{"title":"在气候变化背景下利用人工神经网络和蒙特卡罗模拟研究未来海洋气候的新模式。","authors":"Nerea Portillo Juan, Vicente Negro Valdecantos","doi":"10.1016/j.ocemod.2024.102384","DOIUrl":null,"url":null,"abstract":"<div><p>This paper proposes a new model to study future coastal maritime climate under climate change context. This new model combines statistical analysis, Monte Carlo simulations and Artificial Neural Networks (ANNs). Statistical analysis and Monte Carlo simulations are used to extrapolate future wave climate under climate change context at a regional level and ANNs are used to propagate these projected sea states obtained in deep water to the coast. The use of ANNs allows for the utilization of large amounts of data at a very low computational cost, and the use of Monte Carlo simulations enables the generation of future climate change projections at a regional level. The combination of the two methodologies results in a very accurate (MSE of 0.02 m and 1 s) and computationally inexpensive hybrid model that allows projections of coastal maritime climate considering climate change. This new methodology has been validated and applied in the Western Mediterranean for the long-term regime and for extreme events, obtaining increases in extreme events up to 1.5 m in wave height and up to 1.8 s in wave period by 2050.</p></div>","PeriodicalId":19457,"journal":{"name":"Ocean Modelling","volume":"190 ","pages":"Article 102384"},"PeriodicalIF":3.1000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1463500324000714/pdfft?md5=57413f642e0872fede7ee58226b42d66&pid=1-s2.0-S1463500324000714-main.pdf","citationCount":"0","resultStr":"{\"title\":\"A novel model for the study of future maritime climate using artificial neural networks and Monte Carlo simulations under the context of climate change\",\"authors\":\"Nerea Portillo Juan, Vicente Negro Valdecantos\",\"doi\":\"10.1016/j.ocemod.2024.102384\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper proposes a new model to study future coastal maritime climate under climate change context. This new model combines statistical analysis, Monte Carlo simulations and Artificial Neural Networks (ANNs). Statistical analysis and Monte Carlo simulations are used to extrapolate future wave climate under climate change context at a regional level and ANNs are used to propagate these projected sea states obtained in deep water to the coast. The use of ANNs allows for the utilization of large amounts of data at a very low computational cost, and the use of Monte Carlo simulations enables the generation of future climate change projections at a regional level. The combination of the two methodologies results in a very accurate (MSE of 0.02 m and 1 s) and computationally inexpensive hybrid model that allows projections of coastal maritime climate considering climate change. This new methodology has been validated and applied in the Western Mediterranean for the long-term regime and for extreme events, obtaining increases in extreme events up to 1.5 m in wave height and up to 1.8 s in wave period by 2050.</p></div>\",\"PeriodicalId\":19457,\"journal\":{\"name\":\"Ocean Modelling\",\"volume\":\"190 \",\"pages\":\"Article 102384\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1463500324000714/pdfft?md5=57413f642e0872fede7ee58226b42d66&pid=1-s2.0-S1463500324000714-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ocean Modelling\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1463500324000714\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"METEOROLOGY & ATMOSPHERIC SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ocean Modelling","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1463500324000714","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
本文提出了一种研究气候变化背景下未来沿海海洋气候的新模式。这一新模式结合了统计分析、蒙特卡罗模拟和人工神经网络(ANN)。统计分析和蒙特卡洛模拟用于推断区域气候变化背景下的未来波浪气候,而人工神经网络则用于将这些在深水获得的预测海况传播到沿岸。使用 ANN 可以以极低的计算成本利用大量数据,而使用 Monte Carlo 仿真则可以生成区域一级的未来气候变化预测。将这两种方法结合起来,可以得到一个非常精确(MSE 为 0.02 米和 1 秒)、计算成本低廉的混合模式,可以对考虑到气候变化的沿岸海洋气候进行预测。这一新方法已在西地中海的长期制度和极端事件中得到验证和应用,到 2050 年,极端事件的波高增加可达 1.5 米,波长增加可达 1.8 秒。
A novel model for the study of future maritime climate using artificial neural networks and Monte Carlo simulations under the context of climate change
This paper proposes a new model to study future coastal maritime climate under climate change context. This new model combines statistical analysis, Monte Carlo simulations and Artificial Neural Networks (ANNs). Statistical analysis and Monte Carlo simulations are used to extrapolate future wave climate under climate change context at a regional level and ANNs are used to propagate these projected sea states obtained in deep water to the coast. The use of ANNs allows for the utilization of large amounts of data at a very low computational cost, and the use of Monte Carlo simulations enables the generation of future climate change projections at a regional level. The combination of the two methodologies results in a very accurate (MSE of 0.02 m and 1 s) and computationally inexpensive hybrid model that allows projections of coastal maritime climate considering climate change. This new methodology has been validated and applied in the Western Mediterranean for the long-term regime and for extreme events, obtaining increases in extreme events up to 1.5 m in wave height and up to 1.8 s in wave period by 2050.
期刊介绍:
The main objective of Ocean Modelling is to provide rapid communication between those interested in ocean modelling, whether through direct observation, or through analytical, numerical or laboratory models, and including interactions between physical and biogeochemical or biological phenomena. Because of the intimate links between ocean and atmosphere, involvement of scientists interested in influences of either medium on the other is welcome. The journal has a wide scope and includes ocean-atmosphere interaction in various forms as well as pure ocean results. In addition to primary peer-reviewed papers, the journal provides review papers, preliminary communications, and discussions.