Who is manipulating the weather

Scientists in the United Arab Emirates are making it rain — artificially — using electrical charges from drones to manipulate the weather and force rainfall across the desert nation. Meteorological officials released video footage this week showing a downpour over Ras al Khaimah, as well as several other regions.

The new method of cloud seeding shows promise in helping to mitigate drought conditions worldwide, without as many environmental concerns as previous methods involving salt flares. Annually, the United Arab Emirates receives about 4 inches of rain per year. Also expected from the requirement for reporting are religious activities or other ceremonies, rites and rituals intended to modify the weather. However, after the Administrator has received initial notification of a planned activity, he may waive some of the subsequent reporting requirements.

This decision to waive certain reporting requirements will be based on the general acceptability, from a technical or scientific viewpoint, of the apparatus and techniques to be used.

The following forms should be used:. When creating your reports, please use the following coding system as your NOAA file name: year, state, first four digits of the project name, and the respective report number. Since we are going to explore the weather and climate manipulation as an optimal control problem, let us consider an abstract dynamical system of the form with the initial conditions Suppose that the state vector belongs to the class of continuously differentiable functions and the control vector belongs to the class of piecewise continuous functions.

We can assume that control vector depends on the state of a system , which means that system 6 is a closed-loop control system, representing the ECS. Suppose also that system 6 is controllable and control vector belongs to the set of admissible controls. It is necessary to emphasize that the set of admissible controls is determined on the foundation of physical feasibility and technical implementability of methods of weather and climate control.

The optimal control aim is to synthesize the control law that ensures the accomplishment of the control objective. Formally an optimal control problem statement can be written as follows. Find the control vector and the orbit , which is generated by , such that the given performance index cost function reaches a minimum maximum value; that is,. An integrand of the performance index. We denote by a set of state variables on which the cost function is defined.

Equation 6 represents the dynamic constraints. Performance index 8 corresponds to the Bolza problem, while the problems of Mayer and Lagrange are its special cases. The formulation of cost function is not trivial and depends on the problem under consideration. Unfortunately, there are no universal approaches regarding how the performance index can be specified.

As an example, consider an optimal control problem for the large-scale atmospheric dynamics that is characterized by the slowly moving Rossby waves. These planetary-scale waves strongly influence weather conditions over large geographical regions. Equation 9 is a forced barotropic vorticity equation since its right-hand side is nonzero. The forcing term is determined by the vertical motion at lower boundary. The natural forcing of the atmospheric Rossby waves is of thermal and orographic origin.

These two mechanisms are described by the right-hand side term in 9 , that is, by the vertical velocity. Therefore, this velocity can be considered as a control variable. Equation 9 can be transformed into the inhomogeneous Helmholtz equation [ 52 ]: Here , where is a geostrophic stream function and is the geopotential; is a coefficient that implicitly depends on ; is a correlation coefficient that describes statistical relationship between the surface pressure and the mid-tropospheric geopotential; , where is Jacobian.

Equation 10 is considered in a closed domain of the -plane with a piecewise continuous boundary. The boundary curve in parametric form is represented as and , where and are continuous functions of the parameter.

Suppose that the coordinate origin coincides with the North Pole; then , and , where is a polar coordinate of a generic point on the circle. The solution to 10 is defined on the temporal interval.

Specifying along the boundary and introducing the new dependent variable , where is the time step of numerical integration, one can obtain the Dirichlet problem: where.

Problem 11 is solved numerically to obtain the stream function where is the initial condition. Then one can calculate the forecast of geopotential field , which characterizes the dynamics of Rossby waves.

Note that the forward difference is applied on the first time step and then a central difference can be employed. Let us define the performance index as follows: where the pair satisfies 13 and is the desired spatial distribution of in the domain.

Here is a set of admissible controls and is a set of some additional constraints on the state variable. Indeed the linearization of the vorticity equation around the unperturbed westerly zonal flow and then representation of the solution to the linearized equation in the form of plane waves give the following expression for the phase speed of Rossby waves: where is the amplitude of perturbation of stream function , and are the zonal and meridional wavenumbers, is the Rossby parameter, and.

The latest formula shows that the vertical structure of the atmosphere via the term contributes to the dispersion properties of Rossby waves. Meanwhile, the term depends on the correlation coefficient , which relates the vertical velocity with the stream function at the equivalent-barotropic level of the atmosphere. Consequently, the phase velocity of Rossby waves is in a function of.

By introducing new dependent and parametric variables 13 can be written in the normal form [ 54 ]: Adjoin 17 to the cost function 14 with spatial-varying Lagrange multipliers , , , , , and : The Hamiltonian associated with the optimal control problem is of the form The augmented cost function is then rewritten as or in the vector form where , , and.

We can select both and to cause the first term in parentheses in the double integral to vanish: The function does not change along the boundary ; therefore its variation on. Functions and are not defined on the boundary ; therefore we can require the relationship to hold along.

Then in polar coordinate we can obtain the boundary conditions for 17 : Then the first variation in becomes At the stationary point , which can be achieved if Equations 25 and 28 with boundary conditions 13 and 26 are the necessary conditions of optimality that can be represented in the expanded form as Thus, to find the control that minimizes cost function 14 one must solve the set of 12 partial differential equations 17 and 29 with 12 unknowns and with specified boundary conditions:.

For particular case of the optimal control problem we obtain and the necessary conditions for optimality take the form Since , the second and third equations in 31 are similar to the first two equations of system 17 ; therefore, the following assumptions can be made [ 55 ]: where is an arbitrary constant. These assumptions are compatible with boundary conditions The substitution of 32 into the first equation of system 32 gives Therefore, we have that in the domain.

It follows that the cost function attains its absolute minimum under constraint In order to find the optimal control that minimizes the cost function, one should solve the following problem in the domain :. The Rossby waves propagate westward relative to the mean quasi-zonal flow.

If the optimal control objective is to reach the stationarity of these waves with respect to the surface by manipulating the lower boundary vertical velocity , we should solve the following equation to obtain the optimal control: , since in this case.

Thus, we mathematically accurately proved the existence of the absolute minimum of cost function 14 under constraint Generally, however, the determination of feasible control variables is not a trivial problem. This method is theoretically based on the fact that some processes in the ECS are inherently unstable under almost regular conditions.

Since in mathematical models used in climate studies control actions that manipulate the weather and climate can be expressed via variations in model parameters that act as controls, sensitivity analysis of atmospheric and climate models allows the determination of parameters that can be considered as controls. Using mathematical models that describe various types of natural instability phenomena, one can find the necessary conditions for instability and estimate the influence of various model parameters on the development of instability.

The obtained results provide very important information that can be taken into account in designing control systems for atmospheric and climate processes.

Since the ECS possesses a full spectrum of properties of complex adaptive systems, the exploration of the atmosphere and other components of the ECS as complex adaptive systems allows the consideration of weather and climate manipulation as an optimization problem within the scope of the optimal control theory. However, the complexity of the ECS makes the control problem extremely difficult to solve.

In this paper, the necessary conditions of optimality are derived for control of the large-scale atmospheric dynamics. This demonstrates that even a relatively simplified control problem for the atmospheric Rossby waves requires significant efforts to obtain the solution. The study of the ECS as a complex adaptive system, the exploration of its feedback mechanisms, and interactions between climate system components represent the most appropriate approach to estimate the effectiveness and feasibility of potential methods to control the weather and climate.

In our subsequent papers we intend to show how the optimal control theory makes it possible to obtain the mathematically accurate solution to the problem of weather and climate manipulation. This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article of the Year Award: Outstanding research contributions of , as selected by our Chief Editors. Read the winning articles. Journal overview. Special Issues. Soldatenko 1 1 St. Academic Editor: Dimitri Volchenkov.

Received 30 Jul Accepted 13 Nov Published 12 Jan Abstract The weather and climate manipulation is examined as an optimal control problem for the earth climate system, which is considered as a complex adaptive dynamical system.

Here, as usual, the ECS is understood as a complex large-scale physical system that consists of five basic and interacting constituent complex subsystems, namely [ 3 ], i atmosphere , the gaseous and aerosol envelope of the earth that propagates from the land, water bodies, and ice-covered surface outward to space, ii hydrosphere , the oceans and other water bodies on the surface of our planet and water that is underground and in the atmosphere, iii cryosphere , the sea ice, freshwater ice, snow cover, glaciers, ice caps and ice sheets, and permafrost, iv lithosphere , the solid, external part of our planet, v biosphere , the part of our planet where life exists; that is, Each component of the ECS is characterized by a finite set of variables, usually called state variables, whose values at a given time determine the instant state of the ECS.

Figure 1. Fast and and slow and variables for the case of. Figure 2. Figure 3. By clicking below to subscribe, you acknowledge that your information will be transferred to Mailchimp for processing. Learn more about Northrop Grumman's privacy practices here. Farmers have long wished they could control the rain, and now weather manipulation can do just that. Cloud seeding , the most common way to modify weather, involves shooting silver iodide or other chemicals into clouds to encourage precipitation.

In other words, a silver bullet can make it rain. Scientists use weather modification to enhance rainfall and increase water supplies, to disperse fog and to minimize hail during storms.

Private companies and state-sponsored groups have even used cloud seeding to drop fresh snow on ski mountains and to squeeze out the rain before major events such as the Beijing Olympics. The idea is not to create clouds out of thin air, but to squeeze every last drop of rain from naturally occurring clouds.

So, what is cloud seeding? Cloud seeding adds substances to clouds by shooting them from the ground or dropping them from planes. Air already contains water vapor, but cloud seeding can encourage the water to condense until it falls from the sky.

Normally, when air rises into the atmosphere, it cools and forms particles called ice nuclei, which clump together to form clouds. When enough of these cloud droplets combine, they grow bigger until they are heavy enough that they fall to the ground in some form of precipitation, determined by the temperature and other conditions. Glaciogenic seeding is a technique for squeezing water from cold clouds.