SGER: Statistical Study of Global Climate Change and Sea Level

本统计研究是基于响应概率函数技术来分析窗户的音爆破裂。在响应概率密度函数技术中，响应被框架为随机变量的乘积。然后检查每个因素的概率密度函数，看看是否可以通过使用某些类型的概率密度函数（如高斯或对数正态）的特定特征来进行任何简化。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。在这个分析中，海平面上升是要分析的响应。它表示为三个随机变量(1)温室气体排放吨数(2)每百万吨温升和(3)每一度温升海平面上升的乘积。在本研究中，分别获得了三个随机变量的数据，并对概率密度函数进行了检验。如果这些概率密度函数可以简化，就会使问题更容易解决。如果不是，卷积技术可以用来找到概率。如果响应概率密度函数技术是适用的，它将被用来初步估计在全球变暖情景下各种海平面上升的概率。更广泛的影响：海平面上升不同幅度的可能性是气候变化问题中的关键问题。这些问题必须在计划适当的行动时得到回答。如果要在成本效益的基础上处理气候变化，那么在估计温室气体限制或沿海适应的预期价值时必须考虑概率。改进对海平面上升概率的估计可能指出需要对关键参数进行额外的观测。

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.