This is part of a continuing series of theoretical weapons. The weapons are theoretical as the United Nations has already banned the weapons (but not banned the building of research of defense from these weapons).
Possible applications of weather modifying weapons.
1) Use surface modifiers on oceans including but not limited to submerged nuclear heaters, airborne solar powered lasers, surface spreaders like oil slicks. This will help modify the temperature of the ocean in certain critical areas at critical times, influencing weather esp winds that bring rains.
Example- Modifying or Enhancing El Nino to influence rain to specific countries.
2) Use of air borne or aircraft borne lasers to start forest fires
3) Use of lasers to enhance the rate of melting of strategic glaciers.
4) Modify and interfere with the timing of an active volcano to prevent big rupture, rather to go for controlled releases.
5) Use of harmonics to influence seismic wave activity in geological reasons.
This is probably the best 5th in an action series sequel I have seen ( though Rocky Number 6 comes close, but Star Wars 5/6 dont)
The sheer chemistry between cars, action, big beef, beautiful iconic imagery, and nice music. This is XXX meets Ocean Eleven meets Welcome to the Jungle. Dwayne the rock Johnson continues to impress with his iconic imagery and so does Vin Diesel. The remaining actors are used tastefully and with much better direction than in some other Fast and Furious movies.
The interactions and interplays between sets, scene and people are clever, the actors know how to act, and fight . and drive.
When it comes to Car movies, you have to give to the Damn Yankees (though the French did come close with Taxi -, but not the fifth element Taxi)
Watch. It. Now. with a beer and chips. and all your homies.
The utilization of computer models for complex real-world processes requires addressing Uncertainty Quantification (UQ). Corresponding issues range from inaccuracies in the models to uncertainty in the parameters or intrinsic stochastic features.
This Summer school will expose students in the mathematical and statistical sciences to common challenges in developing, evaluating and using complex computer models of processes. It is essential that the next generation of researchers be trained on these fundamental issues too often absent of traditional curricula.
Participants will receive not only an overview of the fast developing field of UQ but also specific skills related to data assimilation, sensitivity analysis and the statistical analysis of rare events.
Theoretical concepts and methods will be illustrated on concrete examples and applications from both nuclear engineering and climate modeling.
The main lecturers are:
Dan Cacuci (N.C. State University): data assimilation and applications to nuclear engineering
Dan Cooley (Colorado State University): statistical analysis of rare events
This short course will introduce the current statistical practice for analyzing extreme events. Statistical practice relies on fitting distributions suggested by asymptotic theory to a subset of data considered to be extreme. Both block maximum and threshold exceedance approaches will be presented for both the univariate and multivariate cases.
Doug Nychka (NCAR): data assimilation and applications in climate modeling
Climate prediction and modeling do not incorporate geophysical data in the sequential manner as weather forecasting and comparison to data is typically based on accumulated statistics, such as averages. This arises because a climate model matches the state of the Earth’s atmosphere and ocean “on the average” and so one would not expect the detailed weather fluctuations to be similar between a model and the real system. An emerging area for climate model validation and improvement is the use of data assimilation to scrutinize the physical processes in a model using observations on shorter time scales. The idea is to find a match between the state of the climate model and observed data that is particular to the observed weather. In this way one can check whether short time physical processes such as cloud formation or dynamics of the atmosphere are consistent with what is observed.
Dongbin Xiu (Purdue University): sensitivity analysis and polynomial chaos for differential equations
This lecture will focus on numerical algorithms for stochastic simulations, with an emphasis on the methods based on generalized polynomial chaos methodology. Both the mathematical framework and the technical details will be examined, along with performance comparisons and implementation issues for practical complex systems.
The main lectures will be supplemented by discussion sessions and by presentations from UQ practitioners from both the Sandia and Los Alamos National Laboratories.