LCD method consists mainly of spraying liquid carbonic acid at extremely low temperatures to induce more precipitation from rain clouds.
Cloud seeding, is a scientific process intended to enhance rain and snow. It is a process to improves a cloud’s ability to produce precipitation by adding tiny particles called ice nuclei. These nuclei help the cloud produce precipitation by freezing supercooled liquid water by adding silver iodide nuclei, dry ice. However, these methods lead to serious situation that individual ice particle cannot grow into enough size to induce precipitation due to the generation of too many ice particles in low temperature by heterogeneous nucleation. To solve the above-mentioned problems, a new seeding method was suggested which consists of the generation of ice particles by homogeneous nucleation using liquid carbon dioxide (LC) and the subsequent more effective growth for ice particles without competition process.
Category of the action
Mitigation/Adaptation, Changing public attitudes about climate change
What actions do you propose?
Liquid carbon dioxide (LCD) seeding technique observed facts show that the method will lead to the effective conversion of a large amount of inactive cloud volume into significant precipitation due to the horizontal spreading of cloud volume and the generation of new precipitation. Therefore, the new method would have enough possibility to enhance significant precipitation for water resources through these processes. For example, in the case of dry ice, the seeding material is spread on top of the clouds, while the LC seeding method calls for the material to be spread directly into the cloud at a level where the air temperature is just above 0C. So, stand for this the amount of the rain in the area will increase and that will reduce the impact of droughts. It can lead to more crop yields, and the best part is, this could occur in areas that might not have supported crops in the past. This means that this technology has the potential to get rid of future water scarcity and famine for some regions. Moreover, it would allow for economic growth. If farmers could grow and sell more crops, then a region’s overall economy would improve greatly. Aside from agriculture, the tourism would also be boosted, where previously inhospitable places would be transformed into desirable holiday spots. The boost in the economy would then circulate among the residents and improve their living conditions.
Who will take these actions?
There are a lot of efforts combine from the government and others company to make this process more successful. For example, the Tokyo metropolitan government has tried cloud seeding in an attempt induce rainfall and alleviate one of the worst water shortages on record in the Kanto region. Among its key goals are advancing the science, technology and implementation of rain enhancement and encouraging additional investments in research funding and research partnerships to advance the field, increasing rainfall and ensuring water security globally.
Where will these actions be taken?
The first study for this artificial seeding experiment was carried out over the Genkai Sea, Japan, using liquid carbon dioxide. The seeded cloud was followed by an aircraft and radar at Kyushu University. Researchers have been accumulating data ever since. For practical application, permission needs to be obtained from the family of Fukuda and the University of Utah, which own the patents for the method. In the future, all countries can use it. For example, in UAE there is a lot of series of mountains and technique using liquid carbon dioxide (LCD), that will increase the amount of rain in the mountainous.
What are other key benefits?
Based on cloud seeding technique, it may be inferred that the LCO2 seeding produces stronger dynamic effects and precipitation. So, the method gives the ability to control the weather condition in an area. It does not just make rain, it also regulates water vapor that in turn prevent damages brought by destructive hails and storms.
What are the proposal’s costs?
In the cloud seeding operations, depending on the aim of the operation and conditions of cloud systems, suitable cloud seeding agents should be selected. In hence, correct selection of seeding agent is one of the most important factors to determine effective cloud seeding operation. Since cloud seeding operations are expensive, so the way they select the seeding agent should be more accurate to save the money and get the positive results. Moreover, it is very expensive to produce artificial rain. The chemicals must be delivered to the air via planes, which are hard to come by in places with very minimal income. Poverty-stricken areas suffering drought or famine may need external funding to have cloud seeding.
The liquid carbon dioxide (LCD) seeding technique it takes the standard period of doing any clouds seeding operation. It almost over the short term (5-15 years) which they can study the area and the period of accumulate the clouds above the mountain. On other hand if they use medium term and long term the operation will be more accurate and that’s will help to expect any difference in the weather through the years.
Some other Climate CoLab proposals related to my proposal by focusing in the different type of seeding agent. For example, there is proposal talk about using the pure salt rather than using chemical. The main purpose of this study is to increase the amount of rain and decrease the environment damages.
Maki, T., Morita, O., Suzuki, Y., & Wakimizu, K. (n.d.). Artificial Rainfall Produced by Seeding with Liquid Carbon Dioxide at Miyake and Mikura Islands , Japan.
Enhancement of precipitation by liquid carbon Enhancement of precipitation by liquid carbon dioxide seeding. (2015), (June).
Seeding Clouds to Enhance Precipitation?: Methods and Effectiveness Bart Geerts Dept . of Atmospheric Science University of Wyoming cloud seeding artificial snow making. (n.d.).
Sciences, O., Academy, N. D., City, F., & City, F. (2011). Artificial Cloud Seeding Using Liquid Carbon Dioxide?: Comparisons of Experimental Data and Numerical Analyses, (1990), 1417–1431.https://doi.org/10.1175/2011JAMC2592.1