用于加利福尼亚州基于过程的自下而上气候风险评估的全州范围、基于天气时间的随机天气生成器 - 第 I 部分:模型评估

IF 4 3区 环境科学与生态学 Q2 ENVIRONMENTAL SCIENCES
Nasser Najibi , Alejandro J. Perez , Wyatt Arnold , Andrew Schwarz , Romain Maendly , Scott Steinschneider
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引用次数: 0

摘要

本研究分为两部分,第一部分介绍了一种新颖的基于天气系统的随机天气生成器,以支持对加利福尼亚州水系统进行自下而上的气候脆弱性评估。在本系列的第一部分,我们介绍了模型开发和验证的细节。该模型的基础是识别和模拟天气机制,即大气流动的大尺度模式,然后利用这些模式来模拟全州 6 千米分辨率的局部每日天气。我们对基线模型的 1000 年模拟进行了全面验证,以评估其在不同空间尺度(网格单元、流域)和时间尺度(日、事件、月、年、跨年度到十年)上准确模拟日降水量以及最低和最高温度的能力。结果表明,该模型在这些尺度上有效地再现了全州范围内的大量气候统计数据,包括瞬时、脉冲、干湿极端气候以及极热和极冷时期。此外,该模型还成功地保持了空间相关性和变量间的关系,使模型模拟能够用于跨越加州多个流域的水文和水资源分析。天气生成器可以模拟物理上可信的极端事件(如多日极端降水和严重干旱),这些事件超出了历史上观测到的最坏情况,与气候变化无关。因此,基线模拟可用于了解自然气候变异性对区域水系统洪水和干旱风险的影响。第 2 部分将讨论气候变化情景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A statewide, weather-regime based stochastic weather generator for process-based bottom-up climate risk assessments in California – Part I: Model evaluation

This study is the first of a two-part series presenting a novel weather regime-based stochastic weather generator to support bottom-up climate vulnerability assessments of water systems in California. In Part 1 of this series, we present the details of model development and validation. The model is based on the identification and simulation of weather regimes, or large-scale patterns of atmospheric flow, which are then used to condition the simulation of local, daily weather at a 6 km resolution across the state. We conduct a thorough validation of a baseline, 1000-year model simulation to evaluate its ability to accurately simulate daily precipitation and minimum and maximum temperature at various spatial scales (grid cell, river basin) and temporal scales (daily, event-based, monthly, annual, inter-annual to decadal). Results show that the model effectively reproduces a large suite of climate statistics at these scales across the entire state, including moments, spells, dry and wet extremes, and extreme hot and cold periods. Moreover, the model successfully maintains spatial correlations and inter-variable relationships, enabling the use of model simulations in hydrologic and water resources analyses that span multiple watersheds across California. The weather generator can simulate physically plausible extreme events (e.g., multi-day extreme precipitation and severe drought) that extend beyond the worst case conditions observed historically, independent of climate change. Thus, the baseline simulation can be used to understand the impacts of natural climate variability on both flood and drought risk in regional water systems. Scenarios of climate change are discussed in Part 2.

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来源期刊
Climate Services
Climate Services Multiple-
CiteScore
5.30
自引率
15.60%
发文量
62
期刊介绍: The journal Climate Services publishes research with a focus on science-based and user-specific climate information underpinning climate services, ultimately to assist society to adapt to climate change. Climate Services brings science and practice closer together. The journal addresses both researchers in the field of climate service research, and stakeholders and practitioners interested in or already applying climate services. It serves as a means of communication, dialogue and exchange between researchers and stakeholders. Climate services pioneers novel research areas that directly refer to how climate information can be applied in methodologies and tools for adaptation to climate change. It publishes best practice examples, case studies as well as theories, methods and data analysis with a clear connection to climate services. The focus of the published work is often multi-disciplinary, case-specific, tailored to specific sectors and strongly application-oriented. To offer a suitable outlet for such studies, Climate Services journal introduced a new section in the research article type. The research article contains a classical scientific part as well as a section with easily understandable practical implications for policy makers and practitioners. The journal''s focus is on the use and usability of climate information for adaptation purposes underpinning climate services.
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