模拟埃及环境的最佳全球环流模式的选择

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引用次数: 0

摘要

研究气候变化及其对农业、水资源、卫生和社会等各个部门影响的埃及研究人员通常使用全球环流模式(GCMs)之一,并依赖其结果。他们认为它的结果是事实和真实的,他们研究影响而不考虑结果中的不确定性。这是研究气候变化对不同部门的影响的一个主要缺陷,因为不同模型的结果存在令人信服的差异。因此,影响分析可能导致以与所研究地区的实际情况有关的方式制定政策和制定替代方案。已经发现,对于埃及的情况,最好的全球模式或回收模式必须被中和。正确研究气候变化的影响是制定未来政策的必要组成部分。目前的研究重点是评估埃及gcm的结果。先前的评论表明,在埃及没有研究解决这个问题。因此,采用了下列方法。对耦合模式比对项目(CMIP5)中40个gcm的降水和温度变量进行了分析。通过将整个埃及地区划分为110个单元,每个单元为100公里× 100公里的平方,对埃及的气候变量降水率进行了gcm评估。通过应用5个性能指标对降水和温度进行评价。这些指标列出如下:1)相关系数(CoC), 2)归一化均方根(NRMSE),绝对归一化平均偏差(ANMBE),平均绝对相对误差(AARE)和技能分数(SS)。开发了收益矩阵(40个gcm vs 5个指标),然后应用熵技术确定绩效指标的权重。对冬、春、夏、秋4个季节的业绩指标分别采用归一化方法。这些权重用于帮助对40个gcm进行排名。通过多准则决策排序法(promeee -2)对这些gcm进行排序。最后,与其他39种模式相比,“MPI-ESM-LR”模式是预测埃及全地区气候变化参数(降水和温度)的最佳模式。MPI-ESM-LR GCM模式是由德国马克斯普朗克气象研究所开发的。建议到2100年埃及气候变化项目的结果应采用MPI-ESM-LR GCM的输出结果,而不是其他GCM,只要它能给出最适合埃及气候变化预测的结果。
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Selection of the Optimum Global Circulation Model that Mimics the Circumstances of Egypt
Egyptian researchers in the field of climatic changes and their effects on various sectors, such as agriculture, water resources, health and social usually operate one of the Global Circulation Models (GCMs) and rely on its results. They considered its results as facts and real and they study the impact without reference to the uncertainty in their results. This is a major drawback to study the effect of climate changes on different sectors since there is a persuasive variation in the results of different models. Therefore, the impact analysis may result in building policies and develop alternatives in a way that is related to the real situation of the area under study. It has been found that the best global model or recycling models for the case of Egypt must be neutralized. It is an imperative component for building future policies to study the impact of climate change properly. The current study focuses on assessing the results of GCMs in Egypt. Previous reviews showed that there is no study to address this issue on Egypt. Thus, the following methodology was followed. Forty GCMs in Coupled Model Inter-comparing Project (CMIP5), are analyzed for the variable’s precipitation and temperature. These GCMs were Evaluated for Egypt for the climate variable precipitation rate through dividing the entire Egypt area to 110 cells each cell is square 100 km x 100 km. The precipitation and temperature were evaluated through applying five performance indicators. These indicators are listed as follow: i) coefficient of correlation (CoC) , ii) normalized root mean (NRMSE), absolute normalized mean bias error (ANMBE), average absolute relative error (AARE) and skill score (SS).The Payoff matrix (40 GCMs versus 5 indicators) is developed and then the entropy technique for determination of the performance indicators’ weights is applied. The Normalization technique was applied for each season out of 4 seasons that are winter, spring, summer and autumn on the performance indicators. These weights are applied to assist for ranking the 40 GCMs. The Ranking of these GCMs were obtained through a multi-criterion decision-making outranking method (PROMETHEE-2). Finally, it is proven that the “MPI-ESM-LR” GCM is found to be the best model for predicting the climate change parameters, (precipitation and temperature), all over Egypt compared to the other 39 models. The MPI-ESM-LR GCM model is developed by the Max Planck Institute for Meteorology in Germany. It is recommended that the results of climate change projects for Egypt up until year 2100 has to apply the output results of the GCM named MPI-ESM-LR rather than other GCMs as long as it gives the most proper results for climate change projection of Egypt.
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