{"title":"将天气归因纳入未来水资源预算预测","authors":"Nick Martin","doi":"10.3390/hydrology10120219","DOIUrl":null,"url":null,"abstract":"Weather attribution is a scientific study that estimates the relative likelihood of an observed weather event occurring under different climate regimes. Water budget models are widely used tools that can estimate future water resource management and conservation conditions using daily weather forcing. A stochastic weather generator (WG) is a statistical model of daily weather sequences designed to simulate or represent a climate description. A WG provides a means to generate stochastic, future weather forcing to drive a water budget model to produce future water resource projections. Observed drought magnitude and human-induced climate change likelihood from a weather attribution study provide targets for WG calibration. The attribution-constrained WG approximately reproduces the five-fold increase in probability attributed to observed drought magnitude under climate change. A future (2031–2060) climate description produced by the calibrated WG is significantly hotter, with lower expected soil moisture than the future description obtained from global climate model (GCM) simulation results. The attribution-constrained WG describes future conditions where historical extreme and severe droughts are significantly more likely to occur.","PeriodicalId":37372,"journal":{"name":"Hydrology","volume":"846 ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Incorporating Weather Attribution to Future Water Budget Projections\",\"authors\":\"Nick Martin\",\"doi\":\"10.3390/hydrology10120219\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Weather attribution is a scientific study that estimates the relative likelihood of an observed weather event occurring under different climate regimes. Water budget models are widely used tools that can estimate future water resource management and conservation conditions using daily weather forcing. A stochastic weather generator (WG) is a statistical model of daily weather sequences designed to simulate or represent a climate description. A WG provides a means to generate stochastic, future weather forcing to drive a water budget model to produce future water resource projections. Observed drought magnitude and human-induced climate change likelihood from a weather attribution study provide targets for WG calibration. The attribution-constrained WG approximately reproduces the five-fold increase in probability attributed to observed drought magnitude under climate change. A future (2031–2060) climate description produced by the calibrated WG is significantly hotter, with lower expected soil moisture than the future description obtained from global climate model (GCM) simulation results. The attribution-constrained WG describes future conditions where historical extreme and severe droughts are significantly more likely to occur.\",\"PeriodicalId\":37372,\"journal\":{\"name\":\"Hydrology\",\"volume\":\"846 \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hydrology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/hydrology10120219\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"WATER RESOURCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/hydrology10120219","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 0
摘要
天气归因是一项科学研究,用于估算在不同气候条件下观测到的天气事件发生的相对可能性。水资源预算模型是一种广泛使用的工具,可以利用每日天气预报估算未来的水资源管理和保护条件。随机天气生成器(WG)是一种每日天气序列统计模型,旨在模拟或代表一种气候描述。WG 提供了一种生成随机、未来天气影响的方法,以驱动水资源预算模型,生成未来水资源预测。气象归因研究中观测到的干旱程度和人类引起的气候变化可能性为 WG 校准提供了目标。受归因约束的 WG 近似再现了在气候变化下观测到的干旱程度概率增加五倍的情况。与根据全球气候模式(GCM)模拟结果得出的未来气候描述相比,校准 WG 得出的未来(2031-2060 年)气候描述明显更热,预期土壤湿度更低。受归因约束的 WG 所描述的未来条件更有可能出现历史上的极端干旱和严重干旱。
Incorporating Weather Attribution to Future Water Budget Projections
Weather attribution is a scientific study that estimates the relative likelihood of an observed weather event occurring under different climate regimes. Water budget models are widely used tools that can estimate future water resource management and conservation conditions using daily weather forcing. A stochastic weather generator (WG) is a statistical model of daily weather sequences designed to simulate or represent a climate description. A WG provides a means to generate stochastic, future weather forcing to drive a water budget model to produce future water resource projections. Observed drought magnitude and human-induced climate change likelihood from a weather attribution study provide targets for WG calibration. The attribution-constrained WG approximately reproduces the five-fold increase in probability attributed to observed drought magnitude under climate change. A future (2031–2060) climate description produced by the calibrated WG is significantly hotter, with lower expected soil moisture than the future description obtained from global climate model (GCM) simulation results. The attribution-constrained WG describes future conditions where historical extreme and severe droughts are significantly more likely to occur.
HydrologyEarth and Planetary Sciences-Earth-Surface Processes
CiteScore
4.90
自引率
21.90%
发文量
192
审稿时长
6 weeks
期刊介绍:
Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences, including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology, hydrogeology and hydrogeophysics. Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, ecohydrology, geomorphology, soil science, instrumentation and remote sensing, data and information sciences, civil and environmental engineering are within scope. Social science perspectives on hydrological problems such as resource and ecological economics, sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope. The science published in the Journal of Hydrology is relevant to catchment scales rather than exclusively to a local scale or site. Studies focused on urban hydrological issues are included.