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首页> 外文期刊>Climate dynamics >A new scheme for multivariate, multisite weather generator with inter-variable, inter-site dependence and inter-annual variability based on empirical copula approach
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A new scheme for multivariate, multisite weather generator with inter-variable, inter-site dependence and inter-annual variability based on empirical copula approach

机译：基于经验copula方法的具有变量间，站点间相关性和年际变化的多变量，多站点天气生成器新方案

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摘要

Weather generators (WGs) are often used to develop an ensemble of plausible climate scenarios across multiple spatial and temporal scales for vulnerability assessment and impact studies. Most of the conventional WGs are single-site models, which neglect the spatial dependence in the simulated meteorological field, are improper for regional impact studies. In recent several decades, efforts have been devoted to develop multivariate, multisite weather generators (MMWGs), which are able to reproduce the inter-variable and inter-site dependencies as well as the temporal structures observed in the historical records. Though several improvements have been achieved, the existed MMWGs are either conceptually complex or computationally expensive, and have difficulty in preserving the entire desired attributes. This study proposes a new two-stage scheme for constructing a MMWG. At the first stage, the meteorological series are simulated from a single-site multivariate weather generator (SMWG), which preserves the marginal distributional attributes for each meteorological variable. For the second stage, the inter-variable and inter-site dependencies as well as the temporal structures are reproduced using the Empirical Copula (EC) approach. An application of the proposed MMWG is presented for the Upper Thames River Catchment, Canada, and the performance is evaluated and compared with another two-stage MMWG based on the Iman shuffle approach. Results show that the proposed MMWG not only preserves the marginal distributional attributes, but also restores the inter-variable and inter-site dependencies, the temporal persistence, and the inter-annual variability almost perfectly. The performance of the proposed MMWG outperforms the one based on the Iman shuffle approach in terms of reconstruction of temporal persistence and inter-annual variability, as well as the reproduction of multivariate dependencies. Being conceptually simple and computationally inexpensive, the proposed scheme based on the EC approach is well suited for developing ensemble-based climate scenarios for vulnerability assessment and impact studies.
机译：天气生成器（WGs）通常用于在多个时空尺度上建立合情合理的气候情景集合，以进行脆弱性评估和影响研究。大多数常规工作组都是单站点模型，它忽略了模拟气象领域中的空间依赖性，因此不适用于区域影响研究。在最近的几十年中，致力于开发多变量，多站点天气生成器（MMWG），这些生成器能够重现变量和站点之间的依存关系以及历史记录中观察到的时间结构。尽管已经取得了一些改进，但是现有的MMWG在概念上还是复杂的，或者在计算上都是昂贵的，并且在保留整个所需属性方面存在困难。这项研究提出了一种新的两阶段计划，用于构建MMWG。在第一阶段，从单站点多元天气生成器（SMWG）模拟气象序列，该生成器保留了每个气象变量的边际分布属性。对于第二阶段，使用经验性Copula（EC）方法来再现变量间和站点间的依存关系以及时间结构。提出了拟议的MMWG在加拿大上泰晤士河流域的应用，并对性能进行了评估，并与基于Iman改组方法的两阶段MMWG进行了比较。结果表明，提出的MMWG不仅保留了边际分布属性，而且几乎完美地恢复了变量间和站点间的依存关系，时间持久性和年际变异性。提出的MMWG的性能在重建时间持久性和年际可变性以及多变量依存关系的再现方面优于基于Iman shuffle方法的性能。在概念上简单且计算上不昂贵，基于EC方法的建议方案非常适合开发基于整体的气候情景，以进行脆弱性评估和影响研究。

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