing a wide-area overview, it is challenging to pinpoint and continuously track sudden atmospheric fluctuations in the lower troposphere.
There is a critical need to establish an inexpensive, high-density fixed-point observation method that overcomes these geographical and economic constraints. Localized meteorological phenomena, such as the severe wind gust damage that occurred in Saitama Prefecture in July 2024, often strike within the blind spots of existing observation networks. Therefore, constructing a low-cost, rapid-response observation network is of paramount importance for disaster prevention and mitigation.
This study proposes a novel upper-air wind speed measurement system utilizing a three-point ground observation network combined with a unique geometric calculation model. This method enables omnidirectional measurement across the entire sky and significantly improves estimation accuracy—a feat that has traditionally been difficult to achieve with simple equipment. This paper outlines the proposed observation method and discusses its practical potential.
2. Method
Three commercially available 3D cameras and transparent hemispheres with crosshairs (photo1)were combined and installed at three points (A, B, C). An arbitrary point (O) on the cloud body was targeted, and the angle change from each station was measured retrospectively. The target at time tn was defined as On, and its projection point onto the ground was defined as Hn(photo2).
The equation (1) for calculating the horizontal displacement x is as follows:
x = (1/SABC)*√[-Σ{a2*(SH1CA-SH2CA)*(SH1AB-SH2AB)}] (Σ is the cyclic sum)
On the other hand, equation (2), which requires fewer variables, is x=(a*sin∠H1CB*sin∠H1BH2)/(sin∠H1H2B*sin∠CH1B). In this study, equation (2) was adopted to suppress the accumulation of errors in angle measurement.
The vertical displacement (cloud base altitude) was calculated using equation (3) OnHn=(c*sin∠HnBA*tan∠OAHn)/sin(∠AHnB) (1), and the three-dimensional velocity was obtained by dividing the horizontal and vertical displacements by time.
3. Demonstration Experiment and Results
3.1 Horizontal Demonstration
Observations were conducted at three stations near Shinozaki Station (duration t=1500s). From equation (2), x = (290*sin70°*sin60°)/(sin57°*sin13°)≈1251[m].1251/1500≈0.834[m/s] suggests a horizontal wind of approximately 0.834[m/s] blowing southeast at an altitude of around 2000-7000m during the observation period of 11:25-11:40.
3.2 Vertical Demonstration
Observations were conducted at two stations in Tsukuba City, Ibaraki Prefecture (t=180s). From equation (3), we get O1H1=(1482*sin125° * tan5°)/sin8° = 763.1[m] and O2H2=(1482*sin155°*tan25°)/sin23°=747.5 [m]. The descent velocity is (763.1-747.5)/180≈0.087[m/s], suggesting a weak downdraft during the observed period from 10:17 to 10:20. These results demonstrate that it is possible to understand atmospheric dynamics in three dimensions using simple angle measurements.
4. Discussion and Future Prospects
This study proposes a simple method for estimating upper-air wind speed and demonstrates its effectiveness.
This method does not rely on expensive infrastructure, enables the understanding of atmospheric flow dynamics, and is useful in the following three ways: 1, It has low technical and cost barriers and is excellent for supplementing gaps in conventional observation networks. 2, It does not require consumables, allowing for continuous data collection. 3, It has a high probability of contributing to the construction of a prediction network for localized meteorological disasters. In the future, we aim to establish a permanent observation system, including the use of equation (1), by developing an automated analysis program.
5. references
(1) https://www.yoho.jp/member/interfrex/cloudobs5.htm