SGER: Statistical Study of Global Climate Change and Sea Level

这项统计研究是基于一个响应概率函数技术开发来分析音爆破碎的窗口。在响应概率密度函数技术中，响应被框定为随机变量的乘积。然后检查每个因子的概率密度函数，以查看是否可以通过使用某些类型的概率密度函数（例如高斯或对数正态）的特定特性来进行任何简化。响应概率密度函数技术为分析气候变化引起的海平面上升问题提供了一种新的方法。在此分析中，海平面上升是要分析的响应。它被表示为三个随机变量的乘积：（1）温室气体排放吨数;（2）每百万吨的温度上升;（3）每升温一度的海平面上升。在这项研究中，数据上获得的三个随机变量和概率密度函数进行了检查。如果这些概率密度函数有助于简化，它将使问题更容易。如果不是，可以使用卷积技术来找到概率。如果响应概率密度函数技术是适用的，它将被用来对全球变暖情景下各种海平面上升量的概率进行初步估计。更广泛的影响：各种海平面上升量的概率是气候变化问题中的关键问题。在规划适当行动时必须回答这些问题。如果要从成本效益的角度来处理气候变化问题，那么在估计温室气体限制或沿海适应措施的预期价值时就必须考虑到这些可能性。改进对海平面上升概率的估计可能会指出需要对关键参数进行更多的观测。

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.