A transient stochastic weather generator incorporating climate model uncertainty
A transient stochastic weather generator incorporating climate model uncertainty
复制标题
结合气候模型不确定性的瞬态随机天气发生器
DOI：
10.1016/j.advwatres.2015.08.002
复制
发表时间：
2015
影响因子：
4.7
通讯作者：
C. Kilsby
中科院分区：
文献类型：
--
作者：
V. Glenis;V. Pinamonti;Jim W Hall;C. Kilsby
随机天气生成器 (WG) 可提供降雨和潜在蒸散量 (PET) 等天气变量的长合成时间序列，已在水资源建模中得到广泛应用。当以气候模型预测的气候统计变化（变化因素，CF）为条件时，工作组为气候影响评估和适应规划提供了有用的工具。最新的气候建模练习涉及大量全球和区域气候模型集成，旨在探索气候模型公式和参数设置中不确定性的影响：所谓的“扰动物理系综”（PPE）。在本文中，我们展示了如何通过测试 CF 的多个向量（每个向量源自 PPE 的不同样本）来将这些气候模型不确定性传播到影响研究。我们将其与一种新方法相结合，以参数化 CF 的预计时间演化。我们演示了如何以这些时间相关的 CF 为条件，使用现有的、经过充分验证且广泛使用的工作组来生成未来气候的非平稳模拟，该模拟与英国气象局哈德利中心扰动物理系综的概率输出一致。该工作组能够对自然变化和气候模型不确定性进行广泛采样，为在非平稳气候背景下制定稳健的水资源管理战略提供基础。
Stochastic weather generators (WGs), which provide long synthetic time series of weather variables such as rainfall and potential evapotranspiration (PET), have found widespread use in water resources modelling. When conditioned upon the changes in climatic statistics (change factors, CFs) predicted by climate models, WGs provide a useful tool for climate impacts assessment and adaption planning. The latest climate modelling exercises have involved large numbers of global and regional climate models integrations, designed to explore the implications of uncertainties in the climate model formulation and parameter settings: so called ‘perturbed physics ensembles’ (PPEs). In this paper we show how these climate model uncertainties can be propagated through to impact studies by testing multiple vectors of CFs, each vector derived from a different sample from a PPE. We combine this with a new methodology to parameterise the projected time-evolution of CFs. We demonstrate how, when conditioned upon these time-dependent CFs, an existing, well validated and widely used WG can be used to generate non-stationary simulations of future climate that are consistent with probabilistic outputs from the Met Office Hadley Centre's Perturbed Physics Ensemble. The WG enables extensive sampling of natural variability and climate model uncertainty, providing the basis for development of robust water resources management strategies in the context of a non-stationary climate.
DOI：
10.1016/j.envsoft.2008.04.003
发表时间：
2008-12
期刊：
Environ. Model. Softw.
影响因子：
--
作者：
A. Burton;C. Kilsby;H. Fowler;P. Cowpertwait;P. O'Connell
通讯作者：
A. Burton;C. Kilsby;H. Fowler;P. Cowpertwait;P. O'Connell
影响因子：
2.8
作者：
N. Schütze;S. Kloss;F. Lennartz;Ahmed Al Bakri;G. Schmitz
通讯作者：
N. Schütze;S. Kloss;F. Lennartz;Ahmed Al Bakri;G. Schmitz