This statistical study is based on a response probability function technique developed to analyze sonic boom breakage of windows. In the response probability density function technique, the response is framed as the product of random variables. The probability density function of each factor is then examined to see if any simplifications can be made by using the specific characteristics of some types of probability density functions, such as Gaussian or lognormal. The response probability density function technique represents a new approach to the problem of analyzing sea level rise from climate change. In this analysis, the sea level rise is the response to be analyzed. It is expressed as the product of three random variables (1) the tons of greenhouse gas emissions (2) the temperature rise per million tons and (3) the sea level rise per degree of temperature rise. In this study, data are obtained on each of the three random variables and the probability density functions are examined. If these probability density functions lend themselves to simplifications, it will make the problem easier. If not, convolution techniques can be used to find the probabilities. If the response probability density function technique is applicable it will be used to make preliminary estimates of the probabilities of various amounts of sea level rise under global warming scenarios.
Broader Impacts: The probabilities of various amounts of sea level rise are key questions in the climate change problem. These questions must be answered in planning appropriate actions. If climate change is to be approached on a cost-benefit basis, then the probabilities must be considered in estimating the expected value of greenhouse gas limitations or coastal adaptations. Improving the estimation of sea level rise probabilities may point out the need for additional observations of key parameters.
